WorldWideScience

Sample records for surface temperature snow

  1. Surface energy balance of seasonal snow cover for snow-melt ...

    Indian Academy of Sciences (India)

    This study describes time series analysis of snow-melt, radiation data and energy balance for a seasonal snow cover at Dhundi field station of SASE, which lies in Pir Panjal range of the. N–W Himalaya, for a winter season from 13 January to 12 April 2005. The analysis shows that mean snow surface temperature remains ...

  2. What controls the isotopic composition of Greenland surface snow?

    Directory of Open Access Journals (Sweden)

    H. C. Steen-Larsen

    2014-02-01

    Full Text Available Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (δ18O, δD of near-surface water vapor, precipitation and samples of the top (0.5 cm snow surface has been conducted during two summers (2011–2012 at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor δ18O and air temperature (0.85 ± 0.11‰ °C−1 (R = 0.76 for 2012. The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1–5-day periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface

  3. The seasonal cycle of snow cover, sea ice and surface albedo

    Science.gov (United States)

    Robock, A.

    1980-01-01

    The paper examines satellite data used to construct mean snow cover caps for the Northern Hemisphere. The zonally averaged snow cover from these maps is used to calculate the seasonal cycle of zonally averaged surface albedo. The effects of meltwater on the surface, solar zenith angle, and cloudiness are parameterized and included in the calculations of snow and ice albedo. The data allows a calculation of surface albedo for any land or ocean 10 deg latitude band as a function of surface temperature ice and snow cover; the correct determination of the ice boundary is more important than the snow boundary for accurately simulating the ice and snow albedo feedback.

  4. A Snow Density Dataset for Improving Surface Boundary Conditions in Greenland Ice Sheet Firn Modeling

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    Robert S. Fausto

    2018-05-01

    Full Text Available The surface snow density of glaciers and ice sheets is of fundamental importance in converting volume to mass in both altimetry and surface mass balance studies, yet it is often poorly constrained. Site-specific surface snow densities are typically derived from empirical relations based on temperature and wind speed. These parameterizations commonly calculate the average density of the top meter of snow, thereby systematically overestimating snow density at the actual surface. Therefore, constraining surface snow density to the top 0.1 m can improve boundary conditions in high-resolution firn-evolution modeling. We have compiled an extensive dataset of 200 point measurements of surface snow density from firn cores and snow pits on the Greenland ice sheet. We find that surface snow density within 0.1 m of the surface has an average value of 315 kg m−3 with a standard deviation of 44 kg m−3, and has an insignificant annual air temperature dependency. We demonstrate that two widely-used surface snow density parameterizations dependent on temperature systematically overestimate surface snow density over the Greenland ice sheet by 17–19%, and that using a constant density of 315 kg m−3 may give superior results when applied in surface mass budget modeling.

  5. Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

    Science.gov (United States)

    Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

    2016-12-01

    This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size

  6. An electrostatic charge measurement of blowing snow particles focusing on collision frequency to the snow surface

    Science.gov (United States)

    Omiya, S.; Sato, A.

    2010-12-01

    the fixed fetch (12m). The number of collisions of particle was converted from the wind velocity using an equation obtained by Kosugi et al. (2004). Blowing snow particles tend to accumulate negative charges gradually with increase of the number of collisions to the snow surface. As a result, it is demonstrated that the gaps between the field values and the wind tunnel ones were due to difference of the collision frequency of snow particles. Assuming a logarithmic relationship as first approximation between the measured charges and the number of collisions, the charge-to-mass ratios will reach roughly the same value which was obtained in the field with several hundreds collisions. For instance, fetch is needed roughly 200m for blowing snow particles to gain -30 μC/kg under the following conditions: air temperature -20 degrees Celsius, wind velocity 7m/s and hard snow surface. REFERENCE: Kosugi et al., (2004): Dependence of drifting snow saltation length on snow surface hardness. Cold Reg. Sci. Technol., 39, 133-139.

  7. Uptake of acetone, ethanol and benzene to snow and ice: effects of surface area and temperature

    International Nuclear Information System (INIS)

    Abbatt, J P D; Bartels-Rausch, T; Ullerstam, M; Ye, T J

    2008-01-01

    The interactions of gas-phase acetone, ethanol and benzene with smooth ice films and artificial snow have been studied. In one technique, the snow is packed into a cylindrical column and inserted into a low-pressure flow reactor coupled to a chemical-ionization mass spectrometer for gas-phase analysis. At 214 and 228 K, it is found for acetone and ethanol that the adsorbed amounts per surface area match those for adsorption to thin films of ice formed by freezing liquid water, when the specific surface area of the snow (as determined from Kr adsorption at 77 K) and the geometric surface area of the ice films are used. This indicates that freezing thin films of water leads to surfaces that are smooth at the molecular level. Experiments performed to test the effect of film growth on ethanol uptake indicate that uptake is independent of ice growth rate, up to 2.4 μm min -1 . In addition, traditional Brunauer-Emmett-Teller (BET) experiments were performed with these gases on artificial snow from 238 to 266.5 K. A transition from a BET type I isotherm indicative of monolayer formation to a BET type II isotherm indicative of multilayer uptake is observed for acetone at T≥263 K and ethanol at T≥255 K, arising from solution formation on the ice. When multilayer formation does not occur, as was the case for benzene at T≤263 K and for acetone at T≤255 K, the saturated surface coverage increased with increasing temperature, consistent with the quasi-liquid layer affecting adsorption prior to full dissolution/multilayer formation.

  8. A Snow Density Dataset for Improving Surface Boundary Conditions in Greenland Ice Sheet Firn Modeling

    DEFF Research Database (Denmark)

    S. Fausto, Robert; E. Box, Jason; Vandecrux, Baptiste Robert Marcel

    2018-01-01

    The surface snow density of glaciers and ice sheets is of fundamental importance in converting volume to mass in both altimetry and surface mass balance studies, yet it is often poorly constrained. Site-specific surface snow densities are typically derived from empirical relations based...... on temperature and wind speed. These parameterizations commonly calculate the average density of the top meter of snow, thereby systematically overestimating snow density at the actual surface. Therefore, constraining surface snow density to the top 0.1 m can improve boundary conditions in high-resolution firn......-evolution modeling. We have compiled an extensive dataset of 200 point measurements of surface snow density from firn cores and snow pits on the Greenland ice sheet. We find that surface snow density within 0.1 m of the surface has an average value of 315 kg m−3 with a standard deviation of 44 kg m−3, and has...

  9. Surface decontamination using dry ice snow

    International Nuclear Information System (INIS)

    Ryu, Jungdong; Park, Kwangheon; Lee, Bumsik; Kim Yangeun

    1999-01-01

    An adjustable nozzle for controlling the size of dry ice snow was developed. The converging/diverging nozzle can control the size of snows from sub-microns to 10 micron size. Using the nozzle, a surface decontamination device was made. The removal mechanisms of surface contaminants are mechanical impact, partial dissolving and evaporation process, and viscous flow. A heat supply system is added for the prevention of surface ice layer formation. The cleaning power is slightly dependent on the size of snow. Small snows are the better in viscous flow cleaning, while large snows are slightly better in dissolving and sublimation process. Human oils like fingerprints on glass were easy to remove. Decontamination ability was tested using a contaminated pump-housing surface. About 40 to 80% of radioactivity was removed. This device is effective in surface-decontamination of any electrical devices like detector, controllers which cannot be cleaned in aqueous solution. (author)

  10. Air–snow exchange of nitrate: a modelling approach to investigate physicochemical processes in surface snow at Dome C, Antarctica

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    J. Bock

    2016-10-01

    Full Text Available Snowpack is a multiphase (photochemical reactor that strongly influences the air composition in polar and snow-covered regions. Snowpack plays a special role in the nitrogen cycle, as it has been shown that nitrate undergoes numerous recycling stages (including photolysis in the snow before being permanently buried in the ice. However, the current understanding of these physicochemical processes remains very poor. Several modelling studies have attempted to reproduce (photochemical reactions inside snow grains, but these have relied on strong assumptions to characterise snow reactive properties, which are not well defined. Air–snow exchange processes such as adsorption, solid-state diffusion, or co-condensation also affect snow chemical composition. Here, we present a physically based model of these processes for nitrate. Using as input a 1-year-long time series of atmospheric nitrate concentration measured at Dome C, Antarctica, our model reproduces with good agreement the nitrate measurements in the surface snow. By investigating the relative importance of the main exchange processes, this study shows that, on the one hand, the combination of bulk diffusion and co-condensation allows a good reproduction of the measurements (correlation coefficient r = 0.95, with a correct amplitude and timing of summer peak concentration of nitrate in snow. During winter, nitrate concentration in surface snow is mainly driven by thermodynamic equilibrium, whilst the peak observed in summer is explained by the kinetic process of co-condensation. On the other hand, the adsorption of nitric acid on the surface of the snow grains, constrained by an already existing parameterisation for the isotherm, fails to fit the observed variations. During winter and spring, the modelled concentration of adsorbed nitrate is respectively 2.5 and 8.3-fold higher than the measured one. A strong diurnal variation driven by the temperature cycle and a peak occurring in early

  11. Modeling the influence of snow cover temperature and water content on wet-snow avalanche runout

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    C. Vera Valero

    2018-03-01

    Full Text Available Snow avalanche motion is strongly dependent on the temperature and water content of the snow cover. In this paper we use a snow cover model, driven by measured meteorological data, to set the initial and boundary conditions for wet-snow avalanche calculations. The snow cover model provides estimates of snow height, density, temperature and liquid water content. This information is used to prescribe fracture heights and erosion heights for an avalanche dynamics model. We compare simulated runout distances with observed avalanche deposition fields using a contingency table analysis. Our analysis of the simulations reveals a large variability in predicted runout for tracks with flat terraces and gradual slope transitions to the runout zone. Reliable estimates of avalanche mass (height and density in the release and erosion zones are identified to be more important than an exact specification of temperature and water content. For wet-snow avalanches, this implies that the layers where meltwater accumulates in the release zone must be identified accurately as this defines the height of the fracture slab and therefore the release mass. Advanced thermomechanical models appear to be better suited to simulate wet-snow avalanche inundation areas than existing guideline procedures if and only if accurate snow cover information is available.

  12. Potential feedbacks between snow cover, soil moisture and surface energy fluxes in Southern Norway

    Science.gov (United States)

    Brox Nilsen, Irene; Tallaksen, Lena M.; Stordal, Frode

    2017-04-01

    At high latitudes, the snow season has become shorter during the past decades because snowmelt is highly sensitive to a warmer climate. Snowmelt influences the energy balance by changing the albedo and the partitioning between latent and sensible heat fluxes. It further influences the water balance by changing the runoff and soil moisture. In a previous study, we identified southern Norway as a region where significant temperature changes in summer could potentially be explained by land-atmosphere interactions. In this study we hypothesise that changes in snow cover would influence the summer surface fluxes in the succeeding weeks or months. The exceptionally warm summer of 2014 was chosen as a test bed. In Norway, evapotranspiration is not soil moisture limited, but energy limited, under normal conditions. During warm summers, however, such as in 2014, evapotranspiration can be restricted by the available soil moisture. Using the Weather Research and Forecasting (WRF) model we replace the initial ground conditions for 2014 with conditions representative of a snow-poor spring and a snow-rich spring. WRF was coupled to Noah-MP at 3 km horizontal resolution in the inner domain, and the simulations covered mid-May through September 2014. Boundary conditions used to force WRF were taken from the Era-Interim reanalysis. Snow, runoff, soil moisture and soil temperature observational data were provided by the Norwegian Water Resources and Energy Directorate for validation. The validation shows generally good agreement with observations. Preliminary results show that the reduced snowpack, hereafter "sim1" increased the air temperature by up to 5 K and the surface temperature by up to 10 K in areas affected by snow changes. The increased snowpack, hereafter "sim2", decreased the air and surface temperature by the same amount. These are weekly mean values for the first eight simulation weeks from mid May. Because of the higher net energy available ( 100 Wm-2) in sim 1, both

  13. Use of AMSR-E microwave satellite data for land surface characteristics and snow cover variation

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    Mukesh Singh Boori

    2016-12-01

    Full Text Available This data article contains data related to the research article entitled “Global land cover classification based on microwave polarization and gradient ratio (MPGR” [1] and “Microwave polarization and gradient ratio (MPGR for global land surface phenology” [2]. This data article presents land surface characteristics and snow cover variation information from sensors like EOS Advanced Microwave Scanning Radiometer (AMSR-E. This data article use the HDF Explorer, Matlab, and ArcGIS software to process the pixel latitude, longitude, snow water equivalent (SWE, digital elevation model (DEM and Brightness Temperature (BT information from AMSR-E satellite data to provide land surface characteristics and snow cover variation data in all-weather condition at any time. This data information is useful to discriminate different land surface cover types and snow cover variation, which is turn, will help to improve monitoring of weather, climate and natural disasters.

  14. Snow cover and temperature relationships in North America and Eurasia

    Science.gov (United States)

    Foster, J.; Owe, M.; Rango, A.

    1983-01-01

    In this study the snow cover extent during the autumn months in both North America and Eurasia has been related to the ensuing winter temperature as measured at several locations near the center of each continent. The relationship between autumn snow cover and the ensuing winter temperatures was found to be much better for Eurasia than for North America. For Eurasia the average snow cover extent during the autumn explained as much as 52 percent of the variance in the winter (December-February) temperatures compared to only 12 percent for North America. However, when the average winter snow cover was correlated with the average winter temperature it was found that the relationship was better for North America than for Eurasia. As much as 46 percent of the variance in the winter temperature was explained by the winter snow cover in North America compared to only 12 percent in Eurasia.

  15. Use of a thermal imager for snow pit temperatures

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    C. Shea

    2012-03-01

    Full Text Available Weak snow of interest to avalanche forecasting often forms and changes as thin layers. Thermometers, the current field technology for measuring the temperature gradients across such layers – and for thus estimating the expected vapour flux and future type of crystal metamorphism – are difficult to use at distances shorter than 1 cm. In contrast, a thermal imager can provide thousands of simultaneous temperature measurements across small distances with better accuracy. However, a thermal imager only senses the exposed surface, complicating its methods for access and accuracy of buried temperatures. This paper presents methods for exposing buried layers on pit walls and using a thermal imager to measure temperatures on these walls, correct for lens effects with snow, adjust temperature gradients, adjust time exposed, and calculate temperature gradients over millimetre distances. We find lens error on temperature gradients to be on the order of 0.03 °C between image centre and corners. We find temperature gradient change over time to usually decrease – as expected with atmospheric equalization as a strong effect. Case studies including thermal images and visual macro photographs of crystals, collected during the 2010–2011 winter, demonstrate large temperature differences over millimetre-scale distances that are consistent with observed kinetic metamorphism. Further study is needed to use absolute temperatures independently of supporting gradient data.

  16. Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

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    E. E. Stigter

    2017-07-01

    Full Text Available Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE. Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF. Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May and decreases during the late melt season (June to September as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

  17. How Can Polarization States of Reflected Light from Snow Surfaces Inform Us on Surface Normals and Ultimately Snow Grain Size Measurements?

    Science.gov (United States)

    Schneider, A. M.; Flanner, M.; Yang, P.; Yi, B.; Huang, X.; Feldman, D.

    2016-12-01

    The Snow Grain Size and Pollution (SGSP) algorithm is a method applied to Moderate Resolution Imaging Spectroradiometer data to estimate snow grain size from space-borne measurements. Previous studies validate and quantify potential sources of error in this method, but because it assumes flat snow surfaces, however, large scale variations in surface normals can cause biases in its estimates due to its dependence on solar and observation zenith angles. To address these variations, we apply the Monte Carlo method for photon transport using data containing the single scattering properties of different ice crystals to calculate polarization states of reflected monochromatic light at 1500nm from modeled snow surfaces. We evaluate the dependence of these polarization states on solar and observation geometry at 1500nm because multiple scattering is generally a mechanism for depolarization and the ice crystals are relatively absorptive at this wavelength. Using 1500nm thus results in a higher number of reflected photons undergoing fewer scattering events, increasing the likelihood of reflected light having higher degrees of polarization. In evaluating the validity of the model, we find agreement with previous studies pertaining to near-infrared spectral directional hemispherical reflectance (i.e. black-sky albedo) and similarities in measured bidirectional reflectance factors, but few studies exist modeling polarization states of reflected light from snow surfaces. Here, we present novel results pertaining to calculated polarization states and compare dependences on solar and observation geometry for different idealized snow surfaces. If these dependencies are consistent across different ice particle shapes and sizes, then these findings could inform the SGSP algorithm by providing useful relationships between measurable physical quantities and solar and observation geometry to better understand variations in snow surface normals from remote sensing observations.

  18. Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

    Science.gov (United States)

    Zaitchik, Benjamin F.; Rodell, Matthew

    2008-01-01

    Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

  19. The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

    Science.gov (United States)

    Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

    2006-01-01

    Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

  20. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique improve the simulation accuracy of mean seasonal (October throughout May snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the

  1. Simulating Snow in Canadian Boreal Environments with CLASS for ESM-SnowMIP

    Science.gov (United States)

    Wang, L.; Bartlett, P. A.; Derksen, C.; Ireson, A. M.; Essery, R.

    2017-12-01

    The ability of land surface schemes to provide realistic simulations of snow cover is necessary for accurate representation of energy and water balances in climate models. Historically, this has been particularly challenging in boreal forests, where poor treatment of both snow masking by forests and vegetation-snow interaction has resulted in biases in simulated albedo and snowpack properties, with subsequent effects on both regional temperatures and the snow albedo feedback in coupled simulations. The SnowMIP (Snow Model Intercomparison Project) series of experiments or `MIPs' was initiated in order to provide assessments of the performance of various snow- and land-surface-models at selected locations, in order to understand the primary factors affecting model performance. Here we present preliminary results of simulations conducted for the third such MIP, ESM-SnowMIP (Earth System Model - Snow Model Intercomparison Project), using the Canadian Land Surface Scheme (CLASS) at boreal forest sites in central Saskatchewan. We assess the ability of our latest model version (CLASS 3.6.2) to simulate observed snowpack properties (snow water equivalent, density and depth) and above-canopy albedo over 13 winters. We also examine the sensitivity of these simulations to climate forcing at local and regional scales.

  2. [Characteristics of mercury exchange flux between soil and atmosphere under the snow retention and snow melting control].

    Science.gov (United States)

    Zhang, Gang; Wang, Ning; Ai, Jian-Chao; Zhang, Lei; Yang, Jing; Liu, Zi-Qi

    2013-02-01

    Jiapigou gold mine, located in the upper Songhua River, was once the largest mine in China due to gold output, where gold extraction with algamation was widely applied to extract gold resulting in severe mercury pollution to ambient environmental medium. In order to study the characteristics of mercury exchange flux between soil (snow) and atmosphere under the snow retention and snow melting control, sampling sites were selected in equal distances along the slope which is situated in the typical hill-valley terrain unit. Mercury exchange flux between soil (snow) and atmosphere was determined with the method of dynamic flux chamber and in all sampling sites the atmosphere concentration from 0 to 150 cm near to the earth in the vertical direction was measured. Furthermore, the impact factors including synchronous meteorology, the surface characteristics under the snow retention and snow melting control and the mercury concentration in vertical direction were also investigated. The results are as follows: During the period of snow retention and melting the air mercury tends to gather towards valley bottom along the slope and an obvious deposit tendency process was found from air to the earth's surface under the control of thermal inversion due to the underlying surface of cold source (snow surface). However, during the period of snow melting, mercury exchange flux between the soil and atmosphere on the surface of the earth with the snow being melted demonstrates alternative deposit and release processes. As for the earth with snow covered, the deposit level of mercury exchange flux between soil and atmosphere is lower than that during the period of snow retention. The relationship between mercury exchange flux and impact factors shows that in snow retention there is a remarkable negative linear correlation between mercury exchange flux and air mercury concentration as well as between the former and the air temperature. In addition, in snow melting mercury exchange

  3. Improvement of Mars surface snow albedo modeling in LMD Mars GCM with SNICAR

    Science.gov (United States)

    Singh, D.; Flanner, M.; Millour, E.

    2017-12-01

    The current version of Laboratoire de Météorologie Dynamique (LMD) Mars GCM (original-MGCM) uses annually repeating (prescribed) albedo values from the Thermal Emission Spectrometer observations. We integrate the Snow, Ice, and Aerosol Radiation (SNICAR) model with MGCM (SNICAR-MGCM) to prognostically determine H2O and CO2 ice cap albedos interactively in the model. Over snow-covered regions mean SNICAR-MGCM albedo is higher by about 0.034 than original-MGCM. Changes in albedo and surface dust content also impact the shortwave energy flux at the surface. SNICAR-MGCM model simulates a change of -1.26 W/m2 shortwave flux on a global scale. Globally, net CO2 ice deposition increases by about 4% over one Martian annual cycle as compared to original-MGCM simulations. SNICAR integration reduces the net mean global surface temperature, and the global surface pressure of Mars by about 0.87% and 2.5% respectively. Changes in albedo also show a similar distribution as dust deposition over the globe. The SNICAR-MGCM model generates albedos with higher sensitivity to surface dust content as compared to original-MGCM. For snow-covered regions, we improve the correlation between albedo and optical depth of dust from -0.91 to -0.97 with SNICAR-MGCM as compared to original-MGCM. Using new diagnostic capabilities with this model, we find that cryospheric surfaces (with dust) increase the global surface albedo of Mars by 0.022. The cryospheric effect is severely muted by dust in snow, however, which acts to decrease the planet-mean surface albedo by 0.06.

  4. The Impact Of Snow Melt On Surface Runoff Of Sava River In Slovenia

    Science.gov (United States)

    Horvat, A.; Brilly, M.; Vidmar, A.; Kobold, M.

    2009-04-01

    Snow is a type of precipitation in the form of crystalline water ice, consisting of a multitude of snowflakes that fall from clouds. Snow remains on the ground until it melts or sublimates. Spring snow melt is a major source of water supply to areas in temperate zones near mountains that catch and hold winter snow, especially those with a prolonged dry summer. In such places, water equivalent is of great interest to water managers wishing to predict spring runoff and the water supply of cities downstream. In temperate zone like in Slovenia the snow melts in the spring and contributes certain amount of water to surface flow. This amount of water can be great and can cause serious floods in case of fast snow melt. For this reason we tried to determine the influence of snow melt on the largest river basin in Slovenia - Sava River basin, on surface runoff. We would like to find out if snow melt in Slovenian Alps can cause spring floods and how serious it can be. First of all we studied the caracteristics of Sava River basin - geology, hydrology, clima, relief and snow conditions in details for each subbasin. Furtermore we focused on snow and described the snow phenomenom in Slovenia, detailed on Sava River basin. We collected all available data on snow - snow water equivalent and snow depth. Snow water equivalent is a much more useful measurement to hydrologists than snow depth, as the density of cool freshly fallen snow widely varies. New snow commonly has a density of between 5% and 15% of water. But unfortunately there is not a lot of available data of SWE available for Slovenia. Later on we compared the data of snow depth and river runoff for some of the 40 winter seasons. Finally we analyzed the use of satellite images for Slovenia to determine the snow cover for hydrology reason. We concluded that snow melt in Slovenia does not have a greater influence on Sava River flow. The snow cover in Alps can melt fast due to higher temperatures but the water distributes

  5. Is Eurasian October snow cover extent increasing?

    International Nuclear Information System (INIS)

    Brown, R D; Derksen, C

    2013-01-01

    A number of recent studies present evidence of an increasing trend in Eurasian snow cover extent (SCE) in the October snow onset period based on analysis of the National Oceanic and Atmospheric Administration (NOAA) historical satellite record. These increases are inconsistent with fall season surface temperature warming trends across the region. Using four independent snow cover data sources (surface observations, two reanalyses, satellite passive microwave retrievals) we show that the increasing SCE is attributable to an internal trend in the NOAA CDR dataset to chart relatively more October snow cover extent over the dataset overlap period (1982–2005). Adjusting the series for this shift results in closer agreement with other independent datasets, stronger correlation with continentally-averaged air temperature anomalies, and a decrease in SCE over 1982–2011 consistent with surface air temperature warming trends over the same period. (letter)

  6. Properties of the surface snow in Princess Elizabeth Land, East Antarctica - climate and non-climate dependent variability of the surface mass balance and stable water isotopic composition

    Science.gov (United States)

    Vladimirova, D.; Ekaykin, A.; Lipenkov, V.; Popov, S. V.; Petit, J. R.; Masson-Delmotte, V.

    2017-12-01

    Glaciological and meteorological observations conducted during the past four decades in Princess Elizabeth Land, East Antarctica, are compiled. The database is used to investigate spatial patterns of surface snow isotopic composition and surface mass balance, including detailed information near subglacial lake Vostok. We show diverse relationships between snow isotopic composition and surface temperature. In the most inland part (elevation 3200-3400 m a.s.l.), surface snow isotopic composition varies independently from surface temperature, and is closely related to the distance to the open water source (with a slope of 0.98±0.17 ‰ per 100 km). Surface mass balance values are higher along the ice sheet slope, and relatively evenly distributed inland. The minimum values of snow isotopic composition and surface mass balance are identified in an area XX km southwestward from Vostok station. The spatial distribution of deuterium excess delineates regions influenced by the Indian Ocean and Pacific Ocean air masses, with Vostok area being situated close to their boundary. Anomalously high deuterium excess values are observed near Dome A, suggesting high kinetic fractionation for its moisture source, or specifically high post-deposition artifacts. The dataset is available for further studies such as the assessment of skills of general circulation or regional atmospheric models, and the search for the oldest ice.

  7. Snow cover as a source of technogenic pollution of surface water during the snow melting period

    OpenAIRE

    Labuzova Olga; Noskova Tatyana; Lysenko Maria; Ovcharenko Elena; Papina Tatyana

    2016-01-01

    The study of pollutants in melt water of snow cover and snow disposal sites in the city of Barnaul showed that during the snow melting period the surface water is not subjected to significant technogenic impact according to a number of studied indices. The oils content is an exception: it can exceed MAC more than 20 times in river- water due to the melting of city disposal sites. Environmental damage due to an oils input into water resources during the snow melting period...

  8. Influence of snow cover distribution on soil temperature and nutrient dynamics in alpine pedoenvironments

    Directory of Open Access Journals (Sweden)

    Ermanno Zanini

    Full Text Available In Alpine sites snow is present on the ground from six to eight months per year in relation to elevation and exposure. Water is therefore immobilized into the solid state for the greater part of the winter season and released to the ground in a short period during spring snowmelt. In these areas, snow distribution exercises a fundamental role in influencing soil temperature and nutrient dynamics, in particular of nitrogen, with great consequences on plant nutrition. The dormant vegetation period, the low temperatures and the persistent snow cover suggest that soil biological activity is only concentrated during summer. As a matter of fact, soils covered with a consistent snow cover are isolated from the air temperature and can not freeze during winter. A snowpack of sufficient thickness, accumulated early in winter, insulates the ground from the surrounding atmosphere maintaining soil temperature closed to 0 °C during the whole winter season. The elevation of the snow line and the shorter permanence of snow on the ground, as a result of global warming (IPCC, 1996, 2001, might reduce the insulation effect of the snowpack, exposing soils of the mountain belt to lower temperatures and to a greater frequency of freeze/thaw cycles, which might alter organic matter dynamics and soil nutrient availability. Such thermal stresses may determine the lysis of microbial cells and the consequent increase of nitrogen and carbon mineralization by the survived microorganisms. Moreover, the freeze/thaw cycles can determine the exposure of exchange surfaces not available before, with release of organic matter of non-microbial origin, which may become available to surviving microorganisms for respiration. The reduced or absent microbial immobilization may cause the accumulation of remarkable amounts of inorganic nitrogen in soil, potentially leachable during spring snowmelt, when plants have not still started the growing season. Changes of snow distribution in

  9. Effects of different temperature treatments on biological ice nuclei in snow samples

    Science.gov (United States)

    Hara, Kazutaka; Maki, Teruya; Kakikawa, Makiko; Kobayashi, Fumihisa; Matsuki, Atsushi

    2016-09-01

    The heat tolerance of biological ice nucleation activity (INA) depends on their types. Different temperature treatments may cause varying degrees of inactivation on biological ice nuclei (IN) in precipitation samples. In this study, we measured IN concentration and bacterial INA in snow samples using a drop freezing assay, and compared the results for unheated snow and snow treated at 40 °C and 90 °C. At a measured temperature of -7 °C, the concentration of IN in untreated snow was 100-570 L-1, whereas the concentration in snow treated at 40 °C and 90 °C was 31-270 L-1 and 2.5-14 L-1, respectively. In the present study, heat sensitive IN inactivated by heating at 40 °C were predominant, and ranged 23-78% of IN at -7 °C compared with untreated samples. Ice nucleation active Pseudomonas strains were also isolated from the snow samples, and heating at 40 °C and 90 °C inactivated these microorganisms. Consequently, different temperature treatments induced varying degrees of inactivation on IN in snow samples. Differences in the concentration of IN across a range of treatment temperatures might reflect the abundance of different heat sensitive biological IN components.

  10. Snow cover as a source of technogenic pollution of surface water during the snow melting period

    Directory of Open Access Journals (Sweden)

    Labuzova Olga

    2016-10-01

    Full Text Available The study of pollutants in melt water of snow cover and snow disposal sites in the city of Barnaul showed that during the snow melting period the surface water is not subjected to significant technogenic impact according to a number of studied indices. The oils content is an exception: it can exceed MAC more than 20 times in river- water due to the melting of city disposal sites. Environmental damage due to an oils input into water resources during the snow melting period can be more than 300000 thousand rubles.

  11. Oxygen isotope variability in snow from western Dronning Maud Land, Antarctica and its relation to temperature

    International Nuclear Information System (INIS)

    Helsen, M.M.; Wal, R.S.W. van de; Broeke, M.R. van den; As, D. van; Reijmer, C.H.; Meijer, H.A.J.

    2005-01-01

    This paper presents (delta) 18 O records from snow pits from four locations in Dronning Maud Land, Antarctica that contain at least four annual cycles. The aim of the study was to analyse in detail these records as well as the prevailing temperatures during accumulation in order to infer to what extent isotopic composition in this area can be interpreted as temperature information. The original seasonal amplitudes of the isotope records were reconstructed by use of a simple back-diffusion model. Automatic weather station data were used to describe the accumulation history and the near-surface temperatures; the temperatures at the atmospheric level of snow formation were inferred from a regional climate model. The results show that the strongly intermittent nature of the accumulation in this area can result in the exclusion of entire seasons from the isotope records. The temperature records also reveal that the oxygen isotope records in these snow pits are biased towards higher temperatures, since snowfall conditions are associated with higher temperatures. This effect is greatest at low temperatures. A comparison between the seasonal extreme isotopic and temperature values points out that on timescales of seasons to several years, isotopic variability cannot be interpreted with confidence as temperature changes at the accumulation sites

  12. Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region

    Science.gov (United States)

    Wang, Wenli; Rinke, Annette; Moore, John C.; Ji, Duoying; Cui, Xuefeng; Peng, Shushi; Lawrence, David M.; McGuire, A. David; Burke, Eleanor J.; Chen, Xiaodong; Delire, Christine; Koven, Charles; MacDougall, Andrew; Saito, Kazuyuki; Zhang, Wenxin; Alkama, Ramdane; Bohn, Theodore J.; Ciais, Philippe; Decharme, Bertrand; Gouttevin, Isabelle; Hajima, Tomohiro; Krinner, Gerhard; Lettenmaier, Dennis P.; Miller, Paul A.; Smith, Benjamin; Sueyoshi, Tetsuo

    2016-01-01

     A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyze simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models and compare them with observations from 268 Russian stations. There are large across-model differences as expressed by simulated differences between near-surface soil and air temperatures, (ΔT), of 3 to 14 K, in the gradients between soil and air temperatures (0.13 to 0.96°C/°C), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, and hence guide improvements to the model’s conceptual structure and process parameterizations. Models with better performance apply multi-layer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (12–16 million km2). However, there is not a simple relationship between the quality of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, likely because several other factors such as differences in the treatment of soil organic matter, soil hydrology, surface energy calculations, and vegetation also provide important controls on simulated permafrost distribution.

  13. Constraining snowmelt in a temperature-index model using simulated snow densities

    KAUST Repository

    Bormann, Kathryn J.

    2014-09-01

    Current snowmelt parameterisation schemes are largely untested in warmer maritime snowfields, where physical snow properties can differ substantially from the more common colder snow environments. Physical properties such as snow density influence the thermal properties of snow layers and are likely to be important for snowmelt rates. Existing methods for incorporating physical snow properties into temperature-index models (TIMs) require frequent snow density observations. These observations are often unavailable in less monitored snow environments. In this study, previous techniques for end-of-season snow density estimation (Bormann et al., 2013) were enhanced and used as a basis for generating daily snow density data from climate inputs. When evaluated against 2970 observations, the snow density model outperforms a regionalised density-time curve reducing biases from -0.027gcm-3 to -0.004gcm-3 (7%). The simulated daily densities were used at 13 sites in the warmer maritime snowfields of Australia to parameterise snowmelt estimation. With absolute snow water equivalent (SWE) errors between 100 and 136mm, the snow model performance was generally lower in the study region than that reported for colder snow environments, which may be attributed to high annual variability. Model performance was strongly dependent on both calibration and the adjustment for precipitation undercatch errors, which influenced model calibration parameters by 150-200%. Comparison of the density-based snowmelt algorithm against a typical temperature-index model revealed only minor differences between the two snowmelt schemes for estimation of SWE. However, when the model was evaluated against snow depths, the new scheme reduced errors by up to 50%, largely due to improved SWE to depth conversions. While this study demonstrates the use of simulated snow density in snowmelt parameterisation, the snow density model may also be of broad interest for snow depth to SWE conversion. Overall, the

  14. Constraining snowmelt in a temperature-index model using simulated snow densities

    KAUST Repository

    Bormann, Kathryn J.; Evans, Jason P.; McCabe, Matthew

    2014-01-01

    Current snowmelt parameterisation schemes are largely untested in warmer maritime snowfields, where physical snow properties can differ substantially from the more common colder snow environments. Physical properties such as snow density influence the thermal properties of snow layers and are likely to be important for snowmelt rates. Existing methods for incorporating physical snow properties into temperature-index models (TIMs) require frequent snow density observations. These observations are often unavailable in less monitored snow environments. In this study, previous techniques for end-of-season snow density estimation (Bormann et al., 2013) were enhanced and used as a basis for generating daily snow density data from climate inputs. When evaluated against 2970 observations, the snow density model outperforms a regionalised density-time curve reducing biases from -0.027gcm-3 to -0.004gcm-3 (7%). The simulated daily densities were used at 13 sites in the warmer maritime snowfields of Australia to parameterise snowmelt estimation. With absolute snow water equivalent (SWE) errors between 100 and 136mm, the snow model performance was generally lower in the study region than that reported for colder snow environments, which may be attributed to high annual variability. Model performance was strongly dependent on both calibration and the adjustment for precipitation undercatch errors, which influenced model calibration parameters by 150-200%. Comparison of the density-based snowmelt algorithm against a typical temperature-index model revealed only minor differences between the two snowmelt schemes for estimation of SWE. However, when the model was evaluated against snow depths, the new scheme reduced errors by up to 50%, largely due to improved SWE to depth conversions. While this study demonstrates the use of simulated snow density in snowmelt parameterisation, the snow density model may also be of broad interest for snow depth to SWE conversion. Overall, the

  15. Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

    Science.gov (United States)

    Adolph, Alden C.; Albert, Mary R.; Hall, Dorothy K.

    2018-03-01

    As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA) meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 °C and a mean bias of -0.4 °C, spanning a range of temperatures from -35 to -5 °C (RMSE = 1.6 °C and mean bias = -0.7 °C prior to cloud masking). For our study area and time series, MODIS surface temperature products agree with skin surface

  16. Low-temperature brown rice storage by using renewable energy from snow

    Energy Technology Data Exchange (ETDEWEB)

    Fujikawa, S.; Kawamura, S.; Fujita, H.; Doi, T.; Okada, K. [Hokkaido Univ., Sapporo, Hokkaido (Japan). Graduate School of Agricultural Science; Homma, K. [Itogumi Construction Co. Ltd, Sapporo, Hokkaido (Japan); Tsuchiya, F. [Obihiro Univ. of Agriculture and Veterinary Medicine, Obihiro, Hokkaido (Japan)

    2010-07-01

    This paper reported on a study that was conducted in Japan to determine whether renewable energy generated from snow can be used to replace the cooling system and electricity used for cooling a rice storehouse that maintained the grain temperature below 15 degrees C. However, the low-temperature storage system required a cooling system and electricity to cool rice in summer. In this study, a snow pile using 890 t of snow was made at the beginning of March next to the rice storehouse. The shape of the snow pile was a trapezium, 17 x 23 m at the bottom and 4 x 10 m at the top and 5 m in height. The snow pile was covered with 200 to 300 mm of wood chips to act as an insulation layer. Approximately 27 per cent of the energy for cooling the rice storehouse could be replaced by using the snow pile in summer. The quality of stored rice was almost similar to that of freshly harvested rice. The study showed that renewable energy generated from snow piles can be used for cooling a high-quality rice storehouse without using electricity.

  17. Snow farming: conserving snow over the summer season

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian; Lehning, Michael

    2018-01-01

    Summer storage of snow for tourism has seen an increasing interest in the last years. Covering large snow piles with materials such as sawdust enables more than two-thirds of the initial snow volume to be conserved. We present detailed mass balance measurements of two sawdust-covered snow piles obtained by terrestrial laser scanning during summer 2015. Results indicate that 74 and 63 % of the snow volume remained over the summer for piles in Davos, Switzerland and Martell, Italy. If snow mass is considered instead of volume, the values increase to 83 and 72 %. The difference is attributed to settling and densification of the snow. Additionally, we adapted the one-dimensional, physically based snow cover model SNOWPACK to perform simulations of the sawdust-covered snow piles. Model results and measurements agreed extremely well at the point scale. Moreover, we analysed the contribution of the different terms of the surface energy balance to snow ablation for a pile covered with a 40 cm thick sawdust layer and a pile without insulation. Short-wave radiation was the dominant source of energy for both scenarios, but the moist sawdust caused strong cooling by long-wave emission and negative sensible and latent heat fluxes. This cooling effect reduces the energy available for melt by up to a factor of 12. As a result only 9 % of the net short-wave energy remained available for melt. Finally, sensitivity studies of the parameters thickness of the sawdust layer, air temperature, precipitation and wind speed were performed. We show that sawdust thickness has a tremendous effect on snow loss. Higher air temperatures and wind speeds increase snow ablation but less significantly. No significant effect of additional precipitation could be found as the sawdust remained wet during the entire summer with the measured quantity of rain. Setting precipitation amounts to zero, however, strongly increased melt. Overall, the 40 cm sawdust provides sufficient protection for mid

  18. Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

    Directory of Open Access Journals (Sweden)

    A. C. Adolph

    2018-03-01

    Full Text Available As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 °C and a mean bias of −0.4 °C, spanning a range of temperatures from −35 to −5 °C (RMSE  =  1.6 °C and mean bias  =  −0.7 °C prior to cloud masking. For our study area and time series

  19. Field observations of the electrostatic charges of blowing snow in Hokkaido, Japan

    Science.gov (United States)

    Omiya, S.; Sato, A.

    2011-12-01

    An electrostatic charge of blowing snow may be a contributing factor in the formation of a snow drift and a snow cornice, and changing of the trajectory of own motion. However, detailed electrification characteristics of blowing snow are not known as there are few reports of charge measurements. We carried out field observations of the electrostatic charges of blowing snow in Tobetsu, Hokkaido, Japan in the mid winter of 2011. An anemovane and a thermohygrometer were used for the meteorological observation. Charge-to-mass ratios of blowing snow were obtained by a Faraday-cage, an electrometer and an electric balance. In this observation period, the air temperature during the blowing snow event was -6.5 to -0.5 degree Celsius. The measured charges in this observation were consistent with the previous studies in sign, which is negative, but they were smaller than the previous one. In most cases, the measured values increased with the temperature decrease, which corresponds with previous studies. However, some results contradicted the tendency, and the maximum value was obtained on the day of the highest air temperature of -0.5 degree Celsius. This discrepancy may be explained from the difference of the snow surface condition on observation day. The day when the maximum value was obtained, the snow surface was covered with old snow, and hard. On the other hand, in many other cases, the snow surface was covered with the fresh snow, and soft. Blowing snow particles on the hard surface can travel longer distance than on the soft one. Therefore, it can be surmised that the hard surface makes the blowing snow particles accumulate a lot of negative charges due to a large number of collisions to the surface. This can be supported by the results of the wind tunnel experiments by Omiya and Sato (2011). By this field observation, it was newly suggested that the electrostatic charge of blowing snow are influenced greatly by the difference of the snow surface condition. REFERENCE

  20. Threshold temperatures mediate the impact of reduced snow cover on overwintering freeze-tolerant caterpillars

    Science.gov (United States)

    Marshall, Katie E.; Sinclair, Brent J.

    2012-01-01

    Decreases in snow cover due to climate change could alter the energetics and physiology of ectothermic animals that overwinter beneath snow, yet how snow cover interacts with physiological thresholds is unknown. We applied numerical simulation of overwintering metabolic rates coupled with field validation to determine the importance of snow cover and freezing to the overwintering lipid consumption of the freeze-tolerant Arctiid caterpillar Pyrrharctia isabella. Caterpillars that overwintered above the snow experienced mean temperatures 1.3°C lower than those below snow and consumed 18.36 mg less lipid of a total 68.97-mg reserve. Simulations showed that linear temperature effects on metabolic rate accounted for only 30% of the difference in lipid consumption. When metabolic suppression by freezing was included, 93% of the difference between animals that overwintered above and below snow was explained. Our results were robust to differences in temperature sensitivity of metabolic rate, changes in freezing point, and the magnitude of metabolic suppression by freezing. The majority of the energy savings was caused by the non-continuous reduction in metabolic rate due to freezing, the first example of the importance of temperature thresholds in the lipid use of overwintering insects.

  1. Brightness temperature simulation of snow cover based on snow grain size evolution using in situ data

    Science.gov (United States)

    Wu, Lili; Li, Xiaofeng; Zhao, Kai; Zheng, Xingming; Jiang, Tao

    2016-07-01

    Snow depth parameter inversion from passive microwave remote sensing is of great significance to hydrological process and climate systems. The Helsinki University of Technology (HUT) model is a commonly used snow emission model. Snow grain size (SGS) is one of the important input parameters, but SGS is difficult to obtain in broad areas. The time series of SGS are first evolved by an SGS evolution model (Jordan 91) using in situ data. A good linear relationship between the effective SGS in HUT and the evolution SGS was found. Then brightness temperature simulations are performed based on the effective SGS and evolution SGS. The results showed that the biases of the simulated brightness temperatures based on the effective SGS and evolution SGS were -6.5 and -3.6 K, respectively, for 18.7 GHz and -4.2 and -4.0 K for 36.5 GHz. Furthermore, the model is performed in six pixels with different land use/cover type in other areas. The results showed that the simulated brightness temperatures based on the evolution SGS were consistent with those from the satellite. Consequently, evolution SGS appears to be a simple method to obtain an appropriate SGS for the HUT model.

  2. EFFECT OF PHOTODESORPTION ON THE SNOW LINES AT THE SURFACE OF OPTICALLY THICK CIRCUMSTELLAR DISKS AROUND HERBIG Ae/Be STARS

    International Nuclear Information System (INIS)

    Oka, Akinori; Nakamoto, Taishi; Inoue, Akio K.; Honda, Mitsuhiko

    2012-01-01

    We investigate the effect of photodesorption on the snow line position at the surface of a protoplanetary disk around a Herbig Ae/Be star, motivated by the detection of water ice particles at the surface of the disk around HD142527 by Honda et al. For this aim, we obtain the density and temperature structure in the disk with a 1+1D radiative transfer and determine the distribution of water ice particles in the disk by the balance between condensation, sublimation, and photodesorption. We find that photodesorption induced by far-ultraviolet radiation from the central star depresses the ice-condensation front toward the mid-plane and pushes the surface snow line significantly outward when the stellar effective temperature exceeds a certain critical value. This critical effective temperature depends on the stellar luminosity and mass, the water abundance in the disk, and the yield of photodesorption. We present an approximate analytic formula for the critical temperature. We separate Herbig Ae/Be stars into two groups on the HR diagram according to the critical temperature: one is the disks where photodesorption is effective and from which we may not find ice particles at the surface, and the other is the disks where photodesorption is not effective. We estimate the snow line position at the surface of the disk around HD142527 to be 100-300 AU, which is consistent with the water ice detection at >140 AU in the disk. All the results depend on the dust grain size in a complex way, and this point requires more work in the future.

  3. Sensitivity of Support Vector Machine Predictions of Passive Microwave Brightness Temperature Over Snow-covered Terrain in High Mountain Asia

    Science.gov (United States)

    Ahmad, J. A.; Forman, B. A.

    2017-12-01

    High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.

  4. Diurnal variations in the UV albedo of arctic snow

    Directory of Open Access Journals (Sweden)

    O. Meinander

    2008-11-01

    Full Text Available The relevance of snow for climate studies is based on its physical properties, such as high surface reflectivity. Surface ultraviolet (UV albedo is an essential parameter for various applications based on radiative transfer modeling. Here, new continuous measurements of the local UV albedo of natural Arctic snow were made at Sodankylä (67°22'N, 26°39'E, 179 m a.s.l. during the spring of 2007. The data were logged at 1-min intervals. The accumulation of snow was up to 68 cm. The surface layer thickness varied from 0.5 to 35 cm with the snow grain size between 0.2 and 2.5 mm. The midday erythemally weighted UV albedo ranged from 0.6 to 0.8 in the accumulation period, and from 0.5 to 0.7 during melting. During the snow melt period, under cases of an almost clear sky and variable cloudiness, an unexpected diurnal decrease of 0.05 in albedo soon after midday, and recovery thereafter, was detected. This diurnal decrease in albedo was found to be asymmetric with respect to solar midday, thus indicating a change in the properties of the snow. Independent UV albedo results with two different types of instruments confirm these findings. The measured temperature of the snow surface was below 0°C on the following mornings. Hence, the reversible diurnal change, evident for ~1–2 h, could be explained by the daily metamorphosis of the surface of the snowpack, in which the temperature of the surface increases, melting some of the snow to liquid water, after which the surface freezes again.

  5. Sulphur dioxide removal by turbulent transfer over grass, snow, and water surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Whelpdale, D M; Shaw, R W

    1974-01-01

    Vertical gradients of sulphur dioxide concentration have been measured over grass, snow, and water surfaces in order to assess the importance of these surfaces as SO/sub 2/ sinks. Concentrations were usually found to be lower near the surface indicating that removal occurs there. Vertical concentration gradients, normalized with repect to the concentration at 8 m, were generally greatest over water and least over snow, independent of meteorological conditions, suggesting that a water surface is the strongest SO/sub 2/ sink, with grass next, and snow weakest. The turbulent transfer of SO/sub 2/ to the interface is discussed in relation to stability of the lower atmosphere and physical and chemical properties of the surfaces. Using a bulk aerodynamic transfer approach similar to that for water vapour, values of SO/sub 2/ flux averaged over periods of from one to several hours were found to be of the order of 1 microgram/M/sup 2//S to the water and grass surfaces, and an order of magnitude smaller to the snow surface. Deposition velocities were found to be of the order of 1 cm/s.

  6. Surprisingly small HONO emissions from snow surfaces at Browning Pass, Antarctica

    Directory of Open Access Journals (Sweden)

    H. J. Beine

    2006-01-01

    Full Text Available Measured Fluxes of nitrous acid at Browning Pass, Antarctica were very low, despite conditions that are generally understood as favorable for HONO emissions, including: acidic snow surfaces, an abundance of NO3- anions in the snow surface, and abundant UV light for NO3- photolysis. Photochemical modeling suggests noon time HONO fluxes of 5–10 nmol m-2 h-1; the measured fluxes, however, were close to zero throughout the campaign. The location and state of NO3- in snow is crucial to its reactivity. The analysis of soluble mineral ions in snow reveals that the NO3- ion is probably present in aged snows as NaNO3. This is peculiar to our study site, and we suggest that this may affect the photochemical reactivity of NO3-, by preventing the release of products, or providing a reactive medium for newly formed HONO. In fresh snow, the NO3- ion is probably present as dissolved or adsorbed HNO3 and yet, no HONO emissions were observed. We speculate that HONO formation from NO3- photolysis may involve electron transfer reactions of NO2 from photosensitized organics and that fresh snows at our site had insufficient concentrations of adequate organic compounds to favor this reaction.

  7. Quasi-steady temperature gradient metamorphism in idealized, dry snow

    International Nuclear Information System (INIS)

    Christon, M.

    1994-01-01

    A three-dimensional model for heat and mass transport in microscale ice lattices of dry snow is formulated consistent with conservation laws and solid-vapor interface constraints. A finite element model that employs continuous mesh deformation is developed, and calculation of the effective diffusion rates in snow, metamorphosing under a temperature gradient, is performed. Results of the research provide basic insight into the movement of heat and water vapor in seasonal snowcovers. Agreement between the numerical results and measured data of effective thermal conductivity is excellent. The enhancement to the water vapor diffusion rate in snow is bracketed in the range of 1.05--2.0 times that of water vapor in dry air

  8. MODIS Snow and Sea Ice Products

    Science.gov (United States)

    Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

    2004-01-01

    In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

  9. Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

    Directory of Open Access Journals (Sweden)

    S. Naha

    2016-06-01

    Full Text Available The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006. Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I and Ensemble Kalman Filter (EnKF that uses observations of snow covered area (SCA to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU, rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated

  10. Effects of dirty snow in nuclear winter simulations

    International Nuclear Information System (INIS)

    Vogelmann, A.M.; Robock, A.; Ellingson, R.G.

    1988-01-01

    A large-scale nuclear war would inject smoke into the atmosphere from burning forests, cities, and industries in targeted areas. This smoke could fall out onto snow and ice and would lower cryospheric albedos by as much as 50%. A global energy balance climate model is used to investigate the maximum effect these ''dirty snow'' albedos have on the surface temperature in nuclear winter simulations which span several years. These effects are investigated for different nuclear winter scenarios, snow precipitation rates, latitudinal distributions of smoke, and seasonal timings. We find that dirty snow, in general, would have a small temperature effect at mid- and low latitudes but could have a large temperature effect at polar latitudes, particularly if the soot is able to reappear significantly in later summers. Factors which limit the climatic importance of the dirty snow are (1) the dirty snow albedo is lowest when the atmosphere still contains a large amount of light-absorbing smoke; (2) even with dirty snow, sea ice areas can still increase, which helps maintain colder temperatures through the sea ice thermal inertial feedback; (3) the snow and ice areas affected by the dirty snow albedos are largest when there is little seasonal solar insolation; and (4) the area affected by the dirty snow is relatively small under all circumstances. copyright American Geophysical Union 1988

  11. Constraining the Surface Energy Balance of Snow in Complex Terrain

    Science.gov (United States)

    Lapo, Karl E.

    values and coupled land-atmosphere models have difficulty representing these processes. We developed a new method analyzing turbulent fluxes at the land surface that relies on using the observed surface temperature, which we called the offline turbulence method. We used this method to test a number of stability schemes as they are implemented within land models. Stability schemes can cause small biases in the simulated sensible heat flux, but these are caused by compensating errors, as no single method was able to accurately reproduce the observed distribution of the sensible heat flux. We described how these turbulence schemes perform within different turbulence regimes, particularly noting the difficulty representing turbulence during conditions with faster wind speeds and the transition between weak and strong wind turbulence regimes. Heterogeneity in the horizontal distribution of surface temperature associated with different land surface types likely explains some of the missing physics within land models and is manifested as counter-gradient fluxes in observations. The coupling of land and atmospheric models needs further attention, as we highlight processes that are missing. Expanding on the utility of surface temperature, Ts, in model evaluations, we demonstrated the utility of using surface temperature in snow models evaluations. Ts is the diagnostic variable of the modeled surface energy balance within physically-based models and is an ideal supplement to traditional evaluation techniques. We demonstrated how modeling decisions affect Ts, specifically testing the impact of vertical layer structure, thermal conductivity, and stability corrections in addition to the effect of uncertainty in forcing data on simulated Ts. The internal modeling decisions had minimal impacts relative to uncertainty in the forcing data. Uncertainty in downwelling longwave was found to have the largest impact on simulated Ts. Using Ts, we demonstrated how various errors in the forcing

  12. Surface Snow Density of East Antarctica Derived from In-Situ Observations

    Science.gov (United States)

    Tian, Y.; Zhang, S.; Du, W.; Chen, J.; Xie, H.; Tong, X.; Li, R.

    2018-04-01

    Models based on physical principles or semi-empirical parameterizations have used to compute the firn density, which is essential for the study of surface processes in the Antarctic ice sheet. However, parameterization of surface snow density is often challenged by the description of detailed local characterization. In this study we propose to generate a surface density map for East Antarctica from all the filed observations that are available. Considering that the observations are non-uniformly distributed around East Antarctica, obtained by different methods, and temporally inhomogeneous, the field observations are used to establish an initial density map with a grid size of 30 × 30 km2 in which the observations are averaged at a temporal scale of five years. We then construct an observation matrix with its columns as the map grids and rows as the temporal scale. If a site has an unknown density value for a period, we will set it to 0 in the matrix. In order to construct the main spatial and temple information of surface snow density matrix we adopt Empirical Orthogonal Function (EOF) method to decompose the observation matrix and only take first several lower-order modes, because these modes already contain most information of the observation matrix. However, there are a lot of zeros in the matrix and we solve it by using matrix completion algorithm, and then we derive the time series of surface snow density at each observation site. Finally, we can obtain the surface snow density by multiplying the modes interpolated by kriging with the corresponding amplitude of the modes. Comparative analysis have done between our surface snow density map and model results. The above details will be introduced in the paper.

  13. The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

    Science.gov (United States)

    Kelly, R. E. J.; Saberi, N.; Li, Q.

    2017-12-01

    With moderate to high spatial resolution (observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides SWE estimates that are independent of real or near real

  14. Evaluation of North Eurasian snow-off dates in the ECHAM5.4 atmospheric general circulation model

    Directory of Open Access Journals (Sweden)

    P. Räisänen

    2014-12-01

    Full Text Available The timing of springtime end of snowmelt (snow-off date in northern Eurasia in version 5.4 of the ECHAM5 atmospheric general circulation model (GCM is evaluated through comparison with a snow-off date data set based on space-borne microwave radiometer measurements and with Russian snow course data. ECHAM5 reproduces well the observed gross geographical pattern of snow-off dates, with earliest snow-off (in March in the Baltic region and latest snow-off (in June in the Taymyr Peninsula and in northeastern parts of the Russian Far East. The primary biases are (1 a delayed snow-off in southeastern Siberia (associated with too low springtime temperature and too high surface albedo, in part due to insufficient shielding by canopy; and (2 an early bias in the western and northern parts of northern Eurasia. Several sensitivity experiments were conducted, where biases in simulated atmospheric circulation were corrected through nudging and/or the treatment of surface albedo was modified. While this alleviated some of the model biases in snow-off dates, 2 m temperature and surface albedo, especially the early bias in snow-off in the western parts of northern Eurasia proved very robust and was actually larger in the nudged runs. A key issue underlying the snow-off biases in ECHAM5 is that snowmelt occurs at too low temperatures. Very likely, this is related to the treatment of the surface energy budget. On one hand, the surface temperature Ts is not computed separately for the snow-covered and snow-free parts of the grid cells, which prevents Ts from rising above 0 °C before all snow has vanished. Consequently, too much of the surface net radiation is consumed in melting snow and too little in heating the air. On the other hand, ECHAM5 does not include a canopy layer. Thus, while the albedo reduction due to canopy is accounted for, the shielding of snow on ground by the overlying canopy is not considered, which leaves too much solar radiation available for

  15. A distributed snow-evolution modeling system (SnowModel)

    Science.gov (United States)

    Glen E. Liston; Kelly. Elder

    2006-01-01

    SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...

  16. Snow multivariable data assimilation for hydrological predictions in mountain areas

    Science.gov (United States)

    Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

    2016-04-01

    The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

  17. Spatiotemporal variability in surface energy balance across tundra, snow and ice in Greenland

    DEFF Research Database (Denmark)

    Lund, Magnus; Stiegler, Christian; Abermann, Jakob

    2017-01-01

    The surface energy balance (SEB) is essential for understanding the coupled cryosphere–atmosphere system in the Arctic. In this study, we investigate the spatiotemporal variability in SEB across tundra, snow and ice. During the snow-free period, the main energy sink for ice sites is surface melt....... For tundra, energy is used for sensible and latent heat flux and soil heat flux leading to permafrost thaw. Longer snow-free period increases melting of the Greenland Ice Sheet and glaciers and may promote tundra permafrost thaw. During winter, clouds have a warming effect across surface types whereas during...

  18. A Distributed Snow Evolution Modeling System (SnowModel)

    Science.gov (United States)

    Liston, G. E.; Elder, K.

    2004-12-01

    A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.

  19. Robot Towed Shortwave Infrared Camera for Specific Surface Area Retrieval of Surface Snow

    Science.gov (United States)

    Elliott, J.; Lines, A.; Ray, L.; Albert, M. R.

    2017-12-01

    Optical grain size and specific surface area are key parameters for measuring the atmospheric interactions of snow, as well as tracking metamorphosis and allowing for the ground truthing of remote sensing data. We describe a device using a shortwave infrared camera with changeable optical bandpass filters (centered at 1300 nm and 1550 nm) that can be used to quickly measure the average SSA over an area of 0.25 m^2. The device and method are compared with calculations made from measurements taken with a field spectral radiometer. The instrument is designed to be towed by a small autonomous ground vehicle, and therefore rides above the snow surface on ultra high molecular weight polyethylene (UHMW) skis.

  20. Objective Characterization of Snow Microstructure for Microwave Emission Modeling

    Science.gov (United States)

    Durand, Michael; Kim, Edward J.; Molotch, Noah P.; Margulis, Steven A.; Courville, Zoe; Malzler, Christian

    2012-01-01

    Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter.

  1. Snow contribution to springtime atmospheric predictability over the second half of the twentieth century

    Energy Technology Data Exchange (ETDEWEB)

    Peings, Yannick [CNRM-GAME, Meteo-France et CNRS, Toulouse (France); CNRM/GMGEC/VDR, Toulouse (France); Douville, H.; Alkama, R.; Decharme, B. [CNRM-GAME, Meteo-France et CNRS, Toulouse (France)

    2011-09-15

    A set of global atmospheric simulations has been performed with the ARPEGE-Climat model in order to quantify the contribution of realistic snow conditions to seasonal atmospheric predictability in addition to that of a perfect sea surface temperature (SST) forcing. The focus is on the springtime boreal hemisphere where the combination of a significant snow cover variability and an increasing solar radiation favour the potential snow influence on the surface energy budget. The study covers the whole 1950-2000 period through the use of an original snow mass reanalysis based on an off-line land surface model and possibly constrained by satellite snow cover observations. Two ensembles of 10-member AMIP-type experiments have been first performed with relaxed versus free snow boundary conditions. The nudging towards the monthly snow mass reanalysis significantly improves both potential and actual predictability of springtime surface air temperature over Central Europe and North America. Yet, the impact is confined to the lower troposphere and there is no clear improvement in the predictability of the large-scale atmospheric circulation. Further constraining the prescribed snow boundary conditions with satellite observations does not change much the results. Finally, using the snow reanalysis only for initializing the model on March 1st also leads to a positive impact on predicted low-level temperatures but with a weaker amplitude and persistence. A conditional skill approach as well as some selected case studies provide some guidelines for interpreting these results and suggest that an underestimated snow cover variability and a misrepresentation of ENSO teleconnections may hamper the benefit of an improved snow initialization in the ARPEGE-Climat model. (orig.)

  2. Snow model design for operational purposes

    Science.gov (United States)

    Kolberg, Sjur

    2017-04-01

    A parsimonious distributed energy balance snow model intended for operational use is evaluated using discharge, snow covered area and grain size; the latter two as observed from the MODIS sensor. The snow model is an improvement of the existing GamSnow model, which is a part of the Enki modelling framework. Core requirements for the new version have been: 1. Reduction of calibration freedom, motivated by previous experience of non-identifiable parameters in the existing version 2. Improvement of process representation based on recent advances in physically based snow modelling 3. Limiting the sensitivity to forcing data which are poorly known over the spatial domain of interest (often in mountainous areas) 4. Preference for observable states, and the ability to improve from updates. The albedo calculation is completely revised, now based on grain size through an emulation of the SNICAR model (Flanner and Zender, 2006; Gardener and Sharp, 2010). The number of calibration parameters in the albedo model is reduced from 6 to 2. The wind function governing turbulent energy fluxes has been reduced from 2 to 1 parameter. Following Raleigh et al (2011), snow surface radiant temperature is split from the top layer thermodynamic temperature, using bias-corrected wet-bulb temperature to model the former. Analyses are ongoing, and the poster will bring evaluation results from 16 years of MODIS observations and more than 25 catchments in southern Norway.

  3. Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEP CFSv2

    Science.gov (United States)

    Saha, Subodh Kumar; Sujith, K.; Pokhrel, Samir; Chaudhari, Hemantkumar S.; Hazra, Anupam

    2017-03-01

    The Noah version 2.7.1 is a moderately complex land surface model (LSM), with a single layer snowpack, combined with vegetation and underlying soil layer. Many previous studies have pointed out biases in the simulation of snow, which may hinder the skill of a forecasting system coupled with the Noah. In order to improve the simulation of snow by the Noah, a multilayer snow scheme (up to a maximum of six layers) is introduced. As Noah is the land surface component of the Climate Forecast System version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP), the modified Noah is also coupled with the CFSv2. The offline LSM shows large improvements in the simulation of snow depth, snow water equivalent (SWE), and snow cover area during snow season (October to June). CFSv2 with the modified Noah reveals a dramatic improvements in the simulation of snow depth and 2 m air temperature and moderate improvements in SWE. As suggested in the previous diagnostic and sensitivity study, improvements in the simulation of snow by CFSv2 have lead to the reduction in dry bias over the Indian subcontinent (by a maximum of 2 mm d-1). The multilayer snow scheme shows promising results in the simulation of snow as well as Indian summer monsoon rainfall and hence this development may be the part of the future version of the CFS.

  4. Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

    Science.gov (United States)

    Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

    2007-12-01

    Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

  5. Testing Snow Melt Algorithms in High Relief Topography Using Calibrated Enhanced-Resolution Brightness Temperatures, Hunza River Basin, Pakistan

    Science.gov (United States)

    Ramage, J. M.; Brodzik, M. J.; Hardman, M.; Troy, T. J.

    2017-12-01

    Snow is a vital part of the terrestrial hydrological cycle, a crucial resource for people and ecosystems. In mountainous regions snow is extensive, variable, and challenging to document. Snow melt timing and duration are important factors affecting the transfer of snow mass to soil moisture and runoff. Passive microwave brightness temperature (Tb) changes at 36 and 18 GHz are a sensitive way to detect snow melt onset due to their sensitivity to the abrupt change in emissivity. They are widely used on large icefields and high latitude watersheds. The coarse resolution ( 25 km) of historically available data has precluded effective use in high relief, heterogeneous regions, and gaps between swaths also create temporal data gaps at lower latitudes. New enhanced resolution data products generated from a scatterometer image reconstruction for radiometer (rSIR) technique are available at the original frequencies. We use these Calibrated Enhanced-resolution Brightness (CETB) Temperatures Earth System Data Records (ESDR) to evaluate existing snow melt detection algorithms that have been used in other environments, including the cross polarized gradient ratio (XPGR) and the diurnal amplitude variations (DAV) approaches. We use the 36/37 GHz (3.125 km resolution) and 18/19 GHz (6.25 km resolution) vertically and horizontally polarized datasets from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Radiometer for EOS (AMSR-E) and evaluate them for use in this high relief environment. The new data are used to assess glacier and snow melt records in the Hunza River Basin [area 13,000 sq. km, located at 36N, 74E], a tributary to the Upper Indus Basin, Pakistan. We compare the melt timing results visually and quantitatively to the corresponding EASE-Grid 2.0 25-km dataset, SRTM topography, and surface temperatures from station and reanalysis data. The new dataset is coarser than the topography, but is able to differentiate signals of melt/refreeze timing for

  6. Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017

    Science.gov (United States)

    Revuelto, Jesús; Azorin-Molina, Cesar; Alonso-González, Esteban; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Rico, Ibai; López-Moreno, Juan Ignacio

    2017-12-01

    This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The experimental site is located on the southern side of the Pyrenees between 2000 and 2300 m above sea level, covering an area of 55 ha. The site is a good example of a subalpine environment in which the evolution of snow accumulation and melt are of major importance in many mountain processes. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner (TLS, lidar technology) for certain dates across the snow season (between three and six TLS surveys per snow season) and (iii) time-lapse images showing the evolution of the snow-covered area (SCA). The meteorological variables acquired at the AWS are precipitation, air temperature, incoming and reflected solar radiation, infrared surface temperature, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface), and soil temperature; all were taken at 10 min intervals. Snow depth distribution was measured during 23 field campaigns using a TLS, and daily information on the SCA was also retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.848277) is valuable since it provides high-spatial-resolution information on the snow depth and snow cover, which is particularly useful when combined with meteorological variables to simulate snow energy and mass balance. This information has already been analyzed in various scientific studies on snow pack dynamics and its interaction with the local climatology or topographical characteristics. However, the database generated has great potential for understanding other environmental processes from a hydrometeorological or ecological perspective in which snow dynamics play a

  7. Distributed snow modeling suitable for use with operational data for the American River watershed.

    Science.gov (United States)

    Shamir, E.; Georgakakos, K. P.

    2004-12-01

    The mountainous terrain of the American River watershed (~4300 km2) at the Western slope of the Northern Sierra Nevada is subject to significant variability in the atmospheric forcing that controls the snow accumulation and ablations processes (i.e., precipitation, surface temperature, and radiation). For a hydrologic model that attempts to predict both short- and long-term streamflow discharges, a plausible description of the seasonal and intermittent winter snow pack accumulation and ablation is crucial. At present the NWS-CNRFC operational snow model is implemented in a semi distributed manner (modeling unit of about 100-1000 km2) and therefore lump distinct spatial variability of snow processes. In this study we attempt to account for the precipitation, temperature, and radiation spatial variability by constructing a distributed snow accumulation and melting model suitable for use with commonly available sparse data. An adaptation of the NWS-Snow17 energy and mass balance that is used operationally at the NWS River Forecast Centers is implemented at 1 km2 grid cells with distributed input and model parameters. The input to the model (i.e., precipitation and surface temperature) is interpolated from observed point data. The surface temperature was interpolated over the basin based on adiabatic lapse rates using topographic information whereas the precipitation was interpolated based on maps of climatic mean annual rainfall distribution acquired from PRISM. The model parameters that control the melting rate due to radiation were interpolated based on aspect. The study was conducted for the entire American basin for the snow seasons of 1999-2000. Validation of the Snow Water Equivalent (SWE) prediction is done by comparing to observation from 12 snow Sensors. The Snow Cover Area (SCA) prediction was evaluated by comparing to remotely sensed 500m daily snow cover derived from MODIS. The results that the distribution of snow over the area is well captured and the

  8. Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

    Science.gov (United States)

    Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

    2000-12-01

    The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air

  9. Gaseous elemental mercury (GEM emissions from snow surfaces in northern New York.

    Directory of Open Access Journals (Sweden)

    J Alexander Maxwell

    Full Text Available Snow surface-to-air exchange of gaseous elemental mercury (GEM was measured using a modified Teflon fluorinated ethylene propylene (FEP dynamic flux chamber (DFC in a remote, open site in Potsdam, New York. Sampling was conducted during the winter months of 2011. The inlet and outlet of the DFC were coupled with a Tekran Model 2537A mercury (Hg vapor analyzer using a Tekran Model 1110 two port synchronized sampler. The surface GEM flux ranged from -4.47 ng m(-2 hr(-1 to 9.89 ng m(-2 hr(-1. For most sample periods, daytime GEM flux was strongly correlated with solar radiation. The average nighttime GEM flux was slightly negative and was not well correlated with any of the measured meteorological variables. Preliminary, empirical models were developed to estimate GEM emissions from snow surfaces in northern New York. These models suggest that most, if not all, of the Hg deposited with and to snow is reemitted to the atmosphere.

  10. Gaseous elemental mercury (GEM) emissions from snow surfaces in northern New York.

    Science.gov (United States)

    Maxwell, J Alexander; Holsen, Thomas M; Mondal, Sumona

    2013-01-01

    Snow surface-to-air exchange of gaseous elemental mercury (GEM) was measured using a modified Teflon fluorinated ethylene propylene (FEP) dynamic flux chamber (DFC) in a remote, open site in Potsdam, New York. Sampling was conducted during the winter months of 2011. The inlet and outlet of the DFC were coupled with a Tekran Model 2537A mercury (Hg) vapor analyzer using a Tekran Model 1110 two port synchronized sampler. The surface GEM flux ranged from -4.47 ng m(-2) hr(-1) to 9.89 ng m(-2) hr(-1). For most sample periods, daytime GEM flux was strongly correlated with solar radiation. The average nighttime GEM flux was slightly negative and was not well correlated with any of the measured meteorological variables. Preliminary, empirical models were developed to estimate GEM emissions from snow surfaces in northern New York. These models suggest that most, if not all, of the Hg deposited with and to snow is reemitted to the atmosphere.

  11. Study of critical free-area ratio during the snow-melting process on pavement using low-temperature heating fluids

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Huajun [School of Energy and Environment Engineering, Hebei University of Technology, Tianjin 300401 (China); Chen, Zhihao [Faculty of Engineering, Yokohama National University, Hodogaya, Yokohama 240-8501 (Japan)

    2009-01-15

    Critical free-area ratio (CFR) is an interesting phenomenon during the snow-melting process on pavement using low-temperature heating fluids such as geothermal tail water and industrial waste water. This paper is performed to further investigate the mechanism of CFR and its influencing factors. A simplified theoretical model is presented to describe the heat and mass transfer process on pavement. Especially the variation of thermal properties and the capillary effect of snow layer are considered. Numerical computation shows that the above theoretical model is effective for the prediction of CFR during the snow-melting process. Furthermore, the mechanism of CFR is clarified in detail. CFR is independent of the layout of hydronic pipes, the fluid temperature, the idling time, and weather conditions. It is both the non-uniform temperature distribution and complicated porous structure of snow layer that lead to the occurrence of CFR. Besides, the influences of operation parameters including the fluid temperature, the idling time, the pipe spacing and buried depths on snow melting are analyzed, which are helpful for the next optimal design of snow-melting system. (author)

  12. Study of critical free-area ratio during the snow-melting process on pavement using low-temperature heating fluids

    Energy Technology Data Exchange (ETDEWEB)

    Wang Huajun [School of Energy and Environment Engineering, Hebei University of Technology, Tianjin 300401 (China)], E-mail: huajunwang@126.com; Chen Zhihao [Faculty of Engineering, Yokohama National University, Hodogaya, Yokohama 240-8501 (Japan)

    2009-01-15

    Critical free-area ratio (CFR) is an interesting phenomenon during the snow-melting process on pavement using low-temperature heating fluids such as geothermal tail water and industrial waste water. This paper is performed to further investigate the mechanism of CFR and its influencing factors. A simplified theoretical model is presented to describe the heat and mass transfer process on pavement. Especially the variation of thermal properties and the capillary effect of snow layer are considered. Numerical computation shows that the above theoretical model is effective for the prediction of CFR during the snow-melting process. Furthermore, the mechanism of CFR is clarified in detail. CFR is independent of the layout of hydronic pipes, the fluid temperature, the idling time, and weather conditions. It is both the non-uniform temperature distribution and complicated porous structure of snow layer that lead to the occurrence of CFR. Besides, the influences of operation parameters including the fluid temperature, the idling time, the pipe spacing and buried depths on snow melting are analyzed, which are helpful for the next optimal design of snow-melting system.

  13. Study of critical free-area ratio during the snow-melting process on pavement using low-temperature heating fluids

    International Nuclear Information System (INIS)

    Wang Huajun; Chen Zhihao

    2009-01-01

    Critical free-area ratio (CFR) is an interesting phenomenon during the snow-melting process on pavement using low-temperature heating fluids such as geothermal tail water and industrial waste water. This paper is performed to further investigate the mechanism of CFR and its influencing factors. A simplified theoretical model is presented to describe the heat and mass transfer process on pavement. Especially the variation of thermal properties and the capillary effect of snow layer are considered. Numerical computation shows that the above theoretical model is effective for the prediction of CFR during the snow-melting process. Furthermore, the mechanism of CFR is clarified in detail. CFR is independent of the layout of hydronic pipes, the fluid temperature, the idling time, and weather conditions. It is both the non-uniform temperature distribution and complicated porous structure of snow layer that lead to the occurrence of CFR. Besides, the influences of operation parameters including the fluid temperature, the idling time, the pipe spacing and buried depths on snow melting are analyzed, which are helpful for the next optimal design of snow-melting system

  14. Impacts of Synoptic Weather Patterns on Snow Albedo at Sites in New England

    Science.gov (United States)

    Adolph, A. C.; Albert, M. R.; Lazarcik, J.; Dibb, J. E.; Amante, J.; Price, A. N.

    2015-12-01

    Winter snow in the northeastern United States has changed over the last several decades, resulting in shallower snow packs, fewer days of snow cover and increasing precipitation falling as rain in the winter. In addition to these changes which cause reductions in surface albedo, increasing winter temperatures also lead to more rapid snow grain growth, resulting in decreased snow reflectivity. We present in-situ measurements and analyses to test the sensitivity of seasonal snow albedo to varying weather conditions at sites in New England. In particular, we investigate the impact of temperature on snow albedo through melt and grain growth, the impact of precipitation event frequency on albedo through snow "freshening," and the impact of storm path on snow structure and snow albedo. Over three winter seasons between 2013 and 2015, in-situ snow characterization measurements were made at three non-forested sites across New Hampshire. These near-daily measurements include spectrally resolved albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density and local meteorological parameters. Combining this information with storm tracks derived from HYSPLIT modeling, we quantify the current sensitivity of northeastern US snow albedo to temperature as well as precipitation type, frequency and path. Our analysis shows that southerly winter storms result in snow with a significantly lower albedo than storms which come from across the continental US or the Atlantic Ocean. Interannual variability in temperature and statewide spatial variability in snowfall rates at our sites show the relative importance of snowfall amount and temperatures in albedo evolution over the course of the winter.

  15. Satellite-derived, melt-season surface temperature of the Greenland Ice Sheet (2000-2005) and its relationship to mass balance

    Science.gov (United States)

    Hall, D.K.; Williams, R.S.; Casey, K.A.; DiGirolamo, N.E.; Wan, Z.

    2006-01-01

    Mean, clear-sky surface temperature of the Greenland Ice Sheet was measured for each melt season from 2000 to 2005 using Moderate-Resolution Imaging Spectroradiometer (MODIS)–derived land-surface temperature (LST) data-product maps. During the period of most-active melt, the mean, clear-sky surface temperature of the ice sheet was highest in 2002 (−8.29 ± 5.29°C) and 2005 (−8.29 ± 5.43°C), compared to a 6-year mean of −9.04 ± 5.59°C, in agreement with recent work by other investigators showing unusually extensive melt in 2002 and 2005. Surface-temperature variability shows a correspondence with the dry-snow facies of the ice sheet; a reduction in area of the dry-snow facies would indicate a more-negative mass balance. Surface-temperature variability generally increased during the study period and is most pronounced in the 2005 melt season; this is consistent with surface instability caused by air-temperature fluctuations.

  16. NOAA's National Snow Analyses

    Science.gov (United States)

    Carroll, T. R.; Cline, D. W.; Olheiser, C. M.; Rost, A. A.; Nilsson, A. O.; Fall, G. M.; Li, L.; Bovitz, C. T.

    2005-12-01

    NOAA's National Operational Hydrologic Remote Sensing Center (NOHRSC) routinely ingests all of the electronically available, real-time, ground-based, snow data; airborne snow water equivalent data; satellite areal extent of snow cover information; and numerical weather prediction (NWP) model forcings for the coterminous U.S. The NWP model forcings are physically downscaled from their native 13 km2 spatial resolution to a 1 km2 resolution for the CONUS. The downscaled NWP forcings drive an energy-and-mass-balance snow accumulation and ablation model at a 1 km2 spatial resolution and at a 1 hour temporal resolution for the country. The ground-based, airborne, and satellite snow observations are assimilated into the snow model's simulated state variables using a Newtonian nudging technique. The principle advantages of the assimilation technique are: (1) approximate balance is maintained in the snow model, (2) physical processes are easily accommodated in the model, and (3) asynoptic data are incorporated at the appropriate times. The snow model is reinitialized with the assimilated snow observations to generate a variety of snow products that combine to form NOAA's NOHRSC National Snow Analyses (NSA). The NOHRSC NSA incorporate all of the available information necessary and available to produce a "best estimate" of real-time snow cover conditions at 1 km2 spatial resolution and 1 hour temporal resolution for the country. The NOHRSC NSA consist of a variety of daily, operational, products that characterize real-time snowpack conditions including: snow water equivalent, snow depth, surface and internal snowpack temperatures, surface and blowing snow sublimation, and snowmelt for the CONUS. The products are generated and distributed in a variety of formats including: interactive maps, time-series, alphanumeric products (e.g., mean areal snow water equivalent on a hydrologic basin-by-basin basis), text and map discussions, map animations, and quantitative gridded products

  17. Snow cover distribution over elevation zones in a mountainous catchment

    Science.gov (United States)

    Panagoulia, D.; Panagopoulos, Y.

    2009-04-01

    A good understanding of the elevetional distribution of snow cover is necessary to predict the timing and volume of runoff. In a complex mountainous terrain the snow cover distribution within a watershed is highly variable in time and space and is dependent on elevation, slope, aspect, vegetation type, surface roughness, radiation load, and energy exchange at the snow-air interface. Decreases in snowpack due to climate change could disrupt the downstream urban and agricultural water supplies, while increases could lead to seasonal flooding. Solar and longwave radiation are dominant energy inputs driving the ablation process. Turbulent energy exchange at the snow cover surface is important during the snow season. The evaporation of blowing and drifting snow is strongly dependent upon wind speed. Much of the spatial heterogeneity of snow cover is the result of snow redistribution by wind. Elevation is important in determining temperature and precipitation gradients along hillslopes, while the temperature gradients determine where precipitation falls as rain and snow and contribute to variable melt rates within the hillslope. Under these premises, the snow accumulation and ablation (SAA) model of the US National Weather Service (US NWS) was applied to implement the snow cover extent over elevation zones of a mountainous catchment (the Mesochora catchment in Western-Central Greece), taking also into account the indirectly included processes of sublimation, interception, and snow redistribution. The catchment hydrology is controlled by snowfall and snowmelt and the simulated discharge was computed from the soil moisture accounting (SMA) model of the US NWS and compared to the measured discharge. The elevationally distributed snow cover extent presented different patterns with different time of maximization, extinction and return during the year, producing different timing of discharge that is a crucial factor for the control and management of water resources systems.

  18. Global warming in the context of 2000 years of Australian alpine temperature and snow cover.

    Science.gov (United States)

    McGowan, Hamish; Callow, John Nikolaus; Soderholm, Joshua; McGrath, Gavan; Campbell, Micheline; Zhao, Jian-Xin

    2018-03-13

    Annual resolution reconstructions of alpine temperatures are rare, particularly for the Southern Hemisphere, while no snow cover reconstructions exist. These records are essential to place in context the impact of anthropogenic global warming against historical major natural climate events such as the Roman Warm Period (RWP), Medieval Climate Anomaly (MCA) and Little Ice Age (LIA). Here we show for a marginal alpine region of Australia using a carbon isotope speleothem reconstruction, warming over the past five decades has experienced equivalent magnitude of temperature change and snow cover decline to the RWP and MCA. The current rate of warming is unmatched for the past 2000 years and seasonal snow cover is at a minimum. On scales of several decades, mean maximum temperatures have undergone considerable change ≈ ± 0.8 °C highlighting local scale susceptibility to rapid temperature change, evidence of which is often masked in regional to hemisphere scale temperature reconstructions.

  19. Uncertainty in solid precipitation and snow depth prediction for Siberia using the Noah and Noah-MP land surface models

    Science.gov (United States)

    Suzuki, Kazuyoshi; Zupanski, Milija

    2018-01-01

    In this study, we investigate the uncertainties associated with land surface processes in an ensemble predication context. Specifically, we compare the uncertainties produced by a coupled atmosphere-land modeling system with two different land surface models, the Noah- MP land surface model (LSM) and the Noah LSM, by using the Maximum Likelihood Ensemble Filter (MLEF) data assimilation system as a platform for ensemble prediction. We carried out 24-hour prediction simulations in Siberia with 32 ensemble members beginning at 00:00 UTC on 5 March 2013. We then compared the model prediction uncertainty of snow depth and solid precipitation with observation-based research products and evaluated the standard deviation of the ensemble spread. The prediction skill and ensemble spread exhibited high positive correlation for both LSMs, indicating a realistic uncertainty estimation. The inclusion of a multiple snowlayer model in the Noah-MP LSM was beneficial for reducing the uncertainties of snow depth and snow depth change compared to the Noah LSM, but the uncertainty in daily solid precipitation showed minimal difference between the two LSMs. The impact of LSM choice in reducing temperature uncertainty was limited to surface layers of the atmosphere. In summary, we found that the more sophisticated Noah-MP LSM reduces uncertainties associated with land surface processes compared to the Noah LSM. Thus, using prediction models with improved skill implies improved predictability and greater certainty of prediction.

  20. Continuous Estimates of Surface Density and Annual Snow Accumulation with Multi-Channel Snow/Firn Penetrating Radar in the Percolation Zone, Western Greenland Ice Sheet

    Science.gov (United States)

    Meehan, T.; Marshall, H. P.; Bradford, J.; Hawley, R. L.; Osterberg, E. C.; McCarthy, F.; Lewis, G.; Graeter, K.

    2017-12-01

    A priority of ice sheet surface mass balance (SMB) prediction is ascertaining the surface density and annual snow accumulation. These forcing data can be supplied into firn compaction models and used to tune Regional Climate Models (RCM). RCMs do not accurately capture subtle changes in the snow accumulation gradient. Additionally, leading RCMs disagree among each other and with accumulation studies in regions of the Greenland Ice Sheet (GrIS) over large distances and temporal scales. RCMs tend to yield inconsistencies over GrIS because of sparse and outdated validation data in the reanalysis pool. Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) implemented multi-channel 500 MHz Radar in multi-offset configuration throughout two traverse campaigns totaling greater than 3500 km along the western percolation zone of GrIS. The multi-channel radar has the capability of continuously estimating snow depth, average density, and annual snow accumulation, expressed at 95% confidence (+-) 0.15 m, (+-) 17 kgm-3, (+-) 0.04 m w.e. respectively, by examination of the primary reflection return from the previous year's summer surface.

  1. Remote Sensing-based Methodologies for Snow Model Adjustments in Operational Streamflow Prediction

    Science.gov (United States)

    Bender, S.; Miller, W. P.; Bernard, B.; Stokes, M.; Oaida, C. M.; Painter, T. H.

    2015-12-01

    Water management agencies rely on hydrologic forecasts issued by operational agencies such as NOAA's Colorado Basin River Forecast Center (CBRFC). The CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate research-oriented, remotely-sensed snow data into CBRFC operations and to improve the accuracy of CBRFC forecasts. The partnership has yielded valuable analysis of snow surface albedo as represented in JPL's MODIS Dust Radiative Forcing in Snow (MODDRFS) data, across the CBRFC's area of responsibility. When dust layers within a snowpack emerge, reducing the snow surface albedo, the snowmelt rate may accelerate. The CBRFC operational snow model (SNOW17) is a temperature-index model that lacks explicit representation of snowpack surface albedo. CBRFC forecasters monitor MODDRFS data for emerging dust layers and may manually adjust SNOW17 melt rates. A technique was needed for efficient and objective incorporation of the MODDRFS data into SNOW17. Initial development focused in Colorado, where dust-on-snow events frequently occur. CBRFC forecasters used retrospective JPL-CBRFC analysis and developed a quantitative relationship between MODDRFS data and mean areal temperature (MAT) data. The relationship was used to generate adjusted, MODDRFS-informed input for SNOW17. Impacts of the MODDRFS-SNOW17 MAT adjustment method on snowmelt-driven streamflow prediction varied spatially and with characteristics of the dust deposition events. The largest improvements occurred in southwestern Colorado, in years with intense dust deposition events. Application of the method in other regions of Colorado and in "low dust" years resulted in minimal impact. The MODDRFS-SNOW17 MAT technique will be implemented in CBRFC operations in late 2015, prior to spring 2016 runoff. Collaborative investigation of remote sensing-based adjustment methods for the CBRFC operational hydrologic forecasting environment will continue over the next several years.

  2. Characteristics of snow cover duration across the northeast United States of America

    Science.gov (United States)

    Leathers, Daniel J.; Luff, Barbara L.

    1997-11-01

    The presence or absence of a snow cover affects a myriad of environmental and societal systems through its modification of the surface radiation balance and its ultimate impact on near-surface air temperatures. Daily snow cover data were collected for a network of 91 stations covering the northeast USA from Maine, south through to West Virginia. The snow cover data along with ancillary temperature, snowfall and precipitation data were used to investigate the characteristics of snow cover duration in this region and the effects of the snow cover on boundary layer climate variables for the snow cover seasons 1948-1949 through to 1987-1988.Results indicate that snow cover duration is variable in both space and time. The duration of a snow cover of 2.5 cm or greater varies from greater than 100 days in northern New England to less than 20 days across areas of Delaware, Maryland and West Virginia. Temporally, snow cover duration for the region as a whole was very short from the late 1940s through to the mid-1950s. From the late 1950s to the end of the period snow cover duration has varied around a consistent mean value. No long-term trends in snow cover duration are apparent in the record for the northeast USA.Principal components analysis and clustering techniques were utilized to isolate spatially coherent regions in which snow cover duration has varied similarly over the period of record. This analysis resulted in the identification of four snow-cover-duration regions across the northeast USA: including (i) the West Virginia area, (ii) the mid-Atlantic from southern New England through to western Pennsylvania, (iii) western and central New York and (iv) northern New England. Snow cover duration is shown to be highly associated with snowfall and temperature but not strongly related to total liquid precipitation. The intra-annual variability of snow cover duration is also investigated for each region.

  3. Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S.

    OpenAIRE

    Oaida, CM; Xue, Y; Flanner, MG; Skiles, SMK; De Sales, F; Painter, TH

    2015-01-01

    © 2015. American Geophysical Union. All Rights Reserved. Two important factors that control snow albedo are snow grain growth and presence of light-absorbing impurities (aerosols) in snow. However, current regional climate models do not include such processes in a physically based manner in their land surface models. We improve snow albedo calculations in the Simplified Simple Biosphere (SSiB) land surface model coupled with the Weather Research and Forecasting (WRF) regional climate model (R...

  4. Snow accretion on overhead wires

    Energy Technology Data Exchange (ETDEWEB)

    Sakamoto, Y. [Meteorological Research Inst. for Technology Co. Ltd., Tokyo (Japan); Tachizaki, S.; Sudo, N. [Tohoku Electric Power Co. Ltd., Miyagi (Japan)

    2005-07-01

    Wet snow accretion can cause extensive damage to transmission systems. This paper reviewed some of the difficulties faced by researchers in the study of wet snow accretion on overhead lines in Japan. The study of snow accretion phenomena is complicated by the range of phase changes in water. Snowflakes produced in an upper atmospheric layer with a temperature below freezing do not melt when they go through a lower atmospheric layer with a temperature above freezing, but are in a mixed state of solid and liquid due to the latent heat of melting. The complicated properties of water make studies of snow accretion difficult, as well as the fact that snow changes its physical properties rapidly, due to the effects of ambient temperature, rainfall, and solar radiation. The adhesive forces that cause snow accretion include freezing; bonding through freezing; sintering; condensation and freezing of vapor in the air; mechanical intertwining of snowflakes; capillary action due to liquids; coherent forces between ice particles and water formed through the metamorphosis of snowflakes. In addition to these complexities, differences in laboratory room environments and natural snow environments can also pose difficulties for researchers. Equations describing the relationship between the density of accreted snow and the meteorological parameters involved were presented, as well as empirical equations which suggested that snow accretion efficiency has a dependency on air temperature. An empirical model for estimating snow loads in Japan was outlined, as well as various experiments observing show shedding. Correlations for wet snow accretion included precipitation intensity; duration of precipitation; air temperature; wind speed and wind direction in relation to the overhead line. Issues concerning topography and wet snow accretion were reviewed. It was concluded that studies of snow accretion will benefit by the collection of data in each matrix of the relevant parameters. 12 refs

  5. Investigation of some regularities of the contamination of the surface snow in the ChAPP region in January-February 1987

    International Nuclear Information System (INIS)

    Glazunov, V.O.; Amosov, M.M.; Eldashev, V.V.; Draj, O.N.; Pashevich, V.I.

    1989-01-01

    The data on the surface snow radioactivity inspection obtained in winter 1987 are analyzed. A share of individual radionuclides in the general pollution of surface snow is considered. Changes in general and individual nuclide contamination dependent of the azimuth and distance are presented. A disperse content of contaminants in the surface snow is analyzed. The sampling techniques and snow sample preparation for γ-spectrometry are reported. 5 refs., 8 figs., 7 tabs

  6. Understanding snow-transport processes shaping the mountain snow-cover

    Directory of Open Access Journals (Sweden)

    R. Mott

    2010-12-01

    Full Text Available Mountain snow-cover is normally heterogeneously distributed due to wind and precipitation interacting with the snow cover on various scales. The aim of this study was to investigate snow deposition and wind-induced snow-transport processes on different scales and to analyze some major drift events caused by north-west storms during two consecutive accumulation periods. In particular, we distinguish between the individual processes that cause specific drifts using a physically based model approach. Very high resolution wind fields (5 m were computed with the atmospheric model Advanced Regional Prediction System (ARPS and used as input for a model of snow-surface processes (Alpine3D to calculate saltation, suspension and preferential deposition of precipitation. Several flow features during north-west storms were identified with input from a high-density network of permanent and mobile weather stations and indirect estimations of wind directions from snow-surface structures, such as snow dunes and sastrugis. We also used Terrestrial and Airborne Laser Scanning measurements to investigate snow-deposition patterns and to validate the model. The model results suggest that the in-slope deposition patterns, particularly two huge cross-slope cornice-like drifts, developed only when the prevailing wind direction was northwesterly and were formed mainly due to snow redistribution processes (saltation-driven. In contrast, more homogeneous deposition patterns on a ridge scale were formed during the same periods mainly due to preferential deposition of precipitation. The numerical analysis showed that snow-transport processes were sensitive to the changing topography due to the smoothing effect of the snow cover.

  7. The role of surface energy fluxes in pan-Arctic snow cover changes

    International Nuclear Information System (INIS)

    Shi Xiaogang; Lettenmaier, Dennis P; Groisman, Pavel Ya; Dery, Stephen J

    2011-01-01

    We analyze snow cover extent (SCE) trends in the National Oceanic and Atmospheric Administration's (NOAA) northern hemisphere weekly satellite SCE data using the Mann-Kendall trend test and find that North American and Eurasian snow cover in the pan-Arctic have declined significantly in spring and summer over the period of satellite record beginning in the early 1970s. These trends are reproduced, both in trend direction and statistical significance, in reconstructions using the variable infiltration capacity (VIC) hydrological model. We find that spring and summer surface radiative and turbulent fluxes generated in VIC have strong correlations with satellite observations of SCE. We identify the role of surface energy fluxes and determine which is most responsible for the observed spring and summer SCE recession. We find that positive trends in surface net radiation (SNR) accompany most of the SCE trends, whereas modeled latent heat (LH) and sensible heat (SH) trends associated with warming on SCE mostly cancel each other, except for North America in spring, and to a lesser extent for Eurasia in summer. In spring over North America and summer in Eurasia, the SH contribution to the observed snow cover trends is substantial. The results indicate that ΔSNR is the primary energy source and ΔSH plays a secondary role in changes of SCE. Compared with ΔSNR and ΔSH, ΔLH has a minor influence on pan-Arctic snow cover changes.

  8. Modeling of multi-phase interactions of reactive nitrogen between snow and air in Antarctica

    Science.gov (United States)

    McCrystall, M.; Chan, H. G. V.; Frey, M. M.; King, M. D.

    2016-12-01

    In polar and snow-covered regions, the snowpack is an important link between atmospheric, terrestrial and oceanic systems. Trace gases, including nitrogen oxides, produced via photochemical reactions in snow are partially released to the lower atmosphere with considerable impact on its composition. However, the post-depositional processes that change the chemical composition and physical properties of the snowpack are still poorly understood. Most current snow chemistry models oversimplify as they assume air-liquid interactions and aqueous phase chemistry taking place at the interface between the snow grain and air. Here, we develop a novel temperature dependent multi-phase (gas-liquid-ice) physical exchange model for reactive nitrogen. The model is validated with existing year-round observations of nitrate in the top 0.5-2 cm of snow and the overlying atmosphere at two very different Antarctic locations: Dome C on the East Antarctic Plateau with very low annual mean temperature (-54ºC) and accumulation rate (rate and high background level of sea salt aerosol. We find that below the eutectic temperature of the H2O/dominant ion mixture the surface snow nitrate is controlled by kinetic adsorption onto the surface of snow grains followed by grain diffusion. Above the eutectic temperature, in addition to the former two processes, thermodynamic equilibrium of HNO3 between interstitial air and liquid water pockets, possibly present at triple junctions or grooves at grain boundaries, greatly enhances the nitrate uptake by snow in agreement with the concentration peak observed in summer.

  9. [Measurement and estimation methods and research progress of snow evaporation in forests].

    Science.gov (United States)

    Li, Hui-Dong; Guan, De-Xin; Jin, Chang-Jie; Wang, An-Zhi; Yuan, Feng-Hui; Wu, Jia-Bing

    2013-12-01

    Accurate measurement and estimation of snow evaporation (sublimation) in forests is one of the important issues to the understanding of snow surface energy and water balance, and it is also an essential part of regional hydrological and climate models. This paper summarized the measurement and estimation methods of snow evaporation in forests, and made a comprehensive applicability evaluation, including mass-balance methods (snow water equivalent method, comparative measurements of snowfall and through-snowfall, snow evaporation pan, lysimeter, weighing of cut tree, weighing interception on crown, and gamma-ray attenuation technique) and micrometeorological methods (Bowen-ratio energy-balance method, Penman combination equation, aerodynamics method, surface temperature technique and eddy covariance method). Also this paper reviewed the progress of snow evaporation in different forests and its influencal factors. At last, combining the deficiency of past research, an outlook for snow evaporation rearch in forests was presented, hoping to provide a reference for related research in the future.

  10. In Situ Observations of Snow Metamorphosis Acceleration Induced by Dust and Black Carbon

    Science.gov (United States)

    Schneider, A. M.; Flanner, M.

    2017-12-01

    Previous studies demonstrate the dependence of shortwave infrared (SWIR) reflectance on snow specific surface area (SSA) and others examine the direct darkening effect dust and black carbon (BC) deposition has on snow and ice-covered surfaces. The extent to which these light absorbing aerosols (LAAs) accelerate snow metamorphosis, however, is challenging to assess in situ as measurement techniques easily disturb snowpack. Here, we use two Near-Infrared Emitting Reflectance Domes (NERDs) to measure 1300 and 1550nm bidirectional reflectance factors (BRFs) of natural snow and experimental plots with added dust and BC. We obtain NERD measurements and subsequently collect and transport snow samples to the nearby U.S. Army Corps of Engineers' Cold Regions Research and Engineering Lab for micro computed tomography (micro-CT) analysis. Snow 1300 (1550) nm BRFs evolve from 0.6 (0.15) in fresh snow to 0.2 (0.03) after metamorphosis. Hourly-scale time evolving snow surface BRFs and SSA estimates from micro-CT reveal more rapid SWIR darkening and snow metamorphosis in contaminated versus natural plots. Cloudiness and high wind speeds can completely obscure these results if LAAs mobilize before absorbing enough radiant energy. These findings verify experimentally that dust and BC deposition can accelerate snow metamorphosis and enhance snow albedo feedback in sunny, calm weather conditions. Although quantifying the enhancement of snow albedo feedback induced by LAAs requires further surface temperature, solar irradiance, and impurity concentration measurements, this study provides experimental verification of positive feedback occurring where dust and BC accelerate snow metamorphosis.

  11. Snow depth retrieval from L-band satellite measurements on Arctic and Antarctic sea ice

    Science.gov (United States)

    Maaß, N.; Kaleschke, L.; Wever, N.; Lehning, M.; Nicolaus, M.; Rossmann, H. L.

    2017-12-01

    The passive microwave mission SMOS provides daily coverage of the polar regions and measures at a low frequency of 1.4 GHz (L-band). SMOS observations have been used to operationally retrieve sea ice thickness up to 1 m and to estimate snow depth in the Arctic for thicker ice. Here, we present how SMOS-retrieved snow depths compare with airborne measurements from NASA's Operation IceBridge mission (OIB) and with AMSR-2 satellite retrievals at higher frequencies, and we show first applications to Antarctic sea ice. In previous studies, SMOS and OIB snow depths showed good agreement on spatial scales from 50 to 1000 km for some days and disagreement for other days. Here, we present a more comprehensive comparison of OIB and SMOS snow depths in the Arctic for 2011 to 2015. We find that the SMOS retrieval works best for cold conditions and depends on auxiliary information on ice surface temperature, here provided by MODIS thermal imagery satellite data. However, comparing SMOS and OIB snow depths is difficult because of the different spatial resolutions (SMOS: 40 km, OIB: 40 m). Spatial variability within the SMOS footprint can lead to different snow conditions as seen from SMOS and OIB. Ideally the comparison is made for uniform conditions: Low lead and open water fraction, low spatial and temporal variability of ice surface temperature, no mixture of multi- and first-year ice. Under these conditions and cold temperatures (surface temperatures below -25°C), correlation coefficients between SMOS and OIB snow depths increase from 0.3 to 0.6. A finding from the comparison with AMSR-2 snow depths is that the SMOS-based maps depend less on the age of the sea ice than the maps derived from higher frequencies. Additionally, we show first results of SMOS snow depths for Antarctic sea ice. SMOS observations are compared to measurements of autonomous snow buoys drifting in the Weddell Sea since 2014. For a better comparability of these point measurements with SMOS data, we use

  12. Impact of CO/sub 2/ on cooling of snow and water surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Choudhury, B [Computer Sciences Corp., Silver Spring, MD; Kukla, G

    1979-08-23

    The levels of CO/sub 2/ in the atmosphere are being increased by the burning of fossil fuels and reduction of biomass. It has been calculated that the increase in CO/sub 2/ levels should lead to global warming because of increased absorption by the atmosphere of terrestrial longwave radiation in the far IR (> 5 ..mu..m). From model computations, CO/sub 2/ is expected to produce the largest climatic effect in high latitudes by reducing the size of ice and snow fields. We present here computations of spectral radiative transfer and scattering within a snow pack and water. The results suggest that CO/sub 2/ significantly reduces the shortwave energy absorbed by the surface of snow and water. The energy deficit, when not compensated by downward atmospheric radiation, may delay the recrystallisation of snow and dissipation of packice and result in a cooling rather than a warming effect.

  13. A STUDY ON SNOW PROFILES AND SURFACE CHARACTERISTICS ALONG 6000km TRANSANTARCTIC ROUTE (Ⅰ)——THE "1990 INTERNATIONAL TRANS-ANTARCTIC EXPEDITION" GLACIOLOGICAL RESEARCH

    Institute of Scientific and Technical Information of China (English)

    秦大河; 任贾文

    1992-01-01

    Along a 5986 km route on Antarctic ice sheet from west to east, 106 snow pits with a depth ranging from 1.0—2.0 m have been dug by the first author of this paper, the Chinese member of the "1990 International Trans-Antarctic Expedition". The basic physical characteristics of the surface layer of the ice sheet on a large scale are obtained through the observations of snow profiles at these snow pits. The sastrugi shapes and major axis azimuths have also been observed or measured on the way. Analysis for these observation data shows that in West Antarctica the meltwater infiltration-congelation is obvious and the annual precipitation is larger than that in East Antarctica, which implies that climate in West Antarctica is warmer, more humid and influenced more greatly by the South Ocean than that in East Antarctica. Radiation ice-glazes frequently found in snow profiles indicate that even in East Antarctica under very low temperatures, surface "melting" occurs in summer due to the long-time solar radiatio

  14. Spatial distributions of soluble salts in surface snow of East Antarctica

    Directory of Open Access Journals (Sweden)

    Yoshinori Iizuka

    2016-07-01

    Full Text Available To better understand how sea salt reacts in surface snow of Antarctica, we collected and identified non-volatile particles in surface snow along a traverse in East Antarctica. Samples were obtained during summer 2012/2013 from coastal to inland regions within 69°S to 80°S and 39°E to 45°E, a total distance exceeding 800 km. The spatial resolution of samples is about one sample per latitude between 1500 and 3800 m altitude. Here, we obtain the atomic ratios of Na, S and Cl, and calculate the masses of sodium sulphate and sodium chloride. The results show that, even in the coast snow sample (69°S, sea salt is highly modified by acid (HNO3 or H2SO4. The fraction of sea salt that reacts with acid increases in the region from 70°S to 74°S below 3000 m a.s.l., where some NaCl remains. At the higher altitudes (above 3300 m a.s.l. in the inland region (74°S to 80°S, the reaction uses almost all of the available NaCl.

  15. Ultra-Wideband Radiometry Remote Sensing of Polar Ice Sheet Temperature Profile, Sea Ice and Terrestrial Snow Thickness: Forward Modeling and Data Analysis

    Science.gov (United States)

    Tsang, L.; Tan, S.; Sanamzadeh, M.; Johnson, J. T.; Jezek, K. C.; Durand, M. T.

    2017-12-01

    The recent development of an ultra-wideband software defined radiometer (UWBRAD) operating over the unprotected spectrum of 0.5 2.0 GHz using radio-frequency interference suppression techniques offers new methodologies for remote sensing of the polar ice sheets, sea ice, and terrestrial snow. The instrument was initially designed for remote sensing of the intragalcial temperature profile of the ice sheet, where a frequency dependent penetration depth yields a frequency dependent brightness temperature (Tb) spectrum that can be linked back to the temperature profile of the ice sheet. The instrument was tested during a short flight over Northwest Greenland in September, 2016. Measurements were successfully made over the different snow facies characteristic of Greenland including the ablation, wet snow and percolation facies, and ended just west of Camp Century during the approach to the dry snow zone. Wide-band emission spectra collected during the flight have been processed and analyzed. Results show that the spectra are highly sensitive to the facies type with scattering from ice lenses being the dominant reason for low Tbs in the percolation zone. Inversion of Tb to physical temperature at depth was conducted on the measurements near Camp Century, achieving a -1.7K ten-meter error compared to borehole measurements. However, there is a relatively large uncertainty in the lower part possibly due to the large scattering near the surface. Wideband radiometry may also be applicable to sea ice and terrestrial snow thickness retrieval. Modeling studies suggest that the UWBRAD spectra reduce ambiguities inherent in other sea ice thickness retrievals by utilizing coherent wave interferences that appear in the Tb spectrum. When applied to a lossless medium such as terrestrial snow, this coherent oscillation turns out to be the single key signature that can be used to link back to snow thickness. In this paper, we report our forward modeling findings in support of instrument

  16. Assimilation of MODIS Ice Surface Temperature and Albedo into the Snow and Ice Model CROCUS Over the Greenland Ice Sheet Along the K-transect Stations

    Science.gov (United States)

    Navari, M.; Margulis, S. A.; Bateni, S. M.; Alexander, P. M.; Tedesco, M.

    2016-12-01

    Estimating the Greenland Ice Sheet (GrIS) surface mass balance (SMB) is an important component of current and future projections of sea level rise. In situ measurement provides direct estimates of the SMB, but are inherently limited by their spatial extent and representativeness. Given this limitation, physically based regional climate models (RCMs) are critical for understanding GrIS physical processes and estimating of the GrIS SMB. However, the uncertainty in estimates of SMB from RCMs is still high. Surface remote sensing (RS) has been used as a complimentary tool to characterize various aspects related to the SMB. The difficulty of using these data streams is that the links between them and the SMB terms are most often indirect and implicit. Given the lack of in situ information, imperfect models, and under-utilized RS data it is critical to merge the available data in a systematic way to better characterize the spatial and temporal variation of the GrIS SMB. This work proposes a data assimilation (DA) framework that yields temporally-continuous and physically consistent SMB estimates that benefit from state-of-the-art models and relevant remote sensing data streams. Ice surface temperature (IST) is the most important factor that regulates partitioning of the net radiation into the subsurface snow/ice, sensible and latent heat fluxes and plays a key role in runoff generation. Therefore it can be expected that a better estimate of surface temperature from a data assimilation system would contribute to a better estimate of surface mass fluxes. Albedo plays an important role in the surface energy balance of the GrIS. However, even advanced albedo modules are not adequate to simulate albedo over the GrIS. Therefore, merging remotely sensed albedo product into a physically based model has a potential to improve the estimates of the GrIS SMB. In this work a MODIS-derived IST and a 16-day albedo product are independently assimilated into the snow and ice model CROCUS

  17. Improving representation of canopy temperatures for modeling subcanopy incoming longwave radiation to the snow surface

    Science.gov (United States)

    Webster, Clare; Rutter, Nick; Jonas, Tobias

    2017-09-01

    A comprehensive analysis of canopy surface temperatures was conducted around a small and large gap at a forested alpine site in the Swiss Alps during the 2015 and 2016 snowmelt seasons (March-April). Canopy surface temperatures within the small gap were within 2-3°C of measured reference air temperature. Vertical and horizontal variations in canopy surface temperatures were greatest around the large gap, varying up to 18°C above measured reference air temperature during clear-sky days. Nighttime canopy surface temperatures around the study site were up to 3°C cooler than reference air temperature. These measurements were used to develop a simple parameterization for correcting reference air temperature for elevated canopy surface temperatures during (1) nighttime conditions (subcanopy shortwave radiation is 0 W m-2) and (2) periods of increased subcanopy shortwave radiation >400 W m-2 representing penetration of shortwave radiation through the canopy. Subcanopy shortwave and longwave radiation collected at a single point in the subcanopy over a 24 h clear-sky period was used to calculate a nighttime bulk offset of 3°C for scenario 1 and develop a multiple linear regression model for scenario 2 using reference air temperature and subcanopy shortwave radiation to predict canopy surface temperature with a root-mean-square error (RMSE) of 0.7°C. Outside of these two scenarios, reference air temperature was used to predict subcanopy incoming longwave radiation. Modeling at 20 radiometer locations throughout two snowmelt seasons using these parameterizations reduced the mean bias and RMSE to below 10 W m s-2 at all locations.

  18. Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees from 2011 to 2017

    Directory of Open Access Journals (Sweden)

    J. Revuelto

    2017-12-01

    Full Text Available This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The experimental site is located on the southern side of the Pyrenees between 2000 and 2300 m above sea level, covering an area of 55 ha. The site is a good example of a subalpine environment in which the evolution of snow accumulation and melt are of major importance in many mountain processes. The climatic data set consists of (i continuous meteorological variables acquired from an automatic weather station (AWS, (ii detailed information on snow depth distribution collected with a terrestrial laser scanner (TLS, lidar technology for certain dates across the snow season (between three and six TLS surveys per snow season and (iii time-lapse images showing the evolution of the snow-covered area (SCA. The meteorological variables acquired at the AWS are precipitation, air temperature, incoming and reflected solar radiation, infrared surface temperature, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface, and soil temperature; all were taken at 10 min intervals. Snow depth distribution was measured during 23 field campaigns using a TLS, and daily information on the SCA was also retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.848277 is valuable since it provides high-spatial-resolution information on the snow depth and snow cover, which is particularly useful when combined with meteorological variables to simulate snow energy and mass balance. This information has already been analyzed in various scientific studies on snow pack dynamics and its interaction with the local climatology or topographical characteristics. However, the database generated has great potential for understanding other environmental processes from a hydrometeorological or ecological perspective in which

  19. Changes in Snow Albedo Resulting from Snow Darkening Caused by Black Carbon

    Science.gov (United States)

    Engels, J.; Kloster, S.; Bourgeois, Q.

    2014-12-01

    We investigate the potential impact of snow darkening caused by pre-industrial and present-day black carbon (BC) emissions on snow albedo and subsequently climate. To assess this impact, we implemented the effect of snow darkening caused by BC emitted from natural as well as anthropogenic sources into the Max Planck Institute for Meteorology Earth System Model (MPI-M ESM). Considerable amounts of BC are emitted e.g. from fires and are transported through the atmosphere for several days before being removed by rain or snow precipitation in snow covered regions. Already very small quantities of BC reduce the snow reflectance significantly, with consequences for snow melting and snow spatial coverage. We implemented the snow albedo reduction caused by BC contamination and snow aging in the one layer land surface component (JSBACH) of the atmospheric general circulation model ECHAM6, developed at MPI-M. For this we used the single-layer simulator of the SNow, Ice, and Aerosol Radiation (SNICAR-Online (Flanner et al., 2007); http://snow.engin.umich.edu) model to derive snow albedo values for BC in snow concentrations ranging between 0 and 1500 ng(BC)/g(snow) for different snow grain sizes for the visible (0.3 - 0.7 μm) and near infrared range (0.7 - 1.5 μm). As snow grains grow over time, we assign different snow ages to different snow grain sizes (50, 150, 500, and 1000 μm). Here, a radius of 50 μm corresponds to new snow, whereas a radius of 1000 μm corresponds to old snow. The deposition rates of BC on snow are prescribed from previous ECHAM6-HAM simulations for two time periods, pre-industrial (1880-1889) and present-day (2000-2009), respectively. We perform a sensitivity study regarding the scavenging of BC by snow melt. To evaluate the newly implemented albedo scheme we will compare the modeled black carbon in snow concentrations to observed ones. Moreover, we will show the impact of the BC contamination and snow aging on the simulated snow albedo. The

  20. Effect of snow cover on soil frost penetration

    Science.gov (United States)

    Rožnovský, Jaroslav; Brzezina, Jáchym

    2017-12-01

    Snow cover occurrence affects wintering and lives of organisms because it has a significant effect on soil frost penetration. An analysis of the dependence of soil frost penetration and snow depth between November and March was performed using data from 12 automated climatological stations located in Southern Moravia, with a minimum period of measurement of 5 years since 2001, which belong to the Czech Hydrometeorological institute. The soil temperatures at 5 cm depth fluctuate much less in the presence of snow cover. In contrast, the effect of snow cover on the air temperature at 2 m height is only very small. During clear sky conditions and no snow cover, soil can warm up substantially and the soil temperature range can be even higher than the range of air temperature at 2 m height. The actual height of snow is also important - increased snow depth means lower soil temperature range. However, even just 1 cm snow depth substantially lowers the soil temperature range and it can therefore be clearly seen that snow acts as an insulator and has a major effect on soil frost penetration and soil temperature range.

  1. Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

    Science.gov (United States)

    Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

    2017-12-01

    We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

  2. The subglacial Lake Vostok (East Antarctica) surface snow is Earth-bound DNA (and dust)-free

    Science.gov (United States)

    Bulat, S.; Marie, D.; Bulat, E.; Alekhina, I.; Petit, J.-R.

    2012-09-01

    The objective was to assess the microbial cell abundance in the surface snow in Central East Antarctica and the fate of microbial genomic DNA during summer short-time exposure to surface climatic (and radiation) conditions at Vostok using flow cytometry and DNA-based methods. The surface snow (until 4m deep) was collected as clean as possible in the vicinity of the Vostok station (3 sites - courtesy of A Ekaykin and ASC Lebedev Physical Iinstitute RAS) and towards the Progress station (4 more sites with one just 29km from the coast - courtesy of A Ekaykin and S Popov) in specially decontaminated plastic crates or containers of various volumes (up to 75 kg of snow). All subsequent snow treatment manipulations (melting, concentrating, genomic DNA extraction, primary PCR set up) were performed in clean room laboratory facilities (LGGE, UJF-CNRS, Grenoble, France). Cell concentrations were determined on meltwater aliquots prepared under clean room conditions using flow cytofluorometry (Biostation, Roscoff, France). The highly concentrated meltwater (until 10000 times down) was used to extract gDNA which were subjected to bacterial 16S rRNA genes amplification in PCR and sequencing. The gDNA of a complex mesophile microbial community for exposure trials were also prepared and put onto a filter under strict clean room conditions. The filters were got exposed open to solar radiation and surface temperature at Vostok during January for various time duration periods (from 25 to 1 day). As a result no microbial cells were confidently detected in surface snow samples differed by sampling sites and people asked to collect as well. Complementary the mineral dust particle abundance did not exceed 16 mkg per liter with the particle size mode about 2.5 mkm as shown using Coulter counter. Preliminary amongst the microparticles no unusual findings (e.g. spherules of cosmic origin) were observed by shape and element composition using electron scanning microscopy. The gDNA studies

  3. Carbon dioxide evolution from snow-covered agricultural ecosystems in Finland

    Directory of Open Access Journals (Sweden)

    Hiroshi Koizumi

    1996-07-01

    Full Text Available The release of CO2 from the snow surface in winter and the soil surface in summer was directly or indirectly measured in three different soil types (peat, sand and clay in agricultural ecosystems in Finland. The closed chamber (CC method was used for the direct and Pick’s diffusion model (DM method for the indirect measurements. The winter soil temperatures at 2-cm depth were between 0 and 1°C for each soil type. The concentration of CO2 within the snowpack increased linearly with snow depth. The average fluxes of CO2 calculated from the gradients of CO2 concentration in the snow using the DM method ranged from 10 to 27 mg CO2 m2h-1 and with the CC method from 18 to 27 mg CO2 m2h-1. These results suggest that the snow insulates the soil thermally, allowing CO2 production to continue at soil temperatures slightly above freezing in the winter. Carbon dioxide formed in the soil can move across the snowpack up to the atmosphere. The winter/summer ratio of CO2 evolution was estimated to exceed 4%. Therefore, the snow-covered crop soil served as a source of CO2 in winter, and CO2 evolution constitutes an important part of the annual CO2 budget in snowy regions.

  4. Performance tests of snow-related variables over the Tibetan Plateau and Himalayas using a new version of NASA GEOS-5 land surface model that includes the snow darkening effect

    Science.gov (United States)

    Yasunari, T. J.; Lau, W. K.; Koster, R. D.; Suarez, M.; Mahanama, S. P.; da Silva, A.; Colarco, P. R.

    2011-12-01

    The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [lon.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1) was

  5. Improving the performance of temperature index snowmelt model of SWAT by using MODIS land surface temperature data.

    Science.gov (United States)

    Yang, Yan; Onishi, Takeo; Hiramatsu, Ken

    2014-01-01

    Simulation results of the widely used temperature index snowmelt model are greatly influenced by input air temperature data. Spatially sparse air temperature data remain the main factor inducing uncertainties and errors in that model, which limits its applications. Thus, to solve this problem, we created new air temperature data using linear regression relationships that can be formulated based on MODIS land surface temperature data. The Soil Water Assessment Tool model, which includes an improved temperature index snowmelt module, was chosen to test the newly created data. By evaluating simulation performance for daily snowmelt in three test basins of the Amur River, performance of the newly created data was assessed. The coefficient of determination (R (2)) and Nash-Sutcliffe efficiency (NSE) were used for evaluation. The results indicate that MODIS land surface temperature data can be used as a new source for air temperature data creation. This will improve snow simulation using the temperature index model in an area with sparse air temperature observations.

  6. Improvement of a snow albedo parameterization in the Snow-Atmosphere-Soil Transfer model: evaluation of impacts of aerosol on seasonal snow cover

    Science.gov (United States)

    Zhong, Efang; Li, Qian; Sun, Shufen; Chen, Wen; Chen, Shangfeng; Nath, Debashis

    2017-11-01

    The presence of light-absorbing aerosols (LAA) in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consideration. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil Transfer (SAST) model, which includes the impacts of LAA on snow. Specifically, the Snow, Ice and Aerosol Radiation (SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot (SASP), Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.

  7. Modelling snow ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard

    Directory of Open Access Journals (Sweden)

    Caixin Wang

    2015-08-01

    Full Text Available Snow ice and superimposed ice formation on landfast sea ice in a Svalbard fjord, Kongsfjorden, was investigated with a high-resolution thermodynamic snow and sea-ice model, applying meteorological weather station data as external forcing. The model shows that sea-ice formation occurs both at the ice bottom and at the snow/ice interface. Modelling results indicated that the total snow ice and superimposed ice, which formed at the snow/ice interface, was about 14 cm during the simulation period, accounting for about 15% of the total ice mass and 35% of the total ice growth. Introducing a time-dependent snow density improved the modelled results, and a time-dependent oceanic heat flux parameterization yielded reasonable ice growth at the ice bottom. Model results suggest that weather conditions, in particular air temperature and precipitation, as well as snow thermal properties and surface albedo are the most critical factors for the development of snow ice and superimposed ice in Kongsfjorden. While both warming air and higher precipitation led to increased snow ice and superimposed ice forming in Kongsfjorden in the model runs, the processes were more sensitive to precipitation than to air temperature.

  8. Impacts of Snow Darkening by Absorbing Aerosols on Eurasian Climate

    Science.gov (United States)

    Kim, Kyu-Myong; Lau, William K M.; Yasunari, Teppei J.; Kim, Maeng-Ki; Koster, Randal D.

    2016-01-01

    The deposition of absorbing aerosols on snow surfaces reduces snow-albedo and allows snowpack to absorb more sunlight. This so-called snow darkening effect (SDE) accelerates snow melting and leads to surface warming in spring. To examine the impact of SDE on weather and climate during late spring and early summer, two sets of NASA GEOS-5 model simulations with and without SDE are conducted. Results show that SDE-induced surface heating is particularly pronounced in Eurasian regions where significant depositions of dust transported from the North African deserts, and black carbon from biomass burning from Asia and Europe occur. In these regions, the surface heating due to SDE increases surface skin temperature by 3-6 degrees Kelvin near the snowline in spring. Surface energy budget analysis indicates that SDE-induced excess heating is associated with a large increase in surface evaporation, subsequently leading to a significant reduction in soil moisture, and increased risks of drought and heat waves in late spring to early summer. Overall, we find that rainfall deficit combined with SDE-induced dry soil in spring provide favorable condition for summertime heat waves over large regions of Eurasia. Increased frequency of summer heat waves with SDE and the region of maximum increase in heat-wave frequency are found along the snow line, providing evidence that early snowmelt by SDE may increase the risks of extreme summer heat wave. Our results suggest that climate models that do not include SDE may significantly underestimate the effect of global warming over extra-tropical continental regions.

  9. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  10. Air and Ground Surface Temperature Relations in a Mountainous Basin, Wolf Creek, Yukon Territory

    Science.gov (United States)

    Roadhouse, Emily A.

    The links between climate and permafrost are well known, but the precise nature of the relationship between air and ground temperatures remains poorly understood, particularly in complex mountain environments. Although previous studies indicate that elevation and potential incoming solar radiation (PISR) are the two leading factors contributing to the existence of permafrost at a given location, additional factors may also contribute significantly to the existence of mountain permafrost, including vegetation cover, snow accumulation and the degree to which individual mountain landscapes are prone to air temperature inversions. Current mountain permafrost models consider only elevation and aspect, and have not been able to deal with inversion effects in a systematic fashion. This thesis explores the relationship between air and ground surface temperatures and the presence of surface-based inversions at 27 sites within the Wolf Creek basin and surrounding area between 2001 and 2006, as a first step in developing an improved permafrost distribution TTOP model. The TTOP model describes the relationship between the mean annual air temperature and the temperature at the top of permafrost in terms of the surface and thermal offsets (Smith and Riseborough, 2002). Key components of this model are n-factors which relate air and ground climate by establishing the ratio between air and surface freezing (winter) and thawing (summer) degree-days, thus summarizing the surface energy balance on a seasonal basis. Here we examine (1) surface offsets and (2) freezing and thawing n-factor variability at a number of sites through altitudinal treeline in the southern Yukon. Thawing n-factors (nt) measured at individual sites remained relatively constant from one year to the next and may be related to land cover. During the winter, the insulating effect of a thick snow cover results in higher surface temperatures, while thin snow cover results in low surface temperatures more closely

  11. Impacts of snow on soil temperature observed across the circumpolar north

    Science.gov (United States)

    Zhang, Yu; Sherstiukov, Artem B.; Qian, Budong; Kokelj, Steven V.; Lantz, Trevor C.

    2018-04-01

    Climate warming has significant impacts on permafrost, infrastructure and soil organic carbon at the northern high latitudes. These impacts are mainly driven by changes in soil temperature (TS). Snow insulation can cause significant differences between TS and air temperature (TA), and our understanding about this effect through space and time is currently limited. In this study, we compiled soil and air temperature observations (measured at about 0.2 m depth and 2 m height, respectively) at 588 sites from climate stations and boreholes across the northern high latitudes. Analysis of this circumpolar dataset demonstrates the large offset between mean TS and TA in the low arctic and northern boreal regions. The offset decreases both northward and southward due to changes in snow conditions. Correlation analysis shows that the coupling between annual TS and TA is weaker, and the response of annual TS to changes in TA is smaller in boreal regions than in the arctic and the northern temperate regions. Consequently, the inter-annual variation and the increasing trends of annual TS are smaller than that of TA in boreal regions. The systematic and significant differences in the relationship between TS and TA across the circumpolar north is important for understanding and assessing the impacts of climate change and for reconstruction of historical climate based on ground temperature profiles for the northern high latitudes.

  12. Vapor flux and recrystallization during dry snow metamorphism under a steady temperature gradient as observed by time-lapse micro-tomography

    Directory of Open Access Journals (Sweden)

    B. R. Pinzer

    2012-10-01

    Full Text Available Dry snow metamorphism under an external temperature gradient is the most common type of recrystallization of snow on the ground. The changes in snow microstructure modify the physical properties of snow, and therefore an understanding of this process is essential for many disciplines, from modeling the effects of snow on climate to assessing avalanche risk. We directly imaged the microstructural changes in snow during temperature gradient metamorphism (TGM under a constant gradient of 50 K m−1, using in situ time-lapse X-ray micro-tomography. This novel and non-destructive technique directly reveals the amount of ice that sublimates and is deposited during metamorphism, in addition to the exact locations of these phase changes. We calculated the average time that an ice volume stayed in place before it sublimated and found a characteristic residence time of 2–3 days. This means that most of the ice changes its phase from solid to vapor and back many times in a seasonal snowpack where similar temperature conditions can be found. Consistent with such a short timescale, we observed a mass turnover of up to 60% of the total ice mass per day. The concept of hand-to-hand transport for the water vapor flux describes the observed changes very well. However, we did not find evidence for a macroscopic vapor diffusion enhancement. The picture of {temperature gradient metamorphism} produced by directly observing the changing microstructure sheds light on the micro-physical processes and could help to improve models that predict the physical properties of snow.

  13. Soot in the atmosphere and snow surface of Antarctica

    International Nuclear Information System (INIS)

    Warren, S.G.; Clarke, A.D.

    1990-01-01

    Samples of snow collected near the south pole during January and February 1986 were analyzed for the presence of light-absorbing particles by passing the melted snow through a nuclepore filter. Transmission of light through the filter showed that snow far from the station contains the equivalent of 0.1-0.3 ng of carbon per gram of snow (ng/g). Samples of ambient air were filtered and found to contain about 1-2 ng of carbon per kilogram of air, giving a scavenging ratio of about 150. The snow downwind of the station exhibited a well-defined plume of soot due to the burning of diesel fuel, but even in the center of the plume 1 km downwind, the soot concentration was only 3 ng/g, too small to affect snow albedo significantly. Measurements of snow albedo near large inland stations are therefore probably representative of their surrounding regions

  14. Photovoltaic cell electrical heating system for removing snow on panel including verification.

    Science.gov (United States)

    Weiss, Agnes; Weiss, Helmut

    2017-11-16

    Small photovoltaic plants in private ownership are typically rated at 5 kW (peak). The panels are mounted on roofs at a decline angle of 20° to 45°. In winter time, a dense layer of snow at a width of e.g., 10 cm keeps off solar radiation from the photovoltaic cells for weeks under continental climate conditions. Practically, no energy is produced over the time of snow coverage. Only until outside air temperature has risen high enough for a rather long-time interval to allow partial melting of snow; the snow layer rushes down in an avalanche. Following this proposal, snow removal can be arranged electrically at an extremely positive energy balance in a fast way. A photovoltaic cell is a large junction area diode inside with a threshold voltage of about 0.6 to 0.7 V (depending on temperature). This forward voltage drop created by an externally driven current through the modules can be efficiently used to provide well-distributed heat dissipation at the cell and further on at the glass surface of the whole panel. The adhesion of snow on glass is widely reduced through this heating in case a thin water film can be produced by this external short time heating. Laboratory experiments provided a temperature increase through rated panel current of more than 10 °C within about 10 min. This heating can initiate the avalanche for snow removal on intention as described before provided the clamping effect on snow at the edge of the panel frame is overcome by an additional heating foil. Basics of internal cell heat production, heating thermal effects in time course, thermographic measurements on temperature distribution, power circuit opportunities including battery storage elements and snow-removal under practical conditions are described.

  15. Experimental observation of transient δ18O interaction between snow and advective airflow under various temperature gradient conditions

    Directory of Open Access Journals (Sweden)

    P. P. Ebner

    2017-07-01

    Full Text Available Stable water isotopes (δ18O obtained from snow and ice samples of polar regions are used to reconstruct past climate variability, but heat and mass transport processes can affect the isotopic composition. Here we present an experimental study on the effect of airflow on the snow isotopic composition through a snow pack in controlled laboratory conditions. The influence of isothermal and controlled temperature gradient conditions on the δ18O content in the snow and interstitial water vapour is elucidated. The observed disequilibrium between snow and vapour isotopes led to the exchange of isotopes between snow and vapour under non-equilibrium processes, significantly changing the δ18O content of the snow. The type of metamorphism of the snow had a significant influence on this process. These findings are pertinent to the interpretation of the records of stable isotopes of water from ice cores. These laboratory measurements suggest that a highly resolved climate history is relevant for the interpretation of the snow isotopic composition in the field.

  16. Estimation of Snow Particle Model Suitable for a Complex and Forested Terrain: Lessons from SnowEx

    Science.gov (United States)

    Gatebe, C. K.; Li, W.; Stamnes, K. H.; Poudyal, R.; Fan, Y.; Chen, N.

    2017-12-01

    SnowEx 2017 obtained consistent and coordinated ground and airborne remote sensing measurements over Grand Mesa in Colorado, which feature sufficient forested stands to have a range of density and height (and other forest conditions); a range of snow depth/snow water equivalent (SWE) conditions; sufficiently flat snow-covered terrain of a size comparable to airborne instrument swath widths. The Cloud Absorption Radiometer (CAR) data from SnowEx are unique and can be used to assess the accuracy of Bidirectional Reflectance-Distribution Functions (BRDFs) calculated by different snow models. These measurements provide multiple angle and multiple wavelength data needed for accurate surface BRDF characterization. Such data cannot easily be obtained by current satellite remote sensors. Compared to ground-based snow field measurements, CAR measurements minimize the effect of self-shading, and are adaptable to a wide variety of field conditions. We plan to use the CAR measurements as the validation data source for our snow modeling effort. By comparing calculated BRDF results from different snow models to CAR measurements, we can determine which model best explains the snow BRDFs, and is therefore most suitable for application to satellite remote sensing of snow parameters and surface energy budget calculations.

  17. Influence of cloud fraction and snow cover to the variation of surface UV radiation at King Sejong station, Antarctica

    Science.gov (United States)

    Lee, Yun Gon; Koo, Ja-Ho; Kim, Jhoon

    2015-10-01

    This study investigated how cloud fraction and snow cover affect the variation of surface ultraviolet (UV) radiation by using surface Erythemal UV (EUV) and Near UV (NUV) observed at the King Sejong Station, Antarctica. First the Radiative Amplification Factor (RAF), the relative change of surface EUV according to the total-column ozone amount, is compared for different cloud fractions and solar zenith angles (SZAs). Generally, all cloudy conditions show that the increase of RAF as SZA becomes larger, showing the larger effects of vertical columnar ozone. For given SZA cases, the EUV transmission through mean cloud layer gradually decreases as cloud fraction increases, but sometimes the maximum of surface EUV appears under partly cloudy conditions. The high surface EUV transmittance under broken cloud conditions seems due to the re-radiation of scattered EUV by cloud particles. NUV transmission through mean cloud layer also decreases as cloud amount increases but the sensitivity to the cloud fraction is larger than EUV. Both EUV and NUV radiations at the surface are also enhanced by the snow cover, and their enhancement becomes higher as SZA increases implying the diurnal variation of surface albedo. This effect of snow cover seems large under the overcast sky because of the stronger interaction between snow surface and cloudy sky.

  18. Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site

    Science.gov (United States)

    Barrere, Mathieu; Domine, Florent; Decharme, Bertrand; Morin, Samuel; Vionnet, Vincent; Lafaysse, Matthieu

    2017-09-01

    Climate change projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.

  19. A simple model for predicting soil temperature in snow-covered and seasonally frozen soil: model description and testing

    Directory of Open Access Journals (Sweden)

    K. Rankinen

    2004-01-01

    Full Text Available Microbial processes in soil are moisture, nutrient and temperature dependent and, consequently, accurate calculation of soil temperature is important for modelling nitrogen processes. Microbial activity in soil occurs even at sub-zero temperatures so that, in northern latitudes, a method to calculate soil temperature under snow cover and in frozen soils is required. This paper describes a new and simple model to calculate daily values for soil temperature at various depths in both frozen and unfrozen soils. The model requires four parameters: average soil thermal conductivity, specific heat capacity of soil, specific heat capacity due to freezing and thawing and an empirical snow parameter. Precipitation, air temperature and snow depth (measured or calculated are needed as input variables. The proposed model was applied to five sites in different parts of Finland representing different climates and soil types. Observed soil temperatures at depths of 20 and 50 cm (September 1981–August 1990 were used for model calibration. The calibrated model was then tested using observed soil temperatures from September 1990 to August 2001. R2-values of the calibration period varied between 0.87 and 0.96 at a depth of 20 cm and between 0.78 and 0.97 at 50 cm. R2-values of the testing period were between 0.87 and 0.94 at a depth of 20cm, and between 0.80 and 0.98 at 50cm. Thus, despite the simplifications made, the model was able to simulate soil temperature at these study sites. This simple model simulates soil temperature well in the uppermost soil layers where most of the nitrogen processes occur. The small number of parameters required means that the model is suitable for addition to catchment scale models. Keywords: soil temperature, snow model

  20. Prediction of Backscatter and Emissivity of Snow at Millimeter Wavelengths.

    Science.gov (United States)

    1980-01-01

    AD-AI16 9A MASSACHUISETTS IMST OF TECH CAMBRIDGE RESEARCH LAB OF-ETC F/6 17/9 PREDICTION OF BACKSCATTER AND EMISSIVITY OF SNOW AT MILLETER --ETC(U...emitting media such as snow. The emissivity in the Ray- leigh- Jeans approximation is then the microwave brightness tempera- ture T divided by an effective...resistivity, and thermal tempera- ture. Jean et al. (Reference 125) compared a theoretical expression for the total apparent temperature of a smooth surface

  1. The Snow Must Go On: Ground Ice Encasement, Snow Compaction and Absence of Snow Differently Cause Soil Hypoxia, CO2 Accumulation and Tree Seedling Damage in Boreal Forest.

    Science.gov (United States)

    Martz, Françoise; Vuosku, Jaana; Ovaskainen, Anu; Stark, Sari; Rautio, Pasi

    2016-01-01

    At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity.

  2. Calculation of new snow densities from sub-daily automated snow measurements

    Science.gov (United States)

    Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Lehning, Michael; Olefs, Marc

    2017-04-01

    In mountain regions there is an increasing demand for high-quality analysis, nowcasting and short-range forecasts of the spatial distribution of snowfall. Operational services, such as for avalanche warning, road maintenance and hydrology, as well as hydropower companies and ski resorts need reliable information on the depth of new snow (HN) and the corresponding water equivalent (HNW). However, the ratio of HNW to HN can vary from 1:3 to 1:30 because of the high variability of new snow density with respect to meteorological conditions. In the past, attempts were made to calculate new snow densities from meteorological parameters mainly using daily values of temperature and wind. Further complex statistical relationships have been used to calculate new snow densities on hourly to sub-hourly time intervals to drive multi-layer snow cover models. However, only a few long-term in-situ measurements of new snow density exist for sub-daily time intervals. Settling processes within the new snow due to loading and metamorphism need to be considered when computing new snow density. As the effect of these processes is more pronounced for long time intervals, a high temporal resolution of measurements is desirable. Within the pluSnow project data of several automatic weather stations with simultaneous measurements of precipitation (pluviometers), snow water equivalent (SWE) using snow pillows and snow depth (HS) measurements using ultrasonic rangers were analysed. New snow densities were calculated for a set of data filtered on the basis of meteorological thresholds. The calculated new snow densities were compared to results from existing new snow density parameterizations. To account for effects of settling of the snow cover, a case study based on a multi-year data set using the snow cover model SNOWPACK at Weissfluhjoch was performed. Measured median values of hourly new snow densities at the different stations range from 54 to 83 kgm-3. This is considerably lower than a 1

  3. Enhanced Surface Warming and Accelerated Snow Melt in the Himalayas and Tibetan Plateau Induced by Absorbing Aerosols

    Science.gov (United States)

    Lau, William K.; Kim, Maeng-Ki; Kim, Kyu-Myong; Lee, Woo-Seop

    2010-01-01

    Numerical experiments with the NASA finite-volume general circulation model show that heating of the atmosphere by dust and black carbon can lead to widespread enhanced warming over the Tibetan Plateau (TP) and accelerated snow melt in the western TP and Himalayas. During the boreal spring, a thick aerosol layer, composed mainly of dust transported from adjacent deserts and black carbon from local emissions, builds up over the Indo-Gangetic Plain, against the foothills of the Himalaya and the TP. The aerosol layer, which extends from the surface to high elevation (approx.5 km), heats the mid-troposphere by absorbing solar radiation. The heating produces an atmospheric dynamical feedback the so-called elevated-heat-pump (EHP) effect, which increases moisture, cloudiness, and deep convection over northern India, as well as enhancing the rate of snow melt in the Himalayas and TP. The accelerated melting of snow is mostly confined to the western TP, first slowly in early April and then rapidly from early to mid-May. The snow cover remains reduced from mid-May through early June. The accelerated snow melt is accompanied by similar phases of enhanced warming of the atmosphere-land system of the TP, with the atmospheric warming leading the surface warming by several days. Surface energy balance analysis shows that the short-wave and long-wave surface radiative fluxes strongly offset each other, and are largely regulated by the changes in cloudiness and moisture over the TP. The slow melting phase in April is initiated by an effective transfer of sensible heat from a warmer atmosphere to land. The rapid melting phase in May is due to an evaporation-snow-land feedback coupled to an increase in atmospheric moisture over the TP induced by the EHP effect.

  4. Enhanced surface warming and accelerated snow melt in the Himalayas and Tibetan Plateau induced by absorbing aerosols

    International Nuclear Information System (INIS)

    Lau, William K M; Kim, Maeng-Ki; Lee, Woo-Seop; Kim, Kyu-Myong

    2010-01-01

    Numerical experiments with the NASA finite-volume general circulation model show that heating of the atmosphere by dust and black carbon can lead to widespread enhanced warming over the Tibetan Plateau (TP) and accelerated snow melt in the western TP and Himalayas. During the boreal spring, a thick aerosol layer, composed mainly of dust transported from adjacent deserts and black carbon from local emissions, builds up over the Indo-Gangetic Plain, against the foothills of the Himalaya and the TP. The aerosol layer, which extends from the surface to high elevation (∼5 km), heats the mid-troposphere by absorbing solar radiation. The heating produces an atmospheric dynamical feedback-the so-called elevated-heat-pump (EHP) effect, which increases moisture, cloudiness, and deep convection over northern India, as well as enhancing the rate of snow melt in the Himalayas and TP. The accelerated melting of snow is mostly confined to the western TP, first slowly in early April and then rapidly from early to mid-May. The snow cover remains reduced from mid-May through early June. The accelerated snow melt is accompanied by similar phases of enhanced warming of the atmosphere-land system of the TP, with the atmospheric warming leading the surface warming by several days. Surface energy balance analysis shows that the short-wave and long-wave surface radiative fluxes strongly offset each other, and are largely regulated by the changes in cloudiness and moisture over the TP. The slow melting phase in April is initiated by an effective transfer of sensible heat from a warmer atmosphere to land. The rapid melting phase in May is due to an evaporation-snow-land feedback coupled to an increase in atmospheric moisture over the TP induced by the EHP effect.

  5. A coupled melt-freeze temperature index approach in a one-layer model to predict bulk volumetric liquid water content dynamics in snow

    Science.gov (United States)

    Avanzi, Francesco; Yamaguchi, Satoru; Hirashima, Hiroyuki; De Michele, Carlo

    2016-04-01

    Liquid water in snow rules runoff dynamics and wet snow avalanches release. Moreover, it affects snow viscosity and snow albedo. As a result, measuring and modeling liquid water dynamics in snow have important implications for many scientific applications. However, measurements are usually challenging, while modeling is difficult due to an overlap of mechanical, thermal and hydraulic processes. Here, we evaluate the use of a simple one-layer one-dimensional model to predict hourly time-series of bulk volumetric liquid water content in seasonal snow. The model considers both a simple temperature-index approach (melt only) and a coupled melt-freeze temperature-index approach that is able to reconstruct melt-freeze dynamics. Performance of this approach is evaluated at three sites in Japan. These sites (Nagaoka, Shinjo and Sapporo) present multi-year time-series of snow and meteorological data, vertical profiles of snow physical properties and snow melt lysimeters data. These data-sets are an interesting opportunity to test this application in different climatic conditions, as sites span a wide latitudinal range and are subjected to different snow conditions during the season. When melt-freeze dynamics are included in the model, results show that median absolute differences between observations and predictions of bulk volumetric liquid water content are consistently lower than 1 vol%. Moreover, the model is able to predict an observed dry condition of the snowpack in 80% of observed cases at a non-calibration site, where parameters from calibration sites are transferred. Overall, the analysis show that a coupled melt-freeze temperature-index approach may be a valid solution to predict average wetness conditions of a snow cover at local scale.

  6. Metagenomic and satellite analyses of red snow in the Russian Arctic

    Directory of Open Access Journals (Sweden)

    Nao Hisakawa

    2015-12-01

    Full Text Available Cryophilic algae thrive in liquid water within snow and ice in alpine and polar regions worldwide. Blooms of these algae lower albedo (reflection of sunlight, thereby altering melting patterns (Kohshima, Seko & Yoshimura, 1993; Lutz et al., 2014; Thomas & Duval, 1995. Here metagenomic DNA analysis and satellite imaging were used to investigate red snow in Franz Josef Land in the Russian Arctic. Franz Josef Land red snow metagenomes confirmed that the communities are composed of the autotroph Chlamydomonas nivalis that is supporting a complex viral and heterotrophic bacterial community. Comparisons with white snow communities from other sites suggest that white snow and ice are initially colonized by fungal-dominated communities and then succeeded by the more complex C. nivalis-heterotroph red snow. Satellite image analysis showed that red snow covers up to 80% of the surface of snow and ice fields in Franz Josef Land and globally. Together these results show that C. nivalis supports a local food web that is on the rise as temperatures warm, with potential widespread impacts on alpine and polar environments worldwide.

  7. Siberia snow depth climatology derived from SSM/I data using a combined dynamic and static algorithm

    Science.gov (United States)

    Grippa, M.; Mognard, N.; Le, Toan T.; Josberger, E.G.

    2004-01-01

    One of the major challenges in determining snow depth (SD) from passive microwave measurements is to take into account the spatiotemporal variations of the snow grain size. Static algorithms based on a constant snow grain size cannot provide accurate estimates of snow pack thickness, particularly over large regions where the snow pack is subjected to big spatial temperature variations. A recent dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from the Special Sensor Microwave/Imager (SSM/I) over the Northern Great Plains (NGP) in the US. In this paper, we develop a combined dynamic and static algorithm to estimate snow depth from 13 years of SSM/I observations over Central Siberia. This region is characterised by extremely cold surface air temperatures and by the presence of permafrost that significantly affects the ground temperature. The dynamic algorithm is implemented to take into account these effects and it yields accurate snow depths early in the winter, when thin snowpacks combine with cold air temperatures to generate rapid crystal growth. However, it is not applicable later in the winter when the grain size growth slows. Combining the dynamic algorithm to a static algorithm, with a temporally constant but spatially varying coefficient, we obtain reasonable snow depth estimates throughout the entire snow season. Validation is carried out by comparing the satellite snow depth monthly averages to monthly climatological data. We show that the location of the snow depth maxima and minima is improved when applying the combined algorithm, since its dynamic portion explicitly incorporate the thermal gradient through the snowpack. The results obtained are presented and evaluated for five different vegetation zones of Central Siberia. Comparison with in situ measurements is also shown and discussed. ?? 2004 Elsevier Inc. All rights reserved.

  8. Arctic tundra shrub invasion and soot deposition: Consequences for spring snowmelt and near-surface air temperatures

    Science.gov (United States)

    Strack, John E.; Pielke, Roger A.; Liston, Glen E.

    2007-12-01

    Invasive shrubs and soot pollution both have the potential to alter the surface energy balance and timing of snow melt in the Arctic. Shrubs reduce the amount of snow lost to sublimation on the tundra during the winter leading to a deeper end-of-winter snowpack. The shrubs also enhance the absorption of energy by the snowpack during the melt season by converting incoming solar radiation to longwave radiation and sensible heat. Soot deposition lowers the albedo of the snow, allowing it to more effectively absorb incoming solar radiation and thus melt faster. This study uses the Colorado State University Regional Atmospheric Modeling System version 4.4 (CSU-RAMS 4.4), equipped with an enhanced snow model, to investigate the effects of shrub encroachment and soot deposition on the atmosphere and snowpack in the Kuparuk Basin of Alaska during the May-June melt period. The results of the simulations suggest that a complete invasion of the tundra by shrubs leads to a 2.2°C warming of 3 m air temperatures and a 108 m increase in boundary layer depth during the melt period. The snow-free date also occurred 11 d earlier despite having a larger initial snowpack. The results also show that a decrease in the snow albedo of 0.1, owing to soot pollution, caused the snow-free date to occur 5 d earlier. The soot pollution caused a 1.0°C warming of 3 m air temperatures and a 25 m average deepening of the boundary layer.

  9. Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

    International Nuclear Information System (INIS)

    Stanzel, Ph; Haberl, U; Nachtnebel, H P

    2008-01-01

    Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

  10. Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Stanzel, Ph; Haberl, U; Nachtnebel, H P [Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Muthgasse 18, 1190 Vienna (Austria)], E-mail: philipp.stanzel@boku.ac.at

    2008-11-01

    Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

  11. Evaluation of snow cover and snow depth on the Qinghai–Tibetan Plateau derived from passive microwave remote sensing

    Directory of Open Access Journals (Sweden)

    L. Dai

    2017-08-01

    Full Text Available Snow cover on the Qinghai–Tibetan Plateau (QTP plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow

  12. Snow Cover Mapping at the Continental to Global Scale Using Combined Visible and Passive Microwave Satellite Data

    Science.gov (United States)

    Armstrong, R. L.; Brodzik, M.; Savoie, M. H.

    2007-12-01

    Over the past several decades both visible and passive microwave satellite data have been utilized for snow mapping at the continental to global scale. Snow mapping using visible data has been based primarily on the magnitude of the surface reflectance, and in more recent cases on specific spectral signatures, while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Both passive microwave and visible data sets indicate a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. We describe the respective problems as well as the advantages and disadvantages of these two types of satellite data for snow cover mapping and demonstrate how a multi-sensor approach is optimal. For the period 1978 to present we combine data from the NOAA weekly snow charts with snow cover derived from the SMMR and SSM/I brightness temperature data. For the period since 2002 we blend NASA EOS MODIS and AMSR-E data sets. Our current product incorporates MODIS data from the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) with microwave-derived snow water equivalent (SWE) at 25 km, resulting in a blended product that includes percent snow cover in the larger grid cell whenever the microwave SWE signal is absent. Validation of AMSR-E at the brightness temperature level is provided through the comparison with data from the well-calibrated heritage SSM/I sensor over large homogeneous snow-covered surfaces (e.g. Dome C region, Antarctica). We also describe how the application of the higher frequency microwave channels (85 and 89 GHz)enhances accurate mapping of shallow and intermittent snow cover.

  13. Snow reliability in ski resorts considering artificial snowmaking

    Science.gov (United States)

    Hofstätter, M.; Formayer, H.; Haas, P.

    2009-04-01

    Snow reliability is the key factor to make skiing on slopes possible and to ensure added value in winter tourism. In this context snow reliability is defined by the duration of a snowpack on the ski runs of at least 50 mm snow water equivalent (SWE), within the main season (Dec-Mar). Furthermore the snowpack should form every winter and be existent early enough in season. In our work we investigate the snow reliability of six Austrian ski resorts. Because nearly all Austrian resorts rely on artificial snowmaking it is of big importance to consider man made snow in the snowpack accumulation and ablation in addition to natural snow. For each study region observed weather data including temperature, precipitation and snow height are used. In addition we differentiate up to three elevations on each site (valley, intermediate, mountain top), being aware of the typical local winter inversion height. Time periods suitable for artificial snow production, for several temperature threshold (-6,-4 or -1 degree Celsius) are calculated on an hourly base. Depending on the actual snowpack height, man made snow can be added in the model with different defined capacities, considering different technologies or the usage of additives. To simulate natural snowpack accumulation and ablation we a simple snow model, based on daily precipitation and temperature. This snow model is optimized at each site separately through certain parameterization factors. Based on the local observations and the monthly climate change signals from the climate model REMO-UBA, we generate long term time series of temperature and precipitation, using the weather generator LARS. Thereby we are not only able to simulate the snow reliability under current, but also under future climate conditions. Our results show significant changes in snow reliability, like an increase of days with insufficient snow heights, especially at mid and low altitudes under natural snow conditions. Artificial snowmaking can partly

  14. CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development

    Science.gov (United States)

    Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Khanbilvardi, R.; Munoz Barreto, J.; Yu, Y.

    2017-12-01

    CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development The Field Snow Research Station (also referred to as Snow Analysis and Field Experiment, SAFE) is operated by the NOAA Center for Earth System Sciences and Remote Sensing Technologies (CREST) in the City University of New York (CUNY). The field station is located within the premises of the Caribou Municipal Airport (46°52'59'' N, 68°01'07'' W) and in close proximity to the National Weather Service (NWS) Regional Forecast Office. The station was established in 2010 to support studies in snow physics and snow remote sensing. The Visible Infrared Imager Radiometer Suite (VIIRS) Land Surface Temperature (LST) Environmental Data Record (EDR) and Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (provided by the Terra and Aqua Earth Observing System satellites) were validated using in situ LST (T-skin) and near-surface air temperature (T-air) observations recorded at CREST-SAFE for the winters of 2013 and 2014. Results indicate that T-air correlates better than T-skin with VIIRS LST data and that the accuracy of nighttime LST retrievals is considerably better than that of daytime. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and night-time values. Results indicate that, although all the data sets showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C). Additionally, we created a liquid water content (LWC)-profiling instrument using time-domain reflectometry (TDR) at CREST-SAFE and tested it during the snow melt period (February-April) immediately after installation in 2014. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Lastly, to improve on global snow cover mapping, a snow product capable of estimating snow depth and snow water

  15. Seasonal and altitudinal variations in snow algal communities on an Alaskan glacier (Gulkana glacier in the Alaska range)

    International Nuclear Information System (INIS)

    Takeuchi, Nozomu

    2013-01-01

    Snow and ice algae are cold tolerant algae growing on the surface of snow and ice, and they play an important role in the carbon cycles for glaciers and snowfields in the world. Seasonal and altitudinal variations in seven major taxa of algae (green algae and cyanobacteria) were investigated on the Gulkana glacier in Alaska at six different elevations from May to September in 2001. The snow algal communities and their biomasses changed over time and elevation. Snow algae were rarely observed on the glacier in May although air temperature had been above 0 ° C since the middle of the month and surface snow had melted. In June, algae appeared in the lower areas of the glacier, where the ablation ice surface was exposed. In August, the distribution of algae was extended to the upper parts of the glacier as the snow line was elevated. In September, the glacier surface was finally covered with new winter snow, which terminated algal growth in the season. Mean algal biomass of the study sites continuously increased and reached 6.3 × 10 μl m −2 in cell volume or 13 mg carbon m −2 in September. The algal community was dominated by Chlamydomonas nivalis on the snow surface, and by Ancylonema nordenskiöldii and Mesotaenium berggrenii on the ice surface throughout the melting season. Other algae were less abundant and appeared in only a limited area of the glacier. Results in this study suggest that algae on both snow and ice surfaces significantly contribute to the net production of organic carbon on the glacier and substantially affect surface albedo of the snow and ice during the melting season. (letter)

  16. Snow observations in Mount Lebanon (2011-2016)

    Science.gov (United States)

    Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; Fanise, Pascal; Drapeau, Laurent; Somma, Janine; Fadel, Ali; Bitar, Ahmad Al; Escadafal, Richard

    2017-08-01

    We present a unique meteorological and snow observational dataset in Mount Lebanon, a mountainous region with a Mediterranean climate, where snowmelt is an essential water resource. The study region covers the recharge area of three karstic river basins (total area of 1092 km2 and an elevation up to 3088 m). The dataset consists of (1) continuous meteorological and snow height observations, (2) snowpack field measurements, and (3) medium-resolution satellite snow cover data. The continuous meteorological measurements at three automatic weather stations (MZA, 2296 m; LAQ, 1840 m; and CED, 2834 m a.s.l.) include surface air temperature and humidity, precipitation, wind speed and direction, incoming and reflected shortwave irradiance, and snow height, at 30 min intervals for the snow seasons (November-June) between 2011 and 2016 for MZA and between 2014 and 2016 for CED and LAQ. Precipitation data were filtered and corrected for Geonor undercatch. Observations of snow height (HS), snow water equivalent, and snow density were collected at 30 snow courses located at elevations between 1300 and 2900 m a.s.l. during the two snow seasons of 2014-2016 with an average revisit time of 11 days. Daily gap-free snow cover extent (SCA) and snow cover duration (SCD) maps derived from MODIS snow products are provided for the same period (2011-2016). We used the dataset to characterize mean snow height, snow water equivalent (SWE), and density for the first time in Mount Lebanon. Snow seasonal variability was characterized with high HS and SWE variance and a relatively high snow density mean equal to 467 kg m-3. We find that the relationship between snow depth and snow density is specific to the Mediterranean climate. The current model explained 34 % of the variability in the entire dataset (all regions between 1300 and 2900 m a.s.l.) and 62 % for high mountain regions (elevation 2200-2900 m a.s.l.). The dataset is suitable for the investigation of snow dynamics and for the forcing

  17. Performance Tests of Snow-Related Variables Over the Tibetan Plateau and Himalayas Using a New Version of NASA GEOS-5 Land Surface Model that Includes the Snow Darkening Effect

    Science.gov (United States)

    Yasunari, Tppei J.; Lau, K.-U.; Koster, Randal D.; Suarez, Max; Mahanama, Sarith; Dasilva, Arlindo M.; Colarco, Peter R.

    2011-01-01

    The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GO CART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3 ; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [Ion.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1

  18. Temporal Monitoring of the Soil Freeze-Thaw Cycles over a Snow-Covered Surface by Using Air-Launched Ground-Penetrating Radar

    KAUST Repository

    Jadoon, Khan

    2015-09-18

    We tested an off-ground ground-penetrating radar (GPR) system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.

  19. Temporal Monitoring of the Soil Freeze-Thaw Cycles over a Snow-Covered Surface by Using Air-Launched Ground-Penetrating Radar

    KAUST Repository

    Jadoon, Khan; Weihermller, Lutz; McCabe, Matthew; Moghadas, Davood; Vereecken, Harry; Lambot, Sbastien

    2015-01-01

    We tested an off-ground ground-penetrating radar (GPR) system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.

  20. Temporal Monitoring of the Soil Freeze-Thaw Cycles over a Snow-Covered Surface by Using Air-Launched Ground-Penetrating Radar

    Directory of Open Access Journals (Sweden)

    Khan Zaib Jadoon

    2015-09-01

    Full Text Available We tested an off-ground ground-penetrating radar (GPR system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.

  1. An observation-based assessment of the influences of air temperature and snow depth on soil temperature in Russia

    International Nuclear Information System (INIS)

    Park, Hotaek; Sherstiukov, Artem B; Fedorov, Alexander N; Polyakov, Igor V; Walsh, John E

    2014-01-01

    This study assessed trends in the variability of soil temperature (T SOIL ) using spatially averaged observation records from Russian meteorological land stations. The contributions of surface air temperature (SAT) and snow depth (SND) to T SOIL variation were quantitatively evaluated. Composite time series of these data revealed positive trends during the period of 1921–2011, with accelerated increases since the 1970s. The T SOIL warming rate over the entire period was faster than the SAT warming rate in both permafrost and non-permafrost regions, suggesting that SND contributes to T SOIL warming. Statistical analysis revealed that the highest correlation between SND and T SOIL was in eastern Siberia, which is underlain by permafrost. SND in this region accounted for 50% or more of the observed variation in T SOIL . T SOIL in the non-permafrost region of western Siberia was significantly correlated with changes in SAT. Thus, the main factors associated with T SOIL variation differed between permafrost and non-permafrost regions. This finding underscores the importance of including SND data when assessing historical and future variations and trends of permafrost in the Northern Hemisphere. (letter)

  2. Photochemical chlorine and bromine activation from artificial saline snow

    Directory of Open Access Journals (Sweden)

    S. N. Wren

    2013-10-01

    Full Text Available The activation of reactive halogen species – particularly Cl2 – from sea ice and snow surfaces is not well understood. In this study, we used a photochemical snow reactor coupled to a chemical ionization mass spectrometer to investigate the production of Br2, BrCl and Cl2 from NaCl/NaBr-doped artificial snow samples. At temperatures above the NaCl-water eutectic, illumination of samples (λ > 310 nm in the presence of gas phase O3 led to the accelerated release of Br2, BrCl and the release of Cl2 in a process that was significantly enhanced by acidity, high surface area and additional gas phase Br2. Cl2 production was only observed when both light and ozone were present. The total halogen release depended on [ozone] and pre-freezing [NaCl]. Our observations support a "halogen explosion" mechanism occurring within the snowpack, which is initiated by heterogeneous oxidation and propagated by Br2 or BrCl photolysis and by recycling of HOBr and HOCl into the snowpack. Our study implicates this important role of active chemistry occurring within the interstitial air of aged (i.e. acidic snow for halogen activation at polar sunrise.

  3. Antarctic snow and global climate

    International Nuclear Information System (INIS)

    Granberg, H.B.

    2001-01-01

    Global circulation models (GCM) indicate that global warming will be most pronounced at polar regions and high latitudes, causing concern about the stability of the Antarctic ice cap. A project entitled the Seasonal Snow in Antarctica examined the properties of the near surface snow to determine the current conditions that influence snow cover development. The goal was to assess the response of the snow cover in Queen Maud Land (QML) to an increased atmospheric carbon dioxide content. The Antarctic snow cover in QML was examined as part of the FINNARP expeditions in 1999 and 2000 which examined the processes that influence the snow cover. Its energy and mass balance were also assessed by examining the near surface snow strata in shallow (1-2 m) pits and by taking measurements of environmental variables. This made it possible to determine if the glacier is in danger of melting at this northerly location in the Antarctic. The study also made it possible to determine which variables need to change and by how much, for significant melting to occur. It was shown that the Antarctic anticyclone creates particular conditions that protect the snow cover from melting. The anticyclone brings dry air from the stratosphere during most of the year and is exempt from the water vapour feedback. It was concluded that even a doubling of atmospheric carbon dioxide will not produce major snow melt runoff. 8 refs

  4. Impact of the snow cover scheme on snow distribution and energy budget modeling over the Tibetan Plateau

    Science.gov (United States)

    Xie, Zhipeng; Hu, Zeyong; Xie, Zhenghui; Jia, Binghao; Sun, Genhou; Du, Yizhen; Song, Haiqing

    2018-02-01

    This paper presents the impact of two snow cover schemes (NY07 and SL12) in the Community Land Model version 4.5 (CLM4.5) on the snow distribution and surface energy budget over the Tibetan Plateau. The simulated snow cover fraction (SCF), snow depth, and snow cover days were evaluated against in situ snow depth observations and a satellite-based snow cover product and snow depth dataset. The results show that the SL12 scheme, which considers snow accumulation and snowmelt processes separately, has a higher overall accuracy (81.8%) than the NY07 (75.8%). The newer scheme performs better in the prediction of overall accuracy compared with the NY07; however, SL12 yields a 15.1% underestimation rate while NY07 overestimated the SCF with a 15.2% overestimation rate. Both two schemes capture the distribution of the maximum snow depth well but show large positive biases in the average value through all periods (3.37, 3.15, and 1.48 cm for NY07; 3.91, 3.52, and 1.17 cm for SL12) and overestimate snow cover days compared with the satellite-based product and in situ observations. Higher altitudes show larger root-mean-square errors (RMSEs) in the simulations of snow depth and snow cover days during the snow-free period. Moreover, the surface energy flux estimations from the SL12 scheme are generally superior to the simulation from NY07 when evaluated against ground-based observations, in particular for net radiation and sensible heat flux. This study has great implications for further improvement of the subgrid-scale snow variations over the Tibetan Plateau.

  5. Modelling the snowmelt and the snow water equivalent by creating a simplified energy balance conceptual snow model

    Science.gov (United States)

    Riboust, Philippe; Thirel, Guillaume; Le Moine, Nicolas; Ribstein, Pierre

    2016-04-01

    A better knowledge of the accumulated snow on the watersheds will help flood forecasting centres and hydro-power companies to predict the amount of water released during spring snowmelt. Since precipitations gauges are sparse at high elevations and integrative measurements of the snow accumulated on watershed surface are hard to obtain, using snow models is an adequate way to estimate snow water equivalent (SWE) on watersheds. In addition to short term prediction, simulating accurately SWE with snow models should have many advantages. Validating the snow module on both SWE and snowmelt should give a more reliable model for climate change studies or regionalization for ungauged watersheds. The aim of this study is to create a new snow module, which has a structure that allows the use of measured snow data for calibration or assimilation. Energy balance modelling seems to be the logical choice for designing a model in which internal variables, such as SWE, could be compared to observations. Physical models are complex, needing high computational resources and many different types of inputs that are not widely measured at meteorological stations. At the opposite, simple conceptual degree-day models offer to simulate snowmelt using only temperature and precipitation as inputs with fast computing. Its major drawback is to be empirical, i.e. not taking into account all of the processes of the energy balance, which makes this kind of model more difficult to use when willing to compare SWE to observed measurements. In order to reach our objectives, we created a snow model structured by a simplified energy balance where each of the processes is empirically parameterized in order to be calculated using only temperature, precipitation and cloud cover variables. This model's structure is similar to the one created by M.T. Walter (2005), where parameterizations from the literature were used to compute all of the processes of the energy balance. The conductive fluxes into the

  6. Impacts of light-absorbing impurities on snow and their quantification with bidirectional reflectance measurements

    Science.gov (United States)

    Gritsevich, Maria; Peltoniemi, Jouni; Meinander, Outi; Dagsson-Waldhauserová, Pavla; Zubko, Nataliya; Hakala, Teemu; Virkkula, Aki; Svensson, Jonas; de Leeuw, Gerrit

    2017-04-01

    rate gets faster than the diffusion rate (under condition of warm outside temperatures), as it was observed at the end of the experiment reported here, dark material starts accumulating into the surface [5]. The BC deposited on snow at warm temperatures initiates rapid melting process and may cause dramatic changes on the snow surface. References 1 Peltoniemi J.I., Hakala T., Suomalainen J., Honkavaara E., Markelin L., Gritsevich M., Eskelinen J., Jaanson P., Ikonen E. (2014): Technical notes: A detailed study for the provision of measurement uncertainty and traceability for goniospectrometers. Journal of Quantitative Spectroscopy & Radiative Transfer 146, 376-390, http://dx.doi.org/10.1016/j.jqsrt.2014.04.011 2 Zubko N., Gritsevich M., Zubko E., Hakala T., Peltoniemi J.I. (2016): Optical measurements of chemically heterogeneous particulate surfaces // Journal of Quantitative Spectroscopy and Radiative Transfer, 178, 422-431, http://dx.doi.org/10.1016/j.jqsrt.2015.12.010 3 Peltoniemi J.I., Gritsevich M., Hakala T., Dagsson-Waldhauserová P., Arnalds Ó., Anttila K., Hannula H.-R., Kivekäs N., Lihavainen H., Meinander O., Svensson J., Virkkula A., de Leeuw G. (2015): Soot on snow exper- iment: bidirectional reflectance factor measurements of contaminated snow // The Cryosphere, 9, 2323-2337, http://dx.doi.org/10.5194/tc-9-2323-2015 4 Svensson J., Virkkula A., Meinander O., Kivekäs N., Hannula H.-R., Järvinen O., Peltoniemi J.I., Gritsevich M., Heikkilä A., Kontu A., Neitola K., Brus D., Dagsson-Waldhauserova P., Anttila K., Vehkamäki M., Hienola A., de Leeuw G. & Lihavainen H. (2016): Soot-doped natural snow and its albedo — results from field experiments. Boreal Environment Research, 21, 481-503, http://www.borenv.net/BER/pdfs/preprints/Svensson1498.pdf 5 Meinander O., Kontu A., Virkkula A., Arola A., Backman L., Dagsson-Waldhauserová P., Järvinen O., Manninen T., Svensson J., de Leeuw G., and Leppäranta M. (2014): Brief communication: Light

  7. Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

    Science.gov (United States)

    Badawy, B.; Fletcher, C. G.

    2017-12-01

    The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

  8. Review of ice and snow runway pavements

    Directory of Open Access Journals (Sweden)

    Greg White

    2018-05-01

    Full Text Available Antarctica is the highest, driest, coldest, windiest, most remote and most pristine place on Earth. Polar operations depend heavily on air transportation and support for personnel and equipment. It follows that improvement in snow and ice runway design, construction and maintenance will directly benefit polar exploration and research. Current technologies and design methods for snow and ice runways remain largely reliant on work performed in the 1950s and 1960s. This paper reviews the design and construction of polar runways using snow and ice as geomaterials. The inability to change existing snow and ice thickness or temperature creates a challenge for polar runway design and construction, as does the highly complex mechanical behaviour of snow, including the phenomena known as sintering. It is recommended that a modern approach be developed for ice and snow runway design, based on conventional rigid and flexible pavement design principles. This requires the development on an analytical model for the prediction of snow strength, based on snow age, temperature history and density. It is also recommended that the feasibility of constructing a snow runway at the South Pole be revisited, in light of contemporary snow sintering methods. Such a runway would represent a revolutionary advance for the logistical support of Antarctic research efforts. Keywords: Runway, Pavement, Snow, Ice, Antarctic

  9. Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

    Science.gov (United States)

    Comiso, Joey C.

    1995-01-01

    Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have

  10. Modelling the physical multiphase interactions of HNO3 between snow and air on the Antarctic Plateau (Dome C) and coast (Halley)

    Science.gov (United States)

    Chan, Hoi Ga; Frey, Markus M.; King, Martin D.

    2018-02-01

    Emissions of nitrogen oxide (NOx = NO + NO2) from the photolysis of nitrate (NO3-) in snow affect the oxidising capacity of the lower troposphere especially in remote regions of high latitudes with little pollution. Current air-snow exchange models are limited by poor understanding of processes and often require unphysical tuning parameters. Here, two multiphase models were developed from physically based parameterisations to describe the interaction of nitrate between the surface layer of the snowpack and the overlying atmosphere. The first model is similar to previous approaches and assumes that below a threshold temperature, To, the air-snow grain interface is pure ice and above To a disordered interface (DI) emerges covering the entire grain surface. The second model assumes that air-ice interactions dominate over all temperatures below melting of ice and that any liquid present above the eutectic temperature is concentrated in micropockets. The models are used to predict the nitrate in surface snow constrained by year-round observations of mixing ratios of nitric acid in air at a cold site on the Antarctic Plateau (Dome C; 75°06' S, 123°33' E; 3233 m a.s.l.) and at a relatively warm site on the Antarctic coast (Halley; 75°35' S, 26°39' E; 35 m a.s.l). The first model agrees reasonably well with observations at Dome C (Cv(RMSE) = 1.34) but performs poorly at Halley (Cv(RMSE) = 89.28) while the second model reproduces with good agreement observations at both sites (Cv(RMSE) = 0.84 at both sites). It is therefore suggested that in winter air-snow interactions of nitrate are determined by non-equilibrium surface adsorption and co-condensation on ice coupled with solid-state diffusion inside the grain, similar to Bock et al. (2016). In summer, however, the air-snow exchange of nitrate is mainly driven by solvation into liquid micropockets following Henry's law with contributions to total surface snow NO3- concentrations of 75 and 80 % at Dome C and Halley

  11. Temperature dependence of bromine activation due to reaction of bromide with ozone in a proxy for organic aerosols and its importance for chemistry in surface snow.

    Science.gov (United States)

    Edebeli, Jacinta; Ammann, Markus; Gilgen, Anina; Trachsel, Jürg; Avak, Sven; Eichler, Anja; Schneebeli, Martin; Bartels-Rausch, Thorsten

    2017-04-01

    Tropospheric ozone depletion events (ODEs) via halogen activation are observed in both cold and warm climates [1-3]. Very recently, it was suggested that this multiphase halogen activation chemistry dominates in the tropical and subtropical upper troposphere [4]. These occurrences beg the question of temperature dependence of halogen activation in sea-salt aerosol, which are often mixtures of sea-salt and organic molecules [3, 5]. With the application of flow-tubes, the aim of this study is to investigate the temperature dependence of bromine activation via ozone interaction in a bromide containing film as a proxy for mixed organic - sea-salt aersol. Citric acid is used in this study as a hygroscopically characterized matrix and a proxy for oxidized organics, which is of relevance to atmospheric chemistry. Here, we present reactive ozone uptake measured between 258 and 289 K. The data show high reproducibility. With available knowledge, we have reproduced the measured uptake with modelled bulk uptake while accounting for temperature dependence of the substrate's properties as diffusivity, viscosity, and gas solubility. This work is part of a cross-disciplinary project with the aim to investigate the impact of metamorphism on impurity location in aging snow and its consequences for chemical reactivity. Metamorphism drastically shapes the structure and physical properties of snow, which has impacts on heat transfer, albedo, and avalanche formation. Such changes can be driven by water vapour fluxes in dry metamorphism with a mass turnover of as much as 60% per day - much greater than previously thought [6]. The consequences for atmospheric science are a current question of research [7]. Here, we show first results of a joint experiment to probe the re-distribution of impurities during snow metamorphism in artificial snow combined with an investigation of the samples structural changes. Future work is planned with the goal to investigate to which extend the observed re

  12. Effects of Planting of Calluna Vulgaris for Stable Snow Accumulation in Winter

    Science.gov (United States)

    Ibuki, R.; Harada, K.

    2017-12-01

    Recent year climate of the winter season is changing and the period of snow accumulation is reduced compared with before. It affects the management of the ski resort. Snowfall had occurred in December 2016, but the snow accumulated after January 2017 at the ski resort located in the Pacific Ocean side of the Northeast region of Japan. This situation is thought to be originated from two reasons, one is snow thawing, another is to be blown away by the strong monsoon wind. We are considering utilizing planting to stabilize snow accumulation. Currently building rock gardens with shrubs, mainly Calluna Vulgaris in the ski resort for attracting customers in the summer. These are difficult to raise in the lowlands of Japan because they are too hot, but because of their good growth in relatively low-temperature highlands, it is rare for local residents to appreciate the value of these. In addition, it is excellent in low temperature resistance, and it will not die even under the snow. We investigated the pressure resistance performance due to snowfall and the appropriateness of growth under the weather conditions of the area. Regarding Calluna Vulgaris, Firefly, the plants were not damaged even under snow more than 1 m. In addition, three years have passed since planting, relatively good growth is shown, and the stock has been growing every year. Based on these results, we plan to stabilize the snow accumulation by carrying out planting of Calluna vulgaris inside the slope. The growth of the Calluna species is gentle and the tree height grows only about 50 cm even if 15 years have passed since planting. Therefore, it is considered that the plant body is hard to put out their head on the snow surface during the ski season. Next season will monitor the snow accumulation around the planting area through the snow season.

  13. Measurement of the Spectral Absorption of Liquid Water in Melting Snow With an Imaging Spectrometer

    Science.gov (United States)

    Green, Robert O.; Dozier, Jeff

    1995-01-01

    Melting of the snowpack is a critical parameter that drives aspects of the hydrology in regions of the Earth where snow accumulates seasonally. New techniques for measurement of snow melt over regional scales offer the potential to improve monitoring and modeling of snow-driven hydrological processes. In this paper we present the results of measuring the spectral absorption of liquid water in a melting snowpack with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data were acquired over Mammoth Mountain, in east central California on 21 May 1994 at 18:35 UTC. The air temperature at 2926 m on Mammoth Mountain at site A was measured at 15-minute intervals during the day preceding the AVIRIS data acquisition. At this elevation. the air temperature did not drop below freezing the night of the May 20 and had risen to 6 degrees Celsius by the time of the overflight on May 21. These temperature conditions support the presence of melting snow at the surface as the AVIRIS data were acquired.

  14. Application of Snowfall and Wind Statistics to Snow Transport Modeling for Snowdrift Control in Minnesota.

    Science.gov (United States)

    Shulski, Martha D.; Seeley, Mark W.

    2004-11-01

    Models were utilized to determine the snow accumulation season (SAS) and to quantify windblown snow for the purpose of snowdrift control for locations in Minnesota. The models require mean monthly temperature, snowfall, density of snow, and wind frequency distribution statistics. Temperature and precipitation data were obtained from local cooperative observing sites, and wind data came from Automated Surface Observing System (ASOS)/Automated Weather Observing System (AWOS) sites in the region. The temperature-based algorithm used to define the SAS reveals a geographic variability in the starting and ending dates of the season, which is determined by latitude and elevation. Mean seasonal snowfall shows a geographic distribution that is affected by topography and proximity to Lake Superior. Mean snowfall density also exhibits variability, with lower-density snow events displaced to higher-latitude positions. Seasonal wind frequencies show a strong bimodal distribution with peaks from the northwest and southeast vector direction, with an exception for locations in close proximity to the Lake Superior shoreline. In addition, for western and south-central Minnesota there is a considerably higher frequency of wind speeds above the mean snow transport threshold of 7 m s-1. As such, this area is more conducive to higher potential snow transport totals. Snow relocation coefficients in this area are in the range of 0.4 0.9, and, according to the empirical models used in this analysis, this range implies that actual snow transport is 40% 90% of the total potential in south-central and western areas of the state.

  15. Small scale variability of snow density on Antarctic sea ice

    Science.gov (United States)

    Wever, N.; Leonard, K. C.; Paul, S.; Jacobi, H. W.; Proksch, M.; Lehning, M.

    2016-12-01

    Snow on sea ice plays an important role in air-ice-sea interactions. For example, snow may smooth the ice surface when snow drift is occurring, while at the same time it may also generate roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. We present data from an in-situ measurement campaign in the Weddell Sea during two subsequent cruises of RV Polarstern. By comparing snow density from snow pits and snow micro penetrometer (SMP) measurements, augmented by terrestrial laser scanning (TLS) on an area of 50x50 m2, highly resolved density profiles and surface topology were acquired at a horizontal resolution of approximately 30 cm. Average snow densities are about 280 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 170 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters, which disappear over larger distances. A comparison with TLS data indicates that the spatial variability is related to deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density profiles. The fundamental relationship between density variations, surface roughness and changes therein as investigated in this study are interpreted with respect to larger-scale ice-movement and the ice mass balance.

  16. Improving Surface Mass Balance Over Ice Sheets and Snow Depth on Sea Ice

    Science.gov (United States)

    Koenig, Lora Suzanne; Box, Jason; Kurtz, Nathan

    2013-01-01

    Surface mass balance (SMB) over ice sheets and snow on sea ice (SOSI) are important components of the cryosphere. Large knowledge gaps remain in scientists' abilities to monitor SMB and SOSI, including insufficient measurements and difficulties with satellite retrievals. On ice sheets, snow accumulation is the sole mass gain to SMB, and meltwater runoff can be the dominant single loss factor in extremely warm years such as 2012. SOSI affects the growth and melt cycle of the Earth's polar sea ice cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland ice sheet and the smallest satellite-recorded Arctic sea ice extent, making this meeting both timely and relevant.

  17. Accuracy assessment of a net radiation and temperature index snowmelt model using ground observations of snow water equivalent in an alpine basin

    Science.gov (United States)

    Molotch, N. P.; Painter, T. H.; Bales, R. C.; Dozier, J.

    2003-04-01

    In this study, an accumulated net radiation / accumulated degree-day index snowmelt model was coupled with remotely sensed snow covered area (SCA) data to simulate snow cover depletion and reconstruct maximum snow water equivalent (SWE) in the 19.1-km2 Tokopah Basin of the Sierra Nevada, California. Simple net radiation snowmelt models are attractive for operational snowmelt runoff forecasts as they are computationally inexpensive and have low input requirements relative to physically based energy balance models. The objective of this research was to assess the accuracy of a simple net radiation snowmelt model in a topographically heterogeneous alpine environment. Previous applications of net radiation / temperature index snowmelt models have not been evaluated in alpine terrain with intensive field observations of SWE. Solar radiation data from two meteorological stations were distributed using the topographic radiation model TOPORAD. Relative humidity and temperature data were distributed based on the lapse rate calculated between three meteorological stations within the basin. Fractional SCA data from the Landsat Enhanced Thematic Mapper (5 acquisitions) and the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) (2 acquisitions) were used to derive daily SCA using a linear regression between acquisition dates. Grain size data from AVIRIS (4 acquisitions) were used to infer snow surface albedo and interpolated linearly with time to derive daily albedo values. Modeled daily snowmelt rates for each 30-m pixel were scaled by the SCA and integrated over the snowmelt season to obtain estimates of maximum SWE accumulation. Snow surveys consisting of an average of 335 depth measurements and 53 density measurements during April, May and June, 1997 were interpolated using a regression tree / co-krig model, with independent variables of average incoming solar radiation, elevation, slope and maximum upwind slope. The basin was clustered into 7 elevation / average

  18. Blowing snow sublimation and transport over Antarctica from 11 years of CALIPSO observations

    Directory of Open Access Journals (Sweden)

    S. P. Palm

    2017-11-01

    Full Text Available Blowing snow processes commonly occur over the earth's ice sheets when the 10 m wind speed exceeds a threshold value. These processes play a key role in the sublimation and redistribution of snow thereby influencing the surface mass balance. Prior field studies and modeling results have shown the importance of blowing snow sublimation and transport on the surface mass budget and hydrological cycle of high-latitude regions. For the first time, we present continent-wide estimates of blowing snow sublimation and transport over Antarctica for the period 2006–2016 based on direct observation of blowing snow events. We use an improved version of the blowing snow detection algorithm developed for previous work that uses atmospheric backscatter measurements obtained from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization lidar aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite. The blowing snow events identified by CALIPSO and meteorological fields from MERRA-2 are used to compute the blowing snow sublimation and transport rates. Our results show that maximum sublimation occurs along and slightly inland of the coastline. This is contrary to the observed maximum blowing snow frequency which occurs over the interior. The associated temperature and moisture reanalysis fields likely contribute to the spatial distribution of the maximum sublimation values. However, the spatial pattern of the sublimation rate over Antarctica is consistent with modeling studies and precipitation estimates. Overall, our results show that the 2006–2016 Antarctica average integrated blowing snow sublimation is about 393 ± 196 Gt yr−1, which is considerably larger than previous model-derived estimates. We find maximum blowing snow transport amount of 5 Mt km−1 yr−1 over parts of East Antarctica and estimate that the average snow transport from continent to ocean is about 3.7 Gt yr−1. These

  19. Moving sidewalk for snow board gelande; Snow board gerendemuke ugoku hodo

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-04-20

    This is a moving sidewalk installed on the indoor type artificial snow board gelande at Shigenobu-cho, Ehime prefecture, constructed for the first time in Shikoku. It carries snow boarders in gelande. The main specifications are as follows. Type: 800 type. Sidewalk width: 600mm. Length: 76.0m. Speed: 30m/min. Inclination angle: 13 degrees (inclination type). The features are as follows. (1) The tread is rubber-belt made and skid-resistant if it gets wet. (2) It is equipped with the each-part antifreezer, considering the snow quality and the environment where it is used at low temperature. (translated by NEDO)

  20. STUDY ON THE RETRIEVAL OF SNOW DEPTH FROM FY3B/MWRI IN THE ATCTIC

    Directory of Open Access Journals (Sweden)

    L. Li

    2016-06-01

    Full Text Available temperatures. Given the high albedo and low thermal conductivity, snow is regarded as one of the key reasons for the amplification of the warming in polar regions. The distributions of sea ice and snow depth are essential to the whole thermal conduction in the Arctic. This study focused on the retrieval of snow depth on sea ice from brightness temperatures of the MicroWave Radiometer Imager (MWRI onboard the FengYun (FY-3B satellite during the period from December 1, 2010 to April 30, 2011. After cross calibrated to the Advanced Microwave Scanning Radiometer–EOS (AMSR-E Level 2A data, the MWRI brightness temperatures were applied to calculate the sea ice concentrations based on the Arctic Radiation and Turbulence Interaction Study Sea Ice (ASI algorithm. According to the proportional relationship between the snow depth and the surface scattering in 18.7 and 36.5 GHz, the snow depths were derived. In order to eliminate the influence of uncertainties in grain sizes of snow as well as sporadic weather effects, the seven-day averaged snow depths were calculated. Then the results were compared with the snow depths from the AMSR-E Level 3 Sea Ice products. The bias of differences between the MWRI and the AMSR-E Level 3 products are ranged between −1.09 and −0.32 cm,while the standard deviations and the correlation coefficients are ranged from 2.47 to 2.88 cm and from 0.78 to 0.90 for different months. As a result, it could be summarized that FY3B/MWRI showed a promising prospect in retrieving snow depth on sea ice.

  1. Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

    Science.gov (United States)

    Dong, Jiarui; Ek, Mike; Hall, Dorothy K.; Peters-Lidard, Christa; Cosgrove, Brian; Miller, Jeff; Riggs, George A.; Xia, Youlong

    2013-01-01

    In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

  2. Role of the Soil Thermal Inertia in the short term variability of the surface temperature and consequences for the soil-moisture temperature feedback

    Science.gov (United States)

    Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing

    2017-04-01

    A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM

  3. Snow clearance

    CERN Multimedia

    Mauro Nonis

    2005-01-01

    In reply to the numerous questions received, we should like to inform you of the actions and measures taken in an effort to maintain the movements of vehicles and pedestrians since the heavy snow fall on Sunday 23 January. Our contractor's employees began clearing the snow during the morning of Sunday 23 January on the main CERN sites (Meyrin, Prévessin), but an accident prevented them from continuing. The vehicle in question was repaired by Monday morning when two other vehicles joined it to resume snow clearing; priority was given to access points to the main sites and the LHC sites, as well as to the main roads inside the sites. The salt sprinklers were also brought into action that same day; the very low temperature during the night from Monday to Tuesday prevented the snow from melting and compacted the ice; the continuing cold during the day on Tuesday (-6°C at 10:00 on the Meyrin site) meant that all efforts to remove the ice were doomed to failure. In order to ensure more efficie...

  4. Snow Precipitation and Snow Cover Climatic Variability for the Period 1971–2009 in the Southwestern Italian Alps: The 2008–2009 Snow Season Case Study

    Directory of Open Access Journals (Sweden)

    Simona Fratianni

    2010-10-01

    Full Text Available Snow cover greatly influences the climate in the Alpine region and is one of the most relevant parameters for the climate change analysis. Nevertheless, snow precipitation variability is a relatively underexplored field of research because of the lack of long-term, continuous and homogeneous time series. After a historical research aiming to recover continuous records, three high quality time series of snow precipitation and snow depth recorded in the southwestern Italian Alps were analyzed. The comparison between the climatological indices over the 30 years reference period 1971–2000 and the decade 2000–2009 outlined a general decrease in the amount of snow precipitation, and a shift in the seasonal distribution of the snow precipitation in the most recent period. In the analysis of the last decade snow seasons characteristics, the attention was focused on the heavy snowfalls that occurred in Piedmont during the 2008–2009 snow season: MODerate resolution Imager Spectroradiometer (MODIS snow cover products were used to evaluate snow cover extension at different times during the snow season, and the results were set in relation to the temperatures.

  5. Snow loads in a changing climate: new risks?

    Directory of Open Access Journals (Sweden)

    U. Strasser

    2008-01-01

    Full Text Available In January/February 2006, heavy snowfalls in Bavaria (Germany lead to a series of infrastructural damage of catastrophic nature. Since on many collapsed roofs the total snow load was not exceptional, serious engineering deficiencies in roof construction and a sudden rise in the total snow load were considered to be the trigger of the events. An analysis of the then meteorological conditions reveals, that the early winter of 2005/2006 was characterised by an exceptional continuous snow cover, temperatures remained around the freezing point and no significant snowmelt was evident. The frequent freezing/thawing cycles were followed by a general compaction of the snow load. This resulted in a re-distribution and a new concentration of the snow load on specific locations on roofs. With respect to climate change, the question arises as to whether the risks relating to snow loads will increase. The future probability of a continuous snow cover occurrence with frequent freezing/thawing cycles will probably decline due to predicted higher temperatures. However, where temperatures remain low, an increase in winter precipitation will result in increased snow loads. Furthermore, the variability of extremes is predicted to increase. If heavy snowfall events are more frequent, the risk of a trigger event will likely increase. Finally, an attempt will be made here in this paper to outline a concept for an operational warning system for the Bavarian region. This system envisages to predict the development and risk of critical snow loads for a 3-day time period, utilising a combination of climate and snow modelling data and using this together with a snow pillow device (located on roofs and the results of which.

  6. Wind-driven snow conditions control the occurrence of contemporary marginal mountain permafrost in the Chic-Choc Mountains, south-eastern Canada: a case study from Mont Jacques-Cartier

    Science.gov (United States)

    Davesne, Gautier; Fortier, Daniel; Domine, Florent; Gray, James T.

    2017-06-01

    We present data on the distribution and thermophysical properties of snow collected sporadically over 4 decades along with recent data of ground surface temperature from Mont Jacques-Cartier (1268 m a.s.l.), the highest summit in the Appalachians of south-eastern Canada. We demonstrate that the occurrence of contemporary permafrost is necessarily associated with a very thin and wind-packed winter snow cover which brings local azonal topo-climatic conditions on the dome-shaped summit. The aims of this study were (i) to understand the snow distribution pattern and snow thermophysical properties on the Mont Jacques-Cartier summit and (ii) to investigate the impact of snow on the spatial distribution of the ground surface temperature (GST) using temperature sensors deployed over the summit. Results showed that above the local treeline, the summit is characterized by a snow cover typically less than 30 cm thick which is explained by the strong westerly winds interacting with the local surface roughness created by the physiography and surficial geomorphology of the site. The snowpack structure is fairly similar to that observed on windy Arctic tundra with a top dense wind slab (300 to 450 kg m-3) of high thermal conductivity, which facilitates heat transfer between the ground surface and the atmosphere. The mean annual ground surface temperature (MAGST) below this thin and wind-packed snow cover was about -1 °C in 2013 and 2014, for the higher, exposed, blockfield-covered sector of the summit characterized by a sporadic herbaceous cover. In contrast, for the gentle slopes covered with stunted spruce (krummholz), and for the steep leeward slope to the south-east of the summit, the MAGST was around 3 °C in 2013 and 2014. The study concludes that the permafrost on Mont Jacques-Cartier, most widely in the Chic-Choc Mountains and by extension in the southern highest summits of the Appalachians, is therefore likely limited to the barren wind-exposed surface of the summit

  7. Performance evaluation of snow and ice plows.

    Science.gov (United States)

    2015-11-01

    Removal of ice and snow from road surfaces is a critical task in the northern tier of the United States, : including Illinois. Highways with high levels of traffic are expected to be cleared of snow and ice quickly : after each snow storm. This is ne...

  8. Snow and ice blocking of tunnels

    Energy Technology Data Exchange (ETDEWEB)

    Lia, Leif

    1998-12-31

    Hydroelectric power development in cold regions causes much concern about operational reliability and dam safety. This thesis studies the temperature distribution in tunnels by means of air temperature measurements in six tunnel spillways and five diversion tunnels. The measurements lasted for two consecutive winters. The air through flow tunnel is used as it causes cooling of both rock and water. In open spillway tunnels, frost reaches the entire tunnel. In spillway tunnels with walls, the frost zones reach about 100 m from the downstream end. In mildly-inclined diversion tunnels, a frost free zone is located in the middle of the tunnel and snow and ice problems were only observed in the inlet and outlet. Severe aufeis is accumulation is observed in the frost zones. The heat transfer from rock to air, water and ice is calculated and used in a prediction model for the calculation of aufeis build-up together with local field observation data. The water penetration of snow plugs is also calculated, based on the heat balance. It takes 20 to 50 days for water to enter the blocked tunnel. The empirical values are 30 to 60 days, but only 1 day if the temperature of the snow pack is 0{sup o}C. Sensitivity analyses are carried out for temperature variations in rock, snow, water and ice. Systematic field observation shows that it is important for hydropower companies to know about the effects of snow and ice blocking in an area. A risk analysis of dam safety is presented for a real case. Finally, the thesis proposes solutions which can reduce the snow and ice problems. 79 refs., 63 figs., 11 tabs.

  9. Spatial-temporal dynamics of chemical composition of surface snow in East Antarctica along the Progress station-Vostok station transect

    Science.gov (United States)

    Khodzher, T. V.; Golobokova, L. P.; Osipov, E. Yu.; Shibaev, Yu. A.; Lipenkov, V. Ya.; Osipova, O. P.; Petit, J. R.

    2014-05-01

    In January of 2008, during the 53rd Russian Antarctic Expedition, surface snow samples were taken from 13 shallow (0.7 to 1.5 m depth) snow pits along the first tractor traverse from Progress to Vostok stations, East Antarctica. Sub-surface snow/firn layers are dated from 2.1 to 18 yr. The total length of the coast to inland traverse is more than 1280 km. Here we analysed spatial variability of concentrations of sulphate ions and elements and their fluxes in the snow deposited within the 2006-2008 time interval. Anions were analysed by high-performance liquid chromatography (HPLC), and the determination of selected metals, including Na, K, Mg, Ca and Al, was carried out by mass spectroscopy with atomization by induced coupled plasma (ICP-MS). Surface snow concentration records were examined for trends versus distance inland, elevation, accumulation rate and slope gradient. Na shows a significant positive correlation with accumulation rate, which decreases as distance from the sea and altitude increase. K, Ca and Mg concentrations do not show any significant relationship either with distance inland or with elevation. Maximal concentrations of these elements with a prominent Al peak are revealed in the middle part of the traverse (500-600 km from the coast). Analysis of element correlations and atmospheric circulation patterns allow us to suggest their terrestrial origin (e.g. aluminosilicates carried as a continental dust) from the Antarctic nunatak areas. Sulphate concentrations show no significant relationship with distance inland, elevation, slope gradient and accumulation rate. Non-sea salt secondary sulphate is the most important contribution to the total sulphate budget along the traverse. Sulphate of volcanic origin attributed to the Pinatubo eruption (1991) was revealed in the snow pit at 1276 km (depth 120-130 cm).

  10. 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy

    Directory of Open Access Journals (Sweden)

    N. Calonne

    2012-09-01

    Full Text Available We used three-dimensional (3-D images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K. This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. For several snow samples, a significant anisotropy of permeability was detected and is consistent with that observed for the effective thermal conductivity obtained from the same samples. The anisotropy coefficient, defined as the ratio of the vertical over the horizontal components of K, ranges from 0.74 for a sample of decomposing precipitation particles collected in the field to 1.66 for a depth hoar specimen. Because the permeability is related to a characteristic length, we introduced a dimensionless tensor K*=K/res2, where the equivalent sphere radius of ice grains (res is computed from the specific surface area of snow (SSA and the ice density (ρi as follows: res=3/(SSA×ρi. We define K and K* as the average of the diagonal components of K and K*, respectively. The 35 values of K* were fitted to snow density (ρs and provide the following regression: K = (3.0 ± 0.3 res2 exp((−0.0130 ± 0.0003ρs. We noted that the anisotropy of permeability does not affect significantly the proposed equation. This regression curve was applied to several independent datasets from the literature and compared to other existing regression curves or analytical models. The results show that it is probably the best currently available simple relationship linking the average value of permeability, K, to snow density and specific surface area.

  11. Wind-driven snow conditions control the occurrence of contemporary marginal mountain permafrost in the Chic-Choc Mountains, south-eastern Canada: a case study from Mont Jacques-Cartier

    Directory of Open Access Journals (Sweden)

    G. Davesne

    2017-06-01

    Full Text Available We present data on the distribution and thermophysical properties of snow collected sporadically over 4 decades along with recent data of ground surface temperature from Mont Jacques-Cartier (1268 m a.s.l., the highest summit in the Appalachians of south-eastern Canada. We demonstrate that the occurrence of contemporary permafrost is necessarily associated with a very thin and wind-packed winter snow cover which brings local azonal topo-climatic conditions on the dome-shaped summit. The aims of this study were (i to understand the snow distribution pattern and snow thermophysical properties on the Mont Jacques-Cartier summit and (ii to investigate the impact of snow on the spatial distribution of the ground surface temperature (GST using temperature sensors deployed over the summit. Results showed that above the local treeline, the summit is characterized by a snow cover typically less than 30 cm thick which is explained by the strong westerly winds interacting with the local surface roughness created by the physiography and surficial geomorphology of the site. The snowpack structure is fairly similar to that observed on windy Arctic tundra with a top dense wind slab (300 to 450 kg m−3 of high thermal conductivity, which facilitates heat transfer between the ground surface and the atmosphere. The mean annual ground surface temperature (MAGST below this thin and wind-packed snow cover was about −1 °C in 2013 and 2014, for the higher, exposed, blockfield-covered sector of the summit characterized by a sporadic herbaceous cover. In contrast, for the gentle slopes covered with stunted spruce (krummholz, and for the steep leeward slope to the south-east of the summit, the MAGST was around 3 °C in 2013 and 2014. The study concludes that the permafrost on Mont Jacques-Cartier, most widely in the Chic-Choc Mountains and by extension in the southern highest summits of the Appalachians, is therefore likely limited to the barren wind

  12. Combining snow depth and innovative skier flow measurements in order to improve snow grooming techniques

    Science.gov (United States)

    Carmagnola, Carlo Maria; Albrecht, Stéphane; Hargoaa, Olivier

    2017-04-01

    In the last decades, ski resort managers have massively improved their snow management practices, in order to adapt their strategies to the inter-annual variability in snow conditions and to the effects of climate change. New real-time informations, such as snow depth measurements carried out on the ski slopes by grooming machines during their daily operations, have become available, allowing high saving, efficiency and optimization gains (reducing for instance the groomer fuel consumption and operation time and the need for machine-made snow production). In order to take a step forward in improving the grooming techniques, it would be necessary to keep into account also the snow erosion by skiers, which depends mostly on the snow surface properties and on the skier attendance. Today, however, most ski resort managers have only a vague idea of the evolution of the skier flows on each slope during the winter season. In this context, we have developed a new sensor (named Skiflux) able to measure the skier attendance using an infrared beam crossing the slopes. Ten Skiflux sensors have been deployed during the 2016/17 winter season at Val Thorens ski area (French Alps), covering a whole sector of the resort. A dedicated software showing the number of skier passages in real time as been developed as well. Combining this new Skiflux dataset with the snow depth measurements from grooming machines (Snowsat System) and the snow and meteorological conditions measured in-situ (Liberty System from Technoalpin), we were able to create a "real-time skiability index" accounting for the quality of the surface snow and its evolution during the day. Moreover, this new framework allowed us to improve the preparation of ski slopes, suggesting new strategies for adapting the grooming working schedule to the snow quality and the skier attendance. In the near future, this work will benefit from the advances made within the H2020 PROSNOW project ("Provision of a prediction system allowing

  13. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Science.gov (United States)

    Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

    2017-09-01

    The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff

  14. Assimilation and High Resolution Forecasts of Surface and Near Surface Conditions for the 2010 Vancouver Winter Olympic and Paralympic Games

    Science.gov (United States)

    Bernier, Natacha B.; Bélair, Stéphane; Bilodeau, Bernard; Tong, Linying

    2014-01-01

    A dynamical model was experimentally implemented to provide high resolution forecasts at points of interests in the 2010 Vancouver Olympics and Paralympics Region. In a first experiment, GEM-Surf, the near surface and land surface modeling system, is driven by operational atmospheric forecasts and used to refine the surface forecasts according to local surface conditions such as elevation and vegetation type. In this simple form, temperature and snow depth forecasts are improved mainly as a result of the better representation of real elevation. In a second experiment, screen level observations and operational atmospheric forecasts are blended to drive a continuous cycle of near surface and land surface hindcasts. Hindcasts of the previous day conditions are then regarded as today's optimized initial conditions. Hence, in this experiment, given observations are available, observation driven hindcasts continuously ensure that daily forecasts are issued from improved initial conditions. GEM-Surf forecasts obtained from improved short-range hindcasts produced using these better conditions result in improved snow depth forecasts. In a third experiment, assimilation of snow depth data is applied to further optimize GEM-Surf's initial conditions, in addition to the use of blended observations and forecasts for forcing. Results show that snow depth and summer temperature forecasts are further improved by the addition of snow depth data assimilation.

  15. Photochemical degradation of PCBs in snow.

    Science.gov (United States)

    Matykiewiczová, Nina; Klánová, Jana; Klán, Petr

    2007-12-15

    This work represents the first laboratory study known to the authors describing photochemical behavior of persistent organic pollutants in snow at environmentally relevant concentrations. The snow samples were prepared by shock freezing of the corresponding aqueous solutions in liquid nitrogen and were UV-irradiated in a photochemical cold chamber reactor at -25 degrees C, in which simultaneous monitoring of snow-air exchange processeswas also possible. The main photodegradation pathway of two model snow contaminants, PCB-7 and PCB-153 (c approximately 100 ng kg(-1)), was found to be reductive dehalogenation. Possible involvement of the water molecules of snow in this reaction has been excluded by performing the photolyses in D2O snow. Instead, trace amounts of volatile organic compounds have been proposed to be the major source of hydrogen atom in the reduction, and this hypothesis was confirmed by the experiments with deuterated organic cocontaminants, such as d6-ethanol or d8-tetrahydrofuran. It is argued that bimolecular photoreduction of PCBs was more efficient or feasible than any other phototransformations under the experimental conditions used, including the coupling reactions. The photodegradation of PCBs, however, competed with a desorption process responsible for the pollutant loss from the snow samples, especially in case of lower molecular-mass congeners. Organic compounds, apparently largely located or photoproduced on the surface of snow crystals, had a predisposition to be released to the air but, at the same time, to react with other species in the gas phase. It is concluded that physicochemical properties of the contaminants and trace co-contaminants, their location and local concentrations in the matrix, and the wavelength and intensity of radiation are the most important factors in the evaluation of organic contaminants' lifetime in snow. Based on the results, it has been estimated that the average lifetime of PCBs in surface snow, connected

  16. Pavement Snow Melting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, John W.

    2005-01-01

    The design of pavement snow melting systems is presented based on criteria established by ASHRAE. The heating requirements depends on rate of snow fall, air temperature, relative humidity and wind velocity. Piping materials are either metal or plastic, however, due to corrosion problems, cross-linked polyethylene pipe is now generally used instead of iron. Geothermal energy is supplied to systems through the use of heat pipes, directly from circulating pipes, through a heat exchanger or by allowing water to flow directly over the pavement, by using solar thermal storage. Examples of systems in New Jersey, Wyoming, Virginia, Japan, Argentina, Switzerland and Oregon are presented. Key words: pavement snow melting, geothermal heating, heat pipes, solar storage, Wyoming, Virginia, Japan, Argentina, Klamath Falls.

  17. Utilizing the effective xanthophyll cycle for blooming of Ochromonas smithii and O. itoi (Chrysophyceae on the snow surface.

    Directory of Open Access Journals (Sweden)

    Yukiko Tanabe

    Full Text Available Snow algae inhabit unique environments such as alpine and high latitudes, and can grow and bloom with visualizing on snow or glacier during spring-summer. The chrysophytes Ochromonas smithii and Ochromonas itoi are dominant in yellow-colored snow patches in mountainous heavy snow areas from late May to early June. It is considered to be effective utilizing the xanthophyll cycle and holding sunscreen pigments as protective system for snow algae blooming in the vulnerable environment such as low temperature and nutrients, and strong light, however the study on the photoprotection of chrysophytes snow algae has not been shown. To dissolve how the chrysophytes snow algae can grow and bloom under such an extreme environment, we studied with the object of light which is one point of significance to this problem. We collected the yellow snows and measured photosynthetically active radiation at Mt. Gassan in May 2008 when the bloom occurred, then tried to establish unialgal cultures of O. smithii and O. itoi, and examined their photosynthetic properties by a PAM chlorophyll fluorometer and analyzed the pigment compositions before and after illumination with high-light intensities to investigate the working xanthophyll cycle. This experimental study using unialgal cultures revealed that both O. smithii and O. itoi utilize only the efficient violaxanthin cycle for photoprotection as a dissipation system of surplus energy under prolonged high-light stress, although they possess chlorophyll c with diadinoxanthin.

  18. Sensitivity Analysis of Snow Patterns in Swiss Ski Resorts to Shifts in Temperature, Precipitation and Humidity Under Condition of Climate Change

    Science.gov (United States)

    Uhlmann, B.; Goyette, S.; Beniston, M.

    2008-12-01

    The value of snow as a resource has considerably increased in Swiss mountain regions, in particular in the context of winter tourism. In the perspective of a warming climate, it is thus important to quantify the potential changes in snow amount and duration that could have large repercussions on the economy of ski resorts. Because of the fine spatial variability of snow, the use of a Surface Energy Balance Model (SEBM) is adequate to simulate local snow cover evolution. A perturbation method has been developed to generate plausible future meteorological input data required for SEBM simulations in order to assess the changes in snow cover patterns. Current and future snow depths have also been simulated within the ski areas themselves. The results show a large decrease of the snow depths and duration, even at high elevation in a warmer climate and emphasize the sensitivity of snow to topographical characteristics of the resorts. The study highlights the fact that not only the altitude of a domain but also its exposure, localization inland and slope gradients need to be taken into account when evaluating current and future snow depths. This method enables a precise assessment of the snow pattern over a small area.

  19. Simulating snow maps for Norway: description and statistical evaluation of the seNorge snow model

    Directory of Open Access Journals (Sweden)

    T. M. Saloranta

    2012-11-01

    Full Text Available Daily maps of snow conditions have been produced in Norway with the seNorge snow model since 2004. The seNorge snow model operates with 1 × 1 km resolution, uses gridded observations of daily temperature and precipitation as its input forcing, and simulates, among others, snow water equivalent (SWE, snow depth (SD, and the snow bulk density (ρ. In this paper the set of equations contained in the seNorge model code is described and a thorough spatiotemporal statistical evaluation of the model performance from 1957–2011 is made using the two major sets of extensive in situ snow measurements that exist for Norway. The evaluation results show that the seNorge model generally overestimates both SWE and ρ, and that the overestimation of SWE increases with elevation throughout the snow season. However, the R2-values for model fit are 0.60 for (log-transformed SWE and 0.45 for ρ, indicating that after removal of the detected systematic model biases (e.g. by recalibrating the model or expressing snow conditions in relative units the model performs rather well. The seNorge model provides a relatively simple, not very data-demanding, yet nonetheless process-based method to construct snow maps of high spatiotemporal resolution. It is an especially well suited alternative for operational snow mapping in regions with rugged topography and large spatiotemporal variability in snow conditions, as is the case in the mountainous Norway.

  20. Influence of Western Tibetan Plateau Summer Snow Cover on East Asian Summer Rainfall

    Science.gov (United States)

    Wang, Zhibiao; Wu, Renguang; Chen, Shangfeng; Huang, Gang; Liu, Ge; Zhu, Lihua

    2018-03-01

    The influence of boreal winter-spring eastern Tibetan Plateau snow anomalies on the East Asian summer rainfall variability has been the focus of previous studies. The present study documents the impacts of boreal summer western and southern Tibetan Plateau snow cover anomalies on summer rainfall over East Asia. Analysis shows that more snow cover in the western and southern Tibetan Plateau induces anomalous cooling in the overlying atmospheric column. The induced atmospheric circulation changes are different corresponding to more snow cover in the western and southern Tibetan Plateau. The atmospheric circulation changes accompanying the western Plateau snow cover anomalies are more obvious over the midlatitude Asia, whereas those corresponding to the southern Plateau snow cover anomalies are more prominent over the tropics. As such, the western and southern Tibetan Plateau snow cover anomalies influence the East Asian summer circulation and precipitation through different pathways. Nevertheless, the East Asian summer circulation and precipitation anomalies induced by the western and southern Plateau snow cover anomalies tend to display similar distribution so that they are more pronounced when the western and southern Plateau snow cover anomalies work in coherence. Analysis indicates that the summer snow cover anomalies over the Tibetan Plateau may be related to late spring snow anomalies due to the persistence. The late spring snow anomalies are related to an obvious wave train originating from the western North Atlantic that may be partly associated with sea surface temperature anomalies in the North Atlantic Ocean.

  1. Validation of AVHRR- and MODIS-derived albedos of snow and ice surfaces by means of helicopter measurements

    NARCIS (Netherlands)

    Greuell, W.; Oerlemans, J.

    2005-01-01

    We describe the validation of surface albedos of snow and glacier ice as derived from Advanced Very High Resolution Radiometer (AVHRR) and MOderate Resolution Imaging Spectrometer (MODIS) satellite data. For this purpose we measured surface albedos from a helicopter over Vatnajökull, Iceland, and

  2. Multi-Sensor Approach to Mapping Snow Cover Using Data From NASA's EOS Aqua and Terra Spacecraft

    Science.gov (United States)

    Armstrong, R. L.; Brodzik, M. J.

    2003-12-01

    Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Over the past several decades both optical and passive microwave satellite data have been utilized for snow mapping at the regional to global scale. For the period 1978 to 2002, we have shown earlier that both passive microwave and visible data sets indicate a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are, depending on season, less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Snow mapping using optical data is based on the magnitude of the surface reflectance while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Our previous work has defined the respective advantages and disadvantages of these two types of satellite data for snow cover mapping and it is clear that a blended product is optimal. We present a multi-sensor approach to snow mapping based both on historical data as well as data from current NASA EOS sensors. For the period 1978 to 2002 we combine data from the NOAA weekly snow charts with passive microwave data from the SMMR and SSM/I brightness temperature record. For the current and future time period we blend MODIS and AMSR-E data sets. An example of validation at the brightness temperature level is provided through the comparison of AMSR-E with data from the well-calibrated heritage SSM/I sensor over a large homogeneous snow-covered surface (Dome C, Antarctica). Prototype snow cover maps from AMSR-E compare well with maps derived from SSM/I. Our current blended product is being developed in the 25 km EASE-Grid while the MODIS data being used are in the Climate Modelers Grid (CMG) at approximately 5 km

  3. Small scale variability of snow properties on Antarctic sea ice

    Science.gov (United States)

    Wever, Nander; Leonard, Katherine; Paul, Stephan; Jacobi, Hans-Werner; Proksch, Martin; Lehning, Michael

    2016-04-01

    Snow on sea ice plays an important role in air-ice-sea interactions, as snow accumulation may for example increase the albedo. Snow is also able to smooth the ice surface, thereby reducing the surface roughness, while at the same time it may generate new roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. By comparing snow density and grain size from snow pits and snow micro penetrometer (SMP) measurements, highly resolved density and grain size profiles were acquired during two subsequent cruises of the RV Polarstern in the Weddell Sea, Antarctica, between June and October 2013. During the first cruise, SMP measurements were done along two approximately 40 m transects with a horizontal resolution of approximately 30 cm. During the second cruise, one transect was made with approximately 7.5 m resolution over a distance of 500 m. Average snow densities are about 300 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 180 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters. On the first cruise, the measurements were accompanied by terrestrial laser scanning (TLS) on an area of 50x50 m2. The comparison with the TLS data indicates that the spatial variability is exhibiting similar spatial patterns as deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density or grain size profiles. The fundamental relationship between variations in snow properties, surface roughness and changes therein as investigated in this study is interpreted with respect to large-scale ice movement and the mass balance.

  4. Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction

    Directory of Open Access Journals (Sweden)

    C. Mitterer

    2013-02-01

    Full Text Available Wet-snow avalanches are notoriously difficult to predict; their formation mechanism is poorly understood since in situ measurements representing the thermal and mechanical evolution are difficult to perform. Instead, air temperature is commonly used as a predictor variable for days with high wet-snow avalanche danger – often with limited success. As melt water is a major driver of wet-snow instability and snow melt depends on the energy input into the snow cover, we computed the energy balance for predicting periods with high wet-snow avalanche activity. The energy balance was partly measured and partly modelled for virtual slopes at different elevations for the aspects south and north using the 1-D snow cover model SNOWPACK. We used measured meteorological variables and computed energy balance and its components to compare wet-snow avalanche days to non-avalanche days for four consecutive winter seasons in the surroundings of Davos, Switzerland. Air temperature, the net shortwave radiation and the energy input integrated over 3 or 5 days showed best results in discriminating event from non-event days. Multivariate statistics, however, revealed that for better predicting avalanche days, information on the cold content of the snowpack is necessary. Wet-snow avalanche activity was closely related to periods when large parts of the snowpack reached an isothermal state (0 °C and energy input exceeded a maximum value of 200 kJ m−2 in one day, or the 3-day sum of positive energy input was larger than 1.2 MJ m−2. Prediction accuracy with measured meteorological variables was as good as with computed energy balance parameters, but simulated energy balance variables accounted better for different aspects, slopes and elevations than meteorological data.

  5. Regime shift of snow days in Switzerland

    Science.gov (United States)

    Marty, Christoph

    2008-06-01

    The number of days with a snow depth above a certain threshold is the key factor for winter tourism in an Alpine country like Switzerland. An investigation of 34 long-term stations between 200 and 1800 m asl (above sea level) going back for at least the last 60 years (1948-2007) shows an unprecedented series of low snow winters in the last 20 years. The signal is uniform despite high regional differences. A shift detection analysis revealed a significant step-like decrease in snow days at the end of the 1980's with no clear trend since then. This abrupt change resulted in a loss of 20% to 60% of the total snow days. The stepwise increase of the mean winter temperature at the end of the 1980's and its close correlation with the snow day anomalies corroborate the sensitivity of the mid-latitude winter to the climate change induced temperature increase.

  6. Canadian snow and sea ice: historical trends and projections

    Science.gov (United States)

    Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross

    2018-04-01

    The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020-2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.

  7. Combining low-cost GPS receivers with upGPR to derive continuously liquid water content, snow height and snow water equivalent in Alpine snow covers

    Science.gov (United States)

    Koch, Franziska; Schmid, Lino; Prasch, Monika; Heilig, Achim; Eisen, Olaf; Schweizer, Jürg; Mauser, Wolfram

    2015-04-01

    The temporal evolution of Alpine snowpacks is important for assessing water supply, hydropower generation, flood predictions and avalanche forecasts. Especially in high mountain regions with an extremely varying topography, it is until now often difficult to derive continuous and non-destructive information on snow parameters. Since autumn 2012, we are running a new low-cost GPS (Global Positioning System) snow measurement experiment at the high alpine study site Weissfluhjoch (2450 m a.s.l.) in Switzerland. The globally and freely broadcasted GPS L1-band (1.57542 GHz) was continuously recorded with GPS antennas, which are installed at the ground surface underneath the snowpack. GPS raw data, containing carrier-to-noise power density ratio (C/N0) as well as elevation and azimuth angle information for each time step of 1 s, was stored and analyzed for all 32 GPS satellites. Since the dielectric permittivity of an overlying wet snowpack influences microwave radiation, the bulk volumetric liquid water content as well as daily melt-freeze cycles can be derived non-destructively from GPS signal strength losses and external snow height information. This liquid water content information is qualitatively in good accordance with meteorological and snow-hydrological data and quantitatively highly agrees with continuous data derived from an upward-looking ground-penetrating radar (upGPR) working in a similar frequency range. As a promising novelty, we combined the GPS signal strength data with upGPR travel-time information of active impulse radar rays to the snow surface and back from underneath the snow cover. This combination allows determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using any other external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily

  8. Modelling the physical multiphase interactions of HNO3 between snow and air on the Antarctic Plateau (Dome C and coast (Halley

    Directory of Open Access Journals (Sweden)

    H. G. Chan

    2018-02-01

    Full Text Available Emissions of nitrogen oxide (NOx  =  NO + NO2 from the photolysis of nitrate (NO3− in snow affect the oxidising capacity of the lower troposphere especially in remote regions of high latitudes with little pollution. Current air–snow exchange models are limited by poor understanding of processes and often require unphysical tuning parameters. Here, two multiphase models were developed from physically based parameterisations to describe the interaction of nitrate between the surface layer of the snowpack and the overlying atmosphere. The first model is similar to previous approaches and assumes that below a threshold temperature, To, the air–snow grain interface is pure ice and above To a disordered interface (DI emerges covering the entire grain surface. The second model assumes that air–ice interactions dominate over all temperatures below melting of ice and that any liquid present above the eutectic temperature is concentrated in micropockets. The models are used to predict the nitrate in surface snow constrained by year-round observations of mixing ratios of nitric acid in air at a cold site on the Antarctic Plateau (Dome C; 75°06′ S, 123°33′ E; 3233 m a.s.l. and at a relatively warm site on the Antarctic coast (Halley; 75°35′ S, 26°39′ E; 35 m a.s.l. The first model agrees reasonably well with observations at Dome C (Cv(RMSE  =  1.34 but performs poorly at Halley (Cv(RMSE  =  89.28 while the second model reproduces with good agreement observations at both sites (Cv(RMSE  =  0.84 at both sites. It is therefore suggested that in winter air–snow interactions of nitrate are determined by non-equilibrium surface adsorption and co-condensation on ice coupled with solid-state diffusion inside the grain, similar to Bock et al. (2016. In summer, however, the air–snow exchange of nitrate is mainly driven by solvation into liquid micropockets following Henry's law with

  9. Long-term analyses of snow dynamics within the french Alps on the 1900-2100 period. Analyses of historical snow water equivalent observations, modelisations and projections of a hundred of snow courses.

    Science.gov (United States)

    Mathevet, T.; Joel, G.; Gottardi, F.; Nemoz, B.

    2017-12-01

    The aim of this communication is to present analyses of climate variability and change on snow water equivalent (SWE) observations, reconstructions (1900-2016) and scenarii (2020-2100) of a hundred of snow courses dissiminated within the french Alps. This issue became particularly important since a decade, in regions where snow variability had a large impact on water resources availability, poor snow conditions in ski resorts and artificial snow production. As a water resources manager in french mountainuous regions, EDF (french hydropower company) has developed and managed a hydrometeorological network since 1950. A recent data rescue research allowed to digitize long term SWE manual measurments of a hundred of snow courses within the french Alps. EDF have been operating an automatic SWE sensors network, complementary to the snow course network. Based on numerous SWE observations time-series and snow accumulation and melt model (Garavaglia et al., 2017), continuous daily historical SWE time-series have been reconstructed within the 1950-2016 period. These reconstructions have been extented to 1900 using 20 CR reanalyses (ANATEM method, Kuentz et al., 2015) and up to 2100 using GIEC Climate Change scenarii. Considering various mountainous areas within the french Alps, this communication focuses on : (1) long term (1900-2016) analyses of variability and trend of total precipitation, air temperature, snow water equivalent, snow line altitude, snow season length , (2) long term variability of hydrological regime of snow dominated watersheds and (3) future trends (2020 -2100) using GIEC Climate Change scenarii. Comparing historical period (1950-1984) to recent period (1984-2016), quantitative results within a region in the north Alps (Maurienne) shows an increase of air temperature by 1.2 °C, an increase of snow line height by 200m, a reduction of SWE by 200 mm/year and a reduction of snow season length by 15 days. These analyses will be extended from north to south

  10. Experimental Investigation of Concrete Runway Snow Melting Utilizing Heat Pipe Technology

    Directory of Open Access Journals (Sweden)

    Fengchen Chen

    2018-01-01

    Full Text Available A full scale snow melting system with heat pipe technology is built in this work, which avoids the negative effects on concrete structure and environment caused by traditional deicing chemicals. The snow melting, ice-freezing performance and temperature distribution characteristics of heat pipe concrete runway were discussed by the outdoor experiments. The results show that the temperature of the concrete pavement is greatly improved with the heat pipe system. The environment temperature and embedded depth of heat pipe play a dominant role among the decision variables of the snow melting system. Heat pipe snow melting pavement melts the snow completely and avoids freezing at any time when the environment temperature is below freezing point, which is secure enough for planes take-off and landing. Besides, the exportation and recovery of geothermal energy indicate that this system can run for a long time. This paper will be useful for the design and application of the heat pipe used in the runway snow melting.

  11. Experimental Investigation of Concrete Runway Snow Melting Utilizing Heat Pipe Technology.

    Science.gov (United States)

    Chen, Fengchen; Su, Xin; Ye, Qing; Fu, Jianfeng

    2018-01-01

    A full scale snow melting system with heat pipe technology is built in this work, which avoids the negative effects on concrete structure and environment caused by traditional deicing chemicals. The snow melting, ice-freezing performance and temperature distribution characteristics of heat pipe concrete runway were discussed by the outdoor experiments. The results show that the temperature of the concrete pavement is greatly improved with the heat pipe system. The environment temperature and embedded depth of heat pipe play a dominant role among the decision variables of the snow melting system. Heat pipe snow melting pavement melts the snow completely and avoids freezing at any time when the environment temperature is below freezing point, which is secure enough for planes take-off and landing. Besides, the exportation and recovery of geothermal energy indicate that this system can run for a long time. This paper will be useful for the design and application of the heat pipe used in the runway snow melting.

  12. Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

    Science.gov (United States)

    Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

    2017-04-01

    General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All

  13. SNOW THICKNESS ON AUSTRE GRØNFJORDBREEN, SVALBARD, FROM RADAR MEASUREMENTS AND STANDARD SNOW SURVEYS

    Directory of Open Access Journals (Sweden)

    I. I. Lavrentiev

    2018-01-01

    Full Text Available Summary Comparison of two methods of measurements of snow cover thickness on the glacier Austre Grønfjordbreen, Svalbard was performed in the spring of 2014. These methods were the radar (500 MHz observations and standard snow surveys. Measurements were conducted in 77 different points on the surface of the glacier. A good correlation (R2 = 0.98 was revealed. In comparison with the data of snow surveys, the radar measurements show a similar but more detailed pattern of the distribution of the snow cover depth. The discrepancy between the depths of snow cover on maps plotted from data of both methods did not exceed 30 cm in most parts of the glacier. The standard error of interpolation of the radar data onto the entire glacier surface amounts, on average, to 18 cm. This corresponds to the error of radar measurements of 18.8% when an average snow depth is about 160 cm and 9.4% at its maximum thickness of 320 cm. The distance between the measurement points at which the spatial covariance of the snow depth disappears falls between 236 and 283 m along the glacier, and between 117 and 165 m across its position. We compared the results of radar measurements of the pulse-delay time of reflections from the base of the snow cover with the data of manual probe measurements at 10 points and direct measurements of snow depth and average density in 12 snow pits. The average speed of radio waves propagation in the snow was determined as Vcr = 23.4±0.2 cm ns−1. This magnitude and the Looyenga and Kovacs formulas allowed estimating the average density of snow cover ρL = 353.1±13.1 kg m−3 and ρK = 337.4±12.9 kg m−3. The difference from average density measured in 12 pits ρav.meas = 387.4±12.9 kg m−3 amounts to −10.8% and −14.8%. In 2014, according to snow and radar measurements, altitudinal gradient of snow accumulation on the glacier Austre Grønfjordbreen was equal to 0.21 m/100 m, which is smaller than the

  14. Satellite Remote Sensing of Snow/Ice Albedo over the Himalayas

    Science.gov (United States)

    Hsu, N. Christina; Gautam, Ritesh

    2012-01-01

    The Himalayan glaciers and snowpacks play an important role in the hydrological cycle over Asia. The seasonal snow melt from the Himalayan glaciers and snowpacks is one of the key elements to the livelihood of the downstream densely populated regions of South Asia. During the pre-monsoon season (April-May-June), South Asia not only experiences the reversal of the regional meridional tropospheric temperature gradient (i.e., the onset of the summer monsoon), but also is being bombarded by dry westerly airmass that transports mineral dust from various Southwest Asian desert and arid regions into the Indo-Gangetic Plains in northern India. Mixed with heavy anthropogenic pollution, mineral dust constitutes the bulk of regional aerosol loading and forms an extensive and vertically extended brown haze lapping against the southern slopes of the Himalayas. Episodic dust plumes are advected over the Himalayas, and are discernible in satellite imagery, resulting in dust-capped snow surface. Motivated by the potential implications of accelerated snowmelt, we examine the changes in radiative energetics induced by aerosol transport over the Himalayan snow cover by utilizing space borne observations. Our objective lies in the investigation of potential impacts of aerosol solar absorption on the Top-of-Atmosphere (TOA) spectral reflectivity and the broadband albedo, and hence the accelerated snowmelt, particularly in the western Himalayas. Lambertian Equivalent Reflectivity (LER) in the visible and near-infrared wavelengths, derived from Moderate Resolution Imaging Spectroradiometer radiances, is used to generate statistics for determining perturbation caused due to dust layer over snow surface in over ten years of continuous observations. Case studies indicate significant reduction of LER ranging from 5 to 8% in the 412-860nm spectra. Broadband flux observations, from the Clouds and the Earth's Radiant Energy System, are also used to investigate changes in shortwave TOA flux over

  15. The Critical Depth of Freeze-Thaw Soil under Different Types of Snow Cover

    Directory of Open Access Journals (Sweden)

    Qiang Fu

    2017-05-01

    Full Text Available Snow cover is the most common upper boundary condition influencing the soil freeze-thaw process in the black soil farming area of northern China. Snow is a porous dielectric cover, and its unique physical properties affect the soil moisture diffusion, heat conduction, freezing rate and other variables. To understand the spatial distribution of the soil water-heat and the variable characteristics of the critical depth of the soil water and heat, we used field data to analyze the freezing rate of soil and the extent of variation in soil water-heat in a unit soil layer under bare land (BL, natural snow (NS, compacted snow (CS and thick snow (TS treatments. The critical depth of the soil water and heat activity under different snow covers were determined based on the results of the analysis, and the variation fitting curve of the difference sequences on the soil temperature and water content between different soil layers and the surface 5-cm soil layer were used to verify the critical depth. The results were as follows: snow cover slowed the rate of soil freezing, and the soil freezing rate under the NS, CS and TS treatments decreased by 0.099 cm/day, 0.147 cm/day and 0.307 cm/day, respectively, compared with that under BL. In addition, the soil thawing time was delayed, and the effect was more significant with increased snow cover. During freeze-thaw cycles, the extent of variation in the water and heat time series in the shallow soil was relatively large, while there was less variation in the deep layer. There was a critical stratum in the vertical surface during hydrothermal migration, wherein the critical depth of soil water and heat change gradually increased with increasing snow cover. The variance in differences between the surface layer and both the soil water and heat in the different layers exhibited “steady-rising-steady” behavior, and the inflection point of the curve is the critical depth of soil freezing and thawing. This critical

  16. UAS applications in high alpine, snow-covered terrain

    Science.gov (United States)

    Bühler, Y.; Stoffel, A.; Ginzler, C.

    2017-12-01

    Access to snow-covered, alpine terrain is often difficult and dangerous. Hence parameters such as snow depth or snow avalanche release and deposition zones are hard to map in situ with adequate spatial and temporal resolution and with spatial continuous coverage. These parameters are currently operationally measured at automated weather stations and by observer networks. However such isolated point measurements are not able to capture the information spatial continuous and to describe the high spatial variability present in complex mountain topography. Unmanned Aerial Systems (UAS) have the potential to fill this gap by frequently covering selected high alpine areas with high spatial resolution down to ground resolutions of even few millimeters. At the WSL Institute for Snow and Avalanche Research SLF we test different photogrammetric UAS with visual and near infrared bands. During the last three years we were able to gather experience in more than 100 flight missions in extreme terrain. By processing the imagery applying state-of-the-art structure from motion (SfM) software, we were able to accurately document several avalanche events and to photogrammetrically map snow depth with accuracies from 1 to 20 cm (dependent on the flight height above ground) compare to manual snow probe measurements. This was even possible on homogenous snow surfaces with very little texture. A key issue in alpine terrain is flight planning. We need to cover regions at high elevations with large altitude differences (up to 1 km) with high wind speeds (up to 20 m/s) and cold temperatures (down to - 25°C). Only a few UAS are able to cope with these environmental conditions. We will give an overview on our applications of UAS in high alpine terrain that demonstrate the big potential of such systems to acquire frequent, accurate and high spatial resolution geodata in high alpine, snow covered terrain that could be essential to answer longstanding questions in avalanche and snow hydrology

  17. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Directory of Open Access Journals (Sweden)

    A. Ehrlich

    2017-09-01

    Full Text Available The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow. Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C.In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S, λ2 = 1650 nm (sensitive to τ, and λ3 = 2100 nm (sensitive to reff, C are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012 were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice

  18. Experimental and model based investigation of the links between snow bidirectional reflectance and snow microstructure

    Science.gov (United States)

    Dumont, M.; Flin, F.; Malinka, A.; Brissaud, O.; Hagenmuller, P.; Dufour, A.; Lapalus, P.; Lesaffre, B.; Calonne, N.; Rolland du Roscoat, S.; Ando, E.

    2017-12-01

    Snow optical properties are unique among Earth surface and crucial for a wide range of applications. The bi-directional reflectance, hereafter BRDF, of snow is sensible to snow microstructure. However the complex interplays between different parameters of snow microstructure namely size parameters and shape parameters on reflectance are challenging to disentangle both theoretically and experimentally. An accurate understanding and modelling of snow BRDF is required to correctly process satellite data. BRDF measurements might also provide means of characterizing snow morphology. This study presents one of the very few dataset that combined bi-directional reflectance measurements over 500-2500 nm and X-ray tomography of the snow microstructure for three different snow samples and two snow types. The dataset is used to evaluate the approach from Malinka, 2014 that relates snow optical properties to the chord length distribution in the snow microstructure. For low and medium absorption, the model accurately reproduces the measurements but tends to slightly overestimate the anisotropy of the reflectance. The model indicates that the deviation of the ice chord length distribution from an exponential distribution, that can be understood as a characterization of snow types, does not impact the reflectance for such absorptions. The simulations are also impacted by the uncertainties in the ice refractive index values. At high absorption and high viewing/incident zenith angle, the simulations and the measurements disagree indicating that some of the assumptions made in the model are not met anymore. The study also indicates that crystal habits might play a significant role for the reflectance under such geometries and wavelengths. However quantitative relationship between crystal habits and reflectance alongside with potential optical methodologies to classify snow morphology would require an extended dataset over more snow types. This extended dataset can likely be obtained

  19. Photopolarimetric Retrievals of Snow Properties

    Science.gov (United States)

    Ottaviani, M.; van Diedenhoven, B.; Cairns, B.

    2015-01-01

    Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

  20. Quality Assessment of S-NPP VIIRS Land Surface Temperature Product

    Directory of Open Access Journals (Sweden)

    Yuling Liu

    2015-09-01

    Full Text Available The VIIRS Land Surface Temperature (LST Environmental Data Record (EDR has reached validated (V1 stage maturity in December 2014. This study compares VIIRS v1 LST with the ground in situ observations and with heritage LST product from MODIS Aqua and AATSR. Comparisons against U.S. SURFRAD ground observations indicate a similar accuracy among VIIRS, MODIS and AATSR LST, in which VIIRS LST presents an overall accuracy of −0.41 K and precision of 2.35 K. The result over arid regions in Africa suggests that VIIRS and MODIS underestimate the LST about 1.57 K and 2.97 K, respectively. The cross comparison indicates an overall close LST estimation between VIIRS and MODIS. In addition, a statistical method is used to quantify the VIIRS LST retrieval uncertainty taking into account the uncertainty from the surface type input. Some issues have been found as follows: (1 Cloud contamination, particularly the cloud detection error over a snow/ice surface, shows significant impacts on LST validation; (2 Performance of the VIIRS LST algorithm is strongly dependent on a correct classification of the surface type; (3 The VIIRS LST quality can be degraded when significant brightness temperature difference between the two split window channels is observed; (4 Surface type dependent algorithm exhibits deficiency in correcting the large emissivity variations within a surface type.

  1. Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

    Science.gov (United States)

    Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Klein, Andrew G.

    2003-01-01

    Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003.

  2. Snow melting system with electric heating using photovoltaic power generation; Solar yusetsuko

    Energy Technology Data Exchange (ETDEWEB)

    Sasaki, M; Fujita, S; Kaga, T; Koyama, N [Hachinohe Institute of Technology, Aomori (Japan)

    1996-10-27

    This paper clarifies the solar characteristics in Hachinohe district, to investigate a possibility of the snow melting system with electric heating using solar energy. Power demand for snow melting, power generated by the photovoltaic (PV) array, area of PV array, and working conditions of the system, as to temperature, precipitation and snowfall, were investigated. The percentage of sunshine is 44% in Hachinohe district, which has more fortunate natural condition for utilizing solar radiation compared with that of 20% in Aomori prefecture. The intensity of solar radiation in winter from December to March is around 500 W/m{sup 2} in average, which is equivalent to the quantity of solar radiation, around 2 kWh/m{sup 2} a day. When assuming that snow on the road surface is frozen at the snowfall under the air temperature below -3{degree}C, the occurrence frequency is 50% during January and February in Hachinohe district, which means one frozen day for two days and is equivalent to the occurrence frequency of frozen days, 34% in average during winter. The electric application ratio is 0.34 at the maximum in winter. That is, days of 34% for one month are required for snow melting. 3 figs., 3 tabs.

  3. CellDyM: A room temperature operating cryogenic cell for the dynamic monitoring of snow metamorphism by time-lapse X-ray microtomography

    Science.gov (United States)

    Calonne, N.; Flin, F.; Lesaffre, B.; Dufour, A.; Roulle, J.; Puglièse, P.; Philip, A.; Lahoucine, F.; Geindreau, C.; Panel, J.-M.; Roscoat, S. Rolland; Charrier, P.

    2015-05-01

    Monitoring the time evolution of snow microstructure in 3-D is crucial for a better understanding of snow metamorphism. We, therefore, designed a cryogenic cell that precisely controls the experimental conditions of a sample while it is scanned by X-ray tomography. Based on a thermoelectrical regulation and a vacuum insulation, the cell operates at room temperature. It is, thus, adaptable to diverse scanners, offering advantages in terms of imaging techniques, resolution, and speed. Three-dimensional time-lapse series were obtained under equitemperature and temperature gradient conditions at a 7.8 μm precision. The typical features of each metamorphism and the anisotropic faceting behavior between the basal and prismatic planes, known to occur close to -2°C, were observed in less than 30 h. These results are consistent with the temperature fields expected from heat conduction simulations through the cell. They confirm the cell's accuracy and the interest of relatively short periods to study snow metamorphism.

  4. Extraordinary blowing snow transport events in East Antarctica

    Energy Technology Data Exchange (ETDEWEB)

    Scarchilli, Claudio; Agnoletto, Lucia [ENEA, Rome (Italy); Universita di Siena, Dipartimento di Scienze della Terra, Siena (Italy); Frezzotti, Massimo; Grigioni, Paolo; Silvestri, Lorenzo de [ENEA, Rome (Italy); Dolci, Stefano [CNR, Rome (Italy); Consorzio P.N.R.A. S.C.r.l., Rome (Italy)

    2010-06-15

    In the convergence slope/coastal areas of Antarctica, a large fraction of snow is continuously eroded and exported by wind to the atmosphere and into the ocean. Snow transport observations from instruments and satellite images were acquired at the wind convergence zone of Terra Nova Bay (East Antarctica) throughout 2006 and 2007. Snow transport features are well-distinguished in satellite images and can extend vertically up to 200 m as first-order quantitatively estimated by driftometer sensor FlowCapt trademark. Maximum snow transportation occurs in the fall and winter seasons. Snow transportation (drift/blowing) was recorded for {proportional_to}80% of the time, and 20% of time recorded, the flux is >10{sup -2} kg m{sup -2} s{sup -1} with particle density increasing with height. Cumulative snow transportation is {proportional_to}4 orders of magnitude higher than snow precipitation at the site. An increase in wind speed and transportation ({proportional_to}30%) was observed in 2007, which is in agreement with a reduction in observed snow accumulation. Extensive presence of ablation surface (blue ice and wind crust) upwind and downwind of the measurement site suggest that the combine processes of blowing snow sublimation and snow transport remove up to 50% of the precipitation in the coastal and slope convergence area. These phenomena represent a major negative effect on the snow accumulation, and they are not sufficiently taken into account in studies of surface mass balance. The observed wind-driven ablation explains the inconsistency between atmospheric model precipitation and measured snow accumulation value. (orig.)

  5. Insight into biogeochemical inputs and composition of Greenland Ice Sheet surface snow and glacial forefield river catchment environments.

    Science.gov (United States)

    Cameron, Karen; Hagedorn, Birgit; Dieser, Markus; Christner, Brent; Choquette, Kyla; Sletten, Ronald; Lui, Lu; Junge, Karen

    2014-05-01

    The volume of freshwater transported from Greenland to surrounding marine waters has tended to increase annually over the past four decades as a result of warmer surface air temperatures (Bamber et al 2012, Hanna et al 2008). Ice sheet run off is estimated to make up approximately of third of this volume (Bamber et al 2012). However, the biogeochemical composition and seeding sources of the Greenland Ice Sheet supraglacial landscape is largely unknown. In this study, the structure and diversity of surface snow microbial assemblages from two regions of the western Greenland Ice Sheet ice-margin was investigated through the sequencing of small subunit rRNA genes. Furthermore, the origins of microbiota were investigated by examining correlations to molecular data obtained from marine, soil, freshwater and atmospheric environments and to geochemical analytes measured in the snow. Snow was found to contain a diverse assemblage of bacteria (Alphaproteobacteria, Betaproteobacteria and Gammaproteobacteria) and eukarya (Alveolata, Fungi, Stramenopiles and Viridiplantae). Phylotypes related to archaeal Thaumarchaeota and Euryarchaeota phyla were also identified. The structure of microbial assemblages was found to have strong similarities to communities sampled from marine and air environments, and sequences obtained from the South-West region, near Kangerlussuaq, which is bordered by an extensive periglacial expanse, had additional resemblances to soil originating communities. Strong correlations were found between bacterial beta diversity and Na+ and Cl- concentrations. These data suggest that surface snow from western regions of Greenland contain microbiota that are most likely derived from exogenous, wind transported sources. Downstream of the supraglacial environment, Greenland's rivers likely influence the ecology of localized estuary and marine systems. Here we characterize the geochemical and biotic composition of a glacial and glacial forefield fed river catchment in

  6. Greenland Ice Sheet Surface Temperature, Melt, and Mass Loss: 2000-2006

    Science.gov (United States)

    Hall, Dorothy K.; Williams, Richard S., Jr.; Luthcke, Scott B.; DiGirolamo, Nocolo

    2007-01-01

    Extensive melt on the Greenland Ice Sheet has been documented by a variety of ground and satellite measurements in recent years. If the well-documented warming continues in the Arctic, melting of the Greenland Ice Sheet will likely accelerate, contributing to sea-level rise. Modeling studies indicate that an annual or summer temperature rise of 1 C on the ice sheet will increase melt by 20-50% therefore, surface temperature is one of the most important ice-sheet parameters to study for analysis of changes in the mass balance of the ice-sheet. The Greenland Ice Sheet contains enough water to produce a rise in eustatic sea level of up to 7.0 m if the ice were to melt completely. However, even small changes (centimeters) in sea level would cause important economic and societal consequences in the world's major coastal cities thus it is extremely important to monitor changes in the ice-sheet surface temperature and to ultimately quantify these changes in terms of amount of sea-level rise. We have compiled a high-resolution, daily time series of surface temperature of the Greenland Ice Sheet, using the I-km resolution, clear-sky land-surface temperature (LST) standard product from the Moderate-Resolution Imaging Spectroradiometer (MODIS), from 2000 - 2006. We also use Gravity Recovery and Climate Experiment (GRACE) data, averaged over 10-day periods, to measure change in mass of the ice sheet as it melt and snow accumulates. Surface temperature can be used to determine frequency of surface melt, timing of the start and the end of the melt season, and duration of melt. In conjunction with GRACE data, it can also be used to analyze timing of ice-sheet mass loss and gain.

  7. Indicative properties on snow cover based on the results of experimental studies in the winter 2011/12 in the central part of the East European Plain

    Directory of Open Access Journals (Sweden)

    L. M. Kitaev

    2013-01-01

    Full Text Available Local and regional differences in the snow formation were studied in different landscapes of the central part of the East European Plain – within reserves in the Moscow and Tver’ regions (south-north direction; the study period is the winter 2011/12. The observed increase of snow storage in 1.3–1.5 times in the direction south-north is connected, apparently. The difference in the five-day appearance of snow cover maximum is related to differences in regional winter air temperature. Throughout the snow depth and snow storage in spruce are smaller than in deciduous forest – in the ratio of 0.81 in south area and 0.93 in north area; in spruce the large part of solid precipitation is intercepted by the crowns pine trees. Snow stratigraphy at south areas has four layers, six layers at the north area are more variable in snow density and snow storage. Perhaps, gravitational conversion is more noticeable due to larger snow depth. Snow density and snow storage at the open areas are more heterogeneous than in the forest. This is due to sharp fluctuations in air temperature, wind transport and compaction of snow, evaporation from the snow surface. The stratigraphy of snow also reflects the history of winter changes of air temperature and snow accumulation. Common feature for reserves at south and north is the availability of layers with maximum snow storage in the middle of the snow thickness, which were formed during the air temperature drops to the lowest seasonal values in period with increase of snow depth to maximum. Formation of depth hoar in snow thickness are touched everywhere the bottom and middle layers, respectively, it was formed both before and during the period with minimal air temperature. Thus, the results of experimental studies confirm the significance of the differences of individual components of the landscape setting. Analytical conclusions are largely qualitative in nature due to the lack to date of initial information, and

  8. Variability in snow cover phenology in China from 1952 to 2010

    OpenAIRE

    C. Q. Ke; X. C. Li; H. Xie; X. Liu; C. Kou

    2015-01-01

    Daily snow observation data from 672 stations, particularly the 352 stations with over ten annual mean snow cover days (SCD), during 1952–2010 in China, are used in this study. We first examine spatiotemporal variations and trends of SCD, snow cover onset date (SCOD), and snow cover end date (SCED). We then investigate SCD relationships with number of days with temperature below 0 °C (TBZD), mean air temperature (MAT), and Arctic Oscillation (AO) index, the ...

  9. Observations of distributed snow depth and snow duration within diverse forest structures in a maritime mountain watershed

    Science.gov (United States)

    Dickerson-Lange, Susan E.; Lutz, James A.; Gersonde, Rolf; Martin, Kael A.; Forsyth, Jenna E.; Lundquist, Jessica D.

    2015-11-01

    Spatially distributed snow depth and snow duration data were collected over two to four snow seasons during water years 2011-2014 in experimental forest plots within the Cedar River Municipal Watershed, 50 km east of Seattle, Washington, USA. These 40 × 40 m forest plots, situated on the western slope of the Cascade Range, include unthinned second-growth coniferous forests, variable density thinned forests, forest gaps in which a 20 m diameter (approximately equivalent to one tree height) gap was cut in the middle of each plot, and old-growth forest. Together, this publicly available data set includes snow depth and density observations from manual snow surveys, distributed snow duration observations from ground temperature sensors and time-lapse cameras, meteorological data collected at two open locations and three forested locations, and forest canopy data from airborne light detection and ranging (LiDAR) data and hemispherical photographs. These colocated snow, meteorological, and forest data have the potential to improve understanding of forest influences on snow processes, and provide a unique model-testing data set for hydrological analyses in a forested, maritime watershed. We present empirical snow depletion curves within forests to illustrate an application of these data to improve subgrid representation of snow cover in distributed modeling.

  10. Can GRACE detect winter snows in Japan?

    Science.gov (United States)

    Heki, Kosuke

    2010-05-01

    Current spatial resolution of the GRACE (Gravity Recovery and Climate Experiment) satellites is 300-400 km, and so its hydrological applications have been limited to continents and large islands. The Japanese Islands have width slightly smaller than this spatial resolution, but are known to show large amplitude seasonal changes in surface masses due mainly to winter snow. Such loads are responsible for seasonal crustal deformation observed with GEONET, a dense array of GPS (Global Positioning System) receivers in Japan (Heki, 2001). There is also a dense network of surface meteorological sensors for, e.g. snow depths, atmospheric pressures, etc. Heki (2004) showed that combined effects of surface loads, i.e. snow (predominant), atmosphere, soil moisture, dam impoundment, can explain seasonal crustal deformation observed by GPS to a large extent. The total weight of the winter snow in the Japanese Islands in its peak season may reach ~50 Gt. This is comparable to the annual loss of mountain glaciers in the Asian high mountains (Matsuo & Heki, 2010), and is above the detection level of GRACE. In this study, I use GRACE Level-2 Release-4 data from CSR, Univ. Texas, up to 2009 November, and evaluated seasonal changes in surface loads in and around the Japanese Islands. After applying a 350 km Gaussian filter and a de-striping filter, the peak-to-peak change of the water depth becomes ~4 cm in northern Japan. The maximum value is achieved in February-March. The region of large winter load spans from Hokkaido, Japan, to northeastern Honshu, which roughly coincides with the region of deep snow in Japan. Next I compiled snow depth data from surface meteorological observations, and converted them to loads using time-dependent snow density due to compaction. By applying the same spatial filter as the GRACE data, its spatial pattern becomes similar to the GRACE results. The present study suggests that GRACE is capable of detecting seasonal mass changes in an island arc not

  11. Storing snow for the next winter: Two case studies on the application of snow farming.

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian

    2016-04-01

    Snow farming is the conservation of snow during the warm half-year. This means that large piles of snow are formed in spring in order to be conserved over the summer season. Well-insulating materials such as chipped wood are added as surface cover to reduce melting. The aim of snow farming is to provide a "snow guaranty" for autumn or early winter - this means that a specific amount of snow will definitively be available, independent of the weather conditions. The conserved snow can then be used as basis for the preparation of winter sports grounds such as cross-country tracks or ski runs. This helps in the organization of early winter season sport events such as World Cup races or to provide appropriate training conditions for athletes. We present a study on two snow farming projects, one in Davos (Switzerland) and one in the Martell valley of South Tyrol. At both places snow farming has been used for several years. For the summer season 2015, we monitored both snow piles in order to assess the amount of snow conserved. High resolution terrestrial laser scanning was performed to measure snow volumes of the piles at the beginning and at the end of the summer period. Results showed that only 20% to 30 % of the snow mass was lost due to ablation. This mass loss was surprisingly low considering the extremely warm and dry summer. In order to identify the most relevant drivers of snow melt we also present simulations with the sophisticated snow cover models SNOWPACK and Alpine3D. The simulations are driven by meteorological input data recorded in the vicinity of the piles and enable a detailed analysis of the relevant processes controlling the energy balance. The models can be applied to optimize settings for snow farming and to examine the suitability of new locations, configurations or cover material for future snow farming projects.

  12. Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012

    Science.gov (United States)

    Zhong, Xinyue; Zhang, Tingjun; Kang, Shichang; Wang, Kang; Zheng, Lei; Hu, Yuantao; Wang, Huijuan

    2018-01-01

    Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term (1966-2012) ground-based measurements from 1814 stations. Spatially, long-term (1971-2000) mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade-1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50° N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.

  13. Snow darkening caused by black carbon emitted from fires

    Science.gov (United States)

    Engels, Jessica; Kloster, Silvia; Bourgeois, Quentin

    2014-05-01

    We implemented the effect of snow darkening caused by black carbon (BC) emitted from forest fires into the Max Planck Institute for Meteorology Earth System Model (MPI-M ESM) to estimate its potential climate impact of present day fire occurrence. Considerable amounts of black carbon emitted from fires are transported into snow covered regions. Already very small quantities of black carbon reduce the snow reflectance, with consequences for snow melting and snow spatial coverage. Therefore, the SNICAR (SNow And Ice Radiation) model (Flanner and Zender (2005)) is implemented in the land surface component (JSBACH) of the atmospheric general circulation model ECHAM6, developed at the MPI-M. The SNICAR model includes amongst other processes a complex calculation of the snow albedo depending on black carbon in snow and snow grain growth depending on water vapor fluxes for a five layer snow scheme. For the implementation of the SNICAR model into the one layer scheme of ECHAM6-JSBACH, we used the SNICAR-online version (http://snow.engin.umich.edu). This single-layer simulator provides the albedo of snow for selectable combinations of impurity content (e.g. black carbon), snow grain size, and incident solar flux characteristics. From this scheme we derived snow albedo values for black carbon in snow concentrations ranging between 0 and 1500 ng(BC)/g(snow) and for different snow grain sizes for the visible (0.3 - 0.7 µm) and near infrared range (0.7 - 1.5 µm). As snow grains grow over time, we assign different snow ages to different snow grain sizes (50, 150, 500, and 1000 µm). Here, a radius of 50 µm corresponds to new snow, whereas a radius of 1000 µm corresponds to old snow. The required snow age is taken from the BATS (Biosphere Atmosphere Transfer Scheme, Dickinson et al. (1986)) snow albedo implementation in ECHAM6-JSBACH. Here, we will present an extended evaluation of the model including a comparison of modeled black carbon in snow concentrations to observed

  14. Interactions Between Snow-Adapted Organisms, Minerals and Snow in a Mars-Analog Environment, and Implications for the Possible Formation of Mineral Biosignatures

    Science.gov (United States)

    Hausrath, E.; Bartlett, C. L.; Garcia, A. H.; Tschauner, O. D.; Murray, A. E.; Raymond, J. A.

    2015-12-01

    Increasing evidence suggests that icy environments on bodies such as Mars, Europa, and Enceladus may be important potential habitats in our solar system. Life in icy environments faces many challenges, including water limitation, temperature extremes, and nutrient limitation. Understanding how life has adapted to withstand these challenges on Earth may help understand potential life on other icy worlds, and understanding the interactions of such life with minerals may help shed light on the detection of possible mineral biosignatures. Snow environments, being particularly nutrient limited, may require specific adaptations by the microbiota living there. Previous observations have suggested that associated minerals and microorganisms play an important role in snow algae micronutrient acquisition. Here, in order to interpret micronutrient uptake by snow algae, and potential formation of mineral biosignatures, we present observations of interactions between snow algae and associated microorganisms and minerals in both natural, Mars-analog environments, and laboratory experiments. Samples of snow, dust, snow algae, and microorganisms were collected from Mount Anderson Ridge, CA. Some samples were DAPI-stained and analyzed by epifluorescent microscopy, and others were freeze-dried and examined by scanning electron microscopy, synchrotron X-ray diffraction (XRD) and synchrotron X-ray fluorescence (XRF). Xenic cultures of the snow alga Chloromonas brevispina were also grown under Fe-limiting conditions with and without the Fe-containing mineral nontronite to determine impacts of the mineral on algal growth. Observations from epifluorescent microscopy show bacteria closely associated with the snow algae, consistent with a potential role in micronutrient acquisition. Particles are also present on the algal cell walls, and synchrotron-XRD and XRF observations indicate that they are Fe-rich, and may therefore be a micronutrient source. Laboratory experiments indicated

  15. Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation

    Science.gov (United States)

    Kwon, Yonghwan; Yang, Zong-Liang; Zhao, Long; Hoar, Timothy J.; Toure, Ally M.; Rodell, Matthew

    2016-01-01

    This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T(sub B) at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T(sub B) based on their correlations with the prior T(sub B) (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171m RMSE), the overall snow depth estimates are improved by 1.6% (0.168m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177mRMSE). Significant improvement of the snow depth estimates in the rule-based RA as observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant (p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions.

  16. Influence of surface roughness on the reflective properties of snow

    International Nuclear Information System (INIS)

    Zhuravleva, Tatiana B.; Kokhanovsky, Alexander A.

    2011-01-01

    In this paper the influence of 3D effect on snow reflection function (SRF) and albedo is studied in the framework of the stochastic radiative transfer theory. In particular, the corresponding equations for the averaged intensity of reflected light are solved for the ensemble of realizations of the stochastic field κ(r), describing the distribution of 3D elements on the flat semi-infinite snow layer (SISL). The reflection from the underlying SISL is modeled using the solution of the 1D radiative transfer equation. The corresponding look-up tables were compiled beforehand and used in the simulation process. In accordance with the previous studies, it was found that the albedo of snow layer is reduced (in particular, in the infrared region), if 3D effects are taken into account. There is no such a reduction, if light absorption in snow is absent. The 3D effects may increase or decrease SRF depending on the sastrugi fraction and illumination/observation conditions.

  17. The Snow Darkening Effect and the Simulation of Extremes over Eurasia

    Science.gov (United States)

    Yasunari, T. J.; Lau, W. K. M.; Kim, K. M.; Koster, R. D.

    2014-12-01

    We have recently completed an updated ensemble of NASA GEOS-5 simulations with a snow-darkening module (now officially named GOddard SnoW Impurity Module, or GOSWIM, and summarized in the published paper by Yasunari et al., SOLA, 2014; see at: https://www.jstage.jst.go.jp/article/sola/10/0/10_2014-011/_article). This ensemble ("snow-darkening case (SDC)"), consisting of ten parallel simulations (differing only in their initial conditions) spanning 2002-2011, is compared here to a corresponding ensemble with all snow-darkening effects disabled ("non-SDC"). We focus particularly on the production of extremes associated with snow darkening. To identify regions of interest over Eurasia, we first rank the 100 separate spring (MAM) or summer (JJA) values of a given quantity in each combined 100-yr data (i.e., 10-yr x 10-ensemble), and then compute the differences of the 90th percentile values between SDC and non-SDC. For spring, large differences are seen in a specific area of Europe and Central Asia (ECA), and for summer, they are seen for an area in the Russian Arctic (RA). The next step in our analysis addresses the month-by-month variation of the percentile differences within these identified regions - for each month, and for a given meteorological or hydrological variable, we determined the SDC percentile that corresponds to the 90th percentile value found for the non-SDC ensemble. For example, in the RA domain, the surface air temperature corresponding to the 90th percentile in the non-SDC ensemble has a consistently lower percentile in the SDC data - not only during spring and summer through the increased absorption of radiation by snow polluted with dust, black carbon, and organic carbon, but also in the post-snow season through some form of memory in the system. The temperature extremes in the SDC ensemble thus exceed those of the non-SDC ensemble throughout the year. This analysis supports the idea that the consideration of snow darkening effect in global

  18. Merging a Terrain-Based Parameter and Snow Particle Counter Data for the Assessment of Snow Redistribution in the Col du Lac Blanc Area

    Science.gov (United States)

    Schön, Peter; Prokop, Alexander; Naaim-Bouvet, Florence; Vionnet, Vincent; Guyomarc'h, Gilbert; Heiser, Micha; Nishimura, Kouichi

    2015-04-01

    Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns. It does not, however, provide a quantitative estimate of changes in snow depths. The objective of our research was to introduce a new parameter to quantify changes in snow depths in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its consistently bi-modal wind directions. Our work focused on two pronounced, approximately 10 m high terrain breaks, and we worked with 1 m resolution digital snow surface models (DSM). The DSM and measured changes in snow depths were obtained with high-accuracy terrestrial laser scan (TLS) measurements. First we calculated the terrain-based parameter Sx on a digital snow surface model and correlated Sx with measured changes in snow-depths (Δ SH). Results showed that Δ SH can be approximated by Δ SHestimated = α * Sx, where α is a newly introduced parameter. The parameter α has shown to be linked to the amount of snow deposited influenced by blowing snow flux. At the Col du Lac Blanc test side, blowing snow flux is recorded with snow particle counters (SPC). Snow flux is the number of drifting snow particles per time and area. Hence, the SPC provide data about the duration and intensity of drifting snow events, two important factors not accounted for by the terrain parameter Sx. We analyse how the SPC snow flux data can be used to estimate the magnitude of the new variable parameter α . To simulate the development

  19. Color Image of Snow White Trenches and Scraping

    Science.gov (United States)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on the 31st Martian day of the mission, or Sol 31 (June 26, 2008), after the May 25, 2008 landing. This image shows the trenches informally called 'Snow White 1' (left), 'Snow White 2' (right), and within the Snow White 2 trench, the smaller scraping area called 'Snow White 3.' The Snow White 3 scraped area is about 5 centimeters (2 inches) deep. The dug and scraped areas are within the diggiing site called 'Wonderland.' The Snow White trenches and scraping prove that scientists can take surface soil samples, subsurface soil samples, and icy samples all from one unit. Scientists want to test samples to determine if some ice in the soil may have been liquid in the past during warmer climate cycles. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is led by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver

  20. Chemical characterization of surface snow in Istanbul (NW Turkey) and their association with atmospheric circulations.

    Science.gov (United States)

    Baysal, Asli; Baltaci, Hakki; Ozbek, Nil; Destanoglu, Orhan; Ustabasi, Gul Sirin; Gumus, Gulcin

    2017-06-01

    The understanding of the impurities in natural snow is important in realizing its atmospheric quality, soil characteristics, and the pollution caused to the environment. Knowledge of the occurrence of major ions and trace metals in the snow in the megacity of Istanbul is very limited. This manuscript attempts to understand the origin of major soluble ions (fluoride, acetate, formate, chlorite, chloride, nitrite, chlorate, bromide, nitrate, sulfate, phosphate, and perchlorate) and some trace metals (Fe, Mn, Cd, Co, Ni, Pb, Zn, Cu) in winter surface snow, collected in Istanbul, Turkey. The sampling of the surface snow was conducted after each precipitation during the winter of 2015-2016 at three sites in the city. Besides the statistical evaluation of the major ions, and some trace metal concentrations, the chemical variations along with atmospheric circulations, which are important modification mechanisms that influence the concentrations, were investigated in the study. At examined locations and times, 12 major anions were investigated and in these anions fluoride, chlorite, chlorate, bromide, and perchlorate in the snow samples were below the detection limit; only SO 4 2- , NO 3 - , and CI - were found to be in the range of 1.11-17.90, 0.75-4.52, and 0.19-3.01 mg/L. Also, according to the trace element determination, the concentration was found to be 29.2-53.7, 2.0-16.1, 1.0-2.2, 50.1-71.1, 24.2-35.2, ND-7.9, 43.2-106.6, and 3.0-17.7 μg/L for Fe, Mn, Cd, Co, Ni, Pb, Zn, and Cu, respectively. The major anions and investigated trace elements here originated mainly from anthropogenic and atmospheric circulation and mainly influenced by northerly and southerly circulation patterns. While the main limitations in the present study may be the low number of samples that may not be entirely representative, accurately reflect identification, or support other previously observed local measurements, we believe that the type of data presented in this study has the potential

  1. Variability in snow cover phenology in China from 1952 to 2010

    OpenAIRE

    Ke, Chang-Qing; Li, Xiu-Cang; Xie, Hongjie; Ma, Dong-Hui; Liu, Xun; Kou, Cheng

    2016-01-01

    Daily snow observation data from 672 stations in China, particularly the 296 stations with over 10 mean snow cover days (SCDs) in a year during the period of 1952–2010, are used in this study. We first examine spatiotemporal variations and trends of SCDs, snow cover onset date (SCOD), and snow cover end date (SCED). We then investigate the relationships of SCDs with number of days with temperature below 0 °C (TBZD), mean air temperature (MAT), and Arctic Oscillation (AO) index....

  2. Snow control on active layer and permafrost in steep alpine rock walls (Aiguille du Midi, 3842 m a.s.l, Mont Blanc massif)

    Science.gov (United States)

    Magnin, Florence; Westermann, Sebastian; Pogliotti, Paolo; Ravanel, Ludovic; Deline, Philip

    2016-04-01

    Permafrost degradation through the thickening of the active layer and the rising temperature at depth is a crucial process of rock wall stability. The ongoing increase in rock falls observed during hot periods in mid-latitude mountain ranges is regarded as a result of permafrost degradation. However, the short-term thermal dynamics of alpine rock walls are misunderstood since they result of complex processes related to the interaction of local climate variables, heterogeneous snow cover and heat transfers. As a consequence steady-state and long-term changes that can be approached with simpler process mainly related to air temperature, solar radiations and heat conduction were the most common dynamics to be studied so far. The effect of snow on the bedrock surface temperature is increasingly investigated and has already been demonstrated to be an essential factor of permafrost distribution. Nevertheless, its effect on the year-to-year changes of the active layer thickness and of the permafrost temperature in steep alpine bedrock has not been investigated yet, partly due to the lack of appropriate data. We explore the role of snow accumulations on the active layer and permafrost thermal regime of steep rock walls of a high-elevated site, the Aiguille du Midi (AdM, 3842 m a.s.l, Mont Blanc massif, Western European Alps) by mean of a multi-methods approach. We first analyse six years of temperature records in three 10-m-deep boreholes. Then we describe the snow accumulation patterns on two rock faces by means of automatically processed camera records. Finally, sensitivity analyses of the active layer thickness and permafrost temperature towards timing and magnitude of snow accumulations are performed using the numerical permafrost model CryoGrid 3. The energy balance module is forced with local meteorological measurements on the AdM S face and validated with surface temperature measurements at the weather station location. The heat conduction scheme is calibrated with

  3. New nitrogen uptake strategy: specialized snow roots.

    Science.gov (United States)

    Onipchenko, Vladimir G; Makarov, Mikhail I; van Logtestijn, Richard S P; Ivanov, Viktor B; Akhmetzhanova, Assem A; Tekeev, Dzhamal K; Ermak, Anton A; Salpagarova, Fatima S; Kozhevnikova, Anna D; Cornelissen, Johannes H C

    2009-08-01

    The evolution of plants has yielded a wealth of adaptations for the acquisition of key mineral nutrients. These include the structure, physiology and positioning of root systems. We report the discovery of specialized snow roots as a plant strategy to cope with the very short season for nutrient uptake and growth in alpine snow-beds, i.e. patches in the landscape that remain snow-covered well into the summer. We provide anatomical, chemical and experimental (15)N isotope tracking evidence that the Caucasian snow-bed plant Corydalis conorhiza forms extensive networks of specialized above-ground roots, which grow against gravity to acquire nitrogen directly from within snow packs. Snow roots capture nitrogen that would otherwise partly run off down-slope over a frozen surface, thereby helping to nourish these alpine ecosystems. Climate warming is changing and will change mountain snow regimes, while large-scale anthropogenic N deposition has increased snow N contents. These global changes are likely to impact on the distribution, abundance and functional significance of snow roots.

  4. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.

    2013-03-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  5. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.; Westra, Seth; Evans, Jason P.; McCabe, Matthew

    2013-01-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  6. Sublimation From Snow in Northern Environments

    Science.gov (United States)

    Pomeroy, J. W.

    2002-12-01

    Sublimation from snow is an often neglected component of water and energy balances. Research under the Mackenzie GEWEX Study has attempted to understand the snow and atmospheric processes controlling sublimation and to estimate the magnitude of sublimation in high latitude catchments. Eddy correlation units were used to measure vertical water vapour fluxes from a high latitude boreal forest, snow-covered tundra and shrub-covered tundra in Wolf Creek Research Basin, near Whitehorse Yukon, Territory Canada. Over Jan-Apr. water vapour fluxes from the forest canopy amounted to 18.3 mm, a significant loss from winter snowfall of 54 mm. Most of this loss occurred when the canopy was snow-covered. The weight of snow measured on a suspended, weighed tree indicates that this flux is dominated by sublimation of intercepted snow. In the melt period (April), water vapour fluxes were uniformly small ranging from 0.21 mm/day on the tundra slope, 0.23 mm/day for the forest and 0.27 mm/day for the shrub-tundra. During the melt period the forest and shrub canopies was snow-free and roots were frozen, so the primary source of water vapour from all sites was the surface snow.

  7. A Comparison of the SNICAR Radiative Transfer Model to In Situ Snow Characterization Measurements at Sites in New England, USA

    Science.gov (United States)

    Adolph, A. C.; Albert, M. R.; Dibb, J. E.; Lazarcik, J.; Amante, J.

    2016-12-01

    As a highly reflective material, snow serves as an important control on surface energy balance. Given the current changes in climate and the sensitivity of snow cover to rising temperatures, it is critical that we understand the role of snow and its associated feedbacks in the climate system. Much of snow albedo research has focused on polar or high altitude snow packs, but rapid changes are also occurring in temperate regions; in the northeastern United States of America, changing climate has resulted in shallower snow packs and fewer days of snow cover. As these changes occur and we seek to understand the associated implications for snow albedo within climate dynamics, it is imperative that we are able to accurately represent snow in models. The SNow, ICe, and Aerosol Radiation model (SNICAR), developed by Flanner and Zender (2005) and used in the IPCC assessments, provides upward and downward radiative fluxes of one or many snow layers based on the following inputs: snow depth, density, grain size, and impurity content; solar zenith angle; lighting conditions; and albedo of the surface beneath the snowpack. To our knowledge, the SNICAR model has not been validated with data from a mid-latitude temperate region. Through a measurement campaign that occurred from winter 2013-2016, we have collected over 400 independent observations of a suite of snow characterization measurements and spectral snow albedo from three different sites in New Hampshire, USA. Comparison of our spectral albedo measurements to the SNICAR albedo derived from measured snow properties and illumination conditions will allow for validation of the model or recommendations for improvement based on the sensitivities found in the data.

  8. A Prognostic Methodology for Precipitation Phase Detection using GPM Microwave Observations —With Focus on Snow Cover

    Science.gov (United States)

    Takbiri, Z.; Ebtehaj, A.; Foufoula-Georgiou, E.; Kirstetter, P.

    2017-12-01

    Improving satellite retrieval of precipitation requires increased understanding of its passive microwave signature over different land surfaces. Passive microwave signals over snow-covered surfaces are notoriously difficult to interpret because they record both emission from the land below and absorption/scattering from the liquid/ice crystals. Using data from the Global Precipitation Measurement (GPM) core satellite, we demonstrate that the microwave brightness temperatures of rain and snowfall shifts from a scattering to an emission regime from summer to winter, due to expansion of the less emissive snow cover underneath. We present evidence that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The study also examines a prognostic nearest neighbor matching method for the detection of precipitation and its phase from passive microwave observations using GPM data. The nearest neighbor uses the weighted Euclidean distance metric to search through an a priori database that is populated with coincident GPM radiometer and radar data as well as ancillary snow cover fraction. The results demonstrate prognostic capabilities of the proposed method in detection of terrestrial snowfall. At the global scale, the average probability of hit and false alarm reaches to 0.80 and remains below 0.10, respectively. Surprisingly, the results show that the snow cover may help to better detect precipitation as the detection rate of terrestrial precipitation is increased from 0.75 (no snow cover) to 0.84 (snow-covered surfaces). For solid precipitation, this increased rate of detection is larger than its liquid counterpart by almost 8%. The main reasons are found to be related to the multi-frequency capabilities of the nearest neighbor matching that can properly isolate the atmospheric signal from the background emission and the fact that the precipitation can exhibit an emission-like (warmer

  9. SWEAT: Snow Water Equivalent with AlTimetry

    Science.gov (United States)

    Agten, Dries; Benninga, Harm-Jan; Diaz Schümmer, Carlos; Donnerer, Julia; Fischer, Georg; Henriksen, Marie; Hippert Ferrer, Alexandre; Jamali, Maryam; Marinaci, Stefano; Mould, Toby JD; Phelan, Liam; Rosker, Stephanie; Schrenker, Caroline; Schulze, Kerstin; Emanuel Telo Bordalo Monteiro, Jorge

    2017-04-01

    To study how the water cycle changes over time, satellite and airborne remote sensing missions are typically employed. Over the last 40 years of satellite missions, the measurement of true water inventories stored in sea and land ice within the cryosphere have been significantly hindered by uncertainties introduced by snow cover. Being able to determine the thickness of this snow cover would act to reduce such error, improving current estimations of hydrological and climate models, Earth's energy balance (albedo) calculations and flood predictions. Therefore, the target of the SWEAT (Snow Water Equivalent with AlTimetry) mission is to directly measure the surface Snow Water Equivalent (SWE) on sea and land ice within the polar regions above 60°and below -60° latitude. There are no other satellite missions currently capable of directly measuring SWE. In order to achieve this, the proposed mission will implement a novel combination of Ka- and Ku-band radioaltimeters (active microwave sensors), capable of penetrating into the snow microstructure. The Ka-band altimeter (λ ≈ 0.8 cm) provides a low maximum snow pack penetration depth of up to 20 cm for dry snow at 37 GHz, since the volume scattering of snow dominates over the scattering caused by the underlying ice surface. In contrast, the Ku-band altimeter (λ ≈ 2 cm) provides a high maximum snowpack penetration depth of up to 15 m in high latitudes regions with dry snow, as volume scattering is decreased by a factor of 55. The combined difference in Ka- and Ku-band signal penetration results will provide more accurate and direct determination of SWE. Therefore, the SWEAT mission aims to improve estimations of global SWE interpreted from passive microwave products, and improve the reliability of numerical snow and climate models.

  10. Inorganic carbon addition stimulates snow algae primary productivity

    Science.gov (United States)

    Hamilton, T. L.; Havig, J. R.

    2017-12-01

    Earth has experienced glacial/interglacial oscillations throughout its history. Today over 15 million square kilometers (5.8 million square miles) of Earth's land surface is covered in ice including glaciers, ice caps, and the ice sheets of Greenland and Antarctica, most of which are retreating as a consequence of increased atmospheric CO2. Glaciers are teeming with life and supraglacial snow and ice surfaces are often red due to blooms of photoautotrophic algae. Recent evidence suggests the red pigmentation, secondary carotenoids produced in part to thrive under high irradiation, lowers albedo and accelerates melt. However, there are relatively few studies that report the productivity of snow algae communities and the parameters that constrain their growth on snow and ice surfaces. Here, we demonstrate that snow algae primary productivity can be stimulated by the addition of inorganic carbon. We found an increase in light-dependent carbon assimilation in snow algae microcosms amended with increasing amounts of inorganic carbon. Our snow algae communities were dominated by typical cosmopolitan snow algae species recovered from Alpine and Arctic environments. The climate feedbacks necessary to enter and exit glacial/interglacial oscillations are poorly understood. Evidence and models agree that global Snowball events are accompanied by changes in atmospheric CO2 with increasing CO2 necessary for entering periods of interglacial time. Our results demonstrate a positive feedback between increased CO2 and snow algal productivity and presumably growth. With the recent call for bio-albedo effects to be considered in climate models, our results underscore the need for robust climate models to include feedbacks between supraglacial primary productivity, albedo, and atmospheric CO2.

  11. On the impact of snow cover on daytime pollution dispersion

    Science.gov (United States)

    Segal, M.; Garratt, J. R.; Pielke, R. A.; Hildebrand, P.; Rogers, F. A.; Cramer, J.; Schanot, A.

    A preliminary evaluation of the impact of snow cover on daytime pollutant dispersion conditions is made by using conceptual, scaling, and observational analyses. For uniform snow cover and synoptically unperturbed sunny conditions, observations indicate a considerate suppression of the surface sensible heat flux, the turbulence, and the development of the daytime atmospheric boundary layer (ABL) when compared to snow-free conditions. However, under conditions of non-uniform snow cover, as in urban areas, or associated with vegetated areas or bare ground patches, a milder effect on pollutant dispersion conditions would be expected. Observed concentrations of atmospheric particles within the ABL, and surface pollutant concentrations in urban areas, reflect the impact of snow cover on the modification of ABL characteristics.

  12. Ultraviolet radiation and the snow alga Chlamydomonas nivalis (Bauer) Wille.

    Science.gov (United States)

    Gorton, Holly L; Vogelmann, Thomas C

    2003-06-01

    Aplanospores of Chlamydomonas nivalis are frequently found in high-altitude, persistent snowfields where they are photosynthetically active despite cold temperatures and high levels of visible and ultraviolet (UV) radiation. The goals of this work were to characterize the UV environment of the cells in the snow and to investigate the existence and localization of screening compounds that might prevent UV damage. UV irradiance decreased precipitously in snow, with UV radiation of wavelengths 280-315 nm and UV radiation of wavelengths 315-400 nm dropping to 50% of incident levels in the top 1 and 2 cm, respectively. Isolated cell walls exhibited UV absorbance, possibly by sporopollenin, but this absorbance was weak in images of broken or plasmolyzed cells observed through a UV microscope. The cells also contained UV-absorbing cytoplasmic compounds, with the extrachloroplastic carotenoid astaxanthin providing most of the screening. Additional screening compound(s) soluble in aqueous methanol with an absorption maximum at 335 nm played a minor role. Thus, cells are protected against potentially high levels of UV radiation by the snow itself when they live several centimeters beneath the surface, and they rely on cellular screening compounds, chiefly astaxanthin, when located near the surface where UV fluxes are high.

  13. ESA GlobSnow Snow Water Equivalent (SWE)

    Data.gov (United States)

    National Aeronautics and Space Administration — The European Space Agency (ESA) Global Snow Monitoring for Climate Research (GlobSnow) snow water equivalent (SWE) v2.0 data record contains snow information derived...

  14. Snow and Ice Crust Changes over Northern Eurasia since 1966

    Science.gov (United States)

    Bulygina, O.; Groisman, P. Y.; Razuvaev, V.; Radionov, V.

    2009-12-01

    When temperature of snow cover reaches zero Celsius first time since its establishment, snowmelt starts. In many parts of the world this process can be lengthy. The initial amount of heat that “arrives” to the snowpack might be insufficient for complete snowmelt, during the colder nights re-freeze of the melted snow may occur (thus creating the ice crust layers), and a new cold front (or the departure of the warm front that initiated melt) can decrease temperatures below the freezing point again and stop the snowmelt completely. It well can be that first such snowmelt occurs in winter (thaw day) and for several months thereafter snowpack stays on the ground. However, even the first such melt initiates a process of snow metamorphosis on its surface changing snow albedo and generating snow crust as well as on its bottom generating ice crust. Once emerged, the crusts will not disappear until the complete snowmelt. Furthermore, these crusts have numerous pathways of impact on the wild birds and animals in the Arctic environment as well as on domesticated reindeers. In extreme cases, the crusts may kill some wild species and prevent reindeers’ migration and feeding. Ongoing warming in high latitudes created situations when in the western half of Eurasian continent days with thaw became more frequent. Keeping in mind potential detrimental impacts of winter thaws and associated with them snow/ice crust development, it is worthwhile to study directly what are the major features of snow and ice crust over Eurasia and what is their dynamics. For the purpose of this study, we employed the national snow survey data set archived at the Russian Institute for Hydrometeorological Information. The dataset has routine snow surveys run throughout the cold season each decade (during the intense snowmelt, each 5 days) at all meteorological stations of the former USSR, thereafter, in Russia since 1966. Prior to 1966 snow surveys are also available but the methodology of

  15. Blowing snow detection from ground-based ceilometers : Application to East Antarctica

    NARCIS (Netherlands)

    Gossart, Alexandra; Souverijns, Niels; Gorodetskaya, Irina V.; Lhermitte, S.L.M.; Lenaerts, Jan T M; Schween, Jan H.; Mangold, Alexander; Laffineur, Quentin; van Lipzig, Nicole P. M.

    2017-01-01

    Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the

  16. Global warming: Sea ice and snow cover

    International Nuclear Information System (INIS)

    Walsh, J.E.

    1993-01-01

    In spite of differences among global climate simulations under scenarios where atmospheric CO 2 is doubled, all models indicate at least some amplification of greenouse warming at the polar regions. Several decades of recent data on air temperature, sea ice, and snow cover of the high latitudes of the Northern Hemisphere are summarized to illustrate the general compatibility of recent variations in those parameters. Despite a data void over the Arctic Ocean, some noteworthy patterns emerge. Warming dominates in winter and spring, as projected by global climate models, with the warming strongest over subpolar land areas of Alaska, northwestern Canada, and northern Eurasia. A time-longitude summary of Arctic sea ice variations indicates that timescales of most anomalies range from several months to several years. Wintertime maxima of total sea ice extent contain no apparent secular trends. The statistical significance of trends in recent sea ice variations was evaluated by a Monte Carlo procedure, showing a statistically significant negative trend in the summer. Snow cover data over the 20-y period of record show a noticeable decrease of Arctic snow cover in the late 1980s. This is of potential climatic significance since the accompanying decrease of surface albedo leads to a rapid increase of solar heating. 21 refs., 3 figs., 1 tab

  17. The impact of boundary layer turbulence on snow growth and precipitation: Idealized Large Eddy Simulations

    Science.gov (United States)

    Chu, Xia; Xue, Lulin; Geerts, Bart; Kosović, Branko

    2018-05-01

    Ice particles and supercooled droplets often co-exist in planetary boundary-layer (PBL) clouds. The question examined in this numerical study is how large turbulent PBL eddies affect snow growth and surface precipitation from mixed-phase PBL clouds. In order to simplify this question, this study assumes an idealized BL with well-developed turbulence but no surface heat fluxes or radiative heat exchanges. Large Eddy Simulations with and without resolved PBL turbulence are compared. This comparison demonstrates that the impact on snow growth in mixed-phase clouds is controlled by two opposing mechanisms, a microphysical and a dynamical one. The cloud microphysical impact of large turbulent eddies is based on the difference in saturation vapor pressure over water and over ice. The net outcome of alternating turbulent up- and downdrafts is snow growth by diffusion and/or accretion (riming). On the other hand, turbulence-induced entrainment and detrainment may suppress snow growth. In the case presented herein, the net effect of these microphysical and dynamical processes is positive, but in general the net effect depends on ambient conditions, in particular the profiles of temperature, humidity, and wind.

  18. Past and future of the Austrian snow cover - results from the CC-Snow project

    Science.gov (United States)

    Strasser, Ulrich; Marke, Thomas; Hanzer, Florian; Ragg, Hansjörg; Kleindienst, Hannes; Wilcke, Renate; Gobiet, Andreas

    2013-04-01

    This study has the goal to simulate the evolution of the Austrian snow cover from 1971 to 2050 by means of a coupled modelling scheme, and to estimate the effect of climate change on the evolution of the natural snow cover. The model outcomes are interepreted with focus on both the future natural snow conditions, and the effects on winter skiing tourism. Therefore the regional temperature-index snow model SNOWREG is applied, providing snow maps with a spatial resolution of 250 m. The model is trained by means of assimilating local measurements and observed natural snow cover patterns. Meteorological forcing consists of the output of four realizations of the ENSEMBLES project for the A1B emission scenario. The meteorological variables are downscaled and error corrected with a quantile based empirical-statistical method on a daily time basis. The control simulation is 1971-2000, and the scenario simulation 2021-2050. Spatial interpolation is performed on the basis of parameter-elevation relations. We compare the four different global/regional climate model combinations and their effect on the snow modelling, and we explain the patterns of the resulting snow cover by means of regional climatological characteristics. The provinces Tirol and Styria serve as test regions, being typical examples for the two climatic subregions of Austria. To support the interpretation of the simulation results we apply indicators which enable to define meaningful measures for the comparison of the different periods and regions. Results show that the mean duration of the snow cover will decrease by 15 to 30 days per winter season, mostly in elevations between 2000 and 2500 m. Above 3000 m the higher winter precipitation can compensate this effect, and mean snow cover duration may even slightly increase. We also investigate the local scale by application of the physically based mountain snow model AMUNDSEN. This model is capable of producing 50 m resolution output maps for indicators

  19. Urban pavement surface temperature. Comparison of numerical and statistical approach

    Science.gov (United States)

    Marchetti, Mario; Khalifa, Abderrahmen; Bues, Michel; Bouilloud, Ludovic; Martin, Eric; Chancibaut, Katia

    2015-04-01

    The forecast of pavement surface temperature is very specific in the context of urban winter maintenance. to manage snow plowing and salting of roads. Such forecast mainly relies on numerical models based on a description of the energy balance between the atmosphere, the buildings and the pavement, with a canyon configuration. Nevertheless, there is a specific need in the physical description and the numerical implementation of the traffic in the energy flux balance. This traffic was originally considered as a constant. Many changes were performed in a numerical model to describe as accurately as possible the traffic effects on this urban energy balance, such as tires friction, pavement-air exchange coefficient, and infrared flux neat balance. Some experiments based on infrared thermography and radiometry were then conducted to quantify the effect fo traffic on urban pavement surface. Based on meteorological data, corresponding pavement temperature forecast were calculated and were compared with fiels measurements. Results indicated a good agreement between the forecast from the numerical model based on this energy balance approach. A complementary forecast approach based on principal component analysis (PCA) and partial least-square regression (PLS) was also developed, with data from thermal mapping usng infrared radiometry. The forecast of pavement surface temperature with air temperature was obtained in the specific case of urban configurtation, and considering traffic into measurements used for the statistical analysis. A comparison between results from the numerical model based on energy balance, and PCA/PLS was then conducted, indicating the advantages and limits of each approach.

  20. An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

    Science.gov (United States)

    Panzer, Ben; Gomez-Garcia, Daniel; Leuschen, Carl; Paden, John; Rodriguez-Morales, Fernando; Patel, Azsa; Markus, Thorsten; Holt, Benjamin; Gogineni, Prasad

    2013-01-01

    Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

  1. Springtime warming and reduced snow cover from carbonaceous particles

    Directory of Open Access Journals (Sweden)

    M. G. Flanner

    2009-04-01

    Full Text Available Boreal spring climate is uniquely susceptible to solar warming mechanisms because it has expansive snow cover and receives relatively strong insolation. Carbonaceous particles can influence snow coverage by warming the atmosphere, reducing surface-incident solar energy (dimming, and reducing snow reflectance after deposition (darkening. We apply a range of models and observations to explore impacts of these processes on springtime climate, drawing several conclusions: 1 Nearly all atmospheric particles (those with visible-band single-scatter albedo less than 0.999, including all mixtures of black carbon (BC and organic matter (OM, increase net solar heating of the atmosphere-snow column. 2 Darkening caused by small concentrations of particles within snow exceeds the loss of absorbed energy from concurrent dimming, thus increasing solar heating of snowpack as well (positive net surface forcing. Over global snow, we estimate 6-fold greater surface forcing from darkening than dimming, caused by BC+OM. 3 Equilibrium climate experiments suggest that fossil fuel and biofuel emissions of BC+OM induce 95% as much springtime snow cover loss over Eurasia as anthropogenic carbon dioxide, a consequence of strong snow-albedo feedback and large BC+OM emissions from Asia. 4 Of 22 climate models contributing to the IPCC Fourth Assessment Report, 21 underpredict the rapid warming (0.64°C decade−1 observed over springtime Eurasia since 1979. Darkening from natural and anthropogenic sources of BC and mineral dust exerts 3-fold greater forcing on springtime snow over Eurasia (3.9 W m−2 than North America (1.2 W m−2. Inclusion of this forcing significantly improves simulated continental warming trends, but does not reconcile the low bias in rate of Eurasian spring snow cover decline exhibited by all models, likely because BC deposition trends are negative or near-neutral over much of Eurasia. Improved Eurasian

  2. Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

    Directory of Open Access Journals (Sweden)

    Christian Vögeli

    2016-12-01

    Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.

  3. Snowscape Ecology: Linking Snow Properties to Wildlife Movements and Demography

    Science.gov (United States)

    Prugh, L.; Verbyla, D.; van de Kerk, M.; Mahoney, P.; Sivy, K. J.; Liston, G. E.; Nolin, A. W.

    2017-12-01

    Snow enshrouds up to one third of the global land mass annually and exerts a major influence on animals that reside in these "snowscapes," (landscapes covered in snow). Dynamic snowscapes may have especially strong effects in arctic and boreal regions where dry snow persists for much of the year. Changes in temperature and hydrology are transforming northern regions, with profound implications for wildlife that are not well understood. We report initial findings from a NASA ABoVE project examining effects of snow properties on Dall sheep (Ovis dalli dalli). We used the MODSCAG snow fraction product to map spring snowline elevations and snow-off dates from 2000-2015 throughout the global range of Dall sheep in Alaska and northwestern Canada. We found a negative effect of spring snow cover on Dall sheep recruitment that increased with latitude. Using meteorological data and a daily freeze/thaw status product derived from passive microwave remote sensing from 1983-2012, we found that sheep survival rates increased in years with higher temperatures, less winter precipitation, fewer spring freeze-thaw events, and more winter freeze-thaw events. To examine the effects of snow depth and density on sheep movements, we used location data from GPS-collared sheep and a snowpack evolution model (SnowModel). We found that sheep selected for shallow, fluffy snow at high elevations, but they selected for denser snow as depth increased. Our field measurements identified a critical snow density threshold of 329 (± 18 SE) kg/m3 to support the weight of Dall sheep. Thus, sheep may require areas of shallow, fluffy snow for foraging, while relying on hard-packed snow for winter travel. These findings highlight the importance of multiple snowscape properties on wildlife movements and demography. The integrated study of snow properties and ecological processes, which we call snowscape ecology, will greatly improve global change forecasting.

  4. On the relationship between the snowflake type aloft and the surface precipitation types at temperatures near 0 °C

    Science.gov (United States)

    Sankaré, Housseyni; Thériault, Julie M.

    2016-11-01

    Winter precipitation types can have major consequences on power outages, road conditions and air transportation. The type of precipitation reaching the surface depends strongly on the vertical temperature of the atmosphere, which is often composed of a warm layer aloft and a refreezing layer below it. A small variation of the vertical structure can lead to a change in the type of precipitation near the surface. It has been shown in previous studies that the type of precipitation depends also on the precipitation rate, which is directly linked to the particle size distribution and that a difference as low as 0.5 °C in the vertical temperature profile could change the type of precipitation near the surface. Given the importance of better understanding the formation of winter precipitation type, the goal of this study is to assess the impact of the snowflake habit aloft on the type of precipitation reaching the surface when the vertical temperature is near 0 °C. To address this, a one dimensional cloud model coupled with a bulk microphysics scheme was used. Four snowflake types (dendrite, bullet, column and graupel) have been added to the scheme. The production of precipitation at the surface from these types of snow has been compared to available observations. The results showed that the thickness of the snow-rain transition is four times deeper when columns and graupel only fall through the atmosphere compared to dendrites. Furthermore, a temperature of the melting layer that is three (four) times warmer is required to completely melt columns and graupel (dendrites). Finally, the formation of freezing rain is associated with the presence of lower density snowflakes (dendrites) aloft compared to the production of ice pellets (columns). Overall, this study demonstrated that the type of snowflakes has an impact on the type of precipitation reaching the surface when the temperature is near 0 °C.

  5. CREST-Snow Field Experiment: analysis of snowpack properties using multi-frequency microwave remote sensing data

    Directory of Open Access Journals (Sweden)

    T. Y. Lakhankar

    2013-02-01

    Full Text Available The CREST-Snow Analysis and Field Experiment (CREST-SAFE was carried out during January–March 2011 at the research site of the National Weather Service office, Caribou, ME, USA. In this experiment dual-polarized microwave (37 and 89 GHz observations were accompanied by detailed synchronous observations of meteorology and snowpack physical properties. The objective of this long-term field experiment was to improve understanding of the effect of changing snow characteristics (grain size, density, temperature under various meteorological conditions on the microwave emission of snow and hence to improve retrievals of snow cover properties from satellite observations. In this paper we present an overview of the field experiment and comparative preliminary analysis of the continuous microwave and snowpack observations and simulations. The observations revealed a large difference between the brightness temperature of fresh and aged snowpack even when the snow depth was the same. This is indicative of a substantial impact of evolution of snowpack properties such as snow grain size, density and wetness on microwave observations. In the early spring we frequently observed a large diurnal variation in the 37 and 89 GHz brightness temperature with small depolarization corresponding to daytime snowmelt and nighttime refreeze events. SNTHERM (SNow THERmal Model and the HUT (Helsinki University of Technology snow emission model were used to simulate snowpack properties and microwave brightness temperatures, respectively. Simulated snow depth and snowpack temperature using SNTHERM were compared to in situ observations. Similarly, simulated microwave brightness temperatures using the HUT model were compared with the observed brightness temperatures under different snow conditions to identify different states of the snowpack that developed during the winter season.

  6. Winter survival of Scots pine seedlings under different snow conditions.

    Science.gov (United States)

    Domisch, Timo; Martz, Françoise; Repo, Tapani; Rautio, Pasi

    2018-04-01

    Future climate scenarios predict increased air temperatures and precipitation, particularly at high latitudes, and especially so during winter. Soil temperatures, however, are more difficult to predict, since they depend strongly on the fate of the insulating snow cover. 'Rain-on-snow' events and warm spells during winter can lead to thaw-freeze cycles, compacted snow and ice encasement, as well as local flooding. These adverse conditions could counteract the otherwise positive effects of climatic changes on forest seedling growth. In order to study the effects of different winter and snow conditions on young Scots pine (Pinus sylvestris L.) seedlings, we conducted a laboratory experiment in which 80 1-year-old Scots pine seedlings were distributed between four winter treatments in dasotrons: ambient snow cover (SNOW), compressed snow and ice encasement (ICE), flooded and frozen soil (FLOOD) and no snow (NO SNOW). During the winter treatment period and a 1.5-month simulated spring/early summer phase, we monitored the needle, stem and root biomass of the seedlings, and determined their starch and soluble sugar concentrations. In addition, we assessed the stress experienced by the seedlings by measuring chlorophyll fluorescence, electric impedance and photosynthesis of the previous-year needles. Compared with the SNOW treatment, carbohydrate concentrations were lower in the FLOOD and NO SNOW treatments where the seedlings had almost died before the end of the experiment, presumably due to frost desiccation of aboveground parts during the winter treatments. The seedlings of the ICE treatment showed dead needles and stems only above the snow and ice cover. The results emphasize the importance of an insulating and protecting snow cover for small forest tree seedlings, and that future winters with changed snow patterns might affect the survival of tree seedlings and thus forest productivity.

  7. NHM-SMAP: spatially and temporally high-resolution nonhydrostatic atmospheric model coupled with detailed snow process model for Greenland Ice Sheet

    Science.gov (United States)

    Niwano, Masashi; Aoki, Teruo; Hashimoto, Akihiro; Matoba, Sumito; Yamaguchi, Satoru; Tanikawa, Tomonori; Fujita, Koji; Tsushima, Akane; Iizuka, Yoshinori; Shimada, Rigen; Hori, Masahiro

    2018-02-01

    To improve surface mass balance (SMB) estimates for the Greenland Ice Sheet (GrIS), we developed a 5 km resolution regional climate model combining the Japan Meteorological Agency Non-Hydrostatic atmospheric Model and the Snow Metamorphism and Albedo Process model (NHM-SMAP) with an output interval of 1 h, forced by the Japanese 55-year reanalysis (JRA-55). We used in situ data to evaluate NHM-SMAP in the GrIS during the 2011-2014 mass balance years. We investigated two options for the lower boundary conditions of the atmosphere: an offline configuration using snow, firn, and ice albedo, surface temperature data from JRA-55, and an online configuration using values from SMAP. The online configuration improved model performance in simulating 2 m air temperature, suggesting that the surface analysis provided by JRA-55 is inadequate for the GrIS and that SMAP results can better simulate physical conditions of snow/firn/ice. It also reproduced the measured features of the GrIS climate, diurnal variations, and even a strong mesoscale wind event. In particular, it successfully reproduced the temporal evolution of the GrIS surface melt area extent as well as the record melt event around 12 July 2012, at which time the simulated melt area extent reached 92.4 %. Sensitivity tests showed that the choice of calculation schemes for vertical water movement in snow and firn has an effect as great as 200 Gt year-1 in the GrIS-wide accumulated SMB estimates; a scheme based on the Richards equation provided the best performance.

  8. The effects of additional black carbon on Arctic sea ice surface albedo: variation with sea ice type and snow cover

    OpenAIRE

    A. A. Marks; M. D. King

    2013-01-01

    Black carbon in sea ice will decrease sea ice surface albedo through increased absorption of incident solar radiation, exacerbating sea ice melting. Previous literature has reported different albedo responses to additions of black carbon in sea ice and has not considered how a snow cover may mitigate the effect of black carbon in sea ice. Sea ice is predominately snow covered. Visible light absorption and light scattering coefficients are calculated for a typical first year and multi-y...

  9. The Art and Science of Snow Microbiology: Data Paintings of the Finnish Arctic

    Science.gov (United States)

    Reasor, K.; Lipson, D.

    2017-12-01

    A challenge in science-art collaborations is to create artwork that accurately represents scientific results while standing as an independent art object. Art associated with science may merely be illustrative, serving to decorate a scientific study, or conversely, science-art may only superficially derive from data without addressing its broader scientific meaning. A fully integrated work of science-art requires copious communication between the scientist and artist. Here we present the results of a collaboration between a microbial ecologist and a painter, to study and depict the nature of microbial communities in the snowpack of the Finnish Arctic around Lake Kilpisjärvi. Snow profiles were studied along an altitudinal gradient that spanned the lake, a mountain birch forest, the transitional forest near tree line, and the alpine above tree line on the fell, Saana. Snow from the top, middle and bottom of each profile was characterized physically, chemically and microbiologically. The snowpack provided an insulating layer such that temperatures close to 0°C were found at the base of the snowpack. Windblown areas outside the protective influence of the forest (lake, alpine) had thinner, denser snowpacks. Bacterial cell counts (performed by flow cytometry) were highest in the protected area at the base of the snowpack, lowest in the middle and intermediate at the snow surface. Sequencing of the 16S rRNA gene showed a diverse assemblage of bacteria on the surface that resembled typical soil species, while the base harbored a community dominated by Gammaproteobacteria. The artist chose to depict the results using four pairs of paintings, corresponding to the four elevations. The pairs consist of a landscape oil painting of the site and a "data painting," in which a simplified version of the landscape is shown in grayscale and snow characteristics are overlaid in color. Snow density is shown using value (the lightness or darkness of a color) and temperature is coded

  10. Early results from NASA's SnowEx campaign

    Science.gov (United States)

    Kim, Edward; Gatebe, Charles; Hall, Dorothy; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Hiemstra, Chris; Brucker, Ludovic; Crawford, Chris; Kang, Do Hyuk; De Marco, Eugenia; Beckley, Matt; Entin, Jared

    2017-04-01

    SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earth's terrestrial snow-covered regions? Year 1 (2016-17) focuses on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site is Grand Mesa and the secondary site is the Senator Beck Basin, both in western, Colorado, USA. Ten core sensors on four core aircraft will make observations using a broad suite of airborne sensors including active and passive microwave, and active and passive optical/infrared sensing techniques to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also includes an extensive range of ground truth measurements—in-situ samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some early results will be presented. Seasonal snow cover is the largest single component of the cryosphere in areal extent (covering an average of 46M km2 of Earth's surface (31 % of land areas) each year). This seasonal snow has major societal impacts in the areas of water resources, natural hazards (floods and droughts), water security, and weather and climate. The only practical way to estimate the quantity of snow on a consistent global basis is through satellites. Yet, current space-based techniques underestimate storage of snow water equivalent (SWE) by as much as 50%, and model-based estimates can differ greatly vs. estimates based on remotely-sensed observations. At peak coverage, as much as half of snow-covered terrestrial areas involve forested areas, so quantifying the challenge represented by forests is important to plan any future snow mission. Single-sensor approaches may work for certain snow types and certain conditions, but not for others

  11. Modelling stable atmospheric boundary layers over snow

    NARCIS (Netherlands)

    Sterk, H.A.M.

    2015-01-01

    Thesis entitled:

    Modelling Stable Atmospheric Boundary Layers over Snow

    H.A.M. Sterk

    Wageningen, 29th of April, 2015

    Summary

    The emphasis of this thesis is on the understanding and forecasting of the Stable Boundary Layer (SBL) over snow-covered surfaces. SBLs

  12. Parameterizations for narrowband and broadband albedo of pure snow and snow containing mineral dust and black carbon

    Science.gov (United States)

    Dang, Cheng; Brandt, Richard E.; Warren, Stephen G.

    2015-06-01

    The reduction of snow spectral albedo by black carbon (BC) and mineral dust, both alone and in combination, is computed using radiative transfer modeling. Broadband albedo is shown for mass fractions covering the full range from pure snow to pure BC and pure dust, and for snow grain radii from 5 µm to 2500 µm, to cover the range of possible grain sizes on planetary surfaces. Parameterizations are developed for opaque homogeneous snowpacks for three broad bands used in general circulation models and several narrower bands. They are functions of snow grain radius and the mass fraction of BC and/or dust and are valid up to BC content of 10 ppm, needed for highly polluted snow. A change of solar zenith angle can be mimicked by changing grain radius. A given mass fraction of BC causes greater albedo reduction in coarse-grained snow; BC and grain radius can be combined into a single variable to compute the reduction of albedo relative to pure snow. The albedo reduction by BC is less if the snow contains dust, a common situation on mountain glaciers and in agricultural and grazing lands. Measured absorption spectra of mineral dust are critically reviewed as a basis for specifying dust properties for modeling. The effect of dust on snow albedo at visible wavelengths can be represented by an "equivalent BC" amount, scaled down by a factor of about 200. Dust has little effect on the near-IR albedo because the near-IR albedo of pure dust is similar to that of pure snow.

  13. Intercomparison and validation of snow albedo parameterization schemes in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Pedersen, Christina A.; Winther, Jan-Gunnar [Norwegian Polar Institute, Tromsoe (Norway)

    2005-09-01

    Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings. (orig.)

  14. The spectral and chemical measurement of pollutants on snow near South Pole, Antarctica

    Science.gov (United States)

    Casey, K. A.; Kaspari, S. D.; Skiles, S. M.; Kreutz, K.; Handley, M. J.

    2017-06-01

    Remote sensing of light-absorbing particles (LAPs), or dark colored impurities, such as black carbon (BC) and dust on snow, is a key remaining challenge in cryospheric surface characterization and application to snow, ice, and climate models. We present a quantitative data set of in situ snow reflectance, measured and modeled albedo, and BC and trace element concentrations from clean to heavily fossil fuel emission contaminated snow near South Pole, Antarctica. Over 380 snow reflectance spectra (350-2500 nm) and 28 surface snow samples were collected at seven distinct sites in the austral summer season of 2014-2015. Snow samples were analyzed for BC concentration via a single particle soot photometer and for trace element concentration via an inductively coupled plasma mass spectrometer. Snow impurity concentrations ranged from 0.14 to 7000 part per billion (ppb) BC, 9.5 to 1200 ppb sulfur, 0.19 to 660 ppb iron, 0.013 to 1.9 ppb chromium, 0.13 to 120 ppb copper, 0.63 to 6.3 ppb zinc, 0.45 to 82 parts per trillion (ppt) arsenic, 0.0028 to 6.1 ppb cadmium, 0.062 to 22 ppb barium, and 0.0044 to 6.2 ppb lead. Broadband visible to shortwave infrared albedo ranged from 0.85 in pristine snow to 0.62 in contaminated snow. LAP radiative forcing, the enhanced surface absorption due to BC and trace elements, spanned from snow to 70 W m-2 for snow with high BC and trace element content. Measured snow reflectance differed from modeled snow albedo due to specific impurity-dependent absorption features, which we recommend be further studied and improved in snow albedo models.

  15. Estimation of snow albedo reduction by light absorbing impurities using Monte Carlo radiative transfer model

    Science.gov (United States)

    Sengupta, D.; Gao, L.; Wilcox, E. M.; Beres, N. D.; Moosmüller, H.; Khlystov, A.

    2017-12-01

    Radiative forcing and climate change greatly depends on earth's surface albedo and its temporal and spatial variation. The surface albedo varies greatly depending on the surface characteristics ranging from 5-10% for calm ocean waters to 80% for some snow-covered areas. Clean and fresh snow surfaces have the highest albedo and are most sensitive to contamination with light absorbing impurities that can greatly reduce surface albedo and change overall radiative forcing estimates. Accurate estimation of snow albedo as well as understanding of feedbacks on climate from changes in snow-covered areas is important for radiative forcing, snow energy balance, predicting seasonal snowmelt, and run off rates. Such information is essential to inform timely decision making of stakeholders and policy makers. Light absorbing particles deposited onto the snow surface can greatly alter snow albedo and have been identified as a major contributor to regional climate forcing if seasonal snow cover is involved. However, uncertainty associated with quantification of albedo reduction by these light absorbing particles is high. Here, we use Mie theory (under the assumption of spherical snow grains) to reconstruct the single scattering parameters of snow (i.e., single scattering albedo ῶ and asymmetry parameter g) from observation-based size distribution information and retrieved refractive index values. The single scattering parameters of impurities are extracted with the same approach from datasets obtained during laboratory combustion of biomass samples. Instead of using plane-parallel approximation methods to account for multiple scattering, we have used the simple "Monte Carlo ray/photon tracing approach" to calculate the snow albedo. This simple approach considers multiple scattering to be the "collection" of single scattering events. Using this approach, we vary the effective snow grain size and impurity concentrations to explore the evolution of snow albedo over a wide

  16. Research of Snow-Melt Process on a Heated Platform

    Directory of Open Access Journals (Sweden)

    Vasilyev Gregory P.

    2016-01-01

    Full Text Available The article has shown the results of experimental researches of the snow-melt on a heated platform-near building heat-pump snow-melt platform. The near-building (yard heat pump platforms for snow melt with the area up to 10-15 m2 are a basis of the new ideology of organization of the street cleaning of Moscow from snow in the winter period which supposes the creation in the megalopolis of the «distributed snow-melt system» (DSMS using non-traditional energy sources. The results of natural experimental researches are presented for the estimation of efficiency of application in the climatic conditions of Moscow of heat pumps in the snow-melt systems. The researches were conducted on a model sample of the near-building heat-pump platform which uses the low-potential thermal energy of atmospheric air. The conducted researches have confirmed experimentally in the natural conditions the possibility and efficiency of using of atmospheric air as a source of low-potential thermal energy for evaporation of the snow-melt heat pump systems in the climatic conditions of Moscow. The results of laboratory researches of snow-melt process on a heated horizontal platform are presented. The researches have revealed a considerable dependence of efficiency of the snow-melt process on its piling mode (form-building and the organization of the process of its piling mode (form-building and the organization of the process of its (snow mass heat exchange with the surface of the heated platform. In the process of researches the effect of formation of an «ice dome» under the melting snow mass called by the fact that in case of the thickness of snow loaded on the platform more than 10 cm the water formed from the melting snow while the contact with the heating surface don’t spread on it, but soaks into the snow, wets it due to capillary effect and freezes. The formation of «ice dome» leads to a sharp increase of snow-melt period and decreases the operating

  17. Long-term variability in Northern Hemisphere snow cover and associations with warmer winters

    Science.gov (United States)

    McCabe, Gregory J.; Wolock, David M.

    2010-01-01

    A monthly snow accumulation and melt model is used with gridded monthly temperature and precipitation data for the Northern Hemisphere to generate time series of March snow-covered area (SCA) for the period 1905 through 2002. The time series of estimated SCA for March is verified by comparison with previously published time series of SCA for the Northern Hemisphere. The time series of estimated Northern Hemisphere March SCA shows a substantial decrease since about 1970, and this decrease corresponds to an increase in mean winter Northern Hemisphere temperature. The increase in winter temperature has caused a decrease in the fraction of precipitation that occurs as snow and an increase in snowmelt for some parts of the Northern Hemisphere, particularly the mid-latitudes, thus reducing snow packs and March SCA. In addition, the increase in winter temperature and the decreases in SCA appear to be associated with a contraction of the circumpolar vortex and a poleward movement of storm tracks, resulting in decreased precipitation (and snow) in the low- to mid-latitudes and an increase in precipitation (and snow) in high latitudes. If Northern Hemisphere winter temperatures continue to warm as they have since the 1970s, then March SCA will likely continue to decrease.

  18. Comparing daily temperature averaging methods: the role of surface and atmosphere variables in determining spatial and seasonal variability

    Science.gov (United States)

    Bernhardt, Jase; Carleton, Andrew M.

    2018-05-01

    The two main methods for determining the average daily near-surface air temperature, twice-daily averaging (i.e., [Tmax+Tmin]/2) and hourly averaging (i.e., the average of 24 hourly temperature measurements), typically show differences associated with the asymmetry of the daily temperature curve. To quantify the relative influence of several land surface and atmosphere variables on the two temperature averaging methods, we correlate data for 215 weather stations across the Contiguous United States (CONUS) for the period 1981-2010 with the differences between the two temperature-averaging methods. The variables are land use-land cover (LULC) type, soil moisture, snow cover, cloud cover, atmospheric moisture (i.e., specific humidity, dew point temperature), and precipitation. Multiple linear regression models explain the spatial and monthly variations in the difference between the two temperature-averaging methods. We find statistically significant correlations between both the land surface and atmosphere variables studied with the difference between temperature-averaging methods, especially for the extreme (i.e., summer, winter) seasons (adjusted R2 > 0.50). Models considering stations with certain LULC types, particularly forest and developed land, have adjusted R2 values > 0.70, indicating that both surface and atmosphere variables control the daily temperature curve and its asymmetry. This study improves our understanding of the role of surface and near-surface conditions in modifying thermal climates of the CONUS for a wide range of environments, and their likely importance as anthropogenic forcings—notably LULC changes and greenhouse gas emissions—continues.

  19. Scales of snow depth variability in high elevation rangeland sagebrush

    Science.gov (United States)

    Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

    2017-09-01

    In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

  20. Improving the Terrain-Based Parameter for the Assessment of Snow Redistribution in the Col du Lac Blanc Area and Comparisons with TLS Snow Depth Data

    Science.gov (United States)

    Schön, Peter; Prokop, Alexander; Naaim-Bouvet, Florence; Nishimura, Kouichi; Vionnet, Vincent; Guyomarc'h, Gilbert

    2014-05-01

    Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns, but has failed to quantitatively describe the snow redistribution, and correlations with measured snow heights were poor. The objective of our research was to a) identify the sources of poor correlations between predicted and measured snow re-distribution and b) improve the parameters ability to qualitatively and quantitatively describe snow redistribution in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its constant wind direction and the availability of data from a meteorological station. Our work focused on areas with terrain edges of approximately 10 m height, and we worked with 1-2 m resolution digital terrain and snow surface data. We first compared the results of the terrain-based parameter calculations to measured snow-depths, obtained by high-accuracy terrestrial laser scan measurements. The results were similar to previous studies: The parameter was able to reproduce observed patterns in snow distribution, but regression analyses showed poor correlations between terrain-based parameter and measured snow-depths. We demonstrate how the correlations between measured and calculated snow heights improve if the parameter is calculated based on a snow surface model instead of a digital terrain model. We show how changing the parameter's search distance and how raster re-sampling and raster smoothing improve the results. To improve the parameter

  1. Retention and radiative forcing of black carbon in eastern Sierra Nevada snow

    Directory of Open Access Journals (Sweden)

    K. M. Sterle

    2013-02-01

    Full Text Available When contaminated by absorbing particles, such as refractory black carbon (rBC and continental dust, snow's albedo decreases and thus its absorption of solar radiation increases, thereby hastening snowmelt. For this reason, an understanding of rBC's affect on snow albedo, melt processes, and radiation balance is critical for water management, especially in a changing climate. Measurements of rBC in a sequence of snow pits and surface snow samples in the eastern Sierra Nevada of California during the snow accumulation and ablation seasons of 2009 show that concentrations of rBC were enhanced sevenfold in surface snow (~25 ng g–1 compared to bulk values in the snowpack (~3 ng g–1. Unlike major ions, which were preferentially released during the initial melt, rBC and continental dust were retained in the snow, enhancing concentrations well into late spring, until a final flush occurred during the ablation period. We estimate a combined rBC and continental dust surface radiative forcing of 20 to 40 W m−2 during April and May, with dust likely contributing a greater share of the forcing.

  2. A new MRI land surface model HAL

    Science.gov (United States)

    Hosaka, M.

    2011-12-01

    A land surface model HAL is newly developed for MRI-ESM1. It is used for the CMIP simulations. HAL consists of three submodels: SiByl (vegetation), SNOWA (snow) and SOILA (soil) in the current version. It also contains a land coupler LCUP which connects some submodels and an atmospheric model. The vegetation submodel SiByl has surface vegetation processes similar to JMA/SiB (Sato et al. 1987, Hirai et al. 2007). SiByl has 2 vegetation layers (canopy and grass) and calculates heat, moisture, and momentum fluxes between the land surface and the atmosphere. The snow submodel SNOWA can have any number of snow layers and the maximum value is set to 8 for the CMIP5 experiments. Temperature, SWE, density, grain size and the aerosol deposition contents of each layer are predicted. The snow properties including the grain size are predicted due to snow metamorphism processes (Niwano et al., 2011), and the snow albedo is diagnosed from the aerosol mixing ratio, the snow properties and the temperature (Aoki et al., 2011). The soil submodel SOILA can also have any number of soil layers, and is composed of 14 soil layers in the CMIP5 experiments. The temperature of each layer is predicted by solving heat conduction equations. The soil moisture is predicted by solving the Darcy equation, in which hydraulic conductivity depends on the soil moisture. The land coupler LCUP is designed to enable the complicated constructions of the submidels. HAL can include some competing submodels (precise and detailed ones, and simpler ones), and they can run at the same simulations. LCUP enables a 2-step model validation, in which we compare the results of the detailed submodels with the in-situ observation directly at the 1st step, and follows the comparison between them and those of the simpler ones at the 2nd step. When the performances of the detailed ones are good, we can improve the simpler ones by using the detailed ones as reference models.

  3. Role of Snow Deposition of Perfluoroalkylated Substances at Coastal Livingston Island (Maritime Antarctica).

    Science.gov (United States)

    Casal, Paulo; Zhang, Yifeng; Martin, Jonathan W; Pizarro, Mariana; Jiménez, Begoña; Dachs, Jordi

    2017-08-01

    Perfluoroalkyl substances (PFAS) are ubiquitous in the environment, including remote polar regions. To evaluate the role of snow deposition as an input of PFAS to Maritime Antarctica, fresh snow deposition, surface snow, streams from melted snow, coastal seawater, and plankton samples were collected over a three-month period (December 2014-February 2015) at Livingston Island. Local sources of PFASs were significant for perfluoroalkyl sulfonates (PFSAs) and C7-14 perfluoroalkyl carboxylates (PFCAs) in snow but limited to the transited areas of the research station. The concentrations of 14 ionizable PFAS (∑PFAS) in freshly deposited snow (760-3600 pg L -1 ) were 1 order of magnitude higher than those in background surface snow (82-430 pg L -1 ). ∑PFAS ranged from 94 to 420 pg L -1 in seawater and from 3.1 to 16 ng g dw -1 in plankton. Ratios of individual PFAS concentrations in freshly deposited snow relative to surface snow (C SD /C Snow ), snowmelt (C SD /C SM ), and seawater (C SD /C SW ) were close to 1 (from 0.44 to 1.4) for all perfluorooctanesulfonate (PFOS) isomers, suggesting that snowfall does not contribute significantly to PFOS in seawater. Conversely, these ratios for PFCAs ranged from 1 to 33 and were positively correlated with the number of carbons in the PFCA alkylated chain. These trends suggest that snow deposition, scavenging sea-salt aerosol bound PFAS, plays a role as a significant input of PFCAs to the Maritime Antarctica.

  4. Wet Snow Mapping in Southern Ontario with Sentinel-1A Observations

    Science.gov (United States)

    Chen, H.; Kelly, R. E. J.

    2017-12-01

    Wet snow is defined as snow with liquid water present in an ice-water mix. It is can be an indicator for the onset of the snowmelt period. Knowledge about the extent of wet snow area can be of great importance for the monitoring of seasonal snowmelt runoff with climate-induced changes in snowmelt duration having implications for operational hydrological and ecological applications. Spaceborne microwave remote sensing has been used to observe seasonal snow under all-weather conditions. Active microwave observations of snow at C-band are sensitive to wet snow due to the high dielectric contrast with non-wet snow surfaces and synthetic aperture radar (SAR) is now openly available to identify and map the wet snow areas globally at relatively fine spatial resolutions ( 100m). In this study, a semi-automated workflow is developed from the change detection method of Nagler et al. (2016) using multi-temporal Sentinel-1A (S1A) dual-polarization observations of Southern Ontario. Weather station data and visible-infrared satellite observations are used to refine the wet snow area estimates. Wet snow information from National Operational Hydrologic Remote Sensing Center (NOHRSC) is used to compare with the S1A estimates. A time series of wet snow maps shows the variations in backscatter from wet snow on a pixel basis. Different land cover types in Southern Ontario are assessed with respect to their impacts on wet snow estimates. While forests and complex land surfaces can impact the ability to map wet snow, the approach taken is robust and illustrates the strong sensitivity of the approach to wet snow backscattering characteristics. The results indicate the feasibility of the change detection method on non-mountainous large areas and address the usefulness of Sentinel-1A data for wet snow mapping.

  5. Bioavailability of mineral-bound iron to a snow algae-bacteria co-culture and implications for albedo-altering snow algae blooms.

    Science.gov (United States)

    Harrold, Z R; Hausrath, E M; Garcia, A H; Murray, A E; Tschauner, O; Raymond, J; Huang, S

    2018-01-26

    Snow algae can form large-scale blooms across the snowpack surface and near-surface environments. These pigmented blooms can decrease snow albedo, increase local melt rates, and may impact the global heat budget and water cycle. Yet, underlying causes for the geospatial occurrence of these blooms remain unconstrained. One possible factor contributing to snow algae blooms is the presence of mineral dust as a micronutrient source. We investigated the bioavailability of iron (Fe) -bearing minerals, including forsterite (Fo 90 , Mg 1.8 Fe 0.2 SiO 4 ), goethite, smectite and pyrite as Fe sources for a Chloromonas brevispina - bacteria co-culture through laboratory-based experimentation. Fo 90 was capable of stimulating snow algal growth and increased the algal growth rate in otherwise Fe-depleted co-cultures. Fo 90 -bearing systems also exhibited a decrease in bacteria:algae ratios compared to Fe-depleted conditions, suggesting a shift in microbial community structure. The C. brevispina co-culture also increased the rate of Fo 90 dissolution relative to an abiotic control. Analysis of 16S rRNA genes in the co-culture identified Gammaproteobacteria , Betaprotoeobacteria and Sphingobacteria , all of which are commonly found in snow and ice environments. Archaea were not detected. Collimonas and Pseudomonas , which are known to enhance mineral weathering rates, comprised two of the top eight (> 1 %) OTUs. These data provide unequivocal evidence that mineral dust can support elevated snow algae growth under otherwise Fe-depleted growth conditions, and that snow algae can enhance mineral dissolution under these conditions. IMPORTANCE Fe, a key micronutrient for photosynthetic growth, is necessary to support the formation of high-density snow algae blooms. The laboratory experiments described herein allow for a systematic investigation of snow algae-bacteria-mineral interactions and their ability to mobilize and uptake mineral-bound Fe. Results provide unequivocal and

  6. Radiative effects of light-absorbing particles deposited in snow over Himalayas using WRF-Chem simulations

    Science.gov (United States)

    Sarangi, C.; Qian, Y.; Painter, T. H.; Liu, Y.; Lin, G.; Wang, H.

    2017-12-01

    Radiative forcing induced by light-absorbing particles (LAP) deposited on snow is an important surface forcing. It has been debated that an aerosol-induced increase in atmospheric and surface warming over Tibetan Plateau (TP) prior to the South Asian summer monsoon can have a significant effect on the regional thermodynamics and South Asian monsoon circulation. However, knowledge about the radiative effects due to deposition of LAP in snow over TP is limited. In this study we have used a high-resolution WRF-Chem (coupled with online chemistry and snow-LAP-radiation model) simulations during 2013-2014 to estimate the spatio-temporal variation in LAP deposition on snow, specifically black carbon (BC) and dust particles, in Himalayas. Simulated distributions in meteorology, aerosol concentrations, snow albedo, snow grain size and snow depth are evaluated against satellite and in-situ measurements. The spatio-temporal change in snow albedo and snow grain size with variation in LAP deposition is investigated and the resulting shortwave LAP radiative forcing at surface is calculated. The LAP-radiative forcing due to aerosol deposition, both BC and dust, is higher in magnitude over Himalayan slopes (terrain height below 4 km) compared to that over TP (terrain height above 4 km). We found that the shortwave aerosol radiative forcing efficiency at surface due to increase in deposited mass of BC particles in snow layer ( 25 (W/m2)/ (mg/m2)) is manifold higher than the efficiency of dust particles ( 0.1 (W/m2)/ (mg/m2)) over TP. However, the radiative forcing of dust deposited in snow is similar in magnitude (maximum 20-30 W/m2) to that of BC deposited in snow over TP. This is mainly because the amount of dust deposited in snow over TP can be about 100 times greater than the amount of BC deposited in snow during polluted conditions. The impact of LAP on surface energy balance, snow melting and atmospheric thermodynamics is also examined.

  7. Sentinels for snow science

    Science.gov (United States)

    Gascoin, S.; Grizonnet, M.; Baba, W. M.; Hagolle, O.; Fayad, A.; Mermoz, S.; Kinnard, C.; Fatima, K.; Jarlan, L.; Hanich, L.

    2017-12-01

    Current spaceborne sensors do not allow retrieving the snow water equivalent in mountain regions, "the most important unsolved problem in snow hydrology" (Dozier, 2016). While the NASA is operating an airborne mission to survey the SWE in the western USA, elsewhere, however, snow scientists and water managers do not have access to routine SWE measurements at the scale of a mountain range. In this presentation we suggest that the advent of the Copernicus Earth Observation programme opens new perspectives to address this issue in mountain regions worldwide. The Sentinel-2 mission will provide global-scale multispectral observations at 20 m resolution every 5-days (cloud permitting). The Sentinel-1 mission is already imaging the global land surface with a C-band radar at 10 m resolution every 6 days. These observations are unprecedented in terms of spatial and temporal resolution. However, the nature of the observation (radiometry, wavelength) is in the continuity of previous and ongoing missions. As a result, it is relatively straightforward to re-use algorithms that were developed by the remote sensing community over the last decades. For instance, Sentinel-2 data can be used to derive maps of the snow cover extent from the normalized difference snow index, which was initially proposed for Landsat. In addition, the 5-days repeat cycle allows the application of gap-filling algorithms, which were developed for MODIS based on the temporal dimension. The Sentinel-1 data can be used to detect the wet snow cover and track melting areas as proposed for ERS in the early 1990's. Eventually, we show an example where Sentinel-2-like data improved the simulation of the SWE in the data-scarce region of the High Atlas in Morocco through assimilation in a distributed snowpack model. We encourage snow scientists to embrace Sentinel-1 and Sentinel-2 data to enhance our knowledge on the snow cover dynamics in mountain regions.

  8. Experimental investigation of ice and snow melting process on pavement utilizing geothermal tail water

    International Nuclear Information System (INIS)

    Wang Huajun; Zhao Jun; Chen Zhihao

    2008-01-01

    Road ice and snow melting based on low temperature geothermal tail water is of significance to realize energy cascading utilization. A small scale ice and snow melting system is built in this work. Experiments of dynamic melting processes of crushed ice, solid ice, artificial snow and natural snow are conducted on concrete pavement. The results show that the melting process of ice and snow includes three phases: a starting period, a linear period and an accelerated period. The critical value of the snow free area ratio between the linear period and the accelerated period is about 0.6. The physical properties of ice and snow, linked with ambient conditions, have an obvious effect on the melting process. The difference of melting velocity and melting time between ice and snow is compared. To reduce energy consumption, the formation of ice on roads should be avoided if possible. The idling process is an effective pathway to improve the performance of melting systems. It is feasible to utilize geothermal tail water of about 40 deg. C for melting ice and snow on winter roads, and it is unnecessary to keep too high fluid temperatures during the practical design and applications. Besides, with the exception of solid ice, the density and porosity of snow and ice tend to be decreasing and increasing, respectively, as the ambient temperature decreases

  9. Northern Alaskan land surface response to reduced Arctic sea ice extent

    Energy Technology Data Exchange (ETDEWEB)

    Higgins, Matthew E. [University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, CO (United States); Cassano, John J. [University of Colorado, Cooperative Institute for Research in Environmental Sciences, Department of Atmospheric and Oceanic Sciences, Boulder, CO (United States)

    2012-05-15

    With Arctic sea ice extent at near-record lows, an improved understanding of the relationship between sea ice and the land surface is warranted. We examine the land surface response to changing sea ice by first conducting a simulation using the Community Atmospheric Model version 3.1 with end of the twenty-first century sea ice extent. This future atmospheric response is then used to force the Weather and Research Forecasting Model version 3.1 to examine the terrestrial land surface response at high resolution over the North Slope of Alaska. Similar control simulations with twentieth century sea ice projections are also performed, and in both simulations only sea ice extent is altered. In the future sea ice extent experiment, atmospheric temperature increases significantly due to increases in latent and sensible heat flux, particularly in the winter season. Precipitation and snow pack increase significantly, and the increased snow pack contributes to warmer soil temperatures for most seasons by insulating the land surface. In the summer, however, soil temperatures are reduced due to increased albedo. Despite warmer near-surface atmospheric temperatures, it is found that spring melt is delayed throughout much of the North Slope due to the increased snow pack, and the growing season length is shortened. (orig.)

  10. User Oriented Climatic Information for Planning a Snow Removal Budget.

    Science.gov (United States)

    Cohen, Stewart J.

    1981-12-01

    Many activities associated with the transportation sector are weather sensitive. This study is concerned with highway maintenance activities, specifically snow removal, and the budgeting of same by the Illinois Department of Transportation (IDOT). During the 1978-79 winter, IDOT's snow removal budget was exhausted by the end of January, thereby necessitating the procurement of emergency funds. The following year, the Illinois State Water Survey (ISWS) was asked to provide specialized climatic design information that could be used to assist IDOT in its budget planning for snow removal.Snow removal is often accomplished by spreading road salt over snow- and ice-covered roads, thus improving traction and reducing the risk of vehicles skidding along slippery surfaces. This study demonstrates the computation of `salt days,' a user-oriented climatic variable that indicates the number of days when road salt is required. This variable is defined using certain temperature and snowfall criteria. Results of a pilot study indicate that it is possible to provide statistical outlooks for salt days two months in advance, using correlation analysis. The analysis for several Illinois stations indicates that at various intervals in the data records, November and December temperatures are significantly correlated with February salt days if short periods of record (5-20 years) are used.IDOT originally requested a `2- to 3-month projection.' However, it became clear that only projections of 12 months or longer could benefit annual budget preparation. Confusion existed between the user and the supplier of climatic information regarding the user's needs, and the applicability of the supplier's `climate products' to the user's budget planning procedure. This demonstrates the need for a prolonged effort by the supplier to fully acquaint the user with the various forms of climatic information available. This gap in communication must be overcome so that applied climatology can be integrated

  11. Facilitating the exploitation of ERTS-1 imagery utilizing snow enhancement techniques

    Science.gov (United States)

    Wobber, F. J. (Principal Investigator); Martin, K. R.; Amato, R. V.

    1973-01-01

    The author has identified the following significant results. Snow cover in combination with low angle solar illumination has been found to provide increased tonal contrast of surface feature and is useful in the detection of bedrock fractures. Identical fracture systems were not as readily detectable in the fall due to the lack of a contrasting surface medium (snow) and a relatively high sun angle. Low angle solar illumination emphasizes topographic expressions not as apparent on imagery acquired with a higher sun angle. A strong correlation exists between the major fracture-lineament directions interpreted from multi-sensor imagery (including snow-free and snow cover ERTS) and the strike of bedrock joints recorded in the field indicating the structural origin of interpreted fracture-lineaments. A fracture-annotated ERTS-1 photo base map (1:250,000 scale) is being prepared for western Massachusetts. The map will document the utilization of ERTS-1 imagery for geological analysis in comparative snow-free and snow-covered terrain.

  12. Role of Marine Snows in Microplastic Fate and Bioavailability.

    Science.gov (United States)

    Porter, Adam; Lyons, Brett P; Galloway, Tamara S; Lewis, Ceri

    2018-06-01

    Microplastics contaminate global oceans and are accumulating in sediments at levels thought sufficient to leave a permanent layer in the fossil record. Despite this, the processes that vertically transport buoyant polymers from surface waters to the benthos are poorly understood. Here we demonstrate that laboratory generated marine snows can transport microplastics of different shapes, sizes, and polymers away from the water surface and enhance their bioavailability to benthic organisms. Sinking rates of all tested microplastics increased when incorporated into snows, with large changes observed for the buoyant polymer polyethylene with an increase in sinking rate of 818 m day -1 and for denser polyamide fragments of 916 m day -1 . Incorporation into snows increased microplastic bioavailability for mussels, where uptake increased from zero to 340 microplastics individual -1 for free microplastics to up to 1.6 × 10 5 microplastics individual -1 when incorporated into snows. We therefore propose that marine snow formation and fate has the potential to play a key role in the biogeochemical processing of microplastic pollution.

  13. Modeling the Physical Multi-Phase Interactions of HNO3 Between Snow and Air on the Antarctic Plateau (Dome C) and coast (Halley)

    Science.gov (United States)

    Chan, Hoi Ga; Frey, Markus M.; King, Martin D.

    2017-04-01

    Nitrogen oxides (NOx = NO + NO2) emissions from nitrate (NO3-) photolysis in snow affect the oxidising capacity of the lower troposphere especially in remote regions of the high latitudes with low pollution levels. The porous structure of snowpack allows the exchange of gases with the atmosphere driven by physicochemical processes, and hence, snow can act as both source and sink of atmospheric chemical trace gases. Current models are limited by poor process understanding and often require tuning parameters. Here, two multi-phase physical models were developed from first principles constrained by observed atmospheric nitrate, HNO3, to describe the air-snow interaction of nitrate. Similar to most of the previous approaches, the first model assumes that below a threshold temperature, To, the air-snow grain interface is pure ice and above To, a disordered interface (DI) emerges assumed to be covering the entire grain surface. The second model assumes that Air-Ice interactions dominate over the entire temperature range below melting and that only above the eutectic temperature, liquid is present in the form of micropockets in grooves. The models are validated with available year-round observations of nitrate in snow and air at a cold site on the Antarctica Plateau (Dome C, 75°06'S, 123°33'E, 3233 m a.s.l.) and at a relatively warm site on the Antarctica coast (Halley, 75°35'S, 26°39'E, 35 m a.s.l). The first model agrees reasonably well with observations at Dome C (Cv(RMSE) = 1.34), but performs poorly at Halley (Cv(RMSE) = 89.28) while the second model reproduces with good agreement observations at both sites without any tuning (Cv(RMSE) = 0.84 at both sites). It is therefore suggested that air-snow interactions of nitrate in the winter are determined by non-equilibrium surface adsorption and co-condensation on ice coupled with solid-state diffusion inside the grain. In summer, however, the air-snow exchange of nitrate is mainly driven by solvation into liquid

  14. Role of nitrite in the photochemical formation of radicals in the snow.

    Science.gov (United States)

    Jacobi, Hans-Werner; Kleffmann, Jörg; Villena, Guillermo; Wiesen, Peter; King, Martin; France, James; Anastasio, Cort; Staebler, Ralf

    2014-01-01

    Photochemical reactions in snow can have an important impact on the composition of the atmosphere over snow-covered areas as well as on the composition of the snow itself. One of the major photochemical processes is the photolysis of nitrate leading to the formation of volatile nitrogen compounds. We report nitrite concentrations determined together with nitrate and hydrogen peroxide in surface snow collected at the coastal site of Barrow, Alaska. The results demonstrate that nitrite likely plays a significant role as a precursor for reactive hydroxyl radicals as well as volatile nitrogen oxides in the snow. Pollution events leading to high concentrations of nitrous acid in the atmosphere contributed to an observed increase in nitrite in the surface snow layer during nighttime. Observed daytime nitrite concentrations are much higher than values predicted from steady-state concentrations based on photolysis of nitrate and nitrite indicating that we do not fully understand the production of nitrite and nitrous acid in snow. The discrepancy between observed and expected nitrite concentrations is probably due to a combination of factors, including an incomplete understanding of the reactive environment and chemical processes in snow, and a lack of consideration of the vertical structure of snow.

  15. Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

    Science.gov (United States)

    Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

    2017-06-01

    Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

  16. EXTASE - An Experimental Thermal Probe for Applications in Snow Research and Earth Sciences

    Science.gov (United States)

    Schroeer, K.; Seiferlin, K.; Marczewski, W.; Gadomski, S.; Spohn, T.

    2002-12-01

    EXTASE is a spin-off project from the Rosetta Lander (MUPUS) thermal probe, funded by DLR. The application of this probe is to be tested in different fields, e.g. in snow research, agriculture, permafrost etc. The system consists of the probe itself with a portable field electronic and a computer for control of the system and storage of the data. The probe penetrates the surface ca. 32 cm deep and provides a temperature profile (16 sensors) and thermal conductivity profile of the penetrated layer. The main advantages of the probe in comparison to common temperature profile measurement methods are: - no need to excavate material - minimized influence of the probe on the temperature field - minimized modification of the microstructure of the studied medium. Presently we are concentrating on agriculture (soil humidity) and snow research. Further applications could be e.g.: monitoring waste deposits and the heat released by decomposition, volcanology and ground truth for remote sensing. We present the general concept of the probe and also data obtained during different field measurement campaigns with prototypes of the probe.

  17. Granulation of snow: From tumbler experiments to discrete element simulations

    Science.gov (United States)

    Steinkogler, Walter; Gaume, Johan; Löwe, Henning; Sovilla, Betty; Lehning, Michael

    2015-06-01

    It is well known that snow avalanches exhibit granulation phenomena, i.e., the formation of large and apparently stable snow granules during the flow. The size distribution of the granules has an influence on flow behavior which, in turn, affects runout distances and avalanche velocities. The underlying mechanisms of granule formation are notoriously difficult to investigate within large-scale field experiments, due to limitations in the scope for measuring temperatures, velocities, and size distributions. To address this issue we present experiments with a concrete tumbler, which provide an appropriate means to investigate granule formation of snow. In a set of experiments at constant rotation velocity with varying temperatures and water content, we demonstrate that temperature has a major impact on the formation of granules. The experiments showed that granules only formed when the snow temperature exceeded -1∘C. No evolution in the granule size was observed at colder temperatures. Depending on the conditions, different granulation regimes are obtained, which are qualitatively classified according to their persistence and size distribution. The potential of granulation of snow in a tumbler is further demonstrated by showing that generic features of the experiments can be reproduced by cohesive discrete element simulations. The proposed discrete element model mimics the competition between cohesive forces, which promote aggregation, and impact forces, which induce fragmentation, and supports the interpretation of the granule regime classification obtained from the tumbler experiments. Generalizations, implications for flow dynamics, and experimental and model limitations as well as suggestions for future work are discussed.

  18. Enhanced hemispheric-scale snow mapping through the blending of optical and microwave satellite data

    Science.gov (United States)

    Armstrong, R. L.; Brodzik, M. J.; Savoie, M.; Knowles, K.

    2003-04-01

    Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. Global snow cover fluctuation can now be monitored over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere weekly snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Decadal trends and their significance are compared for the two data types. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as throughout the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the

  19. Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

    Science.gov (United States)

    Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

    2014-12-01

    Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

  20. Simulating polarized light scattering in terrestrial snow based on bicontinuous random medium and Monte Carlo ray tracing

    International Nuclear Information System (INIS)

    Xiong, Chuan; Shi, Jiancheng

    2014-01-01

    To date, the light scattering models of snow consider very little about the real snow microstructures. The ideal spherical or other single shaped particle assumptions in previous snow light scattering models can cause error in light scattering modeling of snow and further cause errors in remote sensing inversion algorithms. This paper tries to build up a snow polarized reflectance model based on bicontinuous medium, with which the real snow microstructure is considered. The accurate specific surface area of bicontinuous medium can be analytically derived. The polarized Monte Carlo ray tracing technique is applied to the computer generated bicontinuous medium. With proper algorithms, the snow surface albedo, bidirectional reflectance distribution function (BRDF) and polarized BRDF can be simulated. The validation of model predicted spectral albedo and bidirectional reflectance factor (BRF) using experiment data shows good results. The relationship between snow surface albedo and snow specific surface area (SSA) were predicted, and this relationship can be used for future improvement of snow specific surface area (SSA) inversion algorithms. The model predicted polarized reflectance is validated and proved accurate, which can be further applied in polarized remote sensing. -- Highlights: • Bicontinuous random medium were used for real snow microstructure modeling. • Photon tracing technique with polarization status tracking ability was applied. • SSA–albedo relationship of snow is close to that of sphere based medium. • Validation of albedo and BRDF showed good results. • Validation of polarized reflectance showed good agreement with experiment data

  1. Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

    Science.gov (United States)

    Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

    2015-01-01

    Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

  2. New Perspectives on Blowing Snow Transport, Sublimation, and Layer Thermodynamic Structure over Antarctica

    Science.gov (United States)

    Palm, Steve; Kayetha, Vinay; Yang, Yuekui; Pauly, Rebecca M.

    2017-01-01

    Blowing snow over Antarctica is a widespread and frequent event. Satellite remote sensing using lidar has shown that blowing snow occurs over 70% of the time over large areas of Antarctica in winter. The transport and sublimation of blowing snow are important terms in the ice sheet mass balance equation and the latter is also an important part of the hydrological cycle. Until now the only way to estimate the magnitude of these processes was through model parameterization. We present a technique that uses direct satellite observations of blowing snow and model (MERRA-2) temperature and humidity fields to compute both transport and sublimation of blowing snow over Antarctica for the period 2006 to 2016. The results show a larger annual continent-wide integrated sublimation than current published estimates and a significant transport of snow from continent to ocean. The talk will also include the lidar backscatter structure of blowing snow layers that often reach heights of 200 to 300 m as well as the first dropsonde measurements of temperature, moisture and wind through blowing snow layers.

  3. Annual Greenland Accumulation Rates (2009-2012) from Airborne Snow Radar

    Science.gov (United States)

    Koenig, Lora S.; Ivanoff, Alvaro; Alexander, Patrick M.; MacGregor, Joseph A.; Fettweis, Xavier; Panzer, Ben; Paden, John D.; Forster, Richard R.; Das, Indrani; McConnell, Joseph R.; hide

    2016-01-01

    Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor its surface mass balance in order to improve sea-level rise predictions. Snow accumulation is the largest component of the ice sheet's surface mass balance, but in situ observations thereof are inherently sparse and models are difficult to evaluate at large scales. Here, we quantify recent Greenland accumulation rates using ultra-wideband (2-6.5 gigahertz) airborne snow radar data collected as part of NASA's Operation IceBridge between 2009 and 2012. We use a semi-automated method to trace the observed radiostratigraphy and then derive annual net accumulation rates for 2009-2012. The uncertainty in these radar-derived accumulation rates is on average 14 percent. A comparison of the radarderived accumulation rates and contemporaneous ice cores shows that snow radar captures both the annual and longterm mean accumulation rate accurately. A comparison with outputs from a regional climate model (MAR - Modele Atmospherique Regional for Greenland and vicinity) shows that this model matches radar-derived accumulation rates in the ice sheet interior but produces higher values over southeastern Greenland. Our results demonstrate that snow radar can efficiently and accurately map patterns of snow accumulation across an ice sheet and that it is valuable for evaluating the accuracy of surface mass balance models.

  4. Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

    Science.gov (United States)

    Forman, Bart; Reichle, Rofl; Rodell, Matt

    2011-01-01

    Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

  5. Time budgets of Snow Geese Chen caerulescens and Ross's Geese Chen rossii in mixed flocks: Implications of body size, ambient temperature and family associations

    Science.gov (United States)

    Jonsson, J.E.; Afton, A.D.

    2009-01-01

    Body size affects foraging and forage intake rates directly via energetic processes and indirectly through interactions with social status and social behaviour. Ambient temperature has a relatively greater effect on the energetics of smaller species, which also generally are more vulnerable to predator attacks than are larger species. We examined variability in an index of intake rates and an index of alertness in Lesser Snow Geese Chen caerulescens caerulescens and Ross's Geese Chen rossii wintering in southwest Louisiana. Specifically we examined variation in these response variables that could be attributed to species, age, family size and ambient temperature. We hypothesized that the smaller Ross's Geese would spend relatively more time feeding, exhibit relatively higher peck rates, spend more time alert or raise their heads up from feeding more frequently, and would respond to declining temperatures by increasing their proportion of time spent feeding. As predicted, we found that Ross's Geese spent more time feeding than did Snow Geese and had slightly higher peck rates than Snow Geese in one of two winters. Ross's Geese spent more time alert than did Snow Geese in one winter, but alert rates differed by family size, independent of species, in contrast to our prediction. In one winter, time spent foraging and walking was inversely related to average daily temperature, but both varied independently of species. Effects of age and family size on time budgets were generally independent of species and in accordance with previous studies. We conclude that body size is a key variable influencing time spent feeding in Ross's Geese, which may require a high time spent feeding at the expense of other activities. ?? 2008 The Authors.

  6. Summer monsoon rainfall variability over North East regions of India and its association with Eurasian snow, Atlantic Sea Surface temperature and Arctic Oscillation

    Science.gov (United States)

    Prabhu, Amita; Oh, Jaiho; Kim, In-won; Kripalani, R. H.; Mitra, A. K.; Pandithurai, G.

    2017-10-01

    This observational study during the 29-year period from 1979 to 2007 evaluates the potential role of Eurasian snow in modulating the North East-Indian Summer Monsoon Rainfall with a lead time of almost 6 months. This link is manifested by the changes in high-latitude atmospheric winter snow variability over Eurasia associated with Arctic Oscillation (AO). Excessive wintertime Eurasian snow leads to an anomalous cooling of the overlying atmosphere and is associated with the negative mode of AO, inducing a meridional wave-train descending over the tropical north Atlantic and is associated with cooling of this region. Once the cold anomalies are established over the tropical Atlantic, it persists up to the following summer leading to an anomalous zonal wave-train further inducing a descending branch over NE-India resulting in weak summer monsoon rainfall.

  7. Microbial Community Analysis of Colored Snow from an Alpine Snowfield in Northern Japan Reveals the Prevalence of Betaproteobacteria with Snow Algae.

    Science.gov (United States)

    Terashima, Mia; Umezawa, Kazuhiro; Mori, Shoichi; Kojima, Hisaya; Fukui, Manabu

    2017-01-01

    Psychrophilic algae blooms can be observed coloring the snow during the melt season in alpine snowfields. These algae are important primary producers on the snow surface environment, supporting the microbial community that coexists with algae, which includes heterotrophic bacteria and fungi. In this study, we analyzed the microbial community of green and red-colored snow containing algae from Mount Asahi, Japan. We found that Chloromonas spp. are the dominant algae in all samples analyzed, and Chlamydomonas is the second-most abundant genus in the red snow. For the bacterial community profile, species belonging to the subphylum Betaproteobacteria were frequently detected in both green and red snow, while members of the phylum Bacteroidetes were also prominent in red snow. Furthermore, multiple independently obtained strains of Chloromonas sp. from inoculates of red snow resulted in the growth of Betaproteobacteria with the alga and the presence of bacteria appears to support growth of the xenic algal cultures under laboratory conditions. The dominance of Betaproteobacteria in algae-containing snow in combination with the detection of Chloromonas sp. with Betaproteobacteria strains suggest that these bacteria can utilize the available carbon source in algae-rich environments and may in turn promote algal growth.

  8. Suppression of the water ice and snow albedo feedback on planets orbiting red dwarf stars and the subsequent widening of the habitable zone.

    Science.gov (United States)

    Joshi, Manoj M; Haberle, Robert M

    2012-01-01

    M stars comprise 80% of main sequence stars, so their planetary systems provide the best chance for finding habitable planets, that is, those with surface liquid water. We have modeled the broadband albedo or reflectivity of water ice and snow for simulated planetary surfaces orbiting two observed red dwarf stars (or M stars), using spectrally resolved data of Earth's cryosphere. The gradual reduction of the albedos of snow and ice at wavelengths greater than 1 μm, combined with M stars emitting a significant fraction of their radiation at these same longer wavelengths, means that the albedos of ice and snow on planets orbiting M stars are much lower than their values on Earth. Our results imply that the ice/snow albedo climate feedback is significantly weaker for planets orbiting M stars than for planets orbiting G-type stars such as the Sun. In addition, planets with significant ice and snow cover will have significantly higher surface temperatures for a given stellar flux if the spectral variation of cryospheric albedo is considered, which in turn implies that the outer edge of the habitable zone around M stars may be 10-30% farther away from the parent star than previously thought.

  9. Feedback mechanisms between snow and atmospheric mercury: Results and observations from field campaigns on the Antarctic plateau.

    Science.gov (United States)

    Spolaor, Andrea; Angot, Hélène; Roman, Marco; Dommergue, Aurélien; Scarchilli, Claudio; Vardè, Massimiliano; Del Guasta, Massimo; Pedeli, Xanthi; Varin, Cristiano; Sprovieri, Francesca; Magand, Olivier; Legrand, Michel; Barbante, Carlo; Cairns, Warren R L

    2018-04-01

    The Antarctic Plateau snowpack is an important environment for the mercury geochemical cycle. We have extensively characterized and compared the changes in surface snow and atmospheric mercury concentrations that occur at Dome C. Three summer sampling campaigns were conducted between 2013 and 2016. The three campaigns had different meteorological conditions that significantly affected mercury deposition processes and its abundance in surface snow. In the absence of snow deposition events, the surface mercury concentration remained stable with narrow oscillations, while an increase in precipitation results in a higher mercury variability. The Hg concentrations detected confirm that snowfall can act as a mercury atmospheric scavenger. A high temporal resolution sampling experiment showed that surface concentration changes are connected with the diurnal solar radiation cycle. Mercury in surface snow is highly dynamic and it could decrease by up to 90% within 4/6 h. A negative relationship between surface snow mercury and atmospheric concentrations has been detected suggesting a mutual dynamic exchange between these two environments. Mercury concentrations were also compared with the Br concentrations in surface and deeper snow, results suggest that Br could have an active role in Hg deposition, particularly when air masses are from coastal areas. This research presents new information on the presence of Hg in surface and deeper snow layers, improving our understanding of atmospheric Hg deposition to the snow surface and the possible role of re-emission on the atmospheric Hg concentration. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

    Science.gov (United States)

    Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

    2018-04-01

    The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their

  11. High-resolution LIDAR and ground observations of snow cover in a complex forested terrain in the Sierra Nevada - implications for optical remote sensing of seasonal snow.

    Science.gov (United States)

    Kostadinov, T. S.; Harpold, A.; Hill, R.; McGwire, K.

    2017-12-01

    Seasonal snow cover is a key component of the hydrologic regime in many regions of the world, especially those in temperate latitudes with mountainous terrain and dry summers. Such regions support large human populations which depend on the mountain snowpack for their water supplies. It is thus important to quantify snow cover accurately and continuously in these regions. Optical remote-sensing methods are able to detect snow and leverage space-borne spectroradiometers with global coverage such as MODIS to produce global snow cover maps. However, snow is harder to detect accurately in mountainous forested terrain, where topography influences retrieval algorithms, and importantly - forest canopies complicate radiative transfer and obfuscate the snow. Current satellite snow cover algorithms assume that fractional snow-covered area (fSCA) under the canopy is the same as the fSCA in the visible portion of the pixel. In-situ observations and first principles considerations indicate otherwise, therefore there is a need for improvement of the under-canopy correction of snow cover. Here, we leverage multiple LIDAR overflights and in-situ observations with a distributed fiber-optic temperature sensor (DTS) to quantify snow cover under canopy as opposed to gap areas at the Sagehen Experimental Forest in the Northern Sierra Nevada, California, USA. Snow-off LIDAR overflights from 2014 are used to create a baseline high-resolution digital elevation model and classify pixels at 1 m resolution as canopy-covered or gap. Low canopy pixels are excluded from the analysis. Snow-on LIDAR overflights conducted by the Airborne Snow Observatory in 2016 are then used to classify all pixels as snow-covered or not and quantify fSCA under canopies vs. in gap areas over the Sagehen watershed. DTS observations are classified as snow-covered or not based on diel temperature fluctuations and used as validation for the LIDAR observations. LIDAR- and DTS-derived fSCA is also compared with

  12. Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

    Science.gov (United States)

    Langlois, A.; Royer, A.; Derksen, C.; Montpetit, B.; Dupont, F.; GoïTa, K.

    2012-12-01

    Satellite-passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two-step iteration method compared to standalone simulations with the snow model.

  13. Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

    NARCIS (Netherlands)

    Stigter, Emmy E.; Wanders, Niko; Saloranta, Tuomo M.; Shea, Joseph M.; Bierkens, M.F.P.; Immerzeel, W.W.

    2017-01-01

    Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water

  14. Changes in Andes snow cover from MODIS data, 2000-2016

    Science.gov (United States)

    Saavedra, Freddy A.; Kampf, Stephanie K.; Fassnacht, Steven R.; Sibold, Jason S.

    2018-03-01

    The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36° S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann-Kendall and Theil-Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño-Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29° S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36° S experienced a significant loss of snow cover (2-5 fewer days of snow year-1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10-30 m year-1 south of 29-30° S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31° S, whereas the SAM better predicted SP south of 31° S.

  15. Snow as a habitat for microorganisms

    Science.gov (United States)

    Hoham, Ronald W.

    1989-01-01

    There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked.

  16. A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model

    Directory of Open Access Journals (Sweden)

    S. Kolberg

    2006-01-01

    Full Text Available A method for assimilating remotely sensed snow covered area (SCA into the snow subroutine of a grid distributed precipitation-runoff model (PRM is presented. The PRM is assumed to simulate the snow state in each grid cell by a snow depletion curve (SDC, which relates that cell's SCA to its snow cover mass balance. The assimilation is based on Bayes' theorem, which requires a joint prior distribution of the SDC variables in all the grid cells. In this paper we propose a spatial model for this prior distribution, and include similarities and dependencies among the grid cells. Used to represent the PRM simulated snow cover state, our joint prior model regards two elevation gradients and a degree-day factor as global variables, rather than describing their effect separately for each cell. This transformation results in smooth normalised surfaces for the two related mass balance variables, supporting a strong inter-cell dependency in their joint prior model. The global features and spatial interdependency in the prior model cause each SCA observation to provide information for many grid cells. The spatial approach similarly facilitates the utilisation of observed discharge. Assimilation of SCA data using the proposed spatial model is evaluated in a 2400 km2 mountainous region in central Norway (61° N, 9° E, based on two Landsat 7 ETM+ images generalized to 1 km2 resolution. An image acquired on 11 May, a week before the peak flood, removes 78% of the variance in the remaining snow storage. Even an image from 4 May, less than a week after the melt onset, reduces this variance by 53%. These results are largely improved compared to a cell-by-cell independent assimilation routine previously reported. Including observed discharge in the updating information improves the 4 May results, but has weak effect on 11 May. Estimated elevation gradients are shown to be sensitive to informational deficits occurring at high altitude, where snowmelt has not started

  17. Snow Water Equivalent SAR and Radiometer

    Data.gov (United States)

    National Aeronautics and Space Administration — After nearly four decades of international effort developing remote sensing techniques, measurement of land surface snow remains a significant challenge. Developing...

  18. Variability in snow depth time series in the Adige catchment

    Directory of Open Access Journals (Sweden)

    Giorgia Marcolini

    2017-10-01

    New hydrological insights for the region: Stations located above and below 1650 m a.s.l. show different dynamics, with the latter experiencing in the last decades a larger reduction of average snow depth and snow cover duration, than the former. Wavelet analyses show that snow dynamics change with elevation and correlate differently with climatic indices at multiple temporal scales. We also observe that starting from the late 1980s snow cover duration and mean seasonal snow depth are below the average in the study area. We also identify an elevation dependent correlation with the temperature. Moreover, correlation with the Mediterranean Oscillation Index and with the North Atlantic Oscillation Index is identified.

  19. Developing an A Priori Database for Passive Microwave Snow Water Retrievals Over Ocean

    Science.gov (United States)

    Yin, Mengtao; Liu, Guosheng

    2017-12-01

    A physically optimized a priori database is developed for Global Precipitation Measurement Microwave Imager (GMI) snow water retrievals over ocean. The initial snow water content profiles are derived from CloudSat Cloud Profiling Radar (CPR) measurements. A radiative transfer model in which the single-scattering properties of nonspherical snowflakes are based on the discrete dipole approximate results is employed to simulate brightness temperatures and their gradients. Snow water content profiles are then optimized through a one-dimensional variational (1D-Var) method. The standard deviations of the difference between observed and simulated brightness temperatures are in a similar magnitude to the observation errors defined for observation error covariance matrix after the 1D-Var optimization, indicating that this variational method is successful. This optimized database is applied in a Bayesian retrieval snow water algorithm. The retrieval results indicated that the 1D-Var approach has a positive impact on the GMI retrieved snow water content profiles by improving the physical consistency between snow water content profiles and observed brightness temperatures. Global distribution of snow water contents retrieved from the a priori database is compared with CloudSat CPR estimates. Results showed that the two estimates have a similar pattern of global distribution, and the difference of their global means is small. In addition, we investigate the impact of using physical parameters to subset the database on snow water retrievals. It is shown that using total precipitable water to subset the database with 1D-Var optimization is beneficial for snow water retrievals.

  20. Modeling the influence of snow cover on low Arctic net ecosystem exchange

    International Nuclear Information System (INIS)

    Luus, K A; Kelly, R E J; Lin, J C; Humphreys, E R; Lafleur, P M; Oechel, W C

    2013-01-01

    The Arctic net ecosystem exchange (NEE) of CO 2 between the land surface and the atmosphere is influenced by the timing of snow onset and melt. The objective of this study was to examine whether uncertainty in model estimates of NEE could be reduced by representing the influence of snow on NEE using remote sensing observations of snow cover area (SCA). Observations of NEE and time-lapse images of SCA were collected over four locations at a low Arctic site (Daring Lake, NWT) in May–June 2010. Analysis of these observations indicated that SCA influences NEE, and that good agreement exists between SCA derived from time-lapse images, Landsat and MODIS. MODIS SCA was therefore incorporated into the vegetation photosynthesis respiration model (VPRM). VPRM was calibrated using observations collected in 2005 at Daring Lake. Estimates of NEE were then generated over Daring Lake and Ivotuk, Alaska (2004–2007) using VPRM formulations with and without explicit representations of the influence of SCA on respiration and/or photosynthesis. Model performance was assessed by comparing VPRM output against unfilled eddy covariance observations from Daring Lake and Ivotuk (2004–2007). The uncertainty in VPRM estimates of NEE was reduced when respiration was estimated as a function of air temperature when SCA ≤ 50% and as a function of soil temperature when SCA > 50%. (letter)

  1. A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

    Science.gov (United States)

    Radkevich, Alexander; Khlopenkov, Konstantin; Rutan, David; Kato, Seiji

    2013-01-01

    Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

  2. The importance of snow albedo for ice sheet evolution over the last glacial cycle

    Directory of Open Access Journals (Sweden)

    M. Willeit

    2018-05-01

    Full Text Available The surface energy and mass balance of ice sheets strongly depends on the amount of solar radiation absorbed at the surface, which is mainly controlled by the albedo of snow and ice. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the representation of snow albedo in the model. It is well known that the albedo of snow depends strongly on snow grain size and the content of light-absorbing impurities. Excluding either the snow aging effect or the dust darkening effect on snow albedo leads to an excessive ice build-up during glacial times and consequently to a failure in simulating deglaciation. While the effect of snow grain growth on snow albedo is well constrained, the albedo reduction due to the presence of dust in snow is much more uncertain because the light-absorbing properties of dust vary widely as a function of dust mineral composition. We also show that assuming slightly different optical properties of dust leads to very different ice sheet and climate evolutions in the model. Conversely, ice sheet evolution is less sensitive to the choice of ice albedo in the model. We conclude that a proper representation of snow albedo is a fundamental prerequisite for a successful simulation of glacial cycles.

  3. Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

    Science.gov (United States)

    Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.; hide

    1993-01-01

    The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17-22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

  4. High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

    Science.gov (United States)

    Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

    2017-12-01

    Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential

  5. Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming

    Science.gov (United States)

    Sexstone, Graham A.; Clow, David W.; Fassnacht, Steven R.; Liston, Glen E.; Hiemstra, Christopher A.; Knowles, John F.; Penn, Colin A.

    2018-01-01

    Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process‐based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio‐temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle‐induced forest mortality and climate warming across the north‐central Colorado Rocky Mountains. EC‐based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub‐canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark‐beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

  6. Central Asian supra-glacier snow melt enhanced by anthropogenic black carbon

    Science.gov (United States)

    Schmale, Julia; Flanner, Mark; Kang, Shichang; Sprenger, Michael; Farinotti, Daniel; Zhang, Qianggong; Guo, Junming; Li, Yang; Lawrence, Mark; Schwikowski, Margit

    2016-04-01

    In Central Asia, more than 60 % of the population depends on water stored in glaciers and mountain snow. Densely populated areas near lower-lying mountain ranges are particularly vulnerable and a recent study showed that the region might lose 50 % of its glacier mass by 2050. While temperature, precipitation and dynamic processes are key drivers of glacial change, deposition of light absorbing impurities such as mineral dust and black carbon can lead to accelerated melting through surface albedo reduction. Here, we discuss the origin of deposited mineral dust and black carbon and their impacts on albedo change and snow melt. 218 snow samples were taken on 4 glaciers, Abramov (Pamir), Suek, Glacier No. 354 and Golubin (Tien Shan), representing deposition between summer 2012 and 2014. They were analyzed for elemental carbon, mineral dust and iron among other parameters. We find the elemental carbon concentration to be at the higher end of the range reported for neighboring mountain ranges between 70 and 502 ng g-1 (interquartile range). To investigate the origin of the snow impurities, we used a Lagrangian particle dispersion model, LAGRANTO. Back trajectory ensembles of 40 members with varied starting points to capture the meteorological spread were released every 6 hours for the covered period at all sites. "Footprints" were calculated and combined with emission inventories to estimate the relative contribution of anthropogenic and natural BC to deposited aerosol on the glaciers. We find that more than 94 % of BC is of anthropogenic origin and the major source region is Central Asia followed by the Middle East. Further exploring the implications of mineral dust and BC deposition, we calculate the snow albedo reduction with the Snow-Ice-Aerosol-Radiative model (SNICAR). Even though mineral dust concentrations were up to a factor of 50 higher than BC concentrations, BC dominates the albedo reduction. Using these results we calculate the snow melt induced by

  7. Inverse analysis of inner surface temperature history from outer surface temperature measurement of a pipe

    International Nuclear Information System (INIS)

    Kubo, S; Ioka, S; Onchi, S; Matsumoto, Y

    2010-01-01

    When slug flow runs through a pipe, nonuniform and time-varying thermal stresses develop and there is a possibility that thermal fatigue occurs. Therefore it is necessary to know the temperature distributions and the stress distributions in the pipe for the integrity assessment of the pipe. It is, however, difficult to measure the inner surface temperature directly. Therefore establishment of the estimation method of the temperature history on inner surface of pipe is needed. As a basic study on the estimation method of the temperature history on the inner surface of a pipe with slug flow, this paper presents an estimation method of the temperature on the inner surface of a plate from the temperature on the outer surface. The relationship between the temperature history on the outer surface and the inner surface is obtained analytically. Using the results of the mathematical analysis, the inverse analysis method of the inner surface temperature history estimation from the outer surface temperature history is proposed. It is found that the inner surface temperature history can be estimated from the outer surface temperature history by applying the inverse analysis method, even when it is expressed by the multiple frequency components.

  8. Validation of MODIS snow cover images over Austria

    Directory of Open Access Journals (Sweden)

    J. Parajka

    2006-01-01

    Full Text Available This study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product over the territory of Austria. The aims are (a to analyse the spatial and temporal variability of the MODIS snow product classes, (b to examine the accuracy of the MODIS snow product against in situ snow depth data, and (c to identify the main factors that may influence the MODIS classification accuracy. We use daily MODIS grid maps (version 4 and daily snow depth measurements at 754 climate stations in the period from February 2000 to December 2005. The results indicate that, on average, clouds obscured 63% of Austria, which may significantly restrict the applicability of the MODIS snow cover images to hydrological modelling. On cloud-free days, however, the classification accuracy is very good with an average of 95%. There is no consistent relationship between the classification errors and dominant land cover type and local topographical variability but there are clear seasonal patterns to the errors. In December and January the errors are around 15% while in summer they are less than 1%. This seasonal pattern is related to the overall percentage of snow cover in Austria, although in spring, when there is a well developed snow pack, errors tend to be smaller than they are in early winter for the same overall percent snow cover. Overestimation and underestimation errors balance during most of the year which indicates little bias. In November and December, however, there appears to exist a tendency for overestimation. Part of the errors may be related to the temporal shift between the in situ snow depth measurements (07:00 a.m. and the MODIS acquisition time (early afternoon. The comparison of daily air temperature maps with MODIS snow cover images indicates that almost all MODIS overestimation errors are caused by the misclassification of cirrus clouds as snow.

  9. Breeding snow: an instrumented sample holder for simultaneous tomographic and thermal studies

    International Nuclear Information System (INIS)

    Pinzer, B; Schneebeli, M

    2009-01-01

    To study the recrystallization processes during temperature gradient metamorphism of snow, we developed a sample holder that allows applying well-defined and stable thermal gradients to a snow sample while it is scanned in an x-ray micro-tomograph. To this end, both the thermal insulation of the sample as well as image contrast and resolution of the tomography had to be optimized. We solved this conflict by using thin aluminum cylinders in combination with highly insulating foam. This design is light, does not corrupt image quality and provides very good thermal decoupling from the environment. The sample holder was instrumented to measure the effective conductivity of the snow sample and calibrated using five materials of known conductivity. Finite element simulations were consistent with the calibration measurements and gave insight into the internal temperature and heat flux fields. With this setup, geometric and thermal evolution of snow under realistic thermal boundary conditions like alternating temperature gradients can be measured

  10. How autumn Eurasian snow anomalies affect east asian winter monsoon: a numerical study

    Science.gov (United States)

    Luo, Xiao; Wang, Bin

    2018-03-01

    Previous studies have found that snow Eurasian anomalies in autumn can affect East Asian winter monsoon (EAWM), but the mechanisms remain controversial and not well understood. The possible mechanisms by which Eurasian autumn snow anomalies affect EAWM are investigated by numerical experiments with a coupled general circulation model and its atmospheric general circulation model component. The leading empirical orthogonal function mode of the October-November mean Eurasian snow cover is characterized by a uniform anomaly over a broad region of central Eurasia (40°N-65°N, 60°E-140°E). However, the results from a 150-ensemble mean simulation with snow depth anomaly specified in October and November reveal that the Mongolian Plateau and Vicinity (MPV, 40°-55°N, 80°-120°E) is the key region for autumn snow anomalies to affect EAWM. The excessive snow forcing can significantly enhance EAWM and the snowfall over the northwestern China and along the EAWM front zone stretching from the southeast China to Japan. The physical process involves a snow-monsoon feedback mechanism. The excessive autumn snow anomalies over the MPV region can persist into the following winter, and significantly enhance winter snow anomalies, which increase surface albedo, reduce incoming solar radiation and cool the boundary layer air, leading to an enhanced Mongolian High and a deepened East Asian trough. The latter, in turn, strengthen surface northwesterly winds, cooling East Asia and increasing snow accumulation over the MPV region and the southeastern China. The increased snow covers feedback to EAWM system through changing albedo, extending its influence southeastward. It is also found that the atmosphere-ocean coupling process can amplify the delayed influence of Eurasian snow mass anomaly on EAWM. The autumn surface albedo anomalies, however, do not have a lasting "memory" effect. Only if the albedo anomalies are artificially extended into December and January, will the EAWM be

  11. Snow and ice: Chapter 3

    Science.gov (United States)

    Littell, Jeremy; McAfee, Stephanie A.; O'Neel, Shad; Sass, Louis; Burgess, Evan; Colt, Steve; Clark, Paul; Hayward, Gregory D.; Colt, Steve; McTeague, Monica L.; Hollingsworth, Teresa N.

    2017-01-01

    Temperature and precipitation are key determinants of snowpack levels. Therefore, climate change is likely to affect the role of snow and ice in the landscapes and hydrology of the Chugach National Forest region.Downscaled climate projections developed by Scenarios Network for Alaska and Arctic Planning (SNAP) are useful for examining projected changes in snow at relatively fine resolution using a variable called “snowday fraction (SDF),” the percentage of days with precipitation falling as snow.We summarized SNAP monthly SDF from five different global climate models for the Chugach region by 500 m elevation bands, and compared historical (1971–2000) and future (2030–2059) SDF. We found that:Snow-day fraction and snow-water equivalent (SWE) are projected to decline most in late autumn (October to November) and at lower elevations.Snow-day fraction is projected to decrease 23 percent (averaged across five climate models) from October to March, between sea level and 500 m. Between sea level and 1000 m, SDF is projected to decrease by 17 percent between October and March.Snow-water equivalent is projected to decrease most in autumn (October and November) and at lower elevations (below 1500 m), an average of -26 percent for the 2030–2059 period compared to 1971– 2000. Averaged across the cool season and the entire domain, SWE is projected to decrease at elevations below 1000 m because of increased temperature, but increase at higher elevations because of increased precipitation.Compared to 1971–2000, the percentage of the landscape that is snowdominant in 2030–2059 is projected to decrease, and the percentage in which rain and snow are co-dominant (transient hydrology) is projected to increase from 27 to 37 percent. Most of this change is at lower elevations.Glaciers on the Chugach National Forest are currently losing about 6 km3 of ice per year; half of this loss comes from Columbia Glacier (Berthier et al. 2010).Over the past decade, almost all

  12. Evaluation of Surface Fatigue Strength Based on Surface Temperature

    Science.gov (United States)

    Deng, Gang; Nakanishi, Tsutomu

    Surface temperature is considered to be an integrated index that is dependent on not only the load and the dimensions at the contact point but also the sliding velocity, rolling velocity, surface roughness, and lubrication conditions. Therefore, the surface durability of rollers and gears can be evaluated more exactly and simply by the use of surface temperature rather than Hertzian stress. In this research, surface temperatures of rollers under different rolling and sliding conditions are measured using a thermocouple. The effects of load P, mean velocity Vm and sliding velocity Vs on surface temperature are clarified. An experimental formula, which expresses the linear relationship between surface temperature and the P0.86Vs1.31Vm-0.83 value, is used to determine surface temperature. By comparing calculated and measured temperature on the tooth surface of a gear, this formula is confirmed to be applicable for gear tooth surface temperature calculation.

  13. Simulation of wind-induced snow transport in alpine terrain using a fully coupled snowpack/atmosphere model

    Science.gov (United States)

    Vionnet, V.; Martin, E.; Masson, V.; Guyomarc'h, G.; Naaim-Bouvet, F.; Prokop, A.; Durand, Y.; Lac, C.

    2013-06-01

    In alpine regions, wind-induced snow transport strongly influences the spatio-temporal evolution of the snow cover throughout the winter season. To gain understanding on the complex processes that drive the redistribution of snow, a new numerical model is developed. It couples directly the detailed snowpack model Crocus with the atmospheric model Meso-NH. Meso-NH/Crocus simulates snow transport in saltation and in turbulent suspension and includes the sublimation of suspended snow particles. A detailed representation of the first meters of the atmosphere allows a fine reproduction of the erosion and deposition process. The coupled model is evaluated against data collected around the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps). For this purpose, a blowing snow event without concurrent snowfall has been selected and simulated. Results show that the model captures the main structures of atmospheric flow in alpine terrain, the vertical profile of wind speed and the snow particles fluxes near the surface. However, the horizontal resolution of 50 m is found to be insufficient to simulate the location of areas of snow erosion and deposition observed by terrestrial laser scanning. When activated, the sublimation of suspended snow particles causes a reduction in deposition of 5.3%. Total sublimation (surface + blowing snow) is three times higher than surface sublimation in a simulation neglecting blowing snow sublimation.

  14. Temperature signal in suspended sediment export from an Alpine catchment

    Science.gov (United States)

    Costa, Anna; Molnar, Peter; Stutenbecker, Laura; Bakker, Maarten; Silva, Tiago A.; Schlunegger, Fritz; Lane, Stuart N.; Loizeau, Jean-Luc; Girardclos, Stéphanie

    2018-01-01

    Suspended sediment export from large Alpine catchments ( > 1000 km2) over decadal timescales is sensitive to a number of factors, including long-term variations in climate, the activation-deactivation of different sediment sources (proglacial areas, hillslopes, etc.), transport through the fluvial system, and potential anthropogenic impacts on the sediment flux (e.g. through impoundments and flow regulation). Here, we report on a marked increase in suspended sediment concentrations observed near the outlet of the upper Rhône River Basin in the mid-1980s. This increase coincides with a statistically significant step-like increase in basin-wide mean air temperature. We explore the possible explanations of the suspended sediment rise in terms of changes in water discharge (transport capacity), and the activation of different potential sources of fine sediment (sediment supply) in the catchment by hydroclimatic forcing. Time series of precipitation and temperature-driven snowmelt, snow cover, and ice melt simulated with a spatially distributed degree-day model, together with erosive rainfall on snow-free surfaces, are tested to explore possible reasons for the rise in suspended sediment concentration. We show that the abrupt change in air temperature reduced snow cover and the contribution of snowmelt, and enhanced ice melt. The results of statistical tests show that the onset of increased ice melt was likely to play a dominant role in the suspended sediment concentration rise in the mid-1980s. Temperature-driven enhanced melting of glaciers, which cover about 10 % of the catchment surface, can increase suspended sediment yields through an increased contribution of sediment-rich glacial meltwater, increased sediment availability due to glacier recession, and increased runoff from sediment-rich proglacial areas. The reduced extent and duration of snow cover in the catchment are also potential contributors to the rise in suspended sediment concentration through

  15. Evaporative loss from soil, native vegetation, and snow as affected by hexadecanol

    Science.gov (United States)

    Henry W. Anderson; Allan J. West; Robert R. Ziemer; Franklin R. Adams

    1963-01-01

    Abstract - Only in a bulldozed brush field and with heavy applications of hexadecanol under snow did significant reductions in evapotranspiration occur with application of hexadecanol to natural stands. Marked reductions in evaporation from snow occurred when hexadecanol emulsion was applied to the snow surface. More than two-thirds of the precipitation in the United...

  16. Using Snow Fences to Augument Fresh Water Supplies in Shallow Arctic Lakes

    Energy Technology Data Exchange (ETDEWEB)

    Stuefer, Svetlana

    2013-03-31

    This project was funded by the U.S. Department of Energy, National Energy Technology Laboratory (NETL) to address environmental research questions specifically related to Alaska's oil and gas natural resources development. The focus of this project was on the environmental issues associated with allocation of water resources for construction of ice roads and ice pads. Earlier NETL projects showed that oil and gas exploration activities in the U.S. Arctic require large amounts of water for ice road and ice pad construction. Traditionally, lakes have been the source of freshwater for this purpose. The distinctive hydrological regime of northern lakes, caused by the presence of ice cover and permafrost, exerts influence on lake water availability in winter. Lakes are covered with ice from October to June, and there is often no water recharge of lakes until snowmelt in early June. After snowmelt, water volumes in the lakes decrease throughout the summer, when water loss due to evaporation is considerably greater than water gained from rainfall. This balance switches in August, when air temperature drops, evaporation decreases, and rain (or snow) is more likely to occur. Some of the summer surface storage deficit in the active layer and surface water bodies (lakes, ponds, wetlands) is recharged during this time. However, if the surface storage deficit is not replenished (for example, precipitation in the fall is low and near‐surface soils are dry), lake recharge is directly affected, and water availability for the following winter is reduced. In this study, we used snow fences to augment fresh water supplies in shallow arctic lakes despite unfavorable natural conditions. We implemented snow‐control practices to enhance snowdrift accumulation (greater snow water equivalent), which led to increased meltwater production and an extended melting season that resulted in lake recharge despite low precipitation during the years of the experiment. For three years (2009

  17. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    Science.gov (United States)

    Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

    2011-01-01

    The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data

  18. Blowing snow detection in Antarctica, from space borne and ground-based remote sensing

    Science.gov (United States)

    Gossart, A.; Souverijns, N.; Lhermitte, S.; Lenaerts, J.; Gorodetskaya, I.; Schween, J. H.; Van Lipzig, N. P. M.

    2017-12-01

    Surface mass balance (SMB) strongly controls spatial and temporal variations in the Antarctic Ice Sheet (AIS) mass balance and its contribution to sea level rise. Currently, the scarcity of observational data and the challenges of climate modelling over the ice sheet limit our understanding of the processes controlling AIS SMB. Particularly, the impact of blowing snow on local SMB is not yet constrained and is subject to large uncertainties. To assess the impact of blowing snow on local SMB, we investigate the attenuated backscatter profiles from ceilometers at two East Antarctic locations in Dronning Maud Land. Ceilometers are robust ground-based remote sensing instruments that yield information on cloud base height and vertical structure, but also provide information on the particles present in the boundary layer. We developed a new algorithm to detect blowing snow (snow particles lifted by the wind from the surface to substantial height) from the ceilometer attenuated backscatter. The algorithm successfully allows to detect strong blowing snow signal from layers thicker than 15 m at the Princess Elisabeth (PE, (72°S, 23°E)) and Neumayer (70°S, 8° W) stations. Applying the algorithm to PE, we retrieve the frequency and annual cycle of blowing snow as well as discriminate between clear sky and overcast conditions during blowing snow. We further apply the blowing snow algorithm at PE to evaluate the blowing snow events detection by satellite imagery (Palm et al., 2011): the near-surface blowing snow layers are apparent in lidar backscatter profiles and enable snowdrift events detection (spatial and temporal frequency, height and optical depth). These data are processed from CALIPSO, at a high resolution (1x1 km digital elevation model). However, the remote sensing detection of blowing snow events by satellite is limited to layers of a minimal thickness of 20-30 m. In addition, thick clouds, mostly occurring during winter storms, can impede drifting snow

  19. Snow measurement Using P-Band Signals of Opportunity Reflectometry

    Science.gov (United States)

    Shah, R.; Yueh, S. H.; Xu, X.; Elder, K.

    2017-12-01

    Snow water storage in land is a critical parameter of the water cycle. In this study, we develop methods for estimating reflectance from bistatic scattering of digital communication Signals of Opportunity (SoOp) across the available microwave spectrum from VHF to Ka band and show results from proof-of-concept experiments at the Fraser Experimental Forest, Colorado to acquire measurements to relate the SoOp phase and reflectivity to a snow-covered soil surface. The forward modeling of this scenario will be presented and multiple sensitivities were conducted. Available SoOp receiver data along with a network of in situ sensor measurements collected since January 2016 will be used to validate theoretical modeling results. In the winter season of 2016 and 2017, we conducted a field experiment using VHF/UHF-band illuminating sources to detect SWE and surface reflectivity. The amplitude of the reflectivity showed sensitivity to the wetness of snow pack and ground reflectivity while the phase showed sensitivity to SWE. This use of this concept can be helpful to measure the snow water storage in land globally.

  20. The origin of sea salt in snow on Arctic sea ice and in coastal regions

    Directory of Open Access Journals (Sweden)

    F. Domine

    2004-01-01

    Full Text Available Snow, through its trace constituents, can have a major impact on lower tropospheric chemistry, as evidenced by ozone depletion events (ODEs in oceanic polar areas. These ODEs are caused by the chemistry of bromine compounds that originate from sea salt bromide. Bromide may be supplied to the snow surface by upward migration from sea ice, by frost flowers being wind-blown to the snow surface, or by wind-transported aerosol generated by sea spray. We investigate here the relative importance of these processes by analyzing ions in snow near Alert and Ny-Ålesund (Canadian and European high Arctic in winter and spring. Vertical ionic profiles in the snowpack on sea ice are measured to test upward migration of sea salt ions and to seek evidence for ion fractionation processes. Time series of the ionic composition of surface snow layers are investigated to quantify wind-transported ions. Upward migration of unfractionated sea salt to heights of at least 17cm was observed in winter snow, leading to Cl- concentration of several hundred µM. Upward migration thus has the potential to supply ions to surface snow layers. Time series show that wind can deposit aerosols to the top few cm of the snow, leading also to Cl- concentrations of several hundred µM, so that both diffusion from sea ice and wind transport can significantly contribute ions to snow. At Ny-Ålesund, sea salt transported by wind was unfractionated, implying that it comes from sea spray rather than frost flowers. Estimations based on our results suggest that the marine snowpack contains about 10 times more Na+ than the frost flowers, so that both the marine snowpack and frost flowers need to be considered as sea salt sources. Our data suggest that ozone depletion chemistry can significantly enhance the Br- content of snow. We speculate that this can also take place in coastal regions and contribute to propagate ODEs inland. Finally, we stress the need to measure snow physical parameters

  1. Production of heterotrophic bacteria inhabiting macroscopic organic aggregates (marine snow) from surface waters

    International Nuclear Information System (INIS)

    Alldredge, A.L.; Cole, J.J.; Caron, D.A.

    1986-01-01

    Macroscopic detrital aggregates, known as marine snow, are a ubiquitous and abundant component of the marine pelagic zone. Descriptions of microbial communities occurring at densities 2-5 orders of magnitude higher on these particles than in the surrounding seawater have led to the suggestion that marine snow may be a site of intense heterotrophic activity. The authors tested this hypothesis using incorporation of [ 3 H]thymidine into macromolecules as a measure of bacterial growth occurring on marine snow from oceanic waters in the North Atlantic and from neritic waters off southern California. Abundances of marine snow ranged from 0.1 to 4.3 aggregates per liter. However, only 0.1-4% ration per cell on aggregates was generally equal to or lower than that of bacteria found free-living in the surrounding seawater, indicating that attached bacteria were not growing more rapidly than free-living bacteria. Bacteria inhabiting aggregates were up to 25 times larger than free-living forms

  2. Snow hydrology in Mediterranean mountain regions: A review

    Science.gov (United States)

    Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; López-Moreno, Juan Ignacio; Drapeau, Laurent; Page, Michel Le; Escadafal, Richard

    2017-08-01

    is suitable for hydrological applications. Further advances in our understanding of the snow processes in Mediterranean snow-dominated basins will be achieved by finer and more accurate representation of the climate forcing. While the theory on the snowpack energy and mass balance is now well established, the connections between the snow cover and the water resources involve complex interactions with the sub-surface processes, which demand future investigation.

  3. Snow cover setting-up dates in the north of Eurasia: relations and feedback to the macro-scale atmospheric circulation

    Directory of Open Access Journals (Sweden)

    V. V. Popova

    2014-01-01

    values –0.82 ÷ –0.85 in 1973–1994 (Fig. 4, а, б. Results of numerical experiments on simulation of observed October snow cover anomaly in 1976 and its impact on Northern Hemisphere sea level pressure in winter months approved potential ability of abrupt increase of albedo caused by snow cover onset to influence on weakening of westerly and negative temperature anomalies in North Eurasia (Fig. 5. Evidently, based on observational data and results of modeling one should conclude that autumn snow cover anomalies in North are able to effect on macro-scale circulation regime in winter, but in condition of weakening of other major factors influencing on circulation, for example sea surface temperature over the oceans. In any case, correlation analysis of earth observations shows that snow cover extent anomalies could not be recognized as cause of negative AO anomalies and severe winters in North Eurasia in last decade.

  4. High fidelity remote sensing of snow properties from MODIS and the Airborne Snow Observatory: Snowflakes to Terabytes

    Science.gov (United States)

    Painter, T.; Mattmann, C. A.; Brodzik, M.; Bryant, A. C.; Goodale, C. E.; Hart, A. F.; Ramirez, P.; Rittger, K. E.; Seidel, F. C.; Zimdars, P. A.

    2012-12-01

    The response of the cryosphere to climate forcings largely determines Earth's climate sensitivity. However, our understanding of the strength of the simulated snow albedo feedback varies by a factor of three in the GCMs used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, mainly caused by uncertainties in snow extent and the albedo of snow-covered areas from imprecise remote sensing retrievals. Additionally, the Western US and other regions of the globe depend predominantly on snowmelt for their water supply to agriculture, industry and cities, hydroelectric power, and recreation, against rising demand from increasing population. In the mountains of the Upper Colorado River Basin, dust radiative forcing in snow shortens snow cover duration by 3-7 weeks. Extended to the entire upper basin, the 5-fold increase in dust load since the late-1800s results in a 3-week earlier peak runoff and a 5% annual loss of total runoff. The remotely sensed dynamics of snow cover duration and melt however have not been factored into hydrological modeling, operational forecasting, and policymaking. To address these deficiencies in our understanding of snow properties, we have developed and validated a suite of MODIS snow products that provide accurate fractional snow covered area and radiative forcing of dust and carbonaceous aerosols in snow. The MODIS Snow Covered Area and Grain size (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRFS) algorithms, developed and transferred from imaging spectroscopy techniques, leverage the complete MODIS surface reflectance spectrum. The two most critical properties for understanding snowmelt runoff and timing are the spatial and temporal distributions of snow water equivalent (SWE) and snow albedo. We have created the Airborne Snow Observatory (ASO), an imaging spectrometer and scanning LiDAR system, to quantify SWE and snow albedo, generate unprecedented knowledge of snow properties, and provide complete

  5. Estimating Snow Cover from Publicly Available Images

    OpenAIRE

    Fedorov, Roman; Camerada, Alessandro; Fraternali, Piero; Tagliasacchi, Marco

    2016-01-01

    In this paper we study the problem of estimating snow cover in mountainous regions, that is, the spatial extent of the earth surface covered by snow. We argue that publicly available visual content, in the form of user generated photographs and image feeds from outdoor webcams, can both be leveraged as additional measurement sources, complementing existing ground, satellite and airborne sensor data. To this end, we describe two content acquisition and processing pipelines that are tailored to...

  6. Towards Year-round Estimation of Terrestrial Water Storage over Snow-Covered Terrain via Multi-sensor Assimilation of GRACE/GRACE-FO and AMSR-E/AMSR-2.

    Science.gov (United States)

    Wang, J.; Xue, Y.; Forman, B. A.; Girotto, M.; Reichle, R. H.

    2017-12-01

    The Gravity and Recovery Climate Experiment (GRACE) has revolutionized large-scale remote sensing of the Earth's terrestrial hydrologic cycle and has provided an unprecedented observational constraint for global land surface models. However, the coarse-scale (in space and time), vertically-integrated measure of terrestrial water storage (TWS) limits GRACE's applicability to smaller scale hydrologic applications. In order to enhance model-based estimates of TWS while effectively adding resolution (in space and time) to the coarse-scale TWS retrievals, a multi-variate, multi-sensor data assimilation framework is presented here that simultaneously assimilates gravimetric retrievals of TWS in conjunction with passive microwave (PMW) brightness temperature (Tb) observations over snow-covered terrain. The framework uses the NASA Catchment Land Surface Model (Catchment) and an ensemble Kalman filter (EnKF). A synthetic assimilation experiment is presented for the Volga river basin in Russia. The skill of the output from the assimilation of synthetic observations is compared with that of model estimates generated without the benefit of assimilating the synthetic observations. It is shown that the EnKF framework improves modeled estimates of TWS, snow depth, and snow mass (a.k.a. snow water equivalent). The data assimilation routine produces a conditioned (updated) estimate that is more accurate and contains less uncertainty during both the snow accumulation phase of the snow season as well as during the snow ablation season.

  7. Snow Matters

    DEFF Research Database (Denmark)

    Gyimóthy, Szilvia; Jensen, Martin Trandberg

    2018-01-01

    attribute of high altitude mountain destinations. Hitherto, researchers mostly engaged with snowclad landscapes as a backstage; trying to deconstruct the complex symbolism and representational qualities of this elusive substance. Despite snow being a strategically crucial condition for tourism in the Alps......This chapter explores the performative potential of snow for Alpine tourism, by drawing attention to its material and nonrepresentational significance for tourism practices. European imagination has been preoccupied with snow since medieval times and even today, snow features as the sine que non...

  8. An 18-yr long (1993–2011 snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 m alt. for driving and evaluating snowpack models

    Directory of Open Access Journals (Sweden)

    S. Morin

    2012-07-01

    Full Text Available A quality-controlled snow and meteorological dataset spanning the period 1 August 1993–31 July 2011 is presented, originating from the experimental station Col de Porte (1325 m altitude, Chartreuse range, France. Emphasis is placed on meteorological data relevant to the observation and modelling of the seasonal snowpack. In-situ driving data, at the hourly resolution, consist of measurements of air temperature, relative humidity, windspeed, incoming short-wave and long-wave radiation, precipitation rate partitioned between snow- and rainfall, with a focus on the snow-dominated season. Meteorological data for the three summer months (generally from 10 June to 20 September, when the continuity of the field record is not warranted, are taken from a local meteorological reanalysis (SAFRAN, in order to provide a continuous and consistent gap-free record. Data relevant to snowpack properties are provided at the daily (snow depth, snow water equivalent, runoff and albedo and hourly (snow depth, albedo, runoff, surface temperature, soil temperature time resolution. Internal snowpack information is provided from weekly manual snowpit observations (mostly consisting in penetration resistance, snow type, snow temperature and density profiles and from a hourly record of temperature and height of vertically free ''settling'' disks. This dataset has been partially used in the past to assist in developing snowpack models and is presented here comprehensively for the purpose of multi-year model performance assessment. The data is placed on the PANGAEA repository (http://dx.doi.org/10.1594/PANGAEA.774249 as well as on the public ftp server ftp://ftp-cnrm.meteo.fr/pub-cencdp/.

  9. Airborne Surveys of Snow Depth over Arctic Sea Ice

    Science.gov (United States)

    Kwok, R.; Panzer, B.; Leuschen, C.; Pang, S.; Markus, T.; Holt, B.; Gogineni, S.

    2011-01-01

    During the spring of 2009, an ultrawideband microwave radar was deployed as part of Operation IceBridge to provide the first cross-basin surveys of snow thickness over Arctic sea ice. In this paper, we analyze data from three approx 2000 km transects to examine detection issues, the limitations of the current instrument, and the regional variability of the retrieved snow depth. Snow depth is the vertical distance between the air \\snow and snow-ice interfaces detected in the radar echograms. Under ideal conditions, the per echogram uncertainty in snow depth retrieval is approx 4 - 5 cm. The finite range resolution of the radar (approx 5 cm) and the relative amplitude of backscatter from the two interfaces limit the direct retrieval of snow depths much below approx 8 cm. Well-defined interfaces are observed over only relatively smooth surfaces within the radar footprint of approx 6.5 m. Sampling is thus restricted to undeformed, level ice. In early April, mean snow depths are 28.5 +/- 16.6 cm and 41.0 +/- 22.2 cm over first-year and multiyear sea ice (MYI), respectively. Regionally, snow thickness is thinner and quite uniform over the large expanse of seasonal ice in the Beaufort Sea, and gets progressively thicker toward the MYI cover north of Ellesmere Island, Greenland, and the Fram Strait. Snow depth over MYI is comparable to that reported in the climatology by Warren et al. Ongoing improvements to the radar system and the utility of these snow depth measurements are discussed.

  10. Pyroclast/snow interactions and thermally driven slurry formation. Part 2: Experiments and theoretical extension to polydisperse tephra

    Science.gov (United States)

    Walder, J.S.

    2000-01-01

    Erosion of snow by pyroclastic flows and surges presumably involves mechanical scour, but there may be thermally driven phenomena involved as well. To investigate this possibility, layers of hot (up to 400??C), uniformly sized, fine- to medium-grained sand were emplaced vertically onto finely shaved ice ('snow'); thus there was no relative shear motion between sand and snow and no purely mechanical scour. In some cases large vapor bubbles, commonly more than 10 mm across, rose through the sand layer, burst at the surface, and caused complete convective overturn of the sand, which then scoured and mixed with snow and transformed into a slurry. In other cases no bubbling occurred and the sand passively melted its way downward into the snow as a wetting front moved upward into the sand. A continuum of behaviors between these two cases was observed. Vigorous bubbling and convection were generally favored by high temperature, small grain size, and small layer thickness. A physically based theory of heat- and mass transfer at the pyroclast/snow interface, developed in Part 1 of this paper, does a good job of explaining the observations as a manifestation of unstable vapor-driven fluidization. The theory, when extrapolated to the behavior of actual, poorly sorted pyroclastic flow sediments, leads to the prediction that the observed 'thermal-scour' phenomenon should also occur for many real pyroclastic flows passing over snow. 'Thermal scour' is therefore likely to be involved in the generation of lahars.

  11. Studies of diffuse and direct solar radiation over snow

    International Nuclear Information System (INIS)

    Wesely, M.L.; Everett, R.G.

    1976-01-01

    Two interesting questions can be addressed by examination of solar radiation records obtained while the surface is covered with snow. One concerns the extent to which airborne particulate matter affects solar radiation received at the surface during winter conditions that are typical of those in the northeastern quarter of the United States. The other relates to the importance of complicated light scatterng in the earth-atmosphere system when the surface albedo is large. With the snow surface reflecting 50% or more of the incident radiation, it is likely that a significant addition to diffuse radiation would result from light that is reflected from the surface and then scattered back to the earth by the atmosphere. Preliminary data from measurements made during the winter of 1975 to 1976 are reported

  12. Frost seen on Snow White Trench

    Science.gov (United States)

    2008-01-01

    The Surface Stereo Imager (SSI) on NASA's Phoenix Mars Lander took this shadow-enhanced false color image of the 'Snow White' trench, on the eastern end of Phoenix's digging area. The image was taken on Sol 144, or the 144th day of the mission, Oct. 20, 2008. Temperatures measured on Sol 151, the last day weather data were received, showed overnight lows of minus128 Fahrenheit (minus 89 Celsius) and day time highs in the minus 50 F (minus 46 C) range. The last communication from the spacecraft came on Nov. 2, 2008. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  13. Process-level model evaluation: a snow and heat transfer metric

    Science.gov (United States)

    Slater, Andrew G.; Lawrence, David M.; Koven, Charles D.

    2017-04-01

    Land models require evaluation in order to understand results and guide future development. Examining functional relationships between model variables can provide insight into the ability of models to capture fundamental processes and aid in minimizing uncertainties or deficiencies in model forcing. This study quantifies the proficiency of land models to appropriately transfer heat from the soil through a snowpack to the atmosphere during the cooling season (Northern Hemisphere: October-March). Using the basic physics of heat diffusion, we investigate the relationship between seasonal amplitudes of soil versus air temperatures due to insulation from seasonal snow. Observations demonstrate the anticipated exponential relationship of attenuated soil temperature amplitude with increasing snow depth and indicate that the marginal influence of snow insulation diminishes beyond an effective snow depth of about 50 cm. A snow and heat transfer metric (SHTM) is developed to quantify model skill compared to observations. Land models within the CMIP5 experiment vary widely in SHTM scores, and deficiencies can often be traced to model structural weaknesses. The SHTM value for individual models is stable over 150 years of climate, 1850-2005, indicating that the metric is insensitive to climate forcing and can be used to evaluate each model's representation of the insulation process.

  14. Analyses of newly digitised and reconstructed snow series over the last 100+ years in Switzerland

    Science.gov (United States)

    Scherrer, S. C.; Wüthrich, C.; Croci-Maspoli, M.; Appenzeller, C.

    2010-09-01

    Snow is an important socio-economic factor in the Swiss Alpine region (tourism, hydro-electricity, drinking water) and responsible for considerable natural hazards such as avalanches. In addition, high-quality long-term snow series can be used as an excellent indicator of climate change. The objectives of this study are threefold. First, suitable long-term snow series from different altitudes and regions in Switzerland have been selected, missing data digitized and the entire series quality checked. Second, the long-term snow series have been used for trend analyses over a time period >100 years. Third, snow depth series have been reconstructed using daily new snow, temperature and precipitation as input variables. This made it possible to analyse snow depth related variables such as days with snow pack. Results show that the snow cover is varying substantially on seasonal and decadal time scales. The analyses of the decadal new snow trends during the last 100 years shows unprecedented low new snow sums in the winter seasons (DJF) of the 1990s. The 100 year trend of days with snow pack reveals a significant decrease for stations below 800 m asl in the winter season (DJF) and for stations around 1800 m asl in spring (MAM). Similar results were found for seasonal new snow sums. The results of the trend analyses are also discussed with respect to temperature and precipitation trends. Finally we will also shortly discuss how especially "precious" snow measurements have been identified and incorporated in a National Basic Climatological Network (NBCN) as well as in the Global Climate Observing System (GCOS).

  15. Digging of 'Snow White' Begins

    Science.gov (United States)

    2008-01-01

    NASA's Phoenix Mars Lander began excavating a new trench, dubbed 'Snow White,' in a patch of Martian soil located near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The trench is about 2 centimeters (.8 inches) deep and 30 centimeters (about 12 inches) long. The 'dump pile' is located at the top of the trench, the side farthest away from the lander, and has been dubbed 'Croquet Ground.' The digging site has been named 'Wonderland.' At this early stage of digging, the Phoenix team did not expect to find any of the white material seen in the first trench, now called 'Dodo-Goldilocks.' That trench showed white material at a depth of about 5 centimeters (2 inches). More digging of Snow White is planned for coming sols, or Martian days. The dark portion of this image is the shadow of the lander's solar panel; the bright areas within this region are not in shadow. Snow White was dug on Sol 22 (June 17, 2008) with Phoenix's Robotic Arm. This picture was acquired on the same day by the lander's Surface Stereo Imager. This image has been enhanced to brighten shaded areas. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  16. An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band

    Directory of Open Access Journals (Sweden)

    Jordi Cristóbal

    2018-03-01

    Full Text Available Land surface temperature (LST is one of the sources of input data for modeling land surface processes. The Landsat satellite series is the only operational mission with more than 30 years of archived thermal infrared imagery from which we can retrieve LST. Unfortunately, stray light artifacts were observed in Landsat-8 TIRS data, mostly affecting Band 11, currently making the split-window technique impractical for retrieving surface temperature without requiring atmospheric data. In this study, a single-channel methodology to retrieve surface temperature from Landsat TM and ETM+ was improved to retrieve LST from Landsat-8 TIRS Band 10 using near-surface air temperature (Ta and integrated atmospheric column water vapor (w as input data. This improved methodology was parameterized and successfully evaluated with simulated data from a global and robust radiosonde database and validated with in situ data from four flux tower sites under different types of vegetation and snow cover in 44 Landsat-8 scenes. Evaluation results using simulated data showed that the inclusion of Ta together with w within a single-channel scheme improves LST retrieval, yielding lower errors and less bias than models based only on w. The new proposed LST retrieval model, developed with both w and Ta, yielded overall errors on the order of 1 K and a bias of −0.5 K validated against in situ data, providing a better performance than other models parameterized using w and Ta or only w models that yielded higher error and bias.

  17. The Ross Sea Dipole - temperature, snow accumulation and sea ice variability in the Ross Sea region, Antarctica, over the past 2700 years

    Science.gov (United States)

    Bertler, Nancy A. N.; Conway, Howard; Dahl-Jensen, Dorthe; Emanuelsson, Daniel B.; Winstrup, Mai; Vallelonga, Paul T.; Lee, James E.; Brook, Ed J.; Severinghaus, Jeffrey P.; Fudge, Taylor J.; Keller, Elizabeth D.; Baisden, W. Troy; Hindmarsh, Richard C. A.; Neff, Peter D.; Blunier, Thomas; Edwards, Ross; Mayewski, Paul A.; Kipfstuhl, Sepp; Buizert, Christo; Canessa, Silvia; Dadic, Ruzica; Kjær, Helle A.; Kurbatov, Andrei; Zhang, Dongqi; Waddington, Edwin D.; Baccolo, Giovanni; Beers, Thomas; Brightley, Hannah J.; Carter, Lionel; Clemens-Sewall, David; Ciobanu, Viorela G.; Delmonte, Barbara; Eling, Lukas; Ellis, Aja; Ganesh, Shruthi; Golledge, Nicholas R.; Haines, Skylar; Handley, Michael; Hawley, Robert L.; Hogan, Chad M.; Johnson, Katelyn M.; Korotkikh, Elena; Lowry, Daniel P.; Mandeno, Darcy; McKay, Robert M.; Menking, James A.; Naish, Timothy R.; Noerling, Caroline; Ollive, Agathe; Orsi, Anaïs; Proemse, Bernadette C.; Pyne, Alexander R.; Pyne, Rebecca L.; Renwick, James; Scherer, Reed P.; Semper, Stefanie; Simonsen, Marius; Sneed, Sharon B.; Steig, Eric J.; Tuohy, Andrea; Ulayottil Venugopal, Abhijith; Valero-Delgado, Fernando; Venkatesh, Janani; Wang, Feitang; Wang, Shimeng; Winski, Dominic A.; Winton, V. Holly L.; Whiteford, Arran; Xiao, Cunde; Yang, Jiao; Zhang, Xin

    2018-02-01

    High-resolution, well-dated climate archives provide an opportunity to investigate the dynamic interactions of climate patterns relevant for future projections. Here, we present data from a new, annually dated ice core record from the eastern Ross Sea, named the Roosevelt Island Climate Evolution (RICE) ice core. Comparison of this record with climate reanalysis data for the 1979-2012 interval shows that RICE reliably captures temperature and snow precipitation variability in the region. Trends over the past 2700 years in RICE are shown to be distinct from those in West Antarctica and the western Ross Sea captured by other ice cores. For most of this interval, the eastern Ross Sea was warming (or showing isotopic enrichment for other reasons), with increased snow accumulation and perhaps decreased sea ice concentration. However, West Antarctica cooled and the western Ross Sea showed no significant isotope temperature trend. This pattern here is referred to as the Ross Sea Dipole. Notably, during the Little Ice Age, West Antarctica and the western Ross Sea experienced colder than average temperatures, while the eastern Ross Sea underwent a period of warming or increased isotopic enrichment. From the 17th century onwards, this dipole relationship changed. All three regions show current warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea but increasing in the western Ross Sea. We interpret this pattern as reflecting an increase in sea ice in the eastern Ross Sea with perhaps the establishment of a modern Roosevelt Island polynya as a local moisture source for RICE.

  18. Measurements of Air and Snow Photochemical Species at WAIS Divide, Antarctica, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains atmospheric mixing ratios of nitric oxide, ozone, hydrogen peroxide, methylhydroperoxide, and concentrations in surface snow and in snow pits...

  19. CHEMICAL COMPOSITION CHANGE OF SUBSURFACE SNOW IN EAST ANTARCTICA WITH DISTANCE FROM THE COAST

    Directory of Open Access Journals (Sweden)

    L. P. Golobokova

    2012-01-01

    Full Text Available The paper presents data on chemical composition of snow in theAntarcticasampled along the first tractor traverse during the 53th Russian Antarctic Expedition from Station Progress (the sea coast to Station Vostok (1,276 kmfrom Progress. Specific features of horizontal and depth distribution of chemical components in snow revealed differences in conditions of formation of snow cover along the traverse in both spatial and time scales. Chemical composition of snow depends on the sources of admixture inputs onto the surface of the ice sheet (marine, continental and volcanic. The influence of sea factor decreases with the distance from the coast. Calculated factor of element enrichment indicated that some ions in snow cover were of continental origin in the middle of the traverse. Elevated concentrations of sulphate ions were recorded in snow-firn cores at 130–150 cmfrom the surface. They were attributed to signals of the Pinatubo volcano eruption (1991. Accumulation rate of snow was calculated for the traverse sites based on the depth of the Pinatubo layer.

  20. Understanding the Role of Wind in Reducing the Surface Mass Balance Estimates over East Antarctica

    Science.gov (United States)

    Das, I.; Scambos, T. A.; Koenig, L.; Creyts, T. T.; Bell, R. E.; van den Broeke, M. R.; Lenaerts, J.; Paden, J. D.

    2014-12-01

    Accurate quantification of surface snow-accumulation over Antarctica is important for mass balance estimates and climate studies based on ice core records. An improved estimate of surface mass balance must include the significant role near-surface wind plays in the sublimation and redistribution of snow across Antarctica. We have developed an empirical model based on airborne radar and lidar observations, and modeled surface mass balance and wind fields to produce a continent-wide prediction of wind-scour zones over Antarctica. These zones have zero to negative surface mass balance, are located over locally steep ice sheet areas (>0.002) and controlled by bedrock topography. The near-surface winds accelerate over these zones, eroding and sublimating the surface snow. This scouring results in numerous localized regions (≤ 200 km2) with reduced surface accumulation. Each year, tens of gigatons of snow on the Antarctic ice sheet are ablated by persistent near-surface katabatic winds over these wind-scour zones. Large uncertainties remain in the surface mass balance estimates over East Antarctica as climate models do not adequately represent the small-scale physical processes that lead to mass loss through sublimation or redistribution over the wind-scour zones. In this study, we integrate Operation IceBridge's snow radar over the Recovery Ice Stream with a series of ice core dielectric and depth-density profiles for improved surface mass balance estimates that reflect the mass loss over the wind-scour zones. Accurate surface mass balance estimates from snow radars require spatially variable depth-density profiles. Using an ensemble of firn cores, MODIS-derived surface snow grain size, modeled accumulation rates and surface temperatures from RACMO2, we assemble spatially variable depth-density profiles and use our mapping of snow density variations to estimate layer mass and net accumulation rates from snow radar layer data. Our study improves the quantification of

  1. Surface studies of water isotopes in Antarctica for quantitative interpretation of deep ice core data

    Science.gov (United States)

    Landais, Amaelle; Casado, Mathieu; Prié, Frédéric; Magand, Olivier; Arnaud, Laurent; Ekaykin, Alexey; Petit, Jean-Robert; Picard, Ghislain; Fily, Michel; Minster, Bénédicte; Touzeau, Alexandra; Goursaud, Sentia; Masson-Delmotte, Valérie; Jouzel, Jean; Orsi, Anaïs

    2017-07-01

    Polar ice cores are unique climate archives. Indeed, most of them have a continuous stratigraphy and present high temporal resolution of many climate variables in a single archive. While water isotopic records (δD or δ18O) in ice cores are often taken as references for past atmospheric temperature variations, their relationship to temperature is associated with a large uncertainty. Several reasons are invoked to explain the limitation of such an approach; in particular, post-deposition effects are important in East Antarctica because of the low accumulation rates. The strong influence of post-deposition processes highlights the need for surface polar research programs in addition to deep drilling programs. We present here new results on water isotopes from several recent surface programs, mostly over East Antarctica. Together with previously published data, the new data presented in this study have several implications for the climatic reconstructions based on ice core isotopic data: (1) The spatial relationship between surface mean temperature and mean snow isotopic composition over the first meters in depth can be explained quite straightforwardly using simple isotopic models tuned to d-excess vs. δ18O evolution in transects on the East Antarctic sector. The observed spatial slopes are significantly higher (∼ 0.7-0.8‰·°C-1 for δ18O vs. temperature) than seasonal slopes inferred from precipitation data at Vostok and Dome C (0.35 to 0.46‰·°C-1). We explain these differences by changes in condensation versus surface temperature between summer and winter in the central East Antarctic plateau, where the inversion layer vanishes in summer. (2) Post-deposition effects linked to exchanges between the snow surface and the atmospheric water vapor lead to an evolution of δ18O in the surface snow, even in the absence of any precipitation event. This evolution preserves the positive correlation between the δ18O of snow and surface temperature, but is

  2. Why on the snow? Winter emergence strategies of snow-active Chironomidae (Diptera) in Poland.

    Science.gov (United States)

    Soszyńska-Maj, Agnieszka; Paasivirta, Lauri; Giłka, Wojciech

    2016-10-01

    A long-term study of adult non-biting midges (Chironomidae) active in winter on the snow in mountain areas and lowlands in Poland yielded 35 species. The lowland and mountain communities differed significantly in their specific composition. The mountain assemblage was found to be more diverse and abundant, with a substantial contribution from the subfamily Diamesinae, whereas Orthocladiinae predominated in the lowlands. Orthocladius wetterensis Brundin was the most characteristic and superdominant species in the winter-active chironomid communities in both areas. Only a few specimens and species of snow-active chironomids were recorded in late autumn and early winter. The abundance of chironomids peaked in late February in the mountain and lowland areas with an additional peak in the mountain areas in early April. However, this second peak of activity consisted mainly of Orthocladiinae, as Diamesinae emerged earliest in the season. Most snow-active species emerged in mid- and late winter, but their seasonal patterns differed between the 2 regions as a result of the different species composition and the duration of snow cover in these regions. Spearman's rank correlation coefficient tests yielded positive results between each season and the number of chironomid individuals recorded in the mountain area. A positive correlation between air temperature, rising to +3.5 °C, and the number of specimens recorded on the snow in the mountain community was statistically significant. The winter emergence and mate-searching strategies of chironomids are discussed in the light of global warming, and a brief compilation of most important published data on the phenomena studied is provided. © 2015 Institute of Zoology, Chinese Academy of Sciences.

  3. Snow Dunes: A Controlling Factor of Melt Pond Distribution on Arctic Sea Ice

    Science.gov (United States)

    Petrich, Chris; Eicken, Hajo; Polashenski, Christopher M.; Sturm, Matthew; Harbeck, Jeremy P.; Perovich, Donald K.; Finnegan, David C.

    2012-01-01

    The location of snow dunes over the course of the ice-growth season 2007/08 was mapped on level landfast first-year sea ice near Barrow, Alaska. Landfast ice formed in mid-December and exhibited essentially homogeneous snow depths of 4-6 cm in mid-January; by early February distinct snow dunes were observed. Despite additional snowfall and wind redistribution throughout the season, the location of the dunes was fixed by March, and these locations were highly correlated with the distribution of meltwater ponds at the beginning of June. Our observations, including ground-based light detection and ranging system (lidar) measurements, show that melt ponds initially form in the interstices between snow dunes, and that the outline of the melt ponds is controlled by snow depth contours. The resulting preferential surface ablation of ponded ice creates the surface topography that later determines the melt pond evolution.

  4. Shifting mountain snow patterns in a changing climate from remote sensing retrieval.

    Science.gov (United States)

    Dedieu, J P; Lessard-Fontaine, A; Ravazzani, G; Cremonese, E; Shalpykova, G; Beniston, M

    2014-09-15

    Observed climate change has already led to a wide range of impacts on environmental systems and society. In this context, many mountain regions seem to be particularly sensitive to a changing climate, through increases in temperature coupled with changes in precipitation regimes that are often larger than the global average (EEA, 2012). In mid-latitude mountains, these driving factors strongly influence the variability of the mountain snow-pack, through a decrease in seasonal reserves and earlier melting of the snow pack. These in turn impact on hydrological systems in different watersheds and, ultimately, have consequences for water management. Snow monitoring from remote sensing provides a unique opportunity to address the question of snow cover regime changes at the regional scale. This study outlines the results retrieved from the MODIS satellite images over a time period of 10 hydrological years (2000-2010) and applied to two case studies of the EU FP7 ACQWA project, namely the upper Rhone and Po in Europe and the headwaters of the Syr Darya in Kyrgyzstan (Central Asia). The satellite data were provided by the MODIS Terra MOD-09 reflectance images (NASA) and MOD-10 snow products (NSIDC). Daily snow maps were retrieved over that decade and the results presented here focus on the temporal and spatial changes in snow cover. This paper highlights the statistical bias observed in some specific regions, expressed by the standard deviation values (STD) of annual snow duration. This bias is linked to the response of snow cover to changes in elevation and can be used as a signal of strong instability in regions sensitive to climate change: with alternations of heavy snowfalls and rapid snow melting processes. The interest of the study is to compare the methodology between the medium scales (Europe) and the large scales (Central Asia) in order to overcome the limits of the applied methodologies and to improve their performances. Results show that the yearly snow cover

  5. Introduction to snow rheology

    International Nuclear Information System (INIS)

    Montmollin, Vincent de

    1978-01-01

    The tests described in the thesis are rotating shearing tests, with rotational constant speed ranging between 0.00075 rpm and 0.75 rpm. The results obtained are similar to those observed with compression tests at constant speed, except that shearing tests are carried out with densities nearly constant. So, we show three different domains when the rotation speed increases: 1) viscous (without failure) 2) brittle of first type (cycles of brittle failures) and 3) brittle of second type (only one brittle failure and solid friction). These results show clearly that the fundamental mechanism that rules the mechanisms of snow, is fast metamorphosis of bonds, binding ice grains: this metamorphosis is important when solicitation speeds are low (permanent rate of shearing in viscous domain, regeneration of the failure surfaces in the brittle domain of the first type) and this metamorphosis does not exist when speed increases (only one failure and solid friction in the brittle domain of second type). It is also included an important bibliographic analysis of the snow mechanics, and an experimental and theoretical study about shock wave propagation in natural snow covers. (author) [fr

  6. Surface formation, preservation, and history of low-porosity crusts at the WAIS Divide site, West Antarctica

    Science.gov (United States)

    Fegyveresi, John M.; Alley, Richard B.; Muto, Atsuhiro; Orsi, Anaïs J.; Spencer, Matthew K.

    2018-01-01

    Observations at the West Antarctic Ice Sheet (WAIS) Divide site show that near-surface snow is strongly altered by weather-related processes such as strong winds and temperature fluctuations, producing features that are recognizable in the deep ice core. Prominent glazed surface crusts develop frequently at the site during summer seasons. Surface, snow pit, and ice core observations made in this study during summer field seasons from 2008-2009 to 2012-2013, supplemented by automated weather station (AWS) data with short- and longwave radiation sensors, revealed that such crusts formed during relatively low-wind, low-humidity, clear-sky periods with intense daytime sunshine. After formation, such glazed surfaces typically developed cracks in a polygonal pattern likely from thermal contraction at night. Cracking was commonest when several clear days occurred in succession and was generally followed by surface hoar growth; vapor escaping through the cracks during sunny days may have contributed to the high humidity that favored nighttime formation of surface hoar. Temperature and radiation observations show that daytime solar heating often warmed the near-surface snow above the air temperature, contributing to upward mass transfer, favoring crust formation from below, and then surface hoar formation. A simple surface energy calculation supports this observation. Subsequent examination of the WDC06A deep ice core revealed that crusts are preserved through the bubbly ice, and some occur in snow accumulated during winters, although not as commonly as in summertime deposits. Although no one has been on site to observe crust formation during winter, it may be favored by greater wintertime wind packing from stronger peak winds, high temperatures and steep temperature gradients from rapid midwinter warmings reaching as high as -15 °C, and perhaps longer intervals of surface stability. Time variations in crust occurrence in the core may provide paleoclimatic information

  7. Surface formation, preservation, and history of low-porosity crusts at the WAIS Divide site, West Antarctica

    Directory of Open Access Journals (Sweden)

    J. M. Fegyveresi

    2018-01-01

    Full Text Available Observations at the West Antarctic Ice Sheet (WAIS Divide site show that near-surface snow is strongly altered by weather-related processes such as strong winds and temperature fluctuations, producing features that are recognizable in the deep ice core. Prominent glazed surface crusts develop frequently at the site during summer seasons. Surface, snow pit, and ice core observations made in this study during summer field seasons from 2008–2009 to 2012–2013, supplemented by automated weather station (AWS data with short- and longwave radiation sensors, revealed that such crusts formed during relatively low-wind, low-humidity, clear-sky periods with intense daytime sunshine. After formation, such glazed surfaces typically developed cracks in a polygonal pattern likely from thermal contraction at night. Cracking was commonest when several clear days occurred in succession and was generally followed by surface hoar growth; vapor escaping through the cracks during sunny days may have contributed to the high humidity that favored nighttime formation of surface hoar. Temperature and radiation observations show that daytime solar heating often warmed the near-surface snow above the air temperature, contributing to upward mass transfer, favoring crust formation from below, and then surface hoar formation. A simple surface energy calculation supports this observation. Subsequent examination of the WDC06A deep ice core revealed that crusts are preserved through the bubbly ice, and some occur in snow accumulated during winters, although not as commonly as in summertime deposits. Although no one has been on site to observe crust formation during winter, it may be favored by greater wintertime wind packing from stronger peak winds, high temperatures and steep temperature gradients from rapid midwinter warmings reaching as high as −15 °C, and perhaps longer intervals of surface stability. Time variations in crust occurrence in the core may provide

  8. Incoming longwave radiation to melting snow: observations, sensitivity and estimation in Northern environments

    Science.gov (United States)

    Sicart, J. E.; Pomeroy, J. W.; Essery, R. L. H.; Bewley, D.

    2006-11-01

    At high latitudes, longwave radiation can provide similar, or higher, amounts of energy to snow than shortwave radiation due to the low solar elevation (cosine effect and increased scattering due to long atmospheric path lengths). This effect is magnified in mountains due to shading and longwave emissions from the complex topography. This study examines longwave irradiance at the snow surface in the Wolf Creek Research Basin, Yukon Territory, Canada (60° 36N, 134° 57W) during the springs of 2002 and 2004. Incoming longwave radiation was estimated from standard meteorological measurements by segregating radiation sources into clear sky, clouds and surrounding terrain. A sensitivity study was conducted to detect the atmospheric and topographic conditions under which emission from adjacent terrain significantly increases the longwave irradiance. The total incoming longwave radiation is more sensitive to sky view factor than to the temperature of the emitting terrain surfaces. Brutsaert's equation correctly simulates the clear-sky irradiance for hourly time steps using temperature and humidity. Longwave emissions from clouds, which raised longwave radiation above that from clear skies by 16% on average, were best estimated using daily atmospheric shortwave transmissivity and hourly relative humidity. An independent test of the estimation procedure for a prairie site near Saskatoon, Saskatchewan, Canada, indicated that the calculations are robust in late winter and spring conditions. Copyright

  9. Remotely sensed soil temperatures beneath snow-free skin-surface using thermal observations from tandem polar-orbiting satellites: An analytical three-time-scale model

    DEFF Research Database (Denmark)

    Zhan, Wenfeng; Zhou, Ji; Ju, Weimin

    2014-01-01

    Subsurface soil temperature is a key variable of land surface processes and not only responds to but also modulates the interactions of energy fluxes at the Earth's surface. Thermal remote sensing has traditionally been regarded as incapable of detecting the soil temperature beneath the skin-surf...

  10. From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

    Science.gov (United States)

    Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

    2017-04-01

    Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation

  11. Impact of snow deposition on major and trace element concentrations and elementary fluxes in surface waters of the Western Siberian Lowland across a 1700 km latitudinal gradient

    Science.gov (United States)

    Shevchenko, Vladimir P.; Pokrovsky, Oleg S.; Vorobyev, Sergey N.; Krickov, Ivan V.; Manasypov, Rinat M.; Politova, Nadezhda V.; Kopysov, Sergey G.; Dara, Olga M.; Auda, Yves; Shirokova, Liudmila S.; Kolesnichenko, Larisa G.; Zemtsov, Valery A.; Kirpotin, Sergey N.

    2017-11-01

    In order to better understand the chemical composition of snow and its impact on surface water hydrochemistry in the poorly studied Western Siberia Lowland (WSL), the surface layer of snow was sampled in February 2014 across a 1700 km latitudinal gradient (ca. 56.5 to 68° N). We aimed at assessing the latitudinal effect on both dissolved and particulate forms of elements in snow and quantifying the impact of atmospheric input to element storage and export fluxes in inland waters of the WSL. The concentration of dissolved+colloidal (metalloids (As, Sb), Mo and U in the discontinuous to continuous permafrost zone (64-68° N) can be explained solely by melting of accumulated snow. The impact of snow deposition on riverine fluxes of elements strongly increased northward, in discontinuous and continuous permafrost zones of frozen peat bogs. This was consistent with the decrease in the impact of rock lithology on river chemical composition in the permafrost zone of the WSL, relative to the permafrost-free regions. Therefore, the present study demonstrates significant and previously underestimated atmospheric input of many major and trace elements to their riverine fluxes during spring floods. A broader impact of this result is that current estimations of river water fluxes response to climate warming in high latitudes may be unwarranted without detailed analysis of winter precipitation.

  12. Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

    Science.gov (United States)

    Skofronick-Jackson, Gail M.; Johnson, Benjamin T.; Munchak, S. Joseph

    2013-01-01

    There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

  13. Impact of climate change in Switzerland on socioeconomic snow indices

    Science.gov (United States)

    Schmucki, Edgar; Marty, Christoph; Fierz, Charles; Weingartner, Rolf; Lehning, Michael

    2017-02-01

    Snow is a key element for many socioeconomic activities in mountainous regions. Due to the sensitivity of the snow cover to variations of temperature and precipitation, major changes caused by climate change are expected to happen. We analyze the evolution of some key snow indices under future climatic conditions. Ten downscaled and postprocessed climate scenarios from the ENSEMBLES database have been used to feed the physics-based snow model SNOWPACK. The projected snow cover has been calculated for 11 stations representing the diverse climates found in Switzerland. For the first time, such a setup is used to reveal changes in frequently applied snow indices and their implications on various socioeconomic sectors. Toward the end of the twenty-first century, a continuous snow cover is likely only guaranteed at high elevations above 2000 m a.s.l., whereas at mid elevations (1000-1700 m a.s.l.), roughly 50 % of all winters might be characterized by an ephemeral snow cover. Low elevations (below 500 m a.s.l.) are projected to experience only 2 days with snowfall per year and show the strongest relative reductions in mean winter snow depth of around 90 %. The range of the mean relative reductions of the snow indices is dominated by uncertainties from different GCM-RCM projections and amounts to approximately 30 %. Despite these uncertainties, all snow indices show a clear decrease in all scenario periods and the relative reductions increase toward lower elevations. These strong reductions can serve as a basis for policy makers in the fields of tourism, ecology, and hydropower.

  14. Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors

    Directory of Open Access Journals (Sweden)

    Claire E. Bulgin

    2018-04-01

    Full Text Available Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified. We present a new approach to do so, applied here to the Advanced Along-Track Scanning Radiometer (AATSR. We use an ensemble of cloud masks based on independent methodologies to investigate the magnitude of cloud detection uncertainties in area-average Land Surface Temperature (LST retrieval. We find that at a grid resolution of 625 km 2 (commensurate with a 0.25 ∘ grid size at the tropics, cloud detection uncertainties are positively correlated with cloud-cover fraction in the cell and are larger during the day than at night. Daytime cloud detection uncertainties range between 2.5 K for clear-sky fractions of 10–20% and 1.03 K for clear-sky fractions of 90–100%. Corresponding night-time uncertainties are 1.6 K and 0.38 K, respectively. Cloud detection uncertainty shows a weaker positive correlation with the number of biomes present within a grid cell, used as a measure of heterogeneity in the background against which the cloud detection must operate (e.g., surface temperature, emissivity and reflectance. Uncertainty due to cloud detection errors is strongly dependent on the dominant land cover classification. We find cloud detection uncertainties of a magnitude of 1.95 K over permanent snow and ice, 1.2 K over open forest, 0.9–1 K over bare soils and 0.09 K over mosaic cropland, for a standardised clear-sky fraction of 74.2%. As the uncertainties arising from cloud detection errors are of a significant magnitude for many surface types and spatially heterogeneous where land classification varies rapidly, LST data producers are encouraged to quantify cloud-related uncertainties in gridded products.

  15. Impact of model resolution on simulated wind, drifting snow and surface mass balance in Terre Adélie, East Antarctica

    NARCIS (Netherlands)

    Lenaerts, J.T.M.|info:eu-repo/dai/nl/314850163; van den Broeke, M.R.|info:eu-repo/dai/nl/073765643; Scarchilli, C.; Agosta, C.

    2012-01-01

    This paper presents the impact of model resolution on the simulated wind speed, drifting snow climate and surface mass balance (SMB) of Terre Ad´elie and its surroundings, East Antarctica. We compare regional climate model simulations at 27 and 5.5 km resolution for the year 2009. The wind speed

  16. Temperature signal in suspended sediment export from an Alpine catchment

    Directory of Open Access Journals (Sweden)

    A. Costa

    2018-01-01

    Full Text Available Suspended sediment export from large Alpine catchments ( >  1000 km2 over decadal timescales is sensitive to a number of factors, including long-term variations in climate, the activation–deactivation of different sediment sources (proglacial areas, hillslopes, etc., transport through the fluvial system, and potential anthropogenic impacts on the sediment flux (e.g. through impoundments and flow regulation. Here, we report on a marked increase in suspended sediment concentrations observed near the outlet of the upper Rhône River Basin in the mid-1980s. This increase coincides with a statistically significant step-like increase in basin-wide mean air temperature. We explore the possible explanations of the suspended sediment rise in terms of changes in water discharge (transport capacity, and the activation of different potential sources of fine sediment (sediment supply in the catchment by hydroclimatic forcing. Time series of precipitation and temperature-driven snowmelt, snow cover, and ice melt simulated with a spatially distributed degree-day model, together with erosive rainfall on snow-free surfaces, are tested to explore possible reasons for the rise in suspended sediment concentration. We show that the abrupt change in air temperature reduced snow cover and the contribution of snowmelt, and enhanced ice melt. The results of statistical tests show that the onset of increased ice melt was likely to play a dominant role in the suspended sediment concentration rise in the mid-1980s. Temperature-driven enhanced melting of glaciers, which cover about 10 % of the catchment surface, can increase suspended sediment yields through an increased contribution of sediment-rich glacial meltwater, increased sediment availability due to glacier recession, and increased runoff from sediment-rich proglacial areas. The reduced extent and duration of snow cover in the catchment are also potential contributors to the rise in suspended sediment

  17. Variability of {sup 10}Be and {delta}{sup 18}O in snow pits from Greenland and a surface traverse from Antarctica

    Energy Technology Data Exchange (ETDEWEB)

    Berggren, A.-M. [Dept. of Earth Sciences, Uppsala University, Villav. 16, 752 36 Uppsala (Sweden); Aldahan, A., E-mail: ala.aldahan@geo.uu.se [Dept. of Earth Sciences, Uppsala University, Villav. 16, 752 36 Uppsala (Sweden); Dept. of Geology, United Arab Emirates University, P.O. Box 17551 Al Ain (United Arab Emirates); Possnert, G. [Tandem Laboratory, Uppsala University, P.O. Box 529, 751 20 Uppsala (Sweden); Hansson, M. [Dept. of Physical Geography and Quaternary Geology, Stockholm University, 106 91 Stockholm (Sweden); Steen-Larsen, H.C. [Centre for Ice and Climate, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej, 30,2100 Copenhagen (Denmark); Sturevik Storm, A. [Dept. of Earth Sciences, Uppsala University, Villav. 16, 752 36 Uppsala (Sweden); Moerth, C.-M. [Dept. of Geology and Geochemistry, Stockholm University, 106 91 Stockholm (Sweden); Murad, A. [Dept. of Geology, United Arab Emirates University, P.O. Box 17551 Al Ain (United Arab Emirates)

    2013-01-15

    To examine temporal variability of {sup 10}Be in glacial ice, we sampled snow to a depth of 160 cm at the NEEM (North Greenland Eemian Ice Drilling) drilling site in Greenland. The samples span three years between the summers of 2006 and 2009. At the same time, spatial variability of {sup 10}Be in glacial ice was explored through collection of the upper {approx}5 cm of surface snow in Antarctica during part of the Swedish-Japanese traverse from Svea to Syowa station during the austral summer in 2007-2008. The results of the Greenlandic {sup 10}Be snow suggested variable concentrations that apparently do not clearly reflect the seasonal change as indicated by the {delta}{sup 18}O data. The {sup 10}Be concentration variability most likely reflects also effects of aerosol loading and deposition pathways, possibly in combination with post-depositional processes. The Antarctic traverse data expose a negative correlation between {sup 10}Be and {delta}{sup 18}O, while there are weaker but still significant correlations to altitude and distance to the coast (approximated by the distance to the 70th latitude). These relationships indicate that geographical factors, mainly the proximity to the coast, may strongly affect {sup 10}Be concentrations in snow in Queen Maud Land, Antarctica.

  18. The impact of atmospheric mineral aerosol deposition on the albedo of snow & sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?

    Directory of Open Access Journals (Sweden)

    M. L. Lamare

    2016-01-01

    Full Text Available Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light-absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiative-transfer model (TUV-snow show that the effects of mineral aerosol deposits are strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass ratio of mineral dust has little effect on albedo. On the contrary, the surface albedo of two snowpacks of equal depth, containing the same mineral aerosol mass ratio, is similar, whether the loading is uniformly distributed or concentrated in multiple layers, regardless of their position or spacing. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.

  19. Measuring snow water equivalent from common-offset GPR records through migration velocity analysis

    Science.gov (United States)

    St. Clair, James; Holbrook, W. Steven

    2017-12-01

    Many mountainous regions depend on seasonal snowfall for their water resources. Current methods of predicting the availability of water resources rely on long-term relationships between stream discharge and snowpack monitoring at isolated locations, which are less reliable during abnormal snow years. Ground-penetrating radar (GPR) has been shown to be an effective tool for measuring snow water equivalent (SWE) because of the close relationship between snow density and radar velocity. However, the standard methods of measuring radar velocity can be time-consuming. Here we apply a migration focusing method originally developed for extracting velocity information from diffracted energy observed in zero-offset seismic sections to the problem of estimating radar velocities in seasonal snow from common-offset GPR data. Diffractions are isolated by plane-wave-destruction (PWD) filtering and the optimal migration velocity is chosen based on the varimax norm of the migrated image. We then use the radar velocity to estimate snow density, depth, and SWE. The GPR-derived SWE estimates are within 6 % of manual SWE measurements when the GPR antenna is coupled to the snow surface and 3-21 % of the manual measurements when the antenna is mounted on the front of a snowmobile ˜ 0.5 m above the snow surface.

  20. Nitrate Deposition to Surface Snow at Summit, Greenland, Following the 9 November 2000 Solar Proton Event

    Science.gov (United States)

    Duderstadt, Katharine A.; Dibb, Jack E.; Schwadron, Nathan A.; Spence, Harlan E.; Jackman, Charles Herbert; Randall, Cora E.; Solomon, Stanley C.; Mills, Michael J.

    2014-01-01

    This study considers whether spurious peaks in nitrate ions in snow sampled at Summit, Greenland from August 2000 to August 2002 are related to solar proton events. After identifying tropospheric sources of nitrate on the basis of correlations with sulfate, ammonium, sodium, and calcium, we use the three-dimensional global Whole Atmosphere Community Climate Model (WACCM) to examine unaccounted for nitrate spikes. Model calculations confirm that solar proton events significantly impact HOx, NOx, and O3 levels in the mesosphere and stratosphere during the weeks and months following the major 9 November 2000 solar proton event. However, SPE-enhanced NOy calculated within the atmospheric column is too small to account for the observed nitrate ion peaks in surface snow. Instead, our WACCM results suggest that nitrate spikes not readily accounted for by measurement correlations are likely of anthropogenic origin. These results, consistent with other recent studies, imply that nitrate spikes in ice cores are not suitable proxies for individual SPEs and motivate the need to identify alternative proxies.

  1. Integration of snow management practices into a detailed snow pack model

    Science.gov (United States)

    Spandre, Pierre; Morin, Samuel; Lafaysse, Matthieu; Lejeune, Yves; François, Hugues; George-Marcelpoil, Emmanuelle

    2016-04-01

    The management of snow on ski slopes is a key socio-economic and environmental issue in mountain regions. Indeed the winter sports industry has become a very competitive global market although this economy remains particularly sensitive to weather and snow conditions. The understanding and implementation of snow management in detailed snowpack models is a major step towards a more realistic assessment of the evolution of snow conditions in ski resorts concerning past, present and future climate conditions. Here we describe in a detailed manner the integration of snow management processes (grooming, snowmaking) into the snowpack model Crocus (Spandre et al., Cold Reg. Sci. Technol., in press). The effect of the tiller is explicitly taken into account and its effects on snow properties (density, snow microstructure) are simulated in addition to the compaction induced by the weight of the grooming machine. The production of snow in Crocus is carried out with respect to specific rules and current meteorological conditions. Model configurations and results are described in detail through sensitivity tests of the model of all parameters related to snow management processes. In-situ observations were carried out in four resorts in the French Alps during the 2014-2015 winter season considering for each resort natural, groomed only and groomed plus snowmaking conditions. The model provides realistic simulations of the snowpack properties with respect to these observations. The main uncertainty pertains to the efficiency of the snowmaking process. The observed ratio between the mass of machine-made snow on ski slopes and the water mass used for production was found to be lower than was expected from the literature, in every resort. The model now referred to as "Crocus-Resort" has been proven to provide realistic simulations of snow conditions on ski slopes and may be used for further investigations. Spandre, P., S. Morin, M. Lafaysse, Y. Lejeune, H. François and E. George

  2. Role of snow-albedo feedback in higher elevation warming over the Himalayas, Tibetan Plateau and Central Asia

    International Nuclear Information System (INIS)

    Ghatak, Debjani; Sinsky, Eric; Miller, James

    2014-01-01

    Recent literature has shown that surface air temperature (SAT) in many high elevation regions, including the Tibetan Plateau (TP) has been increasing at a faster rate than at their lower elevation counterparts. We investigate projected future changes in SAT in the TP and the surrounding high elevation regions (between 25°–45°N and 50°–120°E) and the potential role snow-albedo feedback may have on amplified warming there. We use the Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory (GFDL) model which have different spatial resolutions as well as different climate sensitivities. We find that surface albedo (SA) decreases more at higher elevations than at lower elevations owing to the retreat of the 0 °C isotherm and the associated retreat of the snow line. Both models clearly show amplified warming over Central Asian mountains, the Himalayas, the Karakoram and Pamir during spring. Our results suggest that the decrease of SA and the associated increase in absorbed solar radiation (ASR) owing to the loss of snowpack play a significant role in triggering the warming over the same regions. Decreasing cloud cover in spring also contributes to an increase in ASR over some of these regions in CCSM4. Although the increase in SAT and the decrease in SA are greater in GFDL than CCSM4, the sensitivity of SAT to changes in SA is the same at the highest elevations for both models during spring; this suggests that the climate sensitivity between models may differ, in part, owing to their corresponding treatments of snow cover, snow melt and the associated snow/albedo feedback. (letter)

  3. Post-depositional enrichment of black soot in snow-pack and accelerated melting of Tibetan glaciers

    International Nuclear Information System (INIS)

    Xu Baiqing; Joswiak, Daniel R; Zhao Huabiao; Cao Junji; Liu Xianqin; He Jianqiao

    2012-01-01

    The post-depositional enrichment of black soot in snow-pack was investigated by measuring the redistribution of black soot along monthly snow-pits on a Tien Shan glacier. The one-year experiment revealed that black soot was greatly enriched, defined as the ratio of concentration to original snow concentration, in the unmelted snow-pack by at least an order of magnitude. Greatest soot enrichment was observed in the surface snow and the lower firn-pack within the melt season percolation zone. Black carbon (BC) concentrations as high as 400 ng g −1 in the summer surface snow indicate that soot can significantly contribute to glacier melt. BC concentrations reaching 3000 ng g −1 in the bottom portion of the firn pit are especially concerning given the expected equilibrium-line altitude (ELA) rise associated with future climatic warming, which would expose the dirty underlying firn and ice. Since most of the accumulation area on Tibetan glaciers is within the percolation zone where snow densification is characterized by melting and refreezing, the enrichment of black soot in the snow-pack is of foremost importance. Results suggest the effect of black soot on glacier melting may currently be underestimated. (letter)

  4. Use of gamma surveys from the aircraft for hydrological forecasts on the area with irregular snow pack

    Energy Technology Data Exchange (ETDEWEB)

    Vershinina, L K

    1979-01-01

    Gamma snow surveys from the aircraft based on the measurements of the attenuation of gamma-radiation of soils by the snow pack are discussed. Radiation rate depends on the amount of water on the soil surface and in the top layer 30 to 40 cm deep. Therefore, if measurements are made twice (without snow and with snow pack available) water equivalent of snow cover may be determined only when soil moisture content changes do not occur during the period between the dates of gamma surveys. In the areas with frequent winter thaws, standard land snow surveys do not provide snow storage evaluation with the accuracy sufficient for spring flow prediction. It is shown that when gamma-radiation of absolutely dry soils determined at the laboratory is known as well as of naturally moistened soils during the periods of gamma surveys of the snow pack from the aircraft, and when data is available on soil moisture content obtained from the measurements at the base land network, then a reliable estimation of snow storage on the watershed surfaces in the regions with irregular snow cover is quite possible. This ensures a significant accuracy increase of spring snow melt flood forecasting, particularly concerning winters with little snow.

  5. Use of gamma surveys from the airraft for hydrological forecasts on the area with irregular snow pack

    Energy Technology Data Exchange (ETDEWEB)

    Vershinina, L K [State Hydrological Institute, Leningrad (USSR)

    1979-01-01

    Gamma snow surveys from aircraft based on the measurement of the attenuation of gamma-radiation of soils by the snow pack are discussed. Radiation rate depends on the amount of water on the soil surface and in the top layer 30 to 40 cm deep. Therefore, if measurements are made twice (without snow and with snow pack available) the water equivalent of the snow cover may be determined only in cases when soil moisture content changes do not occur during the period between the dates of gamma surveys. In areas with frequent winter thaws standard land snow surveys do not provide snow storage evaluation with accuracy sufficient for spring flow prediction. It is shown that when gamma-radiation of absolutely dry soils determined at the laboratory is known, as well as of naturally moistened soils during the periods of gamma surveys of the snow pack from aircraft, and when data is available on soil moisture content obtained from measurements at the base land network, then a reliable estimation of snow storage on the watershed surfaces in regions with irregular snow cover is quite possible. This ensures a significant accuracy increase in spring snow melt flood forecasting, in particular during winters with little snow.

  6. Mapping snow depth in alpine terrain with remotely piloted aerial systems and structure-from-motion photogrammetry - first results from a pilot study

    Science.gov (United States)

    Adams, Marc; Fromm, Reinhard; Bühler, Yves; Bösch, Ruedi; Ginzler, Christian

    2016-04-01

    Detailed information on the spatio-temporal distribution of seasonal snow in the alpine terrain plays a major role for the hydrological cycle, natural hazard management, flora and fauna, as well as tourism. Current methods are mostly only valid on a regional scale or require a trade-off between the data's availability, cost and resolution. During a one-year pilot study, we investigated the potential of remotely piloted aerial systems (RPAS) and structure-from-motion photogrammetry for snow depth mapping. We employed multi-copter and fixed-wing RPAS, equipped with different low-cost, off-the shelf sensors, at four test sites in Austria and Switzerland. Over 30 flights were performed during the winter 2014/15, where different camera settings, filters and lenses, as well as data collection routines were tested. Orthophotos and digital surface models (DSM) where calculated from the imagery using structure-from-motion photogrammetry software. Snow height was derived by subtracting snow-free from snow-covered DSMs. The RPAS-results were validated against data collected using a variety of well-established remote sensing (i.e. terrestrial laser scanning, large frame aerial sensors) and in-situ measurement techniques. The results show, that RPAS i) are able to map snow depth within accuracies of 0.07-0.15 m root mean square error (RMSE), when compared to traditional in-situ data; ii) can be operated at lower cost, easier repeatability, less operational constraints and higher GSD than large frame aerial sensors on-board manned aircraft, while achieving significantly higher accuracies; iii) are able to acquire meaningful data even under harsh environmental conditions above 2000 m a.s.l. (turbulence, low temperature and high irradiance, low air density). While providing a first prove-of-concept, the study also showed future challenges and limitations of RPAS-based snow depth mapping, including a high dependency on correct co-registration of snow-free and snow-covered height

  7. California's Snow Gun and its implications for mass balance predictions under greenhouse warming

    Science.gov (United States)

    Howat, I.; Snyder, M.; Tulaczyk, S.; Sloan, L.

    2003-12-01

    Precipitation has received limited treatment in glacier and snowpack mass balance models, largely due to the poor resolution and confidence of precipitation predictions relative to temperature predictions derived from atmospheric models. Most snow and glacier mass balance models rely on statistical or lapse rate-based downscaling of general or regional circulation models (GCM's and RCM's), essentially decoupling sub-grid scale, orographically-driven evolution of atmospheric heat and moisture. Such models invariably predict large losses in the snow and ice volume under greenhouse warming. However, positive trends in the mass balance of glaciers in some warming maritime climates, as well as at high elevations of the Greenland Ice Sheet, suggest that increased precipitation may play an important role in snow- and glacier-climate interactions. Here, we present a half century of April snowpack data from the Sierra Nevada and Cascade mountains of California, USA. This high-density network of snow-course data indicates that a gain in winter snow accumulation at higher elevations has compensated loss in snow volume at lower elevations by over 50% and has led to glacier expansion on Mt. Shasta. These trends are concurrent with a region-wide increase in winter temperatures up to 2° C. They result from the orographic lifting and saturation of warmer, more humid air leading to increased precipitation at higher elevations. Previous studies have invoked such a "Snow Gun" effect to explain contemporaneous records of Tertiary ocean warming and rapid glacial expansion. A climatological context of the California's "snow gun" effect is elucidated by correlation between the elevation distribution of April SWE observations and the phase of the Pacific Decadal Oscillation and the El Nino Southern Oscillation, both controlling the heat and moisture delivered to the U.S. Pacific coast. The existence of a significant "Snow Gun" effect presents two challenges to snow and glacier mass

  8. Concentrations and source regions of light-absorbing particles in snow/ice in northern Pakistan and their impact on snow albedo

    Science.gov (United States)

    Gul, Chaman; Praveen Puppala, Siva; Kang, Shichang; Adhikary, Bhupesh; Zhang, Yulan; Ali, Shaukat; Li, Yang; Li, Xiaofei

    2018-04-01

    Black carbon (BC), water-insoluble organic carbon (OC), and mineral dust are important particles in snow and ice which significantly reduce albedo and accelerate melting. Surface snow and ice samples were collected from the Karakoram-Himalayan region of northern Pakistan during 2015 and 2016 in summer (six glaciers), autumn (two glaciers), and winter (six mountain valleys). The average BC concentration overall was 2130 ± 1560 ng g-1 in summer samples, 2883 ± 3439 ng g-1 in autumn samples, and 992 ± 883 ng g-1 in winter samples. The average water-insoluble OC concentration overall was 1839 ± 1108 ng g-1 in summer samples, 1423 ± 208 ng g-1 in autumn samples, and 1342 ± 672 ng g-1 in winter samples. The overall concentration of BC, OC, and dust in aged snow samples collected during the summer campaign was higher than the concentration in ice samples. The values are relatively high compared to reports by others for the Himalayas and the Tibetan Plateau. This is probably the result of taking more representative samples at lower elevation where deposition is higher and the effects of ageing and enrichment are more marked. A reduction in snow albedo of 0.1-8.3 % for fresh snow and 0.9-32.5 % for aged snow was calculated for selected solar zenith angles during daytime using the Snow, Ice, and Aerosol Radiation (SNICAR) model. The daily mean albedo was reduced by 0.07-12.0 %. The calculated radiative forcing ranged from 0.16 to 43.45 W m-2 depending on snow type, solar zenith angle, and location. The potential source regions of the deposited pollutants were identified using spatial variance in wind vector maps, emission inventories coupled with backward air trajectories, and simple region-tagged chemical transport modeling. Central, south, and west Asia were the major sources of pollutants during the sampling months, with only a small contribution from east Asia. Analysis based on the Weather Research and Forecasting (WRF-STEM) chemical transport model identified a

  9. Observational evidence of changes in global snow and ice cover

    International Nuclear Information System (INIS)

    Barry, R.G.

    1990-01-01

    Sources of observational data on recent variations in the seasonal extent of snow cover and sea ice, of the terminal position and volume of alpine glaciers, and of ground temperature profiles in areas of permafrost are briefly reviewed. Recent evidence of changes in these variables is then examined. The extent of seasonal snow cover in the Northern hemisphere and of sea ice in both hemispheres has fluctuated irregularly over the last 15-20 years with a range of about 10-15% in each case. There is no clear evidence of any recent trends, despite general global warming. In contrast, most glaciers retreated and thinned from before the turn of the century until the 1960s and alaskan permafrost temperatures have risen 2-4 C per century. Recently, glacier advances have been noted, perhaps in response to increased accumulation. Problems of linking climate forcing and snow/ice responses are discussed

  10. Impacts of 1, 1.5, and 2 Degree Warming on Arctic Terrestrial Snow and Sea Ice

    Science.gov (United States)

    Derksen, C.; Mudryk, L.; Howell, S.; Flato, G. M.; Fyfe, J. C.; Gillett, N. P.; Sigmond, M.; Kushner, P. J.; Dawson, J.; Zwiers, F. W.; Lemmen, D.; Duguay, C. R.; Zhang, X.; Fletcher, C. G.; Dery, S. J.

    2017-12-01

    The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC) established the global temperature goal of "holding the increase in the global average temperature to below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels." In this study, we utilize multiple gridded snow and sea ice products (satellite retrievals; assimilation systems; physical models driven by reanalyses) and ensembles of climate model simulations to determine the impacts of observed warming, and project the relative impacts of the UNFCC future warming targets on Arctic seasonal terrestrial snow and sea ice cover. Observed changes during the satellite era represent the response to approximately 1°C of global warming. Consistent with other studies, analysis of the observational record (1970's to present) identifies changes including a shorter snow cover duration (due to later snow onset and earlier snow melt), significant reductions in spring snow cover and summer sea ice extent, and the loss of a large proportion of multi-year sea ice. The spatial patterns of observed snow and sea ice loss are coherent across adjacent terrestrial/marine regions. There are strong pattern correlations between snow and temperature trends, with weaker association between sea ice and temperature due to the additional influence of dynamical effects such wind-driven redistribution of sea ice. Climate model simulations from the Coupled Model Inter-comparison Project Phase 5(CMIP-5) multi-model ensemble, large initial condition ensembles of the Community Earth System Model (CESM) and Canadian Earth System Model (CanESM2) , and warming stabilization simulations from CESM were used to identify changes in snow and ice under further increases to 1.5°C and 2°C warming. The model projections indicate these levels of warming will be reached over the coming 2-4 decades. Warming to 1.5°C results in an increase in the

  11. Twenty-four year record of Northern Hemisphere snow cover derived from passive microwave remote sensing

    Science.gov (United States)

    Armstrong, Richard L.; Brodzik, Mary Jo

    2003-04-01

    Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. It is now possible to monitor the global fluctuation of snow cover over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a smiliar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible statellite data and the visible data typically show higher monthly variability. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as on into the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the negative spectral gradient driving the passive microwave algorithm

  12. First Gridded Spatial Field Reconstructions of Snow from Tree Rings

    Science.gov (United States)

    Coulthard, B. L.; Anchukaitis, K. J.; Pederson, G. T.; Alder, J. R.; Hostetler, S. W.; Gray, S. T.

    2017-12-01

    Western North America's mountain snowpacks provide critical water resources for human populations and ecosystems. Warmer temperatures and changing precipitation patterns will increasingly alter the quantity, extent, and persistence of snow in coming decades. A comprehensive understanding of the causes and range of long-term variability in this system is required for forecasting future anomalies, but snowpack observations are limited and sparse. While individual tree ring-based annual snowpack reconstructions have been developed for specific regions and mountain ranges, we present here the first collection of spatially-explicit gridded field reconstructions of seasonal snowpack within the American Rocky Mountains. Capitalizing on a new western North American snow-sensitive network of over 700 tree-ring chronologies, as well as recent advances in PRISM-based snow modeling, our gridded reconstructions offer a full space-time characterization of snow and associated water resource fluctuations over several centuries. The quality of reconstructions is evaluated against existing observations, proxy-records, and an independently-developed first-order monthly snow model.

  13. Comparison of Commonly-Used Microwave Radiative Transfer Models for Snow Remote Sensing

    Science.gov (United States)

    Royer, Alain; Roy, Alexandre; Montpetit, Benoit; Saint-Jean-Rondeau, Olivier; Picard, Ghislain; Brucker, Ludovic; Langlois, Alexandre

    2017-01-01

    This paper reviews four commonly-used microwave radiative transfer models that take different electromagnetic approaches to simulate snow brightness temperature (T(sub B)): the Dense Media Radiative Transfer - Multi-Layer model (DMRT-ML), the Dense Media Radiative Transfer - Quasi-Crystalline Approximation Mie scattering of Sticky spheres (DMRT-QMS), the Helsinki University of Technology n-Layers model (HUT-nlayers) and the Microwave Emission Model of Layered Snowpacks (MEMLS). Using the same extensively measured physical snowpack properties, we compared the simulated T(sub B) at 11, 19 and 37 GHz from these four models. The analysis focuses on the impact of using different types of measured snow microstructure metrics in the simulations. In addition to density, snow microstructure is defined for each snow layer by grain optical diameter (Do) and stickiness for DMRT-ML and DMRT-QMS, mean grain geometrical maximum extent (D(sub max)) for HUT n-layers and the exponential correlation length for MEMLS. These metrics were derived from either in-situ measurements of snow specific surface area (SSA) or macrophotos of grain sizes (D(sub max)), assuming non-sticky spheres for the DMRT models. Simulated T(sub B) sensitivity analysis using the same inputs shows relatively consistent T(sub B) behavior as a function of Do and density variations for the vertical polarization (maximum deviation of 18 K and 27 K, respectively), while some divergences appear in simulated variations for the polarization ratio (PR). Comparisons with ground based radiometric measurements show that the simulations based on snow SSA measurements have to be scaled with a model-specific factor of Do in order to minimize the root mean square error (RMSE) between measured and simulated T(sub B). Results using in-situ grain size measurements (SSA or D(sub max), depending on the model) give a mean T(sub B) RMSE (19 and 37 GHz) of the order of 16-26 K, which is similar for all models when the snow

  14. The Scattering Properties of Natural Terrestrial Snows versus Icy Satellite Surfaces

    Science.gov (United States)

    Domingue, Deborah; Hartman, Beth; Verbiscer, Anne

    1997-01-01

    Our comparisons of the single particle scattering behavior of terrestrial snows and icy satellite regoliths to the laboratory particle scattering measurements of McGuire and Hapke demonstrate that the differences between icy satellite regoliths and their terrestrial counterparts are due to particle structures and textures. Terrestrial snow particle structures define a region in the single particle scattering function parameter space separate from the regions defined by the McGuire and Hapke artificial laboratory particles. The particle structures and textures of the grains composing icy satellites regoliths are not simple or uniform but consist of a variety of particle structure and texture types, some of which may be a combination of the particle types investigated by McGuire and Hapke.

  15. Iron snow in the Martian core?

    Science.gov (United States)

    Davies, Christopher J.; Pommier, Anne

    2018-01-01

    The decline of Mars' global magnetic field some 3.8-4.1 billion years ago is thought to reflect the demise of the dynamo that operated in its liquid core. The dynamo was probably powered by planetary cooling and so its termination is intimately tied to the thermochemical evolution and present-day physical state of the Martian core. Bottom-up growth of a solid inner core, the crystallization regime for Earth's core, has been found to produce a long-lived dynamo leading to the suggestion that the Martian core remains entirely liquid to this day. Motivated by the experimentally-determined increase in the Fe-S liquidus temperature with decreasing pressure at Martian core conditions, we investigate whether Mars' core could crystallize from the top down. We focus on the "iron snow" regime, where newly-formed solid consists of pure Fe and is therefore heavier than the liquid. We derive global energy and entropy equations that describe the long-timescale thermal and magnetic history of the core from a general theory for two-phase, two-component liquid mixtures, assuming that the snow zone is in phase equilibrium and that all solid falls out of the layer and remelts at each timestep. Formation of snow zones occurs for a wide range of interior and thermal properties and depends critically on the initial sulfur concentration, ξ0. Release of gravitational energy and latent heat during growth of the snow zone do not generate sufficient entropy to restart the dynamo unless the snow zone occupies at least 400 km of the core. Snow zones can be 1.5-2 Gyrs old, though thermal stratification of the uppermost core, not included in our model, likely delays onset. Models that match the available magnetic and geodetic constraints have ξ0 ≈ 10% and snow zones that occupy approximately the top 100 km of the present-day Martian core.

  16. Estimating water equivalent snow depth from related meteorological variables

    International Nuclear Information System (INIS)

    Steyaert, L.T.; LeDuc, S.K.; Strommen, N.D.; Nicodemus, M.L.; Guttman, N.B.

    1980-05-01

    Engineering design must take into consideration natural loads and stresses caused by meteorological elements, such as, wind, snow, precipitation and temperature. The purpose of this study was to determine a relationship of water equivalent snow depth measurements to meteorological variables. Several predictor models were evaluated for use in estimating water equivalent values. These models include linear regression, principal component regression, and non-linear regression models. Linear, non-linear and Scandanavian models are used to generate annual water equivalent estimates for approximately 1100 cooperative data stations where predictor variables are available, but which have no water equivalent measurements. These estimates are used to develop probability estimates of snow load for each station. Map analyses for 3 probability levels are presented

  17. Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments

    Science.gov (United States)

    Griessinger, Nena; Seibert, Jan; Magnusson, Jan; Jonas, Tobias

    2016-09-01

    In Alpine catchments, snowmelt is often a major contribution to runoff. Therefore, modeling snow processes is important when concerned with flood or drought forecasting, reservoir operation and inland waterway management. In this study, we address the question of how sensitive hydrological models are to the representation of snow cover dynamics and whether the performance of a hydrological model can be enhanced by integrating data from a dedicated external snow monitoring system. As a framework for our tests we have used the hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) in the version HBV-light, which has been applied in many hydrological studies and is also in use for operational purposes. While HBV originally follows a temperature-index approach with time-invariant calibrated degree-day factors to represent snowmelt, in this study the HBV model was modified to use snowmelt time series from an external and spatially distributed snow model as model input. The external snow model integrates three-dimensional sequential assimilation of snow monitoring data with a snowmelt model, which is also based on the temperature-index approach but uses a time-variant degree-day factor. The following three variations of this external snow model were applied: (a) the full model with assimilation of observational snow data from a dense monitoring network, (b) the same snow model but with data assimilation switched off and (c) a downgraded version of the same snow model representing snowmelt with a time-invariant degree-day factor. Model runs were conducted for 20 catchments at different elevations within Switzerland for 15 years. Our results show that at low and mid-elevations the performance of the runoff simulations did not vary considerably with the snow model version chosen. At higher elevations, however, best performance in terms of simulated runoff was obtained when using the snowmelt time series from the snow model, which utilized data assimilation

  18. Observed metre scale horizontal variability of elemental carbon in surface snow

    International Nuclear Information System (INIS)

    Svensson, J; Lihavainen, H; Ström, J; Hansson, M; Kerminen, V-M

    2013-01-01

    Surface snow investigated for its elemental carbon (EC) concentration, based on a thermal–optical method, at two different sites during winter and spring of 2010 demonstrates metre scale horizontal variability in concentration. Based on the two sites sampled, a clean and a polluted site, the clean site (Arctic Finland) presents the greatest variability. In side-by-side ratios between neighbouring samples, 5 m apart, a ratio of around two was observed for the clean site. The median for the polluted site had a ratio of 1.2 between neighbouring samples. The results suggest that regions exposed to snowdrift may be more sensitive to horizontal variability in EC concentration. Furthermore, these results highlight the importance of carefully choosing sampling sites and timing, as each parameter will have some effect on EC variability. They also emphasize the importance of gathering multiple samples from a site to obtain a representative value for the area. (letter)

  19. A snow cover climatology for the Pyrenees from MODIS snow products

    Science.gov (United States)

    Gascoin, S.; Hagolle, O.; Huc, M.; Jarlan, L.; Dejoux, J.-F.; Szczypta, C.; Marti, R.; Sanchez, R.

    2015-05-01

    The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively, for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snowpack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50% of the

  20. Modelling snow accumulation on Greenland in Eemian, glacial inception, and modern climates in a GCM

    Directory of Open Access Journals (Sweden)

    H. J. Punge

    2012-11-01

    Full Text Available Changing climate conditions on Greenland influence the snow accumulation rate and surface mass balance (SMB on the ice sheet and, ultimately, its shape. This can in turn affect local climate via orography and albedo variations and, potentially, remote areas via changes in ocean circulation triggered by melt water or calving from the ice sheet. Examining these interactions in the IPSL global model requires improving the representation of snow at the ice sheet surface. In this paper, we present a new snow scheme implemented in LMDZ, the atmospheric component of the IPSL coupled model. We analyse surface climate and SMB on the Greenland ice sheet under insolation and oceanic boundary conditions for modern, but also for two different past climates, the last glacial inception (115 kyr BP and the Eemian (126 kyr BP. While being limited by the low resolution of the general circulation model (GCM, present-day SMB is on the same order of magnitude as recent regional model findings. It is affected by a moist bias of the GCM in Western Greenland and a dry bias in the north-east. Under Eemian conditions, the SMB decreases largely, and melting affects areas in which the ice sheet surface is today at high altitude, including recent ice core drilling sites as NEEM. In contrast, glacial inception conditions lead to a higher mass balance overall due to the reduced melting in the colder summer climate. Compared to the widely applied positive degree-day (PDD parameterization of SMB, our direct modelling results suggest a weaker sensitivity of SMB to changing climatic forcing. For the Eemian climate, our model simulations using interannually varying monthly mean forcings for the ocean surface temperature and sea ice cover lead to significantly higher SMB in southern Greenland compared to simulations forced with climatological monthly means.

  1. Regional pattern of snow characteristics around Antarctic Lake Vostok

    Science.gov (United States)

    Vladimirova, Diana; Ekaykin, Alexey; Popov, Sergey; Shibaev, Yuriy; Kozachek, Anna; Lipenkov, Vladimir

    2015-04-01

    Since 1998 Russian Antarctic Expedition has organized several scientific traverses in the region of subglacial Lake Vostok mainly devoted to the radar echo and seismic sounding of the glacier and water (the results have been published elsewhere). Along with the geophysical studies, a number of glaciological investigations have been carried out: snow pit digging, installation of accumulation stakes, snow sampling to study the stable water isotope content. Here we for the first time present a synthesis of these works and demonstrate a series of maps that characterize the snow density, isotope content and accumulation rate the studied region. A general tendency of the snow accumulation rate and isotope content is a significant increase from south (south-west) to north (north-east) from 35 to 23 mm w.e. per year and from -53,3 ‰ to -57,3 ‰ for delta oxygen-18 respectively, which likely reflects the continental-scale pattern, i.e., increase from inland to the coast. Deuterium excess varies from 11,7 ‰ to 16,3 ‰ is negatively correlated with the isotope content, which is typical for central Antarctica. The snow density demonstrate different pattern: higher values offshore the lake (up to 0,356 g/cm^3), and lower values within the lake's shoreline (lower limit is 0,328 g/cm^3). We suggest that this is related to the katabatic wind activity: very flat nearly horizontal surface of the glacier above the lake is not favorable for the strong winds, which leads to lower surface snow density. Superimposed on the main trend is the regional pattern, namely, curved contour lines in the middle part of the lake. We suggest that it may be related to the local anomalies of the snow drift by wind. Indeed, on the satellite images of the lake one can easily see a snowdrift stretching from the lake's western shore downwind in the middle part of the lake. The isolines of delta oxygen-18 and deuterium excess become perpendicular to each other in the north part of the lake which also

  2. Snow Cover Monitoring Using MODIS Data in Liaoning Province, Northeastern China

    Directory of Open Access Journals (Sweden)

    Yu Lu

    2010-03-01

    Full Text Available This paper presents the results of snow cover monitoring studies in Liaoning Province, northeastern China, using MODIS data. Snow cover plays an important role in both the regional water balance and soil moisture properties during the early spring in northeastern China. In addition, heavy snowfalls commonly trigger hazards such as flooding, caused by rapid snow melt, or crop failure, resulting from fluctuations in soil temperature associated with changes in the snow cover. The latter is a function of both regional, or global, climatic changes, as well as fluctuations in the albedo resulting from variations in the Snow Covered Area (SCA. These impacts are crucial to human activities, especially to those living in middle-latitude areas such as Liaoning Province. Thus, SCA monitoring is currently an important tool in studies of global climate change, particularly because satellite remote sensing data provide timely and efficient snow cover information for large areas. In this study, MODIS L1B data, MODIS Daily Snow Products (MOD10A1 and MODIS 8-day Snow Products (MOD10A2 were used to monitor the SCA of Liaoning Province over the winter months of November–April, 2006–2008. The effects of cloud masking and forest masking on the snow monitoring results were also assessed. The results show that the SCA percentage derived from MODIS L1B data is relatively consistent, but slightly higher than that obtained from MODIS Snow Products. In situ data from 25 snow stations were used to assess the accuracy of snow cover monitoring from the SCA compared to the results from MODIS Snow Products. The studies found that the SCA results were more reliable than MODIS Snow Products in the study area.

  3. Changes in Andes snow cover from MODIS data, 2000–2016

    Directory of Open Access Journals (Sweden)

    F. A. Saavedra

    2018-03-01

    Full Text Available The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensors (500 m, 8-day maximum snow cover extent. This analysis is conducted between 8 and 36° S due to high frequency of cloud (>  30 % of the time south and north of this range. We ran Mann–Kendall and Theil–Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP  =  20 %. We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2 and University of Delaware datasets and climate indices as El Niño–Southern Oscillation (ENSO, Southern Annular Mode (SAM, and Pacific Decadal Oscillation (PDO. Areas north of 29° S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2 with persistent snow cover between 29 and 36° S experienced a significant loss of snow cover (2–5 fewer days of snow year−1. Snow loss was more pronounced (62 % of the area with significant trends on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10–30 m year−1 south of 29–30° S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31° S, whereas the SAM better predicted SP south of 31° S.

  4. Realism versus simplicity in the snow routine of the HBV model

    Science.gov (United States)

    Girons Lopez, Marc; Vis, Marc; Seibert, Jan

    2017-04-01

    The HBV model still enjoys great popularity, in part because of its simplicity. Depicting the hydrological processes in a catchment in a simple way reduces data requirements and minimises parameter uncertainty. However, the representation of some processes might benefit from an increased model complexity. This is, for instance, the case of snow routine in the HBV-light version of the HBV model. HBV-light uses a degree-day method with a single threshold parameter to distinguish between rain and snow and simulate snow melt. Recent research has shown that hydrological models with a more realistic representation of snow processes might be more successful in estimating runoff. In this study we explore and test different improvements to the HBV-light snow routine design by considering different threshold temperature values for rain and snow distinction as well as for the beginning of snow melt, and introducing gradual transitions instead of the current sharp threshold. The use of radiation data, which recently became available as gridded data product in Switzerland, is an additional possibility. These modifications would allow for a more realistic depiction of important hydrological processes in alpine and other snow-covered areas while preserving the characteristic simplicity of HBV. Furthermore, in this contribution we evaluate the balance between introducing more realism into the snow routine of the HBV model and keeping the number of parameters as low as possible.

  5. Drivers and environmental responses to the changing annual snow cycle of northern Alaska

    Science.gov (United States)

    Cox, Christopher J.; Stone, Robert S.; Douglas, David C.; Stanitski, Diane; Divoky, George J.; Dutton, Geoff S.; Sweeney, Colm; George, J. Craig; Longenecker, David U.

    2017-01-01

    On the North Slope of Alaska, earlier spring snowmelt and later onset of autumn snow accumulation are tied to atmospheric dynamics and sea ice conditions, and result in environmental responses.Linkages between atmospheric, ecological and biogeochemical variables in the changing Arctic are analyzed using long-term measurements near Utqiaġvik (formerly Barrow), Alaska. Two key variables are the date when snow disappears in spring, as determined primarily by atmospheric dynamics, precipitation, air temperature, winter snow accumulation and cloud cover, as well as the date of onset of snowpack in autumn that is additionally influenced by ocean temperature and sea ice extent. In 2015 and 2016 the snow melted early at Utqiaġvik due mainly to anomalous warmth during May of both years attributed to atmospheric circulation patterns, with 2016 having the record earliest snowmelt. These years are discussed in the context of a 115-year snowmelt record at Utqiaġvik with a trend toward earlier melting since the mid- 1970s (-2.86 days/decade, 1975-2016). At nearby Cooper Island, where a colony of seabirds, Black Guillemots, have been monitored since 1975, timing of egg laying is correlated with Utqiaġvik snowmelt with 2015 and 2016 being the earliest years in the 42-year record. Ice-out at a nearby freshwater lagoon is also correlated with Utqiaġvik snowmelt. The date when snow begins to accumulate in autumn at Utqiaġvik shows a trend towards later dates (+4.6 days/decade, 1975-2016), with 2016 the latest on record. The relationships between the lengthening snow-free season and regional phenology, soil temperatures, fluxes of gases from the tundra, and to regional sea ice conditions are discussed. Better understanding of these interactions is needed to predict the annual snow cycles in the region at seasonal to decadal scales, and to anticipate coupled environmental responses.

  6. Estimation of bare soil surface temperature from air temperature and ...

    African Journals Online (AJOL)

    Soil surface temperature has critical influence on climate, agricultural and hydrological activities since it serves as a good indicator of the energy budget of the earth's surface. Two empirical models for estimating soil surface temperature from air temperature and soil depth temperature were developed. The coefficient of ...

  7. Measuring snow water equivalent from common-offset GPR records through migration velocity analysis

    Directory of Open Access Journals (Sweden)

    J. St. Clair

    2017-12-01

    Full Text Available Many mountainous regions depend on seasonal snowfall for their water resources. Current methods of predicting the availability of water resources rely on long-term relationships between stream discharge and snowpack monitoring at isolated locations, which are less reliable during abnormal snow years. Ground-penetrating radar (GPR has been shown to be an effective tool for measuring snow water equivalent (SWE because of the close relationship between snow density and radar velocity. However, the standard methods of measuring radar velocity can be time-consuming. Here we apply a migration focusing method originally developed for extracting velocity information from diffracted energy observed in zero-offset seismic sections to the problem of estimating radar velocities in seasonal snow from common-offset GPR data. Diffractions are isolated by plane-wave-destruction (PWD filtering and the optimal migration velocity is chosen based on the varimax norm of the migrated image. We then use the radar velocity to estimate snow density, depth, and SWE. The GPR-derived SWE estimates are within 6 % of manual SWE measurements when the GPR antenna is coupled to the snow surface and 3–21 % of the manual measurements when the antenna is mounted on the front of a snowmobile  ∼  0.5 m above the snow surface.

  8. Snow Monitoring Using Remote Sensing Data: Modification of Normalized Difference Snow Index

    Science.gov (United States)

    Kaplan, G.; Avdan, U.

    2016-12-01

    Snow cover is an important part of the Earth`s climate system so its continuous monitoring is necessary to map snow cover in high resolution. Satellite remote sensing can successfully fetch land cover and land cover changes. Although normalized difference snow index NDSI has quite good accuracy, topography shadow, water bodies and clouds can be easily misplaced as snow. Using Landsat TM, +ETM and TIRS/OLI satellite images, the NDSI was modified for more accurate snow mapping. In this paper, elimination of the misplaced water bodies was made using the high reflectance of the snow in the blue band. Afterwards, the modified NDSI (MNDSI) was used for estimating snow cover through the years on the highest mountains in Republic of Macedonia. The results from this study show that the MNDSI accuracy is bigger than the NDSI`s, totally eliminating the misplaced water bodies, and partly the one caused from topography and clouds. Also, it was noticed that the snow cover in the study area has been lowered through the years. For future studies, the MNDSI should be validated on different study areas with different characteristics.

  9. Light absorption and scattering by aggregates: Application to black carbon and snow grains

    International Nuclear Information System (INIS)

    Liou, K.N.; Takano, Y.; Yang, P.

    2011-01-01

    under the condition of equal geometrical cross section area for both external and internal mixing states; however, nonspherical snowflakes scatter less light in forward directions than spheres, resulting in a substantial reduction of the asymmetry factor. We further demonstrate that small soot particles on the order of 1 μm internally mixed with snow grains could effectively reduce snow albedo by as much as 5-10%. Indeed, the depositions of black carbon would substantially reduce mountain-snow albedo, which would lead to surface warming and snowmelt, critical to regional climatic surface temperature amplification and feedback.

  10. Temporal monitoring of the soil freeze-thaw cycles over snow-cover land by using off-ground GPR

    KAUST Repository

    Jadoon, Khan

    2013-07-01

    We performed off-ground ground-penetrating radar (GPR) measurements over a bare agricultural field to monitor the freeze-thaw cycles over snow-cover. The GPR system consisted of a vector network analyzer combined with an off-ground monostatic horn antenna, thereby setting up an ultra-wideband stepped-frequency continuous-wave radar. Measurements were performed during nine days and the surface of the bare soil was exposed to snow fall, evaporation and precipitation as the GPR antenna was mounted 110 cm above the ground. Soil surface dielectric permittivity was retrieved using an inversion of time-domain GPR data focused on the surface reflection. The GPR forward model used combines a full-waveform solution of Maxwell\\'s equations for three-dimensional wave propagation in planar layered media together with global reflection and transmission functions to account for the antenna and its interactions with the medium. Temperature and permittivity sensors were installed at six depths to monitor the soil dynamics in the top 8 cm depth. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and permittivity data and in particular freeze and thaw events were clearly visible. A good agreement of the trend was observed between the temperature, permittivity and GPR time-lapse data with respect to five freeze-thaw cycles. The GPR-derived permittivity was in good agreement with sensor observations. The proposed method appears to be promising for the real-time mapping and monitoring of the frozen layer at the field scale. © 2013 IEEE.

  11. Improving snow density estimation for mapping SWE with Lidar snow depth: assessment of uncertainty in modeled density and field sampling strategies in NASA SnowEx

    Science.gov (United States)

    Raleigh, M. S.; Smyth, E.; Small, E. E.

    2017-12-01

    The spatial distribution of snow water equivalent (SWE) is not sufficiently monitored with either remotely sensed or ground-based observations for water resources management. Recent applications of airborne Lidar have yielded basin-wide mapping of SWE when combined with a snow density model. However, in the absence of snow density observations, the uncertainty in these SWE maps is dominated by uncertainty in modeled snow density rather than in Lidar measurement of snow depth. Available observations tend to have a bias in physiographic regime (e.g., flat open areas) and are often insufficient in number to support testing of models across a range of conditions. Thus, there is a need for targeted sampling strategies and controlled model experiments to understand where and why different snow density models diverge. This will enable identification of robust model structures that represent dominant processes controlling snow densification, in support of basin-scale estimation of SWE with remotely-sensed snow depth datasets. The NASA SnowEx mission is a unique opportunity to evaluate sampling strategies of snow density and to quantify and reduce uncertainty in modeled snow density. In this presentation, we present initial field data analyses and modeling results over the Colorado SnowEx domain in the 2016-2017 winter campaign. We detail a framework for spatially mapping the uncertainty in snowpack density, as represented across multiple models. Leveraging the modular SUMMA model, we construct a series of physically-based models to assess systematically the importance of specific process representations to snow density estimates. We will show how models and snow pit observations characterize snow density variations with forest cover in the SnowEx domains. Finally, we will use the spatial maps of density uncertainty to evaluate the selected locations of snow pits, thereby assessing the adequacy of the sampling strategy for targeting uncertainty in modeled snow density.

  12. Isotope effect and deuterium excess parameter revolution in ice and snow melt

    International Nuclear Information System (INIS)

    Yin Guan; Ni Shijun; Fan Xiao; Wu Hao

    2003-01-01

    The change of water isotope composition actually is a integrated reaction depending on the change of environment. The ice and snow melt of different seasons in high mountain can obviously influence the change of isotope composition and deuterium excess parameter of surface flow and shallow groundwater. To know the isotopic fractionation caused by this special natural background, explore its forming and evolvement, is unusually important for estimating, the relationship between the environment, climate and water resources in an area. Taking the example of isotope composition of surface flow and shallow groundwater in Daocheng, Sichuan, this paper mainly introduced the changing law of isotope composition and deuterium excess parameter of surface flow and hot-spring on conditions of ice and snow melt with different seasons in high mountain; emphatically discussed the isotope effect and deuterium excess parameter revolution in the process of ice and snow melting and its reason. (authors)

  13. Using wireless sensor networks to improve understanding of rain-on-snow events across the Sierra Nevada

    Science.gov (United States)

    Maurer, T.; Avanzi, F.; Oroza, C.; Malek, S. A.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

    2017-12-01

    We use data gathered from Wireless Sensor Networks (WSNs) between 2008 and 2017 to investigate the temporal/spatial patterns of rain-on-snow events in three river basins of California's Sierra Nevada. Rain-on-snow transitions occur across a broad elevation range (several hundred meters), both between storms and within a given storm, creating an opportunity to use spatially and temporally dense data to forecast and study them. WSNs collect snow depth; meteorological data; and soil moisture and temperature data across relatively dense sensor clusters. Ten to twelve measurement nodes per cluster are placed across 1-km2 areas in locations representative of snow patterns at larger scales. Combining precipitation and snow data from snow-pillow and climate stations with an estimation of dew-point temperature from WSNs, we determine the frequency, timing, and geographic extent of rain-on-snow events. We compare these results to WSN data to evaluate the impact of rain-on-snow events on snowpack energy balance, density, and depth as well as on soil moisture. Rain-on-snow events are compared to dry warm-weather days to identify the relative importance of rain and radiation as the primary energy input to the snowpack for snowmelt generation. An intercomparison of rain-on-snow events for the WSNs in the Feather, American, and Kings River basins captures the behavior across a 2° latitudinal range of the Sierra Nevada. Rain-on-snow events are potentially a more important streamflow generation mechanism in the lower-elevation Feather River basin. Snowmelt response to rain-on-snow events changes throughout the wet season, with later events resulting in more melt due to snow isothermal conditions, coarser grain size, and more-homogeneous snow stratigraphy. Regardless of snowmelt response, rain-on-snow events tend to result in decreasing snow depth and a corresponding increase in snow density. Our results demonstrate that strategically placed WSNs can provide the necessary data at

  14. The Ross Sea Dipole – temperature, snow accumulation and sea ice variability in the Ross Sea region, Antarctica, over the past 2700 years

    Directory of Open Access Journals (Sweden)

    N. A. N. Bertler

    2018-02-01

    Full Text Available High-resolution, well-dated climate archives provide an opportunity to investigate the dynamic interactions of climate patterns relevant for future projections. Here, we present data from a new, annually dated ice core record from the eastern Ross Sea, named the Roosevelt Island Climate Evolution (RICE ice core. Comparison of this record with climate reanalysis data for the 1979–2012 interval shows that RICE reliably captures temperature and snow precipitation variability in the region. Trends over the past 2700 years in RICE are shown to be distinct from those in West Antarctica and the western Ross Sea captured by other ice cores. For most of this interval, the eastern Ross Sea was warming (or showing isotopic enrichment for other reasons, with increased snow accumulation and perhaps decreased sea ice concentration. However, West Antarctica cooled and the western Ross Sea showed no significant isotope temperature trend. This pattern here is referred to as the Ross Sea Dipole. Notably, during the Little Ice Age, West Antarctica and the western Ross Sea experienced colder than average temperatures, while the eastern Ross Sea underwent a period of warming or increased isotopic enrichment. From the 17th century onwards, this dipole relationship changed. All three regions show current warming, with snow accumulation declining in West Antarctica and the eastern Ross Sea but increasing in the western Ross Sea. We interpret this pattern as reflecting an increase in sea ice in the eastern Ross Sea with perhaps the establishment of a modern Roosevelt Island polynya as a local moisture source for RICE.

  15. Variations in Below Canopy Turbulent Flux From Snow in North American Mountain Environments

    Science.gov (United States)

    Essery, R.; Marks, D.; Pomeroy, J.; Grangere, R.; Reba, M.; Hedstrom, N.; Link, T.; Winstral, A.

    2004-12-01

    Sensible and latent heat and mass fluxes from the snow surface are modulated by site canopy density and structure. Forest and shrub canopies reduce wind speeds and alter the radiation and thermal environment which will alter the below canopy energetics that control the magnitude of turbulent fluxes between the snow surface and the atmosphere. In this study eddy covariance (EC) systems were located in three experimental catchments along a mountain transect through the North American Cordillera. Within each catchment, a variety of sites representing the local range of climate, weather, and canopy conditions were selected for measurement of sensible and latent heat and mass flux from the snow surface. EC measurements were made 1) below a uniform pine canopy (2745m) in the Fraser Experimental Forest in Colorado from February through June melt-out in 2003; 2) at an open, unforested site (2100m), and below an Aspen canopy (2055m) within a small headwater catchment in the Reynolds Creek Experimental Watershed, Owyhee Mts., Idaho from October, 2003, through June melt-out, 2004; and 3) at five sites, representing a range of conditions: a) below a dense spruce forest (750m); b) a north-facing shrub-tundra slope (1383m); c) a south-facing shrub-tundra slope; d) the valley bottom between b) and c) (1363m); and e) a tundra site (1402m) in the Wolf Creek Research Basin (WCRB) in the Yukon, Canada during the 2001 and 2002 snow seasons. Summary data from all sites are presented and compared including the relative significance of sublimation losses at each site, the importance of interception losses to the snowcover mass balance, and the occurrence of condensation events. Site and weather conditions that inhibit or enhance flux from the snow surface are discussed. This research will improve snow modeling by allowing better representation of turbulent fluxes from snow in forested regions, and improved simulation of the snowcover mass balance over low deposition, high latitude sites

  16. A multilayer physically based snowpack model simulating direct and indirect radiative impacts of light-absorbing impurities in snow

    Science.gov (United States)

    Tuzet, Francois; Dumont, Marie; Lafaysse, Matthieu; Picard, Ghislain; Arnaud, Laurent; Voisin, Didier; Lejeune, Yves; Charrois, Luc; Nabat, Pierre; Morin, Samuel

    2017-11-01

    Light-absorbing impurities (LAIs) decrease snow albedo, increasing the amount of solar energy absorbed by the snowpack. Its most intuitive and direct impact is to accelerate snowmelt. Enhanced energy absorption in snow also modifies snow metamorphism, which can indirectly drive further variations of snow albedo in the near-infrared part of the solar spectrum because of the evolution of the near-surface snow microstructure. New capabilities have been implemented in the detailed snowpack model SURFEX/ISBA-Crocus (referred to as Crocus) to account for impurities' deposition and evolution within the snowpack and their direct and indirect impacts. Once deposited, the model computes impurities' mass evolution until snow melts out, accounting for scavenging by meltwater. Taking advantage of the recent inclusion of the spectral radiative transfer model TARTES (Two-stream Analytical Radiative TransfEr in Snow model) in Crocus, the model explicitly represents the radiative impacts of light-absorbing impurities in snow. The model was evaluated at the Col de Porte experimental site (French Alps) during the 2013-2014 snow season against in situ standard snow measurements and spectral albedo measurements. In situ meteorological measurements were used to drive the snowpack model, except for aerosol deposition fluxes. Black carbon (BC) and dust deposition fluxes used to drive the model were extracted from simulations of the atmospheric model ALADIN-Climate. The model simulates snowpack evolution reasonably, providing similar performances to our reference Crocus version in terms of snow depth, snow water equivalent (SWE), near-surface specific surface area (SSA) and shortwave albedo. Since the reference empirical albedo scheme was calibrated at the Col de Porte, improvements were not expected to be significant in this study. We show that the deposition fluxes from the ALADIN-Climate model provide a reasonable estimate of the amount of light-absorbing impurities deposited on the

  17. Enhanced solar energy absorption by internally-mixed black carbon in snow grains

    Directory of Open Access Journals (Sweden)

    M. G. Flanner

    2012-05-01

    Full Text Available Here we explore light absorption by snowpack containing black carbon (BC particles residing within ice grains. Basic considerations of particle volumes and BC/snow mass concentrations show that there are generally 0.05–109 BC particles for each ice grain. This suggests that internal BC is likely distributed as multiple inclusions within ice grains, and thus the dynamic effective medium approximation (DEMA (Chýlek and Srivastava, 1983 is a more appropriate optical representation for BC/ice composites than coated-sphere or standard mixing approximations. DEMA calculations show that the 460 nm absorption cross-section of BC/ice composites, normalized to the mass of BC, is typically enhanced by factors of 1.8–2.1 relative to interstitial BC. BC effective radius is the dominant cause of variation in this enhancement, compared with ice grain size and BC volume fraction. We apply two atmospheric aerosol models that simulate interstitial and within-hydrometeor BC lifecycles. Although only ~2% of the atmospheric BC burden is cloud-borne, 71–83% of the BC deposited to global snow and sea-ice surfaces occurs within hydrometeors. Key processes responsible for within-snow BC deposition are development of hydrophilic coatings on BC, activation of liquid droplets, and subsequent snow formation through riming or ice nucleation by other species and aggregation/accretion of ice particles. Applying deposition fields from these aerosol models in offline snow and sea-ice simulations, we calculate that 32–73% of BC in global surface snow resides within ice grains. This fraction is smaller than the within-hydrometeor deposition fraction because meltwater flux preferentially removes internal BC, while sublimation and freezing within snowpack expose internal BC. Incorporating the DEMA into a global climate model, we simulate increases in BC/snow radiative forcing of 43–86%, relative to scenarios that apply external optical properties to all BC. We

  18. Enhanced Solar Energy Absorption by Internally-mixed Black Carbon in Snow Grains

    Energy Technology Data Exchange (ETDEWEB)

    Flanner, M. G.; Liu, Xiaohong; Zhou, Cheng; Penner, Joyce E.; Jiao, C.

    2012-05-30

    Here we explore light absorption by snowpack containing black carbon (BC) particles residing within ice grains. Basic considerations of particle volumes and BC/snow mass concentrations show that there are generally 0:05-109 BC particles for each ice grain. This suggests that internal BC is likely distributed as multiple inclusions within ice grains, and thus the dynamic effective medium approximation (DEMA) (Chylek and Srivastava, 1983) is a more appropriate optical representation for BC/ice composites than coated-sphere or standard mixing approximations. DEMA calculations show that the 460 nm absorption cross-section of BC/ice composites, normalized to the mass of BC, is typically enhanced by factors of 1.8-2.1 relative to interstitial BC. BC effective radius is the dominant cause of variation in this enhancement, compared with ice grain size and BC volume fraction. We apply two atmospheric aerosol models that simulate interstitial and within-hydrometeor BC lifecycles. Although only {approx}2% of the atmospheric BC burden is cloud-borne, 71-83% of the BC deposited to global snow and sea-ice surfaces occurs within hydrometeors. Key processes responsible for within-snow BC deposition are development of hydrophilic coatings on BC, activation of liquid droplets, and subsequent snow formation through riming or ice nucleation by other species and aggregation/accretion of ice particles. Applying deposition fields from these aerosol models in offline snow and sea-ice simulations, we calculate that 32-73% of BC in global surface snow resides within ice grains. This fraction is smaller than the within-hydrometeor deposition fraction because meltwater flux preferentially removes internal BC, while sublimation and freezing within snowpack expose internal BC. Incorporating the DEMA into a global climate model, we simulate increases in BC/snow radiative forcing of 43-86%, relative to scenarios that apply external optical properties to all BC. We show that snow metamorphism

  19. CHEMICAL IMAGING OF THE CO SNOW LINE IN THE HD 163296 DISK

    Energy Technology Data Exchange (ETDEWEB)

    Qi, Chunhua; Öberg, Karin I.; Andrews, Sean M.; Wilner, David J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Bergin, Edwin A. [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States); Hughes, A. Meredith [Van Vleck Observatory, Astronomy Department, Wesleyan University, 96 Foss Hill Drive, Middletown, CT 06459 (United States); Hogherheijde, Michiel [Leiden Observatory, Leiden University, P.O. Box 9513, 2300 RA Leiden (Netherlands); D’Alessio, Paola [Centro de Radioastronomi´a y Astrofísica, Universidad Nacional Autónoma de México, 58089 Morelia, Michoacán, México (Mexico)

    2015-11-10

    The condensation fronts (snow lines) of H{sub 2}O, CO, and other abundant volatiles in the midplane of a protoplanetary disk affect several aspects of planet formation. Locating the CO snow line, where the CO gas column density is expected to drop substantially, based solely on CO emission profiles, is challenging. This has prompted an exploration of chemical signatures of CO freeze-out. We present ALMA Cycle 1 observations of the N{sub 2}H{sup +} J = 3−2 and DCO{sup +} J = 4−3 emission lines toward the disk around the Herbig Ae star HD 163296 at ∼0.″5 (60 AU) resolution, and evaluate their utility as tracers of the CO snow line location. The N{sub 2}H{sup +} emission is distributed in a ring with an inner radius at 90 AU, corresponding to a midplane temperature of 25 K. This result is consistent with a new analysis of optically thin C{sup 18}O data, which implies a sharp drop in CO abundance at 90 AU. Thus N{sub 2}H{sup +} appears to be a robust tracer of the midplane CO snow line. The DCO{sup +} emission also has a ring morphology, but neither the inner nor the outer radius coincide with the CO snow line location of 90 AU, indicative of a complex relationship between DCO{sup +} emission and CO freeze-out in the disk midplane. Compared to TW Hya, CO freezes out at a higher temperature in the disk around HD 163296 (25 versus 17 K in the TW Hya disk), perhaps due to different ice compositions. This highlights the importance of actually measuring the CO snow line location, rather than assuming a constant CO freeze-out temperature for all disks.

  20. Snow depth manipulation experiments in a dry and a moist tundra

    Science.gov (United States)

    Kwon, M. J.; Czimczik, C. I.; Jung, J. Y.; Kim, M.; Lee, Y. K.; Nam, S.; Wagner, I.

    2017-12-01

    As a result of global warming, precipitation in the Arctic is expected to increase by 25-50% by the end of this century, mostly in the form of snow. However, precipitation patterns vary considerable in space and time, and future precipitation patterns are highly uncertain at local and regional scales. The amount of snowfall (or snow depth) influences a number of ecosystem properties in Arctic ecosystems, such as soil temperature over winter and soil moisture in the following growing season. These modifications then affect rates of carbon-related soil processes and photosynthesis, thus CO2 exchange rates between terrestrial ecosystems and the atmosphere. In this study, we investigate the effects of snow depth on the magnitude, sources and temporal dynamics of CO2 fluxes. We installed snow fences in a dry dwarf-shrub (Cambridge Bay, Canada; 69° N, 105° W) and a moist low-shrub (Council, Alaska, USA; 64° N, 165° W) tundra in summer 2017, and established control, and increased and reduced snow depth plots at each snow fence. Summertime CO2 flux rates (net ecosystem exchange, ecosystem respiration, gross primary production) and the fractions of autotrophic and heterotrophic respiration to ecosystem respiration were measured using manual chambers and radiocarbon signatures. Wintertime CO2 flux rates will be measured using soda lime adsorption technique and forced diffusion chambers. Soil temperature and moisture at multiple depths, as well as changes in soil properties and microbial communities will be also observed, to research whether these changes affect CO2 flux rates or patterns. Our study will elucidate how future snow depth and its impact on soil physical and biogeochemical properties influence the magnitude and sources of tundra-atmosphere CO2 exchange in the rapidly warming Arctic.

  1. Marine snow formation in the aftermath of the Deepwater Horizon oil spill in the Gulf of Mexico

    International Nuclear Information System (INIS)

    Passow, U; Ziervogel, K; Asper, V; Diercks, A

    2012-01-01

    The large marine snow formation event observed in oil-contaminated surface waters of the Gulf of Mexico (GoM) after the Deepwater Horizon accident possibly played a key role in the fate of the surface oil. We characterized the unusually large and mucus-rich marine snow that formed and conducted roller table experiments to investigate their formation mechanisms. Once marine snow lost its buoyancy, its sinking velocity, porosity and excess density were then similar to those of diatom or miscellaneous aggregates. The hydrated density of the component particles of the marine snow from the GoM was remarkably variable, suggesting a wide variety of component types. Our experiments suggest that the marine snow appearing at the surface after the oil spill was formed through the interaction of three mechanisms: (1) production of mucous webs through the activities of bacterial oil-degraders associated with the floating oil layer; (2) production of oily particulate matter through interactions of oil components with suspended matter and their coagulation; and (3) coagulation of phytoplankton with oil droplets incorporated into aggregates. Marine snow formed in some, but not all, experiments with water from the subsurface plume of dissolved hydrocarbons, emphasizing the complexity of the conditions leading to the formation of marine snow in oil-contaminated seawater at depth. (letter)

  2. Parameterization of atmosphere-surface exchange of CO2 over sea ice

    DEFF Research Database (Denmark)

    Sørensen, L. L.; Jensen, B.; Glud, Ronnie N.

    2014-01-01

    are discussed. We found the flux to be small during the late winter with fluxes in both directions. Not surprisingly we find that the resistance across the surface controls the fluxes and detailed knowledge of the brine volume and carbon chemistry within the brines as well as knowledge of snow cover and carbon...... chemistry in the ice are essential to estimate the partial pressure of pCO2 and CO2 flux. Further investigations of surface structure and snow cover and driving parameters such as heat flux, radiation, ice temperature and brine processes are required to adequately parameterize the surface resistance....

  3. Features of Duration and Borders of the Bedding of Snow Cover in the Conditions of Climatic Changes in the Territory of Northern Kazakhstan According to Land and Space Monitoring

    Science.gov (United States)

    Salnikov, Vitaliy; Turulina, Galina; Polyakova, Svetlana; Muratova, Nadiya; Kauazov, Azamat; Abugalieva, Aigul; Tazhibayeva, Tamara

    2014-05-01

    Precipitation and air temperature datasets from 34 meteorological stations were analyzed to reveal the regional climate changes at the territory in North Kazakhstan over the last 58 years (i.e., 1950-2008). Peculiarities and conditions of snow cover formation and melting have been analyzed at territory of Northern Kazakhstan using surface and space monitoring data. Methods of both the geo-informational processing of remote probing data and statistical processing of databases on snow cover, air temperature and precipitations have been used. Analysis of snow cover observations data for territory of Northern Kazakhstan has shown that the stable snow cover might be observed since the middle of November till the beginning of April. In a few last decades the tendency is observed for longevity decrease of snow cover bedding that appears to be on the background air temperature increase and insignificant increase of cold period precipitations due to the later bedding of the snow cover and its earlier destruction. Peculiarities of atmospheric circulation in Atlantic-Eurasian sector of Northern Semi sphere and their influence of formation of snow cover at territory of Northern Kazakhstan. The higher longevity of the snow cover bedding is defined by the predominance of E form circulation and lower longevity - by the predominance of W+C circulation form. Analysis conducted of the highest height of snow cover bedding has shown that for period of 1936-2012 in the most cases the statistically reliable decreasing trends are observed with the linear trend coefficients of 0,50 - 0,60 cm/year. The method is offered for determination of probable characteristics of the snow cover decade height. Using data of space monitoring are allocated the frontiers of snow cover bedding for the period of snow melting 1982-2008 and the snow cover melting maps are developed. The results further confirm the proposition that snow cover availability is an important and limiting factor in the generation

  4. Forest Fires Darken Snow for Years following Disturbance: Magnitude, Duration, and Composition of Light Absorbing Impurities in Seasonal Snow across a Chronosequence of Burned Forests in the Colorado River Headwaters

    Science.gov (United States)

    Gleason, K. E.; Arienzo, M. M.; Chellman, N.; McConnell, J.

    2017-12-01

    Charred forests shed black carbon and burned debris, which accumulates and concentrates on winter snowpack, reducing snow surface albedo, and subsequently increasing snowmelt rates, and advancing the date of snow disappearance. Forest fires have occurred across vast areas of the seasonal snow zone in recent decades, however we do not understand the long-term implications of burned forests in montane headwaters to snow hydrology and downstream water resources. Across a chronosequence of nine burned forests in the Colorado River Headwaters, we sampled snow throughout the complete snowpack profile to conserve the composition, properties, and vertical stratigraphy of impurities in the snowpack during maximum snow accumulation. Using state-of-the-art geochemical analyses, we determined the magnitude, composition, and particle size distribution of black carbon, dust, and other impurities in the snowpack relative to years-since fire. Forest fires continue to darken snow for many years following fire, however the magnitude, composition, and particle size distribution of impurities change through time, altering the post-fire radiative forcing on snow as a burned forest ages.

  5. Energy expenditure and clearing snow: a comparison of shovel and snow pusher.

    Science.gov (United States)

    Smolander, J; Louhevaara, V; Ahonen, E; Polari, J; Klen, T

    1995-04-01

    In order to assess the energy demands of manual clearing of snow, nine men did snow clearing work for 15 min with a shovel and a snow pusher. The depth of the snowcover was 400-600 mm representing a very heavy snowfall. Heart rate (HR), oxygen consumption (VO2), pulmonary ventilation (VE), respiratory exchange ratio (R), and rating of perceived exertion (RPE) were determined during the work tasks. HR, VE, R, and RPE were not significantly different between the shovel and snow pusher. HR averaged (+/- SD) 141 +/- 20 b min-1 with the shovel, and 142 +/- 19 beats.min-1 with the snow pusher. VO2 was 2.1 +/- 0.41.min-1 (63 +/- 12%VO2 max) in shovelling and 2.6 +/- 0.51.min-1 (75 +/- 14%VO2max) in snow pushing (p < 0.001). In conclusion manual clearing of snow in conditions representing heavy snowfalls was found to be strenuous physical work, not suitable for persons with cardiac risk factors, but which may serve as a mode of physical training in healthy adults.

  6. Air temperature variability in a high-elevation Himalayan catchment

    NARCIS (Netherlands)

    Heynen, Martin; Miles, Evan; Ragettli, Silvan; Buri, Pascal; Immerzeel, Walter W.; Pellicciotti, Francesca

    2016-01-01

    Air temperature is a key control of processes affecting snow and glaciers in high-elevation catchments, including melt, snowfall and sublimation. It is therefore a key input variable to models of land-surface-atmosphere interaction. Despite this importance, its spatial variability is poorly

  7. Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

    Science.gov (United States)

    Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

    2018-03-01

    Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

  8. Impact of additional surface observation network on short range ...

    Indian Academy of Sciences (India)

    Stations (AWS) surface observations (temperature and moisture) on the short range forecast over the Indian ... models, which are able to resolve mesoscale fea- ... J. Earth Syst. Sci. ..... terization of the snow field in a cloud model; J. Climate.

  9. Quantifying spatial distribution of snow depth errors from LiDAR using Random Forests

    Science.gov (United States)

    Tinkham, W.; Smith, A. M.; Marshall, H.; Link, T. E.; Falkowski, M. J.; Winstral, A. H.

    2013-12-01

    There is increasing need to characterize the distribution of snow in complex terrain using remote sensing approaches, especially in isolated mountainous regions that are often water-limited, the principal source of terrestrial freshwater, and sensitive to climatic shifts and variations. We apply intensive topographic surveys, multi-temporal LiDAR, and Random Forest modeling to quantify snow volume and characterize associated errors across seven land cover types in a semi-arid mountainous catchment at a 1 and 4 m spatial resolution. The LiDAR-based estimates of both snow-off surface topology and snow depths were validated against ground-based measurements across the catchment. Comparison of LiDAR-derived snow depths to manual snow depth surveys revealed that LiDAR based estimates were more accurate in areas of low lying vegetation such as shrubs (RMSE = 0.14 m) as compared to areas consisting of tree cover (RMSE = 0.20-0.35 m). The highest errors were found along the edge of conifer forests (RMSE = 0.35 m), however a second conifer transect outside the catchment had much lower errors (RMSE = 0.21 m). This difference is attributed to the wind exposure of the first site that led to highly variable snow depths at short spatial distances. The Random Forest modeled errors deviated from the field measured errors with a RMSE of 0.09-0.34 m across the different cover types. Results show that snow drifts, which are important for maintaining spring and summer stream flows and establishing and sustaining water-limited plant species, contained 30 × 5-6% of the snow volume while only occupying 10% of the catchment area similar to findings by prior physically-based modeling approaches. This study demonstrates the potential utility of combining multi-temporal LiDAR with Random Forest modeling to quantify the distribution of snow depth with a reasonable degree of accuracy. Future work could explore the utility of Terrestrial LiDAR Scanners to produce validation of snow-on surface

  10. Near-surface temperature lapse rates in a mountainous catchment in the Chilean Andes

    Science.gov (United States)

    Ayala; Schauwecker, S.; Pellicciotti, F.; McPhee, J. P.

    2011-12-01

    In mountainous areas, and in the Chilean Andes in particular, the irregular and sparse distribution of recording stations resolves insufficiently the variability of climatic factors such as precipitation, temperature and relative humidity. Assumptions about air temperature variability in space and time have a strong effect on the performance of hydrologic models that represent snow processes such as accumulation and ablation. These processes have large diurnal variations, and assumptions that average over longer time periods (days, weeks or months) may reduce the predictive capacity of these models under different climatic conditions from those for which they were calibrated. They also introduce large uncertainties when such models are used to predict processes with strong subdiurnal variability such as snowmelt dynamics. In many applications and modeling exercises, temperature is assumed to decrease linearly with elevation, using the free-air moist adiabatic lapse rate (MALR: 0.0065°C/m). Little evidence is provided for this assumption, however, and recent studies have shown that use of lapse rates that are uniform in space and constant in time is not appropriate. To explore the validity of this approach, near-surface (2 m) lapse rates were calculated and analyzed at different temporal resolution, based on a new data set of spatially distributed temperature sensors setup in a high elevation catchment of the dry Andes of Central Chile (approx. 33°S). Five minutes temperature data were collected between January 2011 and April 2011 in the Ojos de Agua catchment, using two Automatic Weather Stations (AWSs) and 13 T-loggers (Hobo H8 Pro Temp with external data logger), ranging in altitude from 2230 to 3590 m.s.l.. The entire catchment was snow free during our experiment. We use this unique data set to understand the main controls over temperature variability in time and space, and test whether lapse rates can be used to describe the spatial variations of air

  11. Snow surface microbiome on the High Antarctic Plateau (DOME C).

    Science.gov (United States)

    Michaud, Luigi; Lo Giudice, Angelina; Mysara, Mohamed; Monsieurs, Pieter; Raffa, Carmela; Leys, Natalie; Amalfitano, Stefano; Van Houdt, Rob

    2014-01-01

    The cryosphere is an integral part of the global climate system and one of the major habitable ecosystems of Earth's biosphere. These permanently frozen environments harbor diverse, viable and metabolically active microbial populations that represent almost all the major phylogenetic groups. In this study, we investigated the microbial diversity in the surface snow surrounding the Concordia Research Station on the High Antarctic Plateau through a polyphasic approach, including direct prokaryotic quantification by flow cytometry and catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH), and phylogenetic identification by 16S RNA gene clone library sequencing and 454 16S amplicon pyrosequencing. Although the microbial abundance was low (<10(3) cells/ml of snowmelt), concordant results were obtained with the different techniques. The microbial community was mainly composed of members of the Alpha-proteobacteria class (e.g. Kiloniellaceae and Rhodobacteraceae), which is one of the most well-represented bacterial groups in marine habitats, Bacteroidetes (e.g. Cryomorphaceae and Flavobacteriaceae) and Cyanobacteria. Based on our results, polar microorganisms could not only be considered as deposited airborne particles, but as an active component of the snowpack ecology of the High Antarctic Plateau.

  12. Snow surface microbiome on the High Antarctic Plateau (DOME C.

    Directory of Open Access Journals (Sweden)

    Luigi Michaud

    Full Text Available The cryosphere is an integral part of the global climate system and one of the major habitable ecosystems of Earth's biosphere. These permanently frozen environments harbor diverse, viable and metabolically active microbial populations that represent almost all the major phylogenetic groups. In this study, we investigated the microbial diversity in the surface snow surrounding the Concordia Research Station on the High Antarctic Plateau through a polyphasic approach, including direct prokaryotic quantification by flow cytometry and catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH, and phylogenetic identification by 16S RNA gene clone library sequencing and 454 16S amplicon pyrosequencing. Although the microbial abundance was low (<10(3 cells/ml of snowmelt, concordant results were obtained with the different techniques. The microbial community was mainly composed of members of the Alpha-proteobacteria class (e.g. Kiloniellaceae and Rhodobacteraceae, which is one of the most well-represented bacterial groups in marine habitats, Bacteroidetes (e.g. Cryomorphaceae and Flavobacteriaceae and Cyanobacteria. Based on our results, polar microorganisms could not only be considered as deposited airborne particles, but as an active component of the snowpack ecology of the High Antarctic Plateau.

  13. Impacts of Recent Climatic Wetting on Distributed Snow and Streamflow Responses in a Terminal Lake Basin.

    Science.gov (United States)

    Van Hoy, D.; Mahmood, T. H.; Jeannotte, T.; Todhunter, P. E.

    2017-12-01

    The recent shift in hydroclimatic conditions in the Northern Great Plains (NGP) has led to an increase in precipitation, rainfall rate, and wetland connectivity over the last few decades. These changes yield an integrated response resulting in high mean annual streamflow and subsequent flooding in many NGP basins such as the terminal Devils Lake Basin (DLB). In this study, we investigate the impacts of recent climatic wetting on distributed hydrologic responses such as snow processes and streamflow using a field-tested and physically-based cold region hydrologic model (CRHM). CHRM is designed for cold prairie regions and has modules to simulate major processes such as blowing snow transport, sublimation, interception, frozen soil infiltration, snowmelt and subsequent streamflow generation. Our modeling focuses on a tributary basin of the DLB known as the Mauvais Coulee Basin (MCB). Since there were no snow observations in the MCB, we conducted a detailed snow survey at distributed locations estimating snow depth, density, and snow water equivalent (SWE) using a prairie snow tube four times during winter of 2016-17. The MCB model was evaluated against distributed snow observations and streamflow measured at the basin outlet (USGS) for the year 2016-2017. Preliminary results indicate that the simulated SWEs at distributed locations and streamflow (NSE ≈ 0.70) are in good agreement with observations. The simulated SWE maps exhibit large spatiotemporal variation during 2016-17 winter due to spatial variability in precipitation, snow redistribution from stubble field to wooded areas, and snow accumulations in small depressions across the subbasins. The main source of snow appears to be the hills and ridges of the eastern and western edges of the basin, while the main sink is the large flat central valleys. The model will be used to examine the effect of recent changes to precipitation and temperature on snow processes and subsequent streamflow for 2004-2017 season. We

  14. Is Snow Gliding a Major Soil Erosion Agent in Steep Alpine Areas?

    International Nuclear Information System (INIS)

    Meusburger, K.; Walter, A.; Alewell, C.; Leitinger, G.; Mabit, L.; Mueller, M.H.

    2015-01-01

    Snow cover is a key hydrological characteristic of mountain areas. Nevertheless, a majority of studies focused on quantifying rates of soil erosion and sediment transport in steep mountain areas has largely neglected the role of snow cover on soil erosion rates (Stanchi et al., 2014). Soil erosion studies have focused almost exclusively on the snow-free periods even though it is well known that wet avalanches can yield enormous erosive forces (Freppaz et al., 2010; Korup and Rixen, 2014). This raises the question whether annual snow cover and particularly the slow movement of snow packages over the soil surface, termed ‘‘snow gliding’’, contribute significantly to the total soil loss in these areas. Three different approaches to estimate soil erosion rates were used to address this question. These include (1) the anthropogenic soil tracer 137 Cs, (2) the Revised Universal Soil Loss Equation (RUSLE), and (3) direct sediment yield measurements of snow glide deposits. The fallout radionuclide 137 Cs integrates total soil loss due to all erosion agents involved, the RUSLE model is suitable to estimate soil loss by water erosion and the sediment yield measurements yield represents a direct estimate of soil removal by snow gliding. Moreover, cumulative snow glide distance was measured for 14 sites and modelled for the surrounding area with the Spatial Snow Glide Model (Leitinger et al., 2008)

  15. Operational satellites and the global monitoring of snow and ice

    Science.gov (United States)

    Walsh, John E.

    1991-01-01

    The altitudinal dependence of the global warming projected by global climate models is at least partially attributable to the albedo-temperature feedback involving snow and ice, which must be regarded as key variables in the monitoring for global change. Statistical analyses of data from IR and microwave sensors monitoring the areal coverage and extent of sea ice have led to mixed conclusions about recent trends of hemisphere sea ice coverage. Seasonal snow cover has been mapped for over 20 years by NOAA/NESDIS on the basis of imagery from a variety of satellite sensors. Multichannel passive microwave data show some promise for the routine monitoring of snow depth over unforested land areas.

  16. Linking Changes in Snow Cover with Nitrogen Cycling and Microbial Abundance and Functional Gene Expression in Agricultural Soils

    Science.gov (United States)

    Goyer, C.; Brin, L.; Zebarth, B.; Burton, D.; Wertz, S.; Chantigny, M.

    2016-12-01

    In eastern Canada, climate change-related warming and increased precipitation may alter winter snow cover, with potential consequences for soil conditions, microbes, and N2O fluxes. We conducted a two-year field study with snow removal, passive snow addition, and ambient treatments in a potato-barley crop system. We measured in situ greenhouse gas (N2O and CO2) fluxes and belowground gas accumulation, and quantified abundance and expression of denitrifier (nirS, nirK, nosZ) and nitrifier (ammonium oxidizing archaeal (AOA) and bacterial (AOB) amoA) genes. Soil gas accumulated throughout winter, and surface fluxes were greatest during spring thaw. Greatest mid-winter soil N2O accumulation and spring thaw N2O fluxes were associated with snow removal in winter 1 and ambient snow in winter 2. High N2O accumulation and fluxes may have been due to increased substrate availability with increased frost intensity in removal plots in winter 1, but with greatest water content in ambient plots in winter 2. In each winter, greatest abundances of nirS, nirK gene denitrifiers and/or amoA gene of AOA were observed in the treatments with the greatest N2O accumulation and fluxes. Gene expression did not vary with treatment, but highest expression of amoA gene of AOA and AOB, and nosZ gene was measured near 0ºC, indicating activity during periods of stable snow cover and spring thaw. Results suggest that the magnitude of fluxes during spring thaw were related to soil conditions and microbial communities present during the prior winter, and not solely those during thaw. Furthermore, the effects of changing snow cover on microbes and N2O fluxes were not a straightforward effect of snow depth, but were likely mediated by temperature and moisture.

  17. Earth System Science at NASA: Teleconnections Between Sea Surface Temperature and Epidemics in Africa

    Science.gov (United States)

    Meeson, Blanche W.

    2000-01-01

    The research carried out in the Earth Sciences in NASA and at NASA's Goddard Space Flight Center will be the focus of the presentations. In addition, one research project that links sea surface temperature to epidemics in Africa will be highlighted. At GSFC research interests span the full breath of disciplines in Earth Science. Branches and research groups focus on areas as diverse as planetary geomagnetics and atmospheric chemistry. These organizations focus on atmospheric sciences (atmospheric chemistry, climate and radiation, regional processes, atmospheric modeling), hydrological sciences (snow, ice, oceans, and seasonal-to-interannual prediction), terrestrial physics (geology, terrestrial biology, land-atmosphere interactions, geophysics), climate modeling (global warming, greenhouse gases, climate change), on sensor development especially using lidar and microwave technologies, and on information technologies, that enable support of scientific and technical research.

  18. Obtaining sub-daily new snow density from automated measurements in high mountain regions

    Science.gov (United States)

    Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Olefs, Marc

    2018-05-01

    The density of new snow is operationally monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and nowcasting applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in situ measurements. In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. Considering the settling of the new snow and the old snowpack, the average hourly new snow density is 68 kg m-3, with a standard deviation of 9 kg m-3. Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the investigated parameterizations. Applying simple linear regressions between new snow density and wet bulb temperature based on the measurements' data resulted in significant relationships (r2 > 0.5 and p ≤ 0.05) for single periods at individual stations only. Higher new snow density was calculated for the highest elevated and most wind-exposed station location. Whereas snow measurements using ultrasonic devices and snow

  19. Snow mechanics and avalanche formation: field experiments on the dynamic response of the snow cover

    Science.gov (United States)

    Schweizer, Jürg; Schneebeli, Martin; Fierz, Charles; Föhn, Paul M. B.

    1995-11-01

    Knowledge about snow mechanics and snow avalanche formation forms the basis of any hazard mitigation measures. The crucial point is the snow stability. The most relevant mechanical properties - the compressive, tensile and shear strength of the individual snow layers within the snow cover - vary substantially in space and time. Among other things the strength of the snow layers depends strongly on the state of stress and the strain rate. The evaluation of the stability of the snow cover is hence a difficult task involving many extrapolations. To gain insight in the release mechanism of slab avalanches triggered by skiers, the skier's impact is measured with a load cell at different depths within the snow cover and for different snow conditions. The study focused on the effects of the dynamic loading and of the damping by snow compaction. In accordance with earlier finite-element (FE) calculations the results show the importance of the depth of the weak layer or interface and the snow conditions, especially the sublayering. In order to directly measure the impact force and to study the snow properties in more detail, a new instrument, called rammrutsch was developed. It combines the properties of the rutschblock with the defined impact properties of the rammsonde. The mechanical properties are determined using (i) the impact energy of the rammrutsch and (ii) the deformations of the snow cover measured with accelerometers and digital image processing of video sequences. The new method is well suited to detect and to measure the mechanical processes and properties of the fracturing layers. The duration of one test is around 10 minutes and the method seems appropriate for determining the spatial variability of the snow cover. A series of experiments in a forest opening showed a clear difference in the snow stability between sites below trees and ones in the free field of the opening.

  20. A Warming Surface but a Cooling Top of Atmosphere Associated with Warm, Moist Air Mass Advection over the Ice and Snow Covered Arctic

    Science.gov (United States)

    Sedlar, J.

    2015-12-01

    Atmospheric advection of heat and moisture from lower latitudes to the high-latitude Arctic is a critical component of Earth's energy cycle. Large-scale advective events have been shown to make up a significant portion of the moist static energy budget of the Arctic atmosphere, even though such events are typically infrequent. The transport of heat and moisture over surfaces covered by ice and snow results in dynamic changes to the boundary layer structure, stability and turbulence, as well as to diabatic processes such as cloud distribution, microphysics and subsequent radiative effects. Recent studies have identified advection into the Arctic as a key mechanism for modulating the melt and freeze of snow and sea ice, via modification to all-sky longwave radiation. This paper examines the radiative impact during summer of such Arctic advective events at the top of the atmosphere (TOA), considering also the important role they play for the surface energy budget. Using infrared sounder measurements from the AIRS satellite, the summer frequency of significantly stable and moist advective events from 2003-2014 are characterized; justification of AIRS profiles over the Arctic are made using radiosoundings during a 3-month transect (ACSE) across the Eastern Arctic basin. One such event was observed within the East Siberian Sea in August 2014 during ACSE, providing in situ verification on the robustness and capability of AIRS to monitor advective cases. Results will highlight the important surface warming aspect of stable, moist instrusions. However a paradox emerges as such events also result in a cooling at the TOA evident on monthly mean TOA radiation. Thus such events have a climatic importance over ice and snow covered surfaces across the Arctic. ERA-Interim reanalyses are examined to provide a longer term perspective on the frequency of such events as well as providing capability to estimate meridional fluxes of moist static energy.

  1. Evaluation of Flat Surface Temperature Probes

    Science.gov (United States)

    Beges, G.; Rudman, M.; Drnovsek, J.

    2011-01-01

    The objective of this paper is elaboration of elements related to metrological analysis in the field of surface temperature measurement. Surface temperature measurements are applicable in many fields. As examples, safety testing of electrical appliances and a pharmaceutical production line represent case studies for surface temperature measurements. In both cases correctness of the result of the surface temperature has an influence on final product safety and quality and thus conformity with specifications. This paper deals with the differences of flat surface temperature probes in measuring the surface temperature. For the purpose of safety testing of electrical appliances, surface temperature measurements are very important for safety of the user. General requirements are presented in European standards, which support requirements in European directives, e.g., European Low Voltage Directive 2006/95/EC and pharmaceutical requirements, which are introduced in official state legislation. This paper introduces a comparison of temperature measurements of an attached thermocouple on the measured surface and measurement with flat surface temperature probes. As a heat generator, a so called temperature artifact is used. It consists of an aluminum plate with an incorporated electrical heating element with very good temperature stability in the central part. The probes and thermocouple were applied with different forces to the surface in horizontal and vertical positions. The reference temperature was measured by a J-type fine-wire (0.2 mm) thermocouple. Two probes were homemade according to requirements in the European standard EN 60335-2-9/A12, one with a fine-wire (0.2 mm) thermocouple and one with 0.5mm of thermocouple wire diameter. Additional commercially available probes were compared. Differences between probes due to thermal conditions caused by application of the probe were found. Therefore, it can happen that measurements are performed with improper equipment or

  2. Scaling and Numerical Model Evaluation of Snow-Cover Effects on the Generation and Modification of Daytime Mesoscale Circulations.

    Science.gov (United States)

    Segal, M.; Garratt, J. R.; Pielke, R. A.; Ye, Z.

    1991-04-01

    Consideration of the sensible heat flux characteristics over a snow surface suggests a significant diminution in the magnitude of the flux, compared to that over a snow-free surface under the same environmental conditions. Consequently, the existence of snow-covered mesoscale areas adjacent to snow-free areas produces horizontal thermal gradients in the lower atmosphere during the daytime, possibly resulting in a `snow breeze.' In addition, suppression of the daytime thermally induced upslope flow over snow-covered slopes is likely to occur. The present paper provides scaling and modeling evaluations of these situations, with quantification of the generated and modified circulations. These evaluations suggest that under ideal situations involved with uniform snow cover over large areas, particularly in late winter and early spring, a noticeable `snow breeze' is likely to develop. Additionally: suppression of the daytime thermally induced upslope flow is significant and may even result in a daytime drainage flow. The effects of bare ground patchiness in the snow cover on these circulations are also explored, both for flat terrain and slope-flow situations. A patchiness fraction greater than 0.5 is found to result in a noticeably reduced snow-breeze circulation, while a patchiness fraction of only 0.1 caused the simulated daytime drainage flow over slopes to he reversed.

  3. Endolithic Microbial Life in Extreme Cold Climate: Snow Is Required, but Perhaps Less Is More

    Directory of Open Access Journals (Sweden)

    Henry J. Sun

    2013-04-01

    Full Text Available Cyanobacteria and lichens living under sandstone surfaces in the McMurdo Dry Valleys require snow for moisture. Snow accumulated beyond a thin layer, however, is counterproductive, interfering with rock insolation, snow melting, and photosynthetic access to light. With this in mind, the facts that rock slope and direction control colonization, and that climate change results in regional extinctions, can be explained. Vertical cliffs, which lack snow cover and are perpetually dry, are devoid of organisms. Boulder tops and edges can trap snow, but gravity and wind prevent excessive buildup. There, the organisms flourish. In places where snow-thinning cannot occur and snow drifts collect, rocks may contain living or dead communities. In light of these observations, the possibility of finding extraterrestrial endolithic communities on Mars cannot be eliminated.

  4. Snow occurrence time on the Russia’s territory in the early 21st century (from satellite data

    Directory of Open Access Journals (Sweden)

    T. B. Titkova

    2017-01-01

    Full Text Available Time of the snow cover appearance, existence and disappearance on the Russia’s territory in the early 21st century (2000–2015 was corrected using the MODIS/Terra satellite data (the 8-day discreteness, and the 0.5×0.5° resolution. The satellite data errors were estimated from data of the ground stations observations. The errors were found to be maximal in autumn and minimal in spring. The relationship between the snow cover characteristics and the climate ones was investigated using data obtained at the ground-based stations together with correlation between dates of snow appearance and loss and the climate parameters. The dependences obtained were tested by means of correlation and regression analysis over the longitudinal sectors. Significant coefficients of correlation (the Student criterion of probability was equal to 0.95 were found between time of the snow cover presence and dates of the temperature drop below 0 °С and the amount of days with negative temperatures. Changes in the climate characteristics result in that due to decreasing of the solid precipitation in winter time the snow presence duration becomes shorter over the European part of Russia and in the Western Siberia. The shortening in the Middle Siberia is caused by the spring warming. Durations of the snow occurrence in the Far East area are different. On the Chukotka peninsula the duration is longer because of the autumn fall in temperature while in the Kamchatka region the snow occurrence time is shorter due to significant decrease of a period with negative temperatures in both the autumn and spring seasons.

  5. A statistical adjustment approach for climate projections of snow conditions in mountain regions using energy balance land surface models

    Science.gov (United States)

    Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Lafaysse, Matthieu

    2017-04-01

    Projections of future climate change have been increasingly called for lately, as the reality of climate change has been gradually accepted and societies and governments have started to plan upcoming mitigation and adaptation policies. In mountain regions such as the Alps or the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenue, particular attention is brought to current and future snow availability. The question of the vulnerability of mountain ecosystems as well as the occurrence of climate-related hazards such as avalanches and debris-flows is also under consideration. In order to generate projections of snow conditions, however, downscaling global climate models (GCMs) by using regional climate models (RCMs) is not sufficient to capture the fine-scale processes and thresholds at play. In particular, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Simulations from GCMs and RCMs moreover suffer from biases compared to local observations, due to their rather coarse spatial and altitudinal resolution, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted using empirical-statistical downscaling and error correction methods, before they can be used to drive specific models such as energy balance land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees and the French Alps for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. We first introduce a thorough evaluation of the method using using model runs from the ALADIN RCM driven by a global reanalysis over the

  6. Temperature dependence of nuclear surface properties

    International Nuclear Information System (INIS)

    Campi, X.; Stringari, S.

    1982-01-01

    Thermal properties of nuclear surface are investigated in a semi-infinite medium. Explicit analytical expression are given for the temperature dependence of surface thickness, surface energy and surface free energy. In this model the temperature effects depend critically on the nuclear incompressibility and on the shape of the effective mass at the surface. To illustrate the relevance of these effects we made an estimate of the temperature dependence of the fission barrier height. (orig.)

  7. A Particle Batch Smoother Approach to Snow Water Equivalent Estimation

    Science.gov (United States)

    Margulis, Steven A.; Girotto, Manuela; Cortes, Gonzalo; Durand, Michael

    2015-01-01

    This paper presents a newly proposed data assimilation method for historical snow water equivalent SWE estimation using remotely sensed fractional snow-covered area fSCA. The newly proposed approach consists of a particle batch smoother (PBS), which is compared to a previously applied Kalman-based ensemble batch smoother (EnBS) approach. The methods were applied over the 27-yr Landsat 5 record at snow pillow and snow course in situ verification sites in the American River basin in the Sierra Nevada (United States). This basin is more densely vegetated and thus more challenging for SWE estimation than the previous applications of the EnBS. Both data assimilation methods provided significant improvement over the prior (modeling only) estimates, with both able to significantly reduce prior SWE biases. The prior RMSE values at the snow pillow and snow course sites were reduced by 68%-82% and 60%-68%, respectively, when applying the data assimilation methods. This result is encouraging for a basin like the American where the moderate to high forest cover will necessarily obscure more of the snow-covered ground surface than in previously examined, less-vegetated basins. The PBS generally outperformed the EnBS: for snow pillows the PBSRMSE was approx.54%of that seen in the EnBS, while for snow courses the PBSRMSE was approx.79%of the EnBS. Sensitivity tests show relative insensitivity for both the PBS and EnBS results to ensemble size and fSCA measurement error, but a higher sensitivity for the EnBS to the mean prior precipitation input, especially in the case where significant prior biases exist.

  8. Snow snake performance monitoring.

    Science.gov (United States)

    2008-12-01

    A recent study, Three-Dimensional Roughness Elements for Snow Retention (FHWA-WY-06/04F) (Tabler 2006), demonstrated : positive evidence for the effectiveness of Snow Snakes, a new type of snow fence suitable for use within the highway right-of...

  9. Projecting the Dependence of Sage-steppe Vegetation on Redistributed Snow in a Warming Climate.

    Science.gov (United States)

    Soderquist, B.; Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Strand, E. K.

    2015-12-01

    In mountainous regions, the redistribution of snow by wind can increase the effective precipitation available to vegetation. Moisture subsidies caused by drifting snow may be critical to plant productivity in semi-arid ecosystems. However, with increasing temperatures, the distribution of precipitation is becoming more uniform as rain replaces drifting snow. Understanding the ecohydrological interactions between sagebrush steppe vegetation communities and the heterogeneous distribution of soil moisture is essential for predicting and mitigating future losses in ecosystem diversity and productivity in regions characterized by snow dominated precipitation regimes. To address the dependence of vegetation productivity on redistributed snow, we simulated the net primary production (NPP) of aspen, sagebrush, and C3 grass plant functional types spanning a precipitation phase (rain:snow) gradient in the Reynolds Creek Experimental Watershed and Critical Zone Observatory (RCEW-CZO). The biogeochemical process model Biome-BGC was used to simulate NPP at three sites located directly below snowdrifts that provide melt water late into the spring. To assess climate change impacts on future plant productivity, mid-century (2046-2065) NPP was simulated using the average temperature increase from the Multivariate Adaptive Constructed Analogs (MACA) data set under the RCP 8.5 emission scenario. At the driest site, mid-century projections of decreased snow cover and increased growing season evaporative demand resulted in limiting soil moisture up to 30 and 40 days earlier for aspen and sage respectively. While spring green up for aspen occurred an average of 13 days earlier under climate change scenarios, NPP remained negative up to 40 days longer during the growing season. These results indicate that the loss of the soil moisture subsidy stemming from prolonged redistributed snow water resources can directly influence ecosystem productivity in the rain:snow transition zone.

  10. Near-Surface Refractory Black Carbon Observations in the Atmosphere and Snow in the McMurdo Dry Valleys, Antarctica, and Potential Impacts of Foehn Winds

    Science.gov (United States)

    Khan, Alia L.; McMeeking, Gavin R.; Schwarz, Joshua P.; Xian, Peng; Welch, Kathleen A.; Berry Lyons, W.; McKnight, Diane M.

    2018-03-01

    Measurements of light-absorbing particles in the boundary layer of the high southern latitudes are scarce, particularly in the McMurdo Dry Valleys (MDV), Antarctica. During the 2013-2014 austral summer near-surface boundary layer refractory black carbon (rBC) aerosols were measured in air by a single-particle soot photometer (SP2) at multiple locations in the MDV. Near-continuous rBC atmospheric measurements were collected at Lake Hoare Camp (LH) over 2 months and for several hours at more remote locations away from established field camps. We investigated periods dominated by both upvalley and downvalley winds to explore the causes of differences in rBC concentrations and size distributions. Snow samples were also collected in a 1 m pit on a glacier near the camp. The range of concentrations rBC in snow was 0.3-1.2 ± 0.3 μg-rBC/L-H2O, and total organic carbon was 0.3-1.4 ± 0.3 mg/L. The rBC concentrations measured in this snow pit are not sufficient to reduce surface albedo; however, there is potential for accumulation of rBC on snow and ice surfaces at low elevation throughout the MDV, which were not measured as part of this study. At LH, the average background rBC mass aerosol concentrations were 1.3 ng/m3. rBC aerosol mass concentrations were slightly lower, 0.09-1.3 ng/m3, at the most remote sites in the MDV. Concentration spikes as high as 200 ng/m3 were observed at LH, associated with local activities. During a foehn wind event, the average rBC mass concentration increased to 30-50 ng/m3. Here we show that the rBC increase could be due to resuspension of locally produced BC from generators, rocket toilets, and helicopters, which may remain on the soil surface until redistributed during high wind events. Quantification of local production and long-range atmospheric transport of rBC to the MDV is necessary for understanding the impacts of this species on regional climate.

  11. Simulation of wind-induced snow transport and sublimation in alpine terrain using a fully coupled snowpack/atmosphere model

    Science.gov (United States)

    Vionnet, V.; Martin, E.; Masson, V.; Guyomarc'h, G.; Naaim-Bouvet, F.; Prokop, A.; Durand, Y.; Lac, C.

    2014-03-01

    In alpine regions, wind-induced snow transport strongly influences the spatio-temporal evolution of the snow cover throughout the winter season. To gain understanding on the complex processes that drive the redistribution of snow, a new numerical model is developed. It directly couples the detailed snowpack model Crocus with the atmospheric model Meso-NH. Meso-NH/Crocus simulates snow transport in saltation and in turbulent suspension and includes the sublimation of suspended snow particles. The coupled model is evaluated against data collected around the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps). First, 1-D simulations show that a detailed representation of the first metres of the atmosphere is required to reproduce strong gradients of blowing snow concentration and compute mass exchange between the snowpack and the atmosphere. Secondly, 3-D simulations of a blowing snow event without concurrent snowfall have been carried out. Results show that the model captures the main structures of atmospheric flow in alpine terrain. However, at 50 m grid spacing, the model reproduces only the patterns of snow erosion and deposition at the ridge scale and misses smaller scale patterns observed by terrestrial laser scanning. When activated, the sublimation of suspended snow particles causes a reduction of deposited snow mass of 5.3% over the calculation domain. Total sublimation (surface + blowing snow) is three times higher than surface sublimation in a simulation neglecting blowing snow sublimation.

  12. Catchment-scale evaluation of pollution potential of urban snow at two residential catchments in southern Finland.

    Science.gov (United States)

    Sillanpää, Nora; Koivusalo, Harri

    2013-01-01

    Despite the crucial role of snow in the hydrological cycle in cold climate conditions, monitoring studies of urban snow quality often lack discussions about the relevance of snow in the catchment-scale runoff management. In this study, measurements of snow quality were conducted at two residential catchments in Espoo, Finland, simultaneously with continuous runoff measurements. The results of the snow quality were used to produce catchment-scale estimates of areal snow mass loads (SML). Based on the results, urbanization reduced areal snow water equivalent but increased pollutant accumulation in snow: SMLs in a medium-density residential catchment were two- to four-fold higher in comparison with a low-density residential catchment. The main sources of pollutants were related to vehicular traffic and road maintenance, but also pet excrement increased concentrations to a high level. Ploughed snow can contain 50% of the areal pollutant mass stored in snow despite its small surface area within a catchment.

  13. Quantifying small-scale spatio-temporal variability of snow stratigraphy in forests based on high-resolution snow penetrometry

    Science.gov (United States)

    Teich, M.; Hagenmuller, P.; Bebi, P.; Jenkins, M. J.; Giunta, A. D.; Schneebeli, M.

    2017-12-01

    Snow stratigraphy, the characteristic layering within a seasonal snowpack, has important implications for snow remote sensing, hydrology and avalanches. Forests modify snowpack properties through interception, wind speed reduction, and changes to the energy balance. The lack of snowpack observations in forests limits our ability to understand the evolution of snow stratigraphy and its spatio-temporal variability as a function of forest structure and to observe snowpack response to changes in forest cover. We examined the snowpack under canopies of a spruce forest in the central Rocky Mountains, USA, using the SnowMicroPen (SMP), a high resolution digital penetrometer. Weekly-repeated penetration force measurements were recorded along 10 m transects every 0.3 m in winter 2015 and bi-weekly along 20 m transects every 0.5 m in 2016 in three study plots beneath canopies of undisturbed, bark beetle-disturbed and harvested forest stands, and an open meadow. To disentangle information about layer hardness and depth variabilities, and to quantitatively compare the different SMP profiles, we applied a matching algorithm to our dataset, which combines several profiles by automatically adjusting their layer thicknesses. We linked spatial and temporal variabilities of penetration force and depth, and thus snow stratigraphy to forest and meteorological conditions. Throughout the season, snow stratigraphy was more heterogeneous in undisturbed but also beneath bark beetle-disturbed forests. In contrast, and despite remaining small diameter trees and woody debris, snow stratigraphy was rather homogenous at the harvested plot. As expected, layering at the non-forested plot varied only slightly over the small spatial extent sampled. At the open and harvested plots, persistent crusts and ice lenses were clearly present in the snowpack, while such hard layers barely occurred beneath undisturbed and disturbed canopies. Due to settling, hardness significantly increased with depth at

  14. A Method for Snow Reanalysis: The Sierra Nevada (USA) Example

    Science.gov (United States)

    Girotto, Manuela; Margulis, Steven; Cortes, Gonzalo; Durand, Michael

    2017-01-01

    This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.

  15. Rapid responses of permafrost and vegetation to experimentally increased snow cover in sub-arctic Sweden

    International Nuclear Information System (INIS)

    Johansson, Margareta; Bosiö, Julia; Akerman, H Jonas; Jackowicz-Korczynski, Marcin; Christensen, Torben R; Callaghan, Terry V

    2013-01-01

    Increased snow depth already observed, and that predicted for the future are of critical importance to many geophysical and biological processes as well as human activities. The future characteristics of sub-arctic landscapes where permafrost is particularly vulnerable will depend on complex interactions between snow cover, vegetation and permafrost. An experimental manipulation was, therefore, set up on a lowland peat plateau with permafrost, in northernmost Sweden, to simulate projected future increases in winter precipitation and to study their effects on permafrost and vegetation. After seven years of treatment, statistically significant differences between manipulated and control plots were found in mean winter ground temperatures, which were 1.5 ° C higher in manipulated plots. During the winter, a difference in minimum temperatures of up to 9 ° C higher could be found in individual manipulated plots compared with control plots. Active layer thicknesses increased at the manipulated plots by almost 20% compared with the control plots and a mean surface subsidence of 24 cm was recorded in the manipulated plots compared to 5 cm in the control plots. The graminoid Eriophorum vaginatum has expanded in the manipulated plots and the vegetation remained green longer in the season. (letter)

  16. Dynamic-stochastic modeling of snow cover formation on the European territory of Russia

    Directory of Open Access Journals (Sweden)

    A. N. Gelfan

    2014-01-01

    Full Text Available A dynamic-stochastic model, which combines a deterministic model of snow cover formation with a stochastic weather generator, has been developed. The deterministic snow model describes temporal change of the snow depth, content of ice and liquid water, snow density, snowmelt, sublimation, re-freezing of melt water, and snow metamorphism. The model has been calibrated and validated against the long-term data of snow measurements over the territory of the European Russia. The model showed good performance in simulating time series of the snow water equivalent and snow depth. The developed weather generator (NEsted Weather Generator, NewGen includes nested generators of annual, monthly and daily time series of weather variables (namely, precipitation, air temperature, and air humidity. The parameters of the NewGen have been adjusted through calibration against the long-term meteorological data in the European Russia. A disaggregation procedure has been proposed for transforming parameters of the annual weather generator into the parameters of the monthly one and, subsequently, into the parameters of the daily generator. Multi-year time series of the simulated daily weather variables have been used as an input to the snow model. Probability properties of the snow cover, such as snow water equivalent and snow depth for return periods of 25 and 100 years, have been estimated against the observed data, showing good correlation coefficients. The described model has been applied to different landscapes of European Russia, from steppe to taiga regions, to show the robustness of the proposed technique.

  17. Observation and modeling of snow melt and superimposed ice formation on sea ice

    OpenAIRE

    Nicolaus, Marcel; Haas, Christian

    2004-01-01

    Sea ice plays a key role within the global climate system. It covers some 7% of earths surface and processes a strong seasonal cycle. Snow on sea ice even amplifies the importance of sea ice in the coupled atmosphere-ice-ocean system, because it dominates surface properties and energy balance (incl. albedo).Several quantitative observations of summer sea ice and its snow cover show the formation of superimposed ice and a gap layer underneath, which was found to be associated to high standing ...

  18. Scavenging of gaseous mercury by acidic snow at Kuujjuarapik, Northern Quebec

    International Nuclear Information System (INIS)

    Lahoutifard, Nazafarin; Poissant, Laurier; Scott, Susannah L.

    2006-01-01

    One fate of gaseous elemental mercury (GEM) in the Arctic has been identified as gas phase oxidation by halogen-containing radicals, leading to abrupt atmospheric mercury depletion concurrent with ozone depletion. Rapid deposition of oxidized mercury leads to snow enrichment in mercury. In this report, we describe experiments that demonstrate the ability of snow to directly scavenge atmospheric mercury. The study was conducted at Kuujjuarapik, Quebec, Canada (latitude 55 o 17'N). A mercury depletion event (MDE) caused the mercury concentration in the surface snow of the coastal snowpack to double, from (9.4 ± 2.0) to (19.2 ± 1.7) ng/L. Independent of the MDE, mercury concentrations increased five-fold, from (10.0 ± 0.1) to (51.4 ± 6.0) ng/L, upon spiking the snow with 500 μM hydrogen peroxide under solar irradiation. Total organic carbon in the spiked irradiated snow samples also decreased, consistent with the formation of strongly oxidizing species. The role of the snowpack in releasing GEM to the atmosphere has been reported; these findings suggest that snow may also play a role in enhancing deposition of mercury

  19. Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

    Science.gov (United States)

    Jiang, L.; Wang, G.

    2017-12-01

    Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map

  20. Deriving Snow-Cover Depletion Curves for Different Spatial Scales from Remote Sensing and Snow Telemetry Data

    Science.gov (United States)

    Fassnacht, Steven R.; Sexstone, Graham A.; Kashipazha, Amir H.; Lopez-Moreno, Juan Ignacio; Jasinski, Michael F.; Kampf, Stephanie K.; Von Thaden, Benjamin C.

    2015-01-01

    During the melting of a snowpack, snow water equivalent (SWE) can be correlated to snow-covered area (SCA) once snow-free areas appear, which is when SCA begins to decrease below 100%. This amount of SWE is called the threshold SWE. Daily SWE data from snow telemetry stations were related to SCA derived from moderate-resolution imaging spectro radiometer images to produce snow-cover depletion curves. The snow depletion curves were created for an 80,000 sq km domain across southern Wyoming and northern Colorado encompassing 54 snow telemetry stations. Eight yearly snow depletion curves were compared, and it is shown that the slope of each is a function of the amount of snow received. Snow-cover depletion curves were also derived for all the individual stations, for which the threshold SWE could be estimated from peak SWE and the topography around each station. A stations peak SWE was much more important than the main topographic variables that included location, elevation, slope, and modelled clear sky solar radiation. The threshold SWE mostly illustrated inter-annual consistency.

  1. Experimental measurement and modeling of snow accumulation and snowmelt in a mountain microcatchment

    Science.gov (United States)

    Danko, Michal; Krajčí, Pavel; Hlavčo, Jozef; Kostka, Zdeněk; Holko, Ladislav

    2016-04-01

    Fieldwork is a very useful source of data in all geosciences. This naturally applies also to the snow hydrology. Snow accumulation and snowmelt are spatially very heterogeneous especially in non-forested, mountain environments. Direct field measurements provide the most accurate information about it. Quantification and understanding of processes, that cause these spatial differences are crucial in prediction and modelling of runoff volumes in spring snowmelt period. This study presents possibilities of detailed measurement and modeling of snow cover characteristics in a mountain experimental microcatchment located in northern part of Slovakia in Western Tatra mountains. Catchment area is 0.059 km2 and mean altitude is 1500 m a.s.l. Measurement network consists of 27 snow poles, 3 small snow lysimeters, discharge measurement device and standard automatic weather station. Snow depth and snow water equivalent (SWE) were measured twice a month near the snow poles. These measurements were used to estimate spatial differences in accumulation of SWE. Snowmelt outflow was measured by small snow lysimeters. Measurements were performed in winter 2014/2015. Snow water equivalent variability was very high in such a small area. Differences between particular measuring points reached 600 mm in time of maximum SWE. The results indicated good performance of a snow lysimeter in case of snowmelt timing identification. Increase of snowmelt measured by the snow lysimeter had the same timing as increase in discharge at catchment's outlet and the same timing as the increase in air temperature above the freezing point. Measured data were afterwards used in distributed rainfall-runoff model MIKE-SHE. Several methods were used for spatial distribution of precipitation and snow water equivalent. The model was able to simulate snow water equivalent and snowmelt timing in daily step reasonably well. Simulated discharges were slightly overestimated in later spring.

  2. Some attributes of snow occurrence and snowmelt/sublimation rates ...

    African Journals Online (AJOL)

    2017-04-02

    Apr 2, 2017 ... regions may be strongly influenced by seasonal fluctuations in ... accurate snow mapping and modelling of snowmelt/runoff are ... regional climate and hydrology, earth surface processes, and rural livelihoods .... from clouds.

  3. Evaluation of the most suitable threshold value for modelling snow glacier melt through T- index approach: the case study of Forni Glacier (Italian Alps)

    Science.gov (United States)

    Senese, Antonella; Maugeri, Maurizio; Vuillermoz, Elisa; Smiraglia, Claudio; Diolaiuti, Guglielmina

    2014-05-01

    Glacier melt occurs whenever the surface temperature is null (273.15 K) and the net energy budget is positive. These conditions can be assessed by analyzing meteorological and energy data acquired by a supraglacial Automatic Weather Station (AWS). In the case this latter is not present at the glacier surface the assessment of actual melting conditions and the evaluation of melt amount is difficult and degree-day (also named T-index) models are applied. These approaches require the choice of a correct temperature threshold. In fact, melt does not necessarily occur at daily air temperatures higher than 273.15 K, since it is determined by the energy budget which in turn is only indirectly affected by air temperature. This is the case of the late spring period when ablation processes start at the glacier surface thus progressively reducing snow thickness. In this study, to detect the most indicative air temperature threshold witnessing melt conditions in the April-June period, we analyzed air temperature data recorded from 2006 to 2012 by a supraglacial AWS (at 2631 m a.s.l.) on the ablation tongue of the Forni Glacier (Italy), and by a weather station located nearby the studied glacier (at Bormio, 1225 m a.s.l.). Moreover we evaluated the glacier energy budget (which gives the actual melt, Senese et al., 2012) and the snow water equivalent values during this time-frame. Then the ablation amount was estimated both from the surface energy balance (MEB from supraglacial AWS data) and from degree-day method (MT-INDEX, in this latter case applying the mean tropospheric lapse rate to temperature data acquired at Bormio changing the air temperature threshold) and the results were compared. We found that the mean tropospheric lapse rate permits a good and reliable reconstruction of daily glacier air temperature conditions and the major uncertainty in the computation of snow melt from degree-day models is driven by the choice of an appropriate air temperature threshold. Then

  4. Using idealized snow forcing to test teleconnections with the Indian summer monsoon in the Hadley Centre GCM

    Energy Technology Data Exchange (ETDEWEB)

    Turner, A.G. [University of Reading, NCAS-Climate, Walker Institute for Climate System Research, Department of Meteorology, Reading (United Kingdom); Slingo, J.M. [University of Reading, NCAS-Climate, Walker Institute for Climate System Research, Department of Meteorology, Reading (United Kingdom); Met Office, Exeter (United Kingdom)

    2011-05-15

    Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible

  5. Use of machine learning techniques for modeling of snow depth

    Directory of Open Access Journals (Sweden)

    G. V. Ayzel

    2017-01-01

    Full Text Available Snow exerts significant regulating effect on the land hydrological cycle since it controls intensity of heat and water exchange between the soil-vegetative cover and the atmosphere. Estimating of a spring flood runoff or a rain-flood on mountainous rivers requires understanding of the snow cover dynamics on a watershed. In our work, solving a problem of the snow cover depth modeling is based on both available databases of hydro-meteorological observations and easily accessible scientific software that allows complete reproduction of investigation results and further development of this theme by scientific community. In this research we used the daily observational data on the snow cover and surface meteorological parameters, obtained at three stations situated in different geographical regions: Col de Porte (France, Sodankyla (Finland, and Snoquamie Pass (USA.Statistical modeling of the snow cover depth is based on a complex of freely distributed the present-day machine learning models: Decision Trees, Adaptive Boosting, Gradient Boosting. It is demonstrated that use of combination of modern machine learning methods with available meteorological data provides the good accuracy of the snow cover modeling. The best results of snow cover depth modeling for every investigated site were obtained by the ensemble method of gradient boosting above decision trees – this model reproduces well both, the periods of snow cover accumulation and its melting. The purposeful character of learning process for models of the gradient boosting type, their ensemble character, and use of combined redundancy of a test sample in learning procedure makes this type of models a good and sustainable research tool. The results obtained can be used for estimating the snow cover characteristics for river basins where hydro-meteorological information is absent or insufficient.

  6. Monitoring Snow and Land Ice Using Satellite data in the GMES Project CryoLand

    Science.gov (United States)

    Bippus, Gabriele; Nagler, Thomas

    2013-04-01

    The main objectives of the project "CryoLand - GMES Service Snow and Land Ice" are to develop, implement and validate services for snow, glaciers and lake and river ice products as a Downstream Service within the Global Monitoring for Environment and Security (GMES) program of the European Commission. CryoLand exploits Earth Observation data from current optical and microwave sensors and of the upcoming GMES Sentinel satellite family. The project prepares also the basis for the cryospheric component of the GMES Land Monitoring services. The CryoLand project team consists of 10 partner organisations from Austria, Finland, Norway, Sweden, Switzerland and Romania and is funded by the 7th Framework Program of the European Commission. The CryoLand baseline products for snow include fractional snow extent from optical satellite data, the extent of melting snow from SAR data, and coarse resolution snow water equivalent maps from passive microwave data. Experimental products include maps of snow surface wetness and temperature. The products range from large scale coverage at medium resolution to regional products with high resolution, in order to address a wide user community. Medium resolution optical data (e.g. MODIS, in the near future Sentinel-3) and SAR (ENVISAT ASAR, in the near future Sentinel-1) are the main sources of EO data for generating large scale products in near real time. For generation of regional products high resolution satellite data are used. Glacier products are based on high resolution optical (e.g. SPOT-5, in the near future Sentinel-2) and SAR (TerraSAR-X, in the near future Sentinel-1) data and include glacier outlines, mapping of glacier facies, glacier lakes and ice velocity. The glacier products are generated on users demand. Current test areas are located in the Alps, Norway, Greenland and the Himalayan Mountains. The lake and river ice products include ice extent and its temporal changes and snow extent on ice. The algorithms for these

  7. Improving snow cover mapping in forests through the use of a canopy reflectance model

    International Nuclear Information System (INIS)

    Klein, A.G.; Hall, D.K.; Riggs, G.A.

    1998-01-01

    MODIS, the moderate resolution imaging spectro radiometer, will be launched in 1998 as part of the first earth observing system (EOS) platform. Global maps of land surface properties, including snow cover, will be created from MODIS imagery. The MODIS snow-cover mapping algorithm that will be used to produce daily maps of global snow cover extent at 500 m resolution is currently under development. With the exception of cloud cover, the largest limitation to producing a global daily snow cover product using MODIS is the presence of a forest canopy. A Landsat Thematic Mapper (TM) time-series of the southern Boreal Ecosystem–Atmosphere Study (BOREAS) study area in Prince Albert National Park, Saskatchewan, was used to evaluate the performance of the current MODIS snow-cover mapping algorithm in varying forest types. A snow reflectance model was used in conjunction with a canopy reflectance model (GeoSAIL) to model the reflectance of a snow-covered forest stand. Using these coupled models, the effects of varying forest type, canopy density, snow grain size and solar illumination geometry on the performance of the MODIS snow-cover mapping algorithm were investigated. Using both the TM images and the reflectance models, two changes to the current MODIS snow-cover mapping algorithm are proposed that will improve the algorithm's classification accuracy in forested areas. The improvements include using the normalized difference snow index and normalized difference vegetation index in combination to discriminate better between snow-covered and snow-free forests. A minimum albedo threshold of 10% in the visible wavelengths is also proposed. This will prevent dense forests with very low visible albedos from being classified incorrectly as snow. These two changes increase the amount of snow mapped in forests on snow-covered TM scenes, and decrease the area incorrectly identified as snow on non-snow-covered TM scenes. (author)

  8. The effects of snow and salt on ice table stability in University Valley, Antarctica

    Science.gov (United States)

    Williams, Kaj; Heldmann, Jennifer L.; McKay, Christopher P.; Mellon, Michael T.

    2018-01-01

    The Antarctic Dry Valleys represent a unique environment where it is possible to study dry permafrost overlaying an ice-rich permafrost. In this paper, two opposing mechanisms for ice table stability in University Valley are addressed: i) diffusive recharge via thin seasonal snow deposits and ii) desiccation via salt deposits in the upper soil column. A high-resolution time-marching soil and snow model was constructed and applied to University Valley, driven by meteorological station atmospheric measurements. It was found that periodic thin surficial snow deposits (observed in University Valley) are capable of drastically slowing (if not completely eliminating) the underlying ice table ablation. The effects of NaCl, CaCl2 and perchlorate deposits were then modelled. Unlike the snow cover, however, the presence of salt in the soil surface (but no periodic snow) results in a slight increase in the ice table recession rate, due to the hygroscopic effects of salt sequestering vapour from the ice table below. Near-surface pore ice frequently forms when large amounts of salt are present in the soil due to the suppression of the saturation vapour pressure. Implications for Mars high latitudes are discussed.

  9. Sampling in the Snow: High School Winter Field Experiences Provide Relevant, Real World Connections Between Scientific Practices and Disciplinary Core Ideas

    Science.gov (United States)

    Hanson, E. W.; Burakowski, E. A.

    2014-12-01

    For much of the northern United States, the months surrounding the winter solstice are times of increased darkness, low temperatures, and frozen landscapes. It's a time when many high school science educators, who otherwise would venture outside with their classes, hunker down and are wary of the outdoors. However, a plethora of learning opportunities lies just beyond the classroom. Working collaboratively, a high school science teacher and a snow scientist have developed multiple activities to engage students in the scientific process of collecting, analyzing and interpreting the winter world using snow data to (1) learn about the insulative properties of snow, and (2) to learn about the role of snow cover on winter climate through its reflective properties while participating in a volunteer network that collects snow depth, albedo (reflectivity), and density data. These outdoor field-based snow investigations incorporate Next Generation Science Standards (NGSS) and disciplinary core ideas, including ESS2.C: The roles of water in Earth's surface processes and ESS2.D: Weather and Climate. Additionally, the lesson plans presented address Common Core State Standards (CCSS) in Mathematics, including the creation and analysis of bar graphs and time series plots (CCSS.Math.HSS-ID.A.1) and xy scatter plots (CCSS.Math.HSS-ID.B.6). High school students participating in the 2013/2014 snow sampling season described their outdoor learning experience as "authentic" and "hands-on" as compared to traditional class indoors. They emphasized that learning outdoors was essential to their understanding of underlying content and concepts because they "learn through actual experience."

  10. Hydrological Implications of Covering Wind-Blown Snow Accumulations with Geotextiles on Mount Aragats, Armenia

    Directory of Open Access Journals (Sweden)

    Alexander Nestler

    2014-07-01

    Full Text Available Snow is an excellent water reservoir, naturally storing large quantities of water at time scales from a few days to several months. In summer-dry countries, like Armenia, runoff due to snow melt from mountain regions is highly important for a sustained water supply (irrigation, hydropower. Snow fields on Mount Aragats, Armenia’s highest peak, often persist until July, providing vital amounts of melt water. Artificially managing these wind-driven snow accumulations as a natural water reservoir might have considerable potential. In the context of the Swiss-Armenian joint venture, Freezwater, snow fields are covered with geotextiles in order to delay snow melt long enough to provide additional melt water in the dry season of the year. In this study, we analyze the hydrological effectiveness of the artificial management of the natural snow cover on Mount Aragats based on various field measurements acquired over a three-year period and numerical modeling. Over the winter season, partly more than five meter-thick snow deposits are formed supported by snow redistribution by strong wind. Repeated mappings of snow fields indicate that snow cover patterns remain highly consistent over time. Measurements of ablation below manually applied geotextiles show a considerable reduction of melt rates by more than 50%. Simulations with an energy-balance model and a distributed temperature-index model allow assessing the hydrological effect of artificial snow management for different initial snow depths and elevations and suggest that coverage is needed at a large scale in order to generate a significant impact on discharge.

  11. Dust radiative forcing in snow of the Upper Colorado River Basin: 1. A 6 year record of energy balance, radiation, and dust concentrations

    Science.gov (United States)

    Painter, Thomas H.; Skiles, S. Mckenzie; Deems, Jeffrey S.; Bryant, Ann C.; Landry, Christopher C.

    2012-07-01

    Dust in snow accelerates snowmelt through its direct reduction of snow albedo and its further indirect reduction of albedo by accelerating the growth of snow grains. Since the westward expansion of the United States that began in the mid-19th century, the mountain snow cover of the Colorado River Basin has been subject to five-fold greater dust loading, largely from the Colorado Plateau and Great Basin. Radiative forcing of snowmelt by dust is not captured by conventional micrometeorological measurements, and must be monitored by a more comprehensive suite of radiation instruments. Here we present a 6 year record of energy balance and detailed radiation measurements in the Senator Beck Basin Study Area, San Juan Mountains, Colorado, USA. Data include broadband irradiance, filtered irradiance, broadband reflected flux, filtered reflected flux, broadband and visible albedo, longwave irradiance, wind speed, relative humidity, and air temperatures. The gradient of the snow surface is monitored weekly and used to correct albedo measurements for geometric effects. The snow is sampled weekly for dust concentrations in plots immediately adjacent to each tower over the melt season. Broadband albedo in the last weeks of snow cover ranged from 0.33 to 0.55 across the 6 years and two sites. Total end of year dust concentration in the top 3 cm of the snow column ranged from 0.23 mg g-1 to 4.16 mg g-1. These measurements enable monitoring and modeling of dust and climate-driven snowmelt forcings in the Upper Colorado River Basin.

  12. Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

    Directory of Open Access Journals (Sweden)

    K. Aalstad

    2018-01-01

    Full Text Available With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD at the 1 km scale by assimilating fractional snow-covered area (fSCA satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation ensemble smoother with multiple data assimilation (ES-MDA scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e. and 0.13, respectively. The ES-MDA either

  13. Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

    Science.gov (United States)

    Aalstad, Kristoffer; Westermann, Sebastian; Vikhamar Schuler, Thomas; Boike, Julia; Bertino, Laurent

    2018-01-01

    With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least

  14. The Alpine snow-albedo feedback in regional climate models

    Science.gov (United States)

    Winter, Kevin J.-P. M.; Kotlarski, Sven; Scherrer, Simon C.; Schär, Christoph

    2017-02-01

    The effect of the snow-albedo feedback (SAF) on 2m temperatures and their future changes in the European Alps is investigated in the ENSEMBLES regional climate models (RCMs) with a focus on the spring season. A total of 14 re-analysis-driven RCM experiments covering the period 1961-2000 and 10 GCM-driven transient climate change projections for 1950-2099 are analysed. A positive springtime SAF is found in all RCMs, but the range of the diagnosed SAF is large. Results are compared against an observation-based SAF estimate. For some RCMs, values very close to this estimate are found; other models show a considerable overestimation of the SAF. Net shortwave radiation has the largest influence of all components of the energy balance on the diagnosed SAF and can partly explain its spatial variability. Model deficiencies in reproducing 2m temperatures above snow and ice and associated cold temperature biases at high elevations seem to contribute to a SAF overestimation in several RCMs. The diagnosed SAF in the observational period strongly influences the estimated SAF contribution to twenty first century temperature changes in the European Alps. This contribution is subject to a clear elevation dependency that is governed by the elevation-dependent change in the number of snow days. Elevations of maximum SAF contribution range from 1500 to 2000 m in spring and are found above 2000 m in summer. Here, a SAF contribution to the total simulated temperature change between 0 and 0.5 °C until 2099 (multi-model mean in spring: 0.26 °C) or 0 and 14 % (multi-model mean in spring: 8 %) is obtained for models showing a realistic SAF. These numbers represent a well-funded but only approximate estimate of the SAF contribution to future warming, and a remaining contribution of model-specific SAF misrepresentations cannot be ruled out.

  15. Ensemble mean climatology of snow darkening effect due to deposition of dust, black carbon, and organic carbon as simulated with the NASA GEOS-5 Earth System Model

    Science.gov (United States)

    Yasunari, T. J.; Lau, W. K.; Mahanama, S. P.; Colarco, P. R.; Koster, R. D.; Kim, K.; da Silva, A.

    2013-12-01

    The importance of the snow darkening effect (SDE) caused by solar absorbing aerosols such as dust and black carbon (BC) on climate has been discussed in previous studies. We have developed a snow darkening package for the catchment land surface model coupled to the NASA Goddard Earth Observing System, version 5 (GEOS-5), Earth System Model. Our snow darkening package includes the schemes for snow albedo and mass concentration calculations in polluted snow by dust, BC, and organic carbon (OC) depositions. The snow darkening package is currently available for seasonal snowpack over the model-defined land areas, excluding sea ice and inland of the ice sheets. The depositions of the solar absorbing aerosols are obtained from the GOCART aerosol module in the GEOS-5. Here we show the preliminary results of ensemble mean climatology (EMC) of the full SDE (i.e., dust+BC+OC). Ensemble simulations covering 10-year of 2002-2011 were carried out with the GEOS-5 including and excluding the full SDE for which each has 10 ensemble members. Shortwave radiative forcing (RF) at the top of atmosphere under all-sky condition for the 10-member EMC of the full SDE was relatively larger over Europe, Central Asia (CA), the Himalayas, the Tibetan Plateau (TP), East Asia (EA), Eastern Siberia (ES), the US, and Canadian Arctic. The RF was the strongest over the Himalayas and the TP in the northern hemisphere. The increases of surface air temperature also well correspond to the RF pattern. Larger reductions of snow water equivalent in seasonal snowpack were seen over the Himalayas, the TP, Alaska, Western Canada, and Arctic regions. We will discuss more on the day of the presentation.

  16. Comparison of different methods to retrieve optical-equivalent snow grain size in central Antarctica

    Directory of Open Access Journals (Sweden)

    T. Carlsen

    2017-11-01

    Full Text Available The optical-equivalent snow grain size affects the reflectivity of snow surfaces and, thus, the local surface energy budget in particular in polar regions. Therefore, the specific surface area (SSA, from which the optical snow grain size is derived, was observed for a 2-month period in central Antarctica (Kohnen research station during austral summer 2013/14. The data were retrieved on the basis of ground-based spectral surface albedo measurements collected by the COmpact RAdiation measurement System (CORAS and airborne observations with the Spectral Modular Airborne Radiation measurement sysTem (SMART. The snow grain size and pollution amount (SGSP algorithm, originally developed to analyze spaceborne reflectance measurements by the MODerate Resolution Imaging Spectroradiometer (MODIS, was modified in order to reduce the impact of the solar zenith angle on the retrieval results and to cover measurements in overcast conditions. Spectral ratios of surface albedo at 1280 and 1100 nm wavelength were used to reduce the retrieval uncertainty. The retrieval was applied to the ground-based and airborne observations and validated against optical in situ observations of SSA utilizing an IceCube device. The SSA retrieved from CORAS observations varied between 27 and 89 m2 kg−1. Snowfall events caused distinct relative maxima of the SSA which were followed by a gradual decrease in SSA due to snow metamorphism and wind-induced transport of freshly fallen ice crystals. The ability of the modified algorithm to include measurements in overcast conditions improved the data coverage, in particular at times when precipitation events occurred and the SSA changed quickly. SSA retrieved from measurements with CORAS and MODIS agree with the in situ observations within the ranges given by the measurement uncertainties. However, SSA retrieved from the airborne SMART data slightly underestimated the ground-based results.

  17. Comparison of different methods to retrieve optical-equivalent snow grain size in central Antarctica

    Science.gov (United States)

    Carlsen, Tim; Birnbaum, Gerit; Ehrlich, André; Freitag, Johannes; Heygster, Georg; Istomina, Larysa; Kipfstuhl, Sepp; Orsi, Anaïs; Schäfer, Michael; Wendisch, Manfred

    2017-11-01

    The optical-equivalent snow grain size affects the reflectivity of snow surfaces and, thus, the local surface energy budget in particular in polar regions. Therefore, the specific surface area (SSA), from which the optical snow grain size is derived, was observed for a 2-month period in central Antarctica (Kohnen research station) during austral summer 2013/14. The data were retrieved on the basis of ground-based spectral surface albedo measurements collected by the COmpact RAdiation measurement System (CORAS) and airborne observations with the Spectral Modular Airborne Radiation measurement sysTem (SMART). The snow grain size and pollution amount (SGSP) algorithm, originally developed to analyze spaceborne reflectance measurements by the MODerate Resolution Imaging Spectroradiometer (MODIS), was modified in order to reduce the impact of the solar zenith angle on the retrieval results and to cover measurements in overcast conditions. Spectral ratios of surface albedo at 1280 and 1100 nm wavelength were used to reduce the retrieval uncertainty. The retrieval was applied to the ground-based and airborne observations and validated against optical in situ observations of SSA utilizing an IceCube device. The SSA retrieved from CORAS observations varied between 27 and 89 m2 kg-1. Snowfall events caused distinct relative maxima of the SSA which were followed by a gradual decrease in SSA due to snow metamorphism and wind-induced transport of freshly fallen ice crystals. The ability of the modified algorithm to include measurements in overcast conditions improved the data coverage, in particular at times when precipitation events occurred and the SSA changed quickly. SSA retrieved from measurements with CORAS and MODIS agree with the in situ observations within the ranges given by the measurement uncertainties. However, SSA retrieved from the airborne SMART data slightly underestimated the ground-based results.

  18. J-SEx : The Jollie Snow Experiment, New Zealand

    Science.gov (United States)

    Kerr, T.; Singh, S.; Kees, L.; Webster, C.; Clark, M.; Hendrikx, J.; Woods, R.

    2012-04-01

    Intensive snow observations have been collected in a steep alpine catchment (the Jollie Valley) in the Southern Alps of New Zealand for four years at the time of maximum snow storage. The campaign, called the Jollie Snow Experiment (J-SEx), was undertaken to improve understanding of snow variability in a steep alpine landscape. Observation methods included manual depth-probing at hundreds of locations with associated snowpit-digging, and surface and air-borne ground penetrating radar. In addition, repeat (daily) oblique photography was carried out on a subcatchment for two of the years. Analysis of the observations, in conjunction with similar observations from around the world has enabled direction to be given for selecting optimal modelling scales, and an indication of what processes need to be resolved at the different scales. For instance, if models are to operate at sub-100 m horizontal scales, they need to resolve drifting, sloughing and avalanching processes. Binary regression tree methods have been applied to identify terrain variables which explain the observed snow mass variability. This has enabled an assessment of total catchment snow storage to be established for each year. This assessment showed that the controlling variables change from year to year, so that no single terrain-based interpolation method may be generally applied. The change in the terrain relationships each year has been taken as an indication that the different frequencies of snowfall-related climate types from one year to the next affects which terrain characteristics have the greatest impact on snow variability. Assessment of terrain effects at the slope scale indicates that slope angle has the potential to be a strong influence on snow variability in that steep slopes do not build up large accumulations, and that low-angled regions below steep areas become areas of large snow build-up. This "slope" effect is clearly evident from the repeat photography, with the last areas to melt

  19. Analysis of Light Absorbing Aerosols in Northern Pakistan: Concentration on Snow/Ice, their Source Regions and Impacts on Snow Albedo

    Science.gov (United States)

    Gul, C.; Praveen, P. S.; Shichang, K.; Adhikary, B.; Zhang, Y.; Ali, S.

    2016-12-01

    Elemental carbon (EC) and light absorbing organic carbon (OC) are important particulate impurities in snow and ice which significantly reduce the albedo of glaciers and accelerate their melting. Snow and ice samples were collected from Karakorum-Himalayan region of North Pakistan during the summer campaign (May-Jun) 2015 and only snow samples were collected during winter (Dec 2015- Jan 2016). Total 41 surface snow/ice samples were collected during summer campaign along different elevation ranges (2569 to 3895 a.m.s.l) from six glaciers: Sachin, Henarche, Barpu, Mear, Gulkin and Passu. Similarly 18 snow samples were collected from Sust, Hoper, Tawas, Astore, Shangla, and Kalam regions during the winter campaign. Quartz filters were used for filtering of melted snow and ice samples which were then analyzed by thermal optical reflectance (TOR) method to determine the concentration of EC and OC. The average concentration of EC (ng/g), OC (ng/g) and dust (ppm) were found as follows: Passu (249.5, 536.8, 475), Barpu (1190, 397.6, 1288), Gulkin (412, 793, 761), Sachin (911, 2130, 358), Mear (678, 2067, 83) and Henarche (755, 1868, 241) respectively during summer campaign. Similarly, average concentration of EC (ng/g), OC (ng/g) and dust (ppm) was found in the samples of Sust (2506, 1039, 131), Hoper (646, 1153, 76), Tawas (650, 1320, 16), Astore (1305, 2161, 97), Shangla (739, 2079, 31) and Kalam (107, 347, 5) respectively during winter campaign. Two methods were adopted to identify the source regions: one coupled emissions inventory with back trajectories, second with a simple region tagged chemical transport modeling analysis. In addition, CALIPSO subtype aerosol composition indicated that frequency of smoke in the atmosphere over the region was highest followed by dust and then polluted dust. SNICAR model was used to estimate the snow albedo reduction from our in-situ measurements. Snow albedo reduction was observed to be 0.3% to 27.6%. The derived results were used

  20. Unexpected Patterns in Snow and Dirt

    Science.gov (United States)

    Ackerson, Bruce J.

    2018-01-01

    For more than 30 years, Albert A. Bartlett published "Thermal patterns in the snow" in this journal. These are patterns produced by heat sources underneath the snow. Bartlett's articles encouraged me to pay attention to patterns in snow and to understanding them. At winter's end the last snow becomes dirty and is heaped into piles. This snow comes from the final clearing of sidewalks and driveways. The patterns observed in these piles defied my intuition. This melting snow develops edges where dirt accumulates, in contrast to ice cubes, which lose sharp edges and become more spherical upon melting. Furthermore, dirt absorbs more radiation than snow and yet doesn't melt and round the sharp edges of snow, where dirt accumulates.

  1. Are we biologically safe with snow precipitation? A case study in beijing.

    Directory of Open Access Journals (Sweden)

    Fangxia Shen

    Full Text Available In this study, the bacterial and fungal abundances, diversities, conductance levels as well as total organic carbon (TOC were investigated in the snow samples collected from five different snow occurrences in Beijing between January and March, 2010. The collected snow samples were melted and cultured at three different temperatures (4, 26 and 37°C. The culturable bacterial concentrations were manually counted and the resulting colony forming units (CFUs at 26°C were further studied using V3 region of 16 S rRNA gene-targeted polymerase chain reaction -denaturing gradient gel electrophoresis (PCR-DGGE. The clone library was constructed after the liquid culturing of snow samples at 26°C. And microscopic method was employed to investigate the fungal diversity in the samples. In addition, outdoor air samples were also collected using mixed cellulose ester (MCE filters and compared with snow samples with respect to described characteristics. The results revealed that snow samples had bacterial concentrations as much as 16000 CFU/ml for those cultured at 26°C, and the conductance levels ranged from 5.6×10(-6 to 2.4×10(-5 S. PCR-DGGE, sequencing and microscopic analysis revealed remarkable bacterial and fungal diversity differences between the snow samples and the outdoor air samples. In addition, DGGE banding profiles for the snow samples collected were also shown distinctly different from one another. Absent from the outdoor air, certain human, plant, and insect fungal pathogens were found in the snow samples. By calculation, culturable bacteria accounted for an average of 3.38% (±1.96% of TOC for the snow samples, and 0.01% for that of outdoor air samples. The results here suggest that snow precipitations are important sources of fungal pathogens and ice nucleators, thus could affect local climate, human health and agriculture security.

  2. Are We Biologically Safe with Snow Precipitation? A Case Study in Beijing

    Science.gov (United States)

    Shen, Fangxia; Yao, Maosheng

    2013-01-01

    In this study, the bacterial and fungal abundances, diversities, conductance levels as well as total organic carbon (TOC) were investigated in the snow samples collected from five different snow occurrences in Beijing between January and March, 2010. The collected snow samples were melted and cultured at three different temperatures (4, 26 and 37°C). The culturable bacterial concentrations were manually counted and the resulting colony forming units (CFUs) at 26°C were further studied using V3 region of 16 S rRNA gene-targeted polymerase chain reaction -denaturing gradient gel electrophoresis (PCR-DGGE). The clone library was constructed after the liquid culturing of snow samples at 26°C. And microscopic method was employed to investigate the fungal diversity in the samples. In addition, outdoor air samples were also collected using mixed cellulose ester (MCE) filters and compared with snow samples with respect to described characteristics. The results revealed that snow samples had bacterial concentrations as much as 16000 CFU/ml for those cultured at 26°C, and the conductance levels ranged from 5.6×10−6 to 2.4×10−5 S. PCR-DGGE, sequencing and microscopic analysis revealed remarkable bacterial and fungal diversity differences between the snow samples and the outdoor air samples. In addition, DGGE banding profiles for the snow samples collected were also shown distinctly different from one another. Absent from the outdoor air, certain human, plant, and insect fungal pathogens were found in the snow samples. By calculation, culturable bacteria accounted for an average of 3.38% (±1.96%) of TOC for the snow samples, and 0.01% for that of outdoor air samples. The results here suggest that snow precipitations are important sources of fungal pathogens and ice nucleators, thus could affect local climate, human health and agriculture security. PMID:23762327

  3. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 3 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Land Surface Temperature Databank contains monthly timescale mean, maximum, and minimum temperature for approximately 40,000 stations globally. It was...

  4. Complex responses of spring alpine vegetation phenology to snow cover dynamics over the Tibetan Plateau, China.

    Science.gov (United States)

    Wang, Siyuan; Wang, Xiaoyue; Chen, Guangsheng; Yang, Qichun; Wang, Bin; Ma, Yuanxu; Shen, Ming

    2017-09-01

    Snow cover dynamics are considered to play a key role on spring phenological shifts in the high-latitude, so investigating responses of spring phenology to snow cover dynamics is becoming an increasingly important way to identify and predict global ecosystem dynamics. In this study, we quantified the temporal trends and spatial variations of spring phenology and snow cover across the Tibetan Plateau by calibrating and analyzing time series of the NOAA AVHRR-derived normalized difference vegetation index (NDVI) during 1983-2012. We also examined how snow cover dynamics affect the spatio-temporal pattern of spring alpine vegetation phenology over the plateau. Our results indicated that 52.21% of the plateau experienced a significant advancing trend in the beginning of vegetation growing season (BGS) and 34.30% exhibited a delaying trend. Accordingly, the snow cover duration days (SCD) and snow cover melt date (SCM) showed similar patterns with a decreasing trend in the west and an increasing trend in the southeast, but the start date of snow cover (SCS) showed an opposite pattern. Meanwhile, the spatial patterns of the BGS, SCD, SCS and SCM varied in accordance with the gradients of temperature, precipitation and topography across the plateau. The response relationship of spring phenology to snow cover dynamics varied within different climate, terrain and alpine plant community zones, and the spatio-temporal response patterns were primarily controlled by the long-term local heat-water conditions and topographic conditions. Moreover, temperature and precipitation played a profound impact on diverse responses of spring phenology to snow cover dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. The impact of the snow cover on sea-ice thickness products retrieved by Ku-band radar altimeters

    Science.gov (United States)

    Ricker, R.; Hendricks, S.; Helm, V.; Perovich, D. K.

    2015-12-01

    Snow on sea ice is a relevant polar climate parameter related to ocean-atmospheric interactions and surface albedo. It also remains an important factor for sea-ice thickness products retrieved from Ku-band satellite radar altimeters like Envisat or CryoSat-2, which is currently on its mission and the subject of many recent studies. Such satellites sense the height of the sea-ice surface above the sea level, which is called sea-ice freeboard. By assuming hydrostatic equilibrium and that the main scattering horizon is given by the snow-ice interface, the freeboard can be transformed into sea-ice thickness. Therefore, information about the snow load on hemispherical scale is crucial. Due to the lack of sufficient satellite products, only climatological values are used in current studies. Since such values do not represent the high variability of snow distribution in the Arctic, they can be a substantial contributor to the total sea-ice thickness uncertainty budget. Secondly, recent studies suggest that the snow layer cannot be considered as homogenous, but possibly rather featuring a complex stratigraphy due to wind compaction and/or ice lenses. Therefore, the Ku-band radar signal can be scattered at internal layers, causing a shift of the main scattering horizon towards the snow surface. This alters the freeboard and thickness retrieval as the assumption that the main scattering horizon is given by the snow-ice interface is no longer valid and introduces a bias. Here, we present estimates for the impact of snow depth uncertainties and snow properties on CryoSat-2 sea-ice thickness retrievals. We therefore compare CryoSat-2 freeboard measurements with field data from ice mass-balance buoys and aircraft campaigns from the CryoSat Validation Experiment. This unique validation dataset includes airborne laser scanner and radar altimeter measurements in spring coincident to CryoSat-2 overflights, and allows us to evaluate how the main scattering horizon is altered by the

  6. Some attributes of snow occurrence and snowmelt/sublimation rates ...

    African Journals Online (AJOL)

    Some attributes of snow occurrence and snowmelt/sublimation rates in the Lesotho ... and trimmed MODIS SNOMAP image using the ArcGIS Spatial Analyst tool. ... and hydrology, earth surface processes, and rural livelihoods in the Lesotho ...

  7. Winter Insulation By Snow Accumulation in a Subarctic Treeline Ecosystem Increases Summer Carbon Cycling Rates

    Science.gov (United States)

    Parker, T.; Subke, J. A.; Wookey, P. A.

    2014-12-01

    The effect of snow accumulation on soil carbon and nutrient cycling is attracting substantial attention from researchers. We know that deeper snow accumulation caused by high stature vegetation increases winter microbial activity and therefore carbon and nitrogen flux rates. However, until now the effect of snow accumulation, by buffering winter soil temperature, on subsequent summer soil processes, has scarcely been considered. We carried out an experiment at an alpine treeline in subarctic Sweden in which soil monoliths, contained within PVC collars, were transplanted between forest (deep winter snow) and tundra heath (shallow winter snow). We measured soil CO2efflux over two growing seasons and quantified soil microbial biomass after the second winter. We showed that respiration rates of transplanted forest soil were significantly reduced compared with control collars (remaining in the forest) as a consequence of colder, but more variable, winter temperatures. We hypothesised that microbial biomass would be reduced in transplanted forests soils but found there was no difference compared to control. We therefore further hypothesised that the similarly sized microbial pool in the control is assembled differently to the transplant. We believe that the warmer winters in forests foster more active consortia of decomposer microbes as a result of different abiotic selection pressures. Using an ecosystem scale experimental approach, we have identified a mechanism that influences summer carbon cycling rates based solely on the amount of snow that accumulates the previous winter. We conclude that modification of snow depth as a consequence of changes in vegetation structure is an important mechanism influencing soil C stocks in ecosystems where snow persists for a major fraction of the year.

  8. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  9. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  10. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  11. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  12. Nitrate photolysis in salty snow

    Science.gov (United States)

    Donaldson, D. J.; Morenz, K.; Shi, Q.; Murphy, J. G.

    2016-12-01

    Nitrate photolysis from snow can have a significant impact on the oxidative capacity of the local atmosphere, but the factors affecting the release of gas phase products are not well understood. Here, we report the first systematic study of the amounts of NO, NO2, and total nitrogen oxides (NOy) emitted from illuminated snow samples as a function of both nitrate and total salt (NaCl and Instant Ocean) concentration. We show that the release of nitrogen oxides to the gas phase is directly related to the expected nitrate concentration in the brine at the surface of the snow crystals, increasing to a plateau value with increasing nitrate, and generally decreasing with increasing NaCl or Instant Ocean (I.O.). In frozen mixed nitrate (25 mM) - salt (0-500 mM) solutions, there is an increase in gas phase NO2 seen at low added salt amounts: NO2 production is enhanced by 35% at low prefreezing [NaCl] and by 70% at similar prefreezing [I.O.]. Raman microscopy of frozen nitrate-salt solutions shows evidence of stronger nitrate exclusion to the air interface in the presence of I.O. than with added NaCl. The enhancement in nitrogen oxides emission in the presence of salts may prove to be important to the atmospheric oxidative capacity in polar regions.

  13. Relocation of major ions in snow along the tundra-taiga ecotone

    Energy Technology Data Exchange (ETDEWEB)

    Pomeroy, J.W.; Marsh, P. (Environment Canada, Saskatoon (Canada)); Lesack, L. (Simon Fraser Univeristy, Burnaby, (Canada))

    1993-01-01

    The chemistry of seasonal snowcovers north of Unuvik, Northwest Territories, Canada was stratified by biophysical landscape. In this region, deposition of ions in winter occurs largely through the redistribution of wind-blown snow with accumulations in forest-edges and valley sides 8 to 12 times that of the open tundra. While dominated by this snow redistribution, the loading of most ions, except for SO[sub 4][sup 2-], does not scale exactly with that of snow, there being several mechanisms by which ion concentrations become relatively enriched or depleted in various landscape units. Vaporisation during temperature-gradient metamorphism in shallow-snow and uptake during either photochemical reactions or gaseous scavenging to well-exposed snow transformed concentrations of NO[sub 3][sup -] by 50%. Dry deposition of aerosols to forested terrain and valley bottoms enriched Cl[sup -], Na[sup +], Mg[sup 2]-[sup +], K[sup +] and Ca[sup 2+] concentrations up to more than two-fold, however scavenging of aerosols to blowing snow particles contributed an additional 40% to the sea-salt enrichment and 20% to the Ca[sup 2+] enrichment in wind-blown treeline forests. It is concluded that central measurements of snow chemistry in the Arctic cannot be reliably extrapolated without reference to changes caused by over-winter physical and chemical metamorphic processes. Associating the physical/chemical changes with readily identifiable Arctic landscape units suggests a simple and robust method for spatial extrapolation. (au) (26 refs.)

  14. Determination of total arsenic and arsenic species in drinking water, surface water, wastewater, and snow from Wielkopolska, Kujawy-Pomerania, and Lower Silesia provinces, Poland.

    Science.gov (United States)

    Komorowicz, Izabela; Barałkiewicz, Danuta

    2016-09-01

    Arsenic is a ubiquitous element which may be found in surface water, groundwater, and drinking water. In higher concentrations, this element is considered genotoxic and carcinogenic; thus, its level must be strictly controlled. We investigated the concentration of total arsenic and arsenic species: As(III), As(V), MMA, DMA, and AsB in drinking water, surface water, wastewater, and snow collected from the provinces of Wielkopolska, Kujawy-Pomerania, and Lower Silesia (Poland). The total arsenic was analyzed by inductively coupled plasma mass spectrometry (ICP-MS), and arsenic species were analyzed with use of high-performance liquid chromatography inductively coupled plasma mass spectrometry (HPLC/ICP-MS). Obtained results revealed that maximum total arsenic concentration determined in drinking water samples was equal to 1.01 μg L(-1). The highest concentration of total arsenic in surface water, equal to 3778 μg L(-1) was determined in Trująca Stream situated in the area affected by geogenic arsenic contamination. Total arsenic concentration in wastewater samples was comparable to those determined in drinking water samples. However, significantly higher arsenic concentration, equal to 83.1 ± 5.9 μg L(-1), was found in a snow sample collected in Legnica. As(V) was present in all of the investigated samples, and in most of them, it was the sole species observed. However, in snow sample collected in Legnica, more than 97 % of the determined concentration, amounting to 81 ± 11 μg L(-1), was in the form of As(III), the most toxic arsenic species.

  15. The value of snow cover

    Science.gov (United States)

    Sokratov, S. A.

    2009-04-01

    Snow is the natural resource, like soil and water. It has specific properties which allow its use not just for skiing but also for houses cooling in summer (Swedish experience), for air fields construction (Arctic and Antarctic), for dams (north of Russia), for buildings (not only snow-houses of some Polar peoples but artistic hotel attracting tourists in Sweden), and as art material (Sapporo snow festival, Finnish events), etc. "Adjustment" of snow distribution and amount is not only rather common practice (avalanche-protection constructions keeping snow on slopes) but also the practice with long history. So-called "snow irrigation" was used in Russia since XIX century to protect winter crop. What is now named "artificial snow production", is part of much larger pattern. What makes it special—it is unavoidable in present climate and economy situation. 5% of national income in Austria is winter tourism. 50% of the economy in Savoy relay on winter tourism. In terms of money this can be less, but in terms of jobs and income involved this would be even more considerable in Switzerland. As an example—the population of Davos is 14000 in Summer and 50000 in Winter. Skiing is growing business. In present time you can find ski slopes in Turkey and Lebanon. To keep a cite suitable for attracting tourists you need certain amount of sunny days and certain amount of snow. The snow cannons are often the only way to keep a place running. On the other hand, more artificial snow does not necessary attract more tourists, while heavy natural snowfall does attract them. Artificial snow making is costly and requires infrastructure (ponds and electric lines) with very narrow range of weather conditions. Related companies are searching for alternatives and one of them can be "weather regulation" by distribution of some chemical components in clouds. It did not happen yet, but can happen soon. The consequences of such interference in Nature is hardly known. The ski tourism is not the

  16. Modelling of snow exceedances

    Science.gov (United States)

    Jordanova, Pavlina K.; Sadovský, Zoltán; Stehlík, Milan

    2017-07-01

    Modelling of snow exceedances is of great importance and interest for ecology, civil engineering and general public. We suggest the favorable fit for exceedances related to the exceptional snow loads from Slovakia, assuming that the data is driven by Generalised Pareto Distribution or Generalized Extreme Value Distribution. Further, the statistical dependence between the maximal snow loads and the corresponding altitudes is studied.

  17. Data Fusion of Gridded Snow Products Enhanced with Terrain Covariates and a Simple Snow Model

    Science.gov (United States)

    Snauffer, A. M.; Hsieh, W. W.; Cannon, A. J.

    2017-12-01

    Hydrologic planning requires accurate estimates of regional snow water equivalent (SWE), particularly areas with hydrologic regimes dominated by spring melt. While numerous gridded data products provide such estimates, accurate representations are particularly challenging under conditions of mountainous terrain, heavy forest cover and large snow accumulations, contexts which in many ways define the province of British Columbia (BC), Canada. One promising avenue of improving SWE estimates is a data fusion approach which combines field observations with gridded SWE products and relevant covariates. A base artificial neural network (ANN) was constructed using three of the best performing gridded SWE products over BC (ERA-Interim/Land, MERRA and GLDAS-2) and simple location and time covariates. This base ANN was then enhanced to include terrain covariates (slope, aspect and Terrain Roughness Index, TRI) as well as a simple 1-layer energy balance snow model driven by gridded bias-corrected ANUSPLIN temperature and precipitation values. The ANN enhanced with all aforementioned covariates performed better than the base ANN, but most of the skill improvement was attributable to the snow model with very little contribution from the terrain covariates. The enhanced ANN improved station mean absolute error (MAE) by an average of 53% relative to the composing gridded products over the province. Interannual peak SWE correlation coefficient was found to be 0.78, an improvement of 0.05 to 0.18 over the composing products. This nonlinear approach outperformed a comparable multiple linear regression (MLR) model by 22% in MAE and 0.04 in interannual correlation. The enhanced ANN has also been shown to estimate better than the Variable Infiltration Capacity (VIC) hydrologic model calibrated and run for four BC watersheds, improving MAE by 22% and correlation by 0.05. The performance improvements of the enhanced ANN are statistically significant at the 5% level across the province and

  18. Snow in a very steep rock face: accumulation and redistribution during and after a snowfall event

    Directory of Open Access Journals (Sweden)

    Christian Gabriel Sommer

    2015-12-01

    Full Text Available Terrestrial laser scanning was used to measure snow thickness changes (perpendicular to the surface in a rock face. The aim was to investigate the accumulation and redistribution of snow in extremely steep terrain (>60°. The north-east face of the Chlein Schiahorn in the region of Davos in eastern Switzerland was scanned before and several times after a snowfall event. A summer scan without snow was acquired to calculate the total snow thickness. An improved postprocessing procedure is introduced. The data quality could be increased by using snow thickness instead of snow depth (measured vertically and by consistently applying Multi Station Adjustment to improve the registration.More snow was deposited in the flatter, smoother areas of the rock face. The spatial variability of the snow thickness change was high. The spatial patterns of the total snow thickness were similar to those of the snow thickness change. The correlation coefficient between them was 0.86. The fresh snow was partly redistributed from extremely steep to flatter terrain, presumably mostly through avalanching. The redistribution started during the snowfall and ended several days later. Snow was able to accumulate permanently at every slope angle. The amount of snow in extremely steep terrain was limited but not negligible. Areas steeper than 60° received 15% of the snowfall and contained 10% of the total amount of snow.

  19. AFSC/RACE/GAP/Nichol: Archival tag depth and temperature data from snow crab

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Seasonal migration of commercial-size (=102 mm carapace width [CW]), morphometrically mature (MM) snow crabs (Chionoecetes opilio) from the eastern Bering Sea was...

  20. Extreme Maximum Land Surface Temperatures.

    Science.gov (United States)

    Garratt, J. R.

    1992-09-01

    There are numerous reports in the literature of observations of land surface temperatures. Some of these, almost all made in situ, reveal maximum values in the 50°-70°C range, with a few, made in desert regions, near 80°C. Consideration of a simplified form of the surface energy balance equation, utilizing likely upper values of absorbed shortwave flux (1000 W m2) and screen air temperature (55°C), that surface temperatures in the vicinity of 90°-100°C may occur for dry, darkish soils of low thermal conductivity (0.1-0.2 W m1 K1). Numerical simulations confirm this and suggest that temperature gradients in the first few centimeters of soil may reach 0.5°-1°C mm1 under these extreme conditions. The study bears upon the intrinsic interest of identifying extreme maximum temperatures and yields interesting information regarding the comfort zone of animals (including man).

  1. A simple algorithm for identifying periods of snow accumulation on a radiometer

    Science.gov (United States)

    Lapo, Karl E.; Hinkelman, Laura M.; Landry, Christopher C.; Massmann, Adam K.; Lundquist, Jessica D.

    2015-09-01

    Downwelling solar, Qsi, and longwave, Qli, irradiances at the earth's surface are the primary energy inputs for many hydrologic processes, and uncertainties in measurements of these two terms confound evaluations of estimated irradiances and negatively impact hydrologic modeling. Observations of Qsi and Qli in cold environments are subject to conditions that create additional uncertainties not encountered in other climates, specifically the accumulation of snow on uplooking radiometers. To address this issue, we present an automated method for estimating these periods of snow accumulation. Our method is based on forest interception of snow and uses common meteorological observations. In this algorithm, snow accumulation must exceed a threshold to obscure the sensor and is only removed through scouring by wind or melting. The algorithm is evaluated at two sites representing different mountain climates: (1) Snoqualmie Pass, Washington (maritime) and (2) the Senator Beck Basin Study Area, Colorado (continental). The algorithm agrees well with time-lapse camera observations at the Washington site and with multiple measurements at the Colorado site, with 70-80% of observed snow accumulation events correctly identified. We suggest using the method for quality controlling irradiance observations in snow-dominated climates where regular, daily maintenance is not possible.

  2. Hydrologic Remote Sensing and Land Surface Data Assimilation.

    Science.gov (United States)

    Moradkhani, Hamid

    2008-05-06

    Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

  3. Concept of electric power output control system for atomic power generation plant utilizing cool energy of stored snow

    International Nuclear Information System (INIS)

    Kamimura, Seiji; Toita, Takayuki

    2003-01-01

    A concept of the SEAGUL system (Snow Enhancing Atomic-power Generation UtiLity) is proposed in this paper. Lowering the temperature of sea water for cooling of atomic-power plant will make a efficiency of power generation better and bring several ten MW additional electric power for 1356 MW class plant. The system concept stands an idea to use huge amount of seasonal storage snow for cooling water temperature control. In a case study for the Kashiwazaki-Kariwa Nuclear Power Station, it is estimated to cool down the sea water of 29degC to 20degC by 80 kt snow for 3 hours in a day would brought 60 MWh electric power per a day. Annually 38.4 Mt of stored snow will bring 1800 MWh electric power. (author)

  4. Changing Snow Cover and Stream Discharge in the Western United States - Wind River Range, Wyoming

    Science.gov (United States)

    Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Barton, Jonathan S.; Riggs, George A.

    2011-01-01

    Earlier onset of springtime weather has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack has important implications for the management of water resources. We studied ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover products, 40 years of stream discharge and meteorological station data and 30 years of snow-water equivalent (SWE) SNOw Telemetry (SNOTEL) data in the Wind River Range (WRR), Wyoming. Results show increasing air temperatures for.the 40-year study period. Discharge from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades. Changes in streamflow may be related to increasing air temperatures which are probably contributing to a reduction in snow cover, although no trend of either increasingly lower streamflow or earlier snowmelt was observed within the decade of the 2000s. And SWE on 1 April does not show an expected downward trend from 1980 to 2009. The extent of snow cover derived from the lowest-elevation zone of the WRR study area is strongly correlated (r=0.91) with stream discharge on 1 May during the decade of the 2000s. The strong relationship between snow cover and streamflow indicates that MODIS snow-cover maps can be used to improve management of water resources in the drought-prone western U.S.

  5. Performances of the snow accumulation melting model SAMM: results in the Northern Apennines test area

    Science.gov (United States)

    Lagomarsino, Daniela; Martelloni, Gianluca; Segoni, Samuele; Catani, Filippo; Fanti, Riccardo

    2013-04-01

    In this work we propose a snow accumulation-melting model (SAMM) to forecast the snowpack height and we compare the results with a simple temperature index model and an improved version of the latter.For this purpose we used rainfall, temperature and snowpack thickness 5-years data series from 7 weather stations in the Northern Apennines (Emilia Romagna Region, Italy). SAMM is based on two modules modelling the snow accumulation and the snowmelt processes. Each module is composed by two equations: a mass conservation equation is solved to model snowpack thickness and an empirical equation is used for the snow density. The processes linked to the accumulation/depletion of the snowpack (e.g. compression of the snowpack due to newly fallen snow and effects of rainfall) are modelled identifying limiting and inhibitory factors according to a kinetic approach. The model depends on 13 empirical parameters, whose optimal values were defined with an optimization algorithm (simplex flexible) using calibration measures of snowpack thickness. From an operational point of view, SAMM uses as input data only temperature and rainfall measurements, bringing the additional advantage of a relatively easy implementation. In order to verify the improvement of SAMM with respect to a temperature-index model, the latter was applied considering, for the amount of snow melt, the following equation: M = fm(T-T0), where M is hourly melt, fm is the melting factor and T0 is a threshold temperature. In this case the calculation of the depth of the snowpack requires the use of 3 parameters: fm, T0 and ?0 (the mean density of the snowpack). We also performed a simulation by replacing the SAMM melting module with the above equation and leaving unchanged the accumulation module: in this way we obtained a model with 9 parameters. The simulations results suggest that any further extension of the simple temperature index model brings some improvements with a consequent decrease of the mean error

  6. Extended Reconstructed Sea Surface Temperature (ERSST)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature analysis derived from the International Comprehensive...

  7. Fukushima Nuclear Accident Recorded in Tibetan Plateau Snow Pits

    Science.gov (United States)

    Wang, Ninglian; Wu, Xiaobo; Kehrwald, Natalie; Li, Zhen; Li, Quanlian; Jiang, Xi; Pu, Jianchen

    2015-01-01

    The β radioactivity of snow-pit samples collected in the spring of 2011 on four Tibetan Plateau glaciers demonstrate a remarkable peak in each snow pit profile, with peaks about ten to tens of times higher than background levels. The timing of these peaks suggests that the high radioactivity resulted from the Fukushima nuclear accident that occurred on March 11, 2011 in eastern Japan. Fallout monitoring studies demonstrate that this radioactive material was transported by the westerlies across the middle latitudes of the Northern Hemisphere. The depth of the peak β radioactivity in each snow pit compared with observational precipitation records, suggests that the radioactive fallout reached the Tibetan Plateau and was deposited on glacier surfaces in late March 2011, or approximately 20 days after the nuclear accident. The radioactive fallout existed in the atmosphere over the Tibetan Plateau for about one month. PMID:25658094

  8. Interannual variability of dust-mass loading and composition of dust deposited on snow cover in the San Juan Mountains, CO, USA: Insights into effects on snow melt

    Science.gov (United States)

    Goldstein, H. L.; Reynolds, R. L.; Derry, J.; Kokaly, R. F.; Moskowitz, B. M.

    2017-12-01

    Dust deposited on snow cover (DOS) in the American West can enhance snow-melt rates and advance the timing of melting, which together can result in earlier-than-normal runoff and overall smaller late-season water supplies. Understanding DOS properties and how they affect the absorption of solar radiation can lead to improved snow-melt models by accounting for important dust components. Here, we report on the interannual variability of DOS-mass loading, particle size, organic matter, and iron mineralogy, and their correspondences to laboratory-measured reflectance of samples from the Swamp Angel Study Plot in the San Juan Mountains, Colorado, USA. Samples were collected near the end of spring in water year 2009 (WY09) and from WY11-WY16, when dust layers deposited throughout the year had merged into one layer at the snow surface. Dust-mass loading on snow ranged 2-64 g/m2, mostly as particles with median sizes of 13-33 micrometers. Average reflectance values of DOS varied little across total (0.4 to 2.50 µm) and visible (0.4 to 0.7 µm) wavelengths at 0.30-0.45 and 0.19-0.27, respectively. Reflectance values lacked correspondence to particle-size. Total reflectance values inversely corresponded to concentrations of (1) organic matter content (4-20 weight %; r2 = 0.71) that included forms of black carbon and locally derived material such as pollen, and (2) magnetite (0.05 to 0.13 weight %; r2 = 0.44). Magnetite may be a surrogate for related dark, light-absorbing minerals. Concentrations of crystalline ferric oxide minerals (hematite+goethite) based on magnetic properties at room-temperature did not show inverse association to visible reflectance values. These ferric oxide measures, however, did not account for the amounts of nano-sized ferric oxides known to exist in these samples. Quantification of such nano-sized particles is required to evaluate their possible effects on visible reflectance. Nonetheless, our results emphasize that reflectance values of year

  9. Antarctic surface temperature and sea ice biases in coupled climate models linked with cloud and land surface properties

    Science.gov (United States)

    Skiles, M.; Painter, T. H.; Marks, D. G.; Hedrick, A. R.

    2014-12-01

    Since 2013 the Airborne Snow Observatory (ASO) has been measuring spatial and temporal distribution of both snow water equivalent and snow albedo, the two most critical properties for understanding snowmelt runoff and timing, across key basins in the Western US. It is generally understood that net solar radiation (as controlled by variations in snow albedo and irradiance) provides the energy available for melt in almost all snow-covered environments. Until now, sparse measurements have restricted the ability to utilize measured net solar radiation in energy balance models, and current process simulations and model prediction of albedo evolution rely on oversimplifications of the processes. Data from ASO offers the unprecedented opportunity to utilize weekly measurements of spatially extensive spectral snow albedo to constrain and update snow albedo in a distributed snowmelt model for the first time. Here, we first investigate the sensitivity of the snow energy balance model SNOBAL to prescribed changes in snow albedo at two instrumented alpine catchments: at the point scale across 10 years at Senator Beck Basin Study Area in the San Juan Mountains, southwestern Colorado, and at the distributed scale across 25 years at Reynolds Creek Experimental Watershed, Idaho. We then compare distributed energy balance and snowmelt results across the ASO measurement record in the Tuolumne Basin in the Sierra Nevada Mountains, California, for model runs with and without integrated snow albedo from ASO.

  10. Retrieving the characteristics of slab ice covering snow by remote sensing

    Directory of Open Access Journals (Sweden)

    F. Andrieu

    2016-09-01

    Full Text Available We present an effort to validate a previously developed radiative transfer model, and an innovative Bayesian inversion method designed to retrieve the properties of slab-ice-covered surfaces. This retrieval method is adapted to satellite data, and is able to provide uncertainties on the results of the inversions. We focused on surfaces composed of a pure slab of water ice covering an optically thick layer of snow in this study. We sought to retrieve the roughness of the ice–air interface, the thickness of the slab layer and the mean grain diameter of the underlying snow. Numerical validations have been conducted on the method, and showed that if the thickness of the slab layer is above 5 mm and the noise on the signal is above 3 %, then it is not possible to invert the grain diameter of the snow. In contrast, the roughness and the thickness of the slab can be determined, even with high levels of noise up to 20 %. Experimental validations have been conducted on spectra collected from laboratory samples of water ice on snow using a spectro-radiogoniometer. The results are in agreement with the numerical validations, and show that a grain diameter can be correctly retrieved for low slab thicknesses, but not for bigger ones, and that the roughness and thickness are correctly inverted in every case.

  11. Impacts of changing climate and snow cover on the flow regime of Jhelum River, Western Himalayas

    KAUST Repository

    Azmat, Muhammad

    2016-11-17

    This study examines the change in climate variables and snow cover dynamics and their impact on the hydrological regime of the Jhelum River basin in Western Himalayas. This study utilized daily streamflow records from Mangla dam, spanning a time period of 19 years (1995–2013), along with precipitation and temperature data over 52 years (1961–2013) from 12 different climate stations in the catchment. Additionally, moderate-resolution imaging spectroradiometer (MODIS) remote sensing product MOD10A2 was utilized to analyze the change in snow cover dynamics during 2000–2013. The Pearson and Kendall rank correlation tests were used to scrutinize snow cover trends and correlation between temperature, precipitation, snow cover area (SCA) and streamflows records. Basin-wide trend analysis showed a slightly increasing tendency in temperature (τ = 0.098) and precipitation (τ = 0.094), during the years 1961–2013. The changes in streamflow indicated a positive (r > 0.12) relationship with respect to temperature but variable trends (r = −0.45–0.41) with respect to precipitation during both the winter and monsoon seasons. This indicates that temperature has a significant impact on the hydrological regime of the basin. MODIS data-based investigations suggested an expansion in SCA during 2000–2013. The changes in SCA of high-altitude zones (>2000 m a.s.l.) depicted a stronger positive correlation with climate variables and streamflow compared with those obtained for low-altitude regions (<2000 m a.s.l.). Overall, these results signify that high-altitude areas contribute to the streamflow largely in the form of snow- and glacier-melt during the early summer season. The streamflow is then further augmented by monsoon rainfall in the low-elevation regions during late summer.

  12. Factors Impacting Spatial Patterns of Snow Distribution in a Small Catchment near Nome, AK

    Science.gov (United States)

    Chen, M.; Wilson, C. J.; Charsley-Groffman, L.; Busey, R.; Bolton, W. R.

    2017-12-01

    Snow cover plays an important role in the climate, hydrology and ecological systems of the Arctic due to its influence on the water balance, thermal regimes, vegetation and carbon flux. Thus, snow depth and coverage have been key components in all the earth system models but are often poorly represented for arctic regions, where fine scale snow distribution data is sparse. The snow data currently used in the models is at coarse resolution, which in turn leads to high uncertainty in model predictions. Through the DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic, high resolution snow distribution data is being developed and applied in catchment scale models to ultimately improve representation of snow and its interactions with other model components in the earth system models . To improve these models, it is important to identify key factors that control snow distribution and quantify the impacts of those factors on snow distribution. In this study, two intensive snow depth surveys (1 to 10 meters scale) were conducted for a 2.3 km2 catchment on the Teller road, near Nome, AK in the winter of 2016 and 2017. We used a statistical model to quantify the impacts of vegetation types, macro-topography, micro-topography, and meteorological parameters on measured snow depth. The results show that snow spatial distribution was similar between 2016 and 2017, snow depth was spatially auto correlated over small distance (2-5 meters), but not spatially auto correlated over larger distance (more than 2-5 meters). The coefficients of variation of snow depth was above 0.3 for all the snow survey transects (500-800 meters long). Variation of snow depth is governed by vegetation height, aspect, slope, surface curvature, elevation and wind speed and direction. We expect that this empirical statistical model can be used to estimate end of winter snow depth for the whole watershed and will further develop the model using data from other arctic regions to estimate

  13. Snowmelt runoff in the Green River basin derived from MODIS snow extent

    Science.gov (United States)

    Barton, J. S.; Hall, D. K.

    2011-12-01

    The Green River represents a vital water supply for southwestern Wyoming, northern Colorado, eastern Utah, and the Lower Colorado River Compact states (Arizona, Nevada, and California). Rapid development in the southwestern United States combined with the recent drought has greatly stressed the water supply of the Colorado River system, and concurrently increased the interest in long-term variations in stream flow. Modeling of snowmelt runoff represents a means to predict flows and reservoir storage, which is useful for water resource planning. An investigation is made into the accuracy of the Snowmelt Runoff Model of Martinec and Rango, driven by Moderate Resolution Imaging Spectroradiometer (MODIS) snow maps for predicting stream flow within the Green River basin. While the moderate resolution of the MODIS snow maps limits the spatial detail that can be captured, the daily coverage is an important advantage of the MODIS imagery. The daily MODIS snow extent is measured using the most recent clear observation for each 500-meter pixel. Auxiliary data used include temperature and precipitation time series from the Snow Telemetry (SNOTEL) and Remote Automated Weather Station (RAWS) networks as well as from National Weather Service records. Also from the SNOTEL network, snow-water equivalence data are obtained to calibrate the conversion between snow extent and runoff potential.

  14. Correlated declines in Pacific arctic snow and sea ice cover

    Science.gov (United States)

    Stone, Robert P.; Douglas, David C.; Belchansky, Gennady I.; Drobot, Sheldon

    2005-01-01

    Simulations of future climate suggest that global warming will reduce Arctic snow and ice cover, resulting in decreased surface albedo (reflectivity). Lowering of the surface albedo leads to further warming by increasing solar absorption at the surface. This phenomenon is referred to as “temperature–albedo feedback.” Anticipation of such a feedback is one reason why scientists look to the Arctic for early indications of global warming. Much of the Arctic has warmed significantly. Northern Hemisphere snow cover has decreased, and sea ice has diminished in area and thickness. As reported in the Arctic Climate Impact Assessment in 2004, the trends are considered to be outside the range of natural variability, implicating global warming as an underlying cause. Changing climatic conditions in the high northern latitudes have influenced biogeochemical cycles on a broad scale. Warming has already affected the sea ice, the tundra, the plants, the animals, and the indigenous populations that depend on them. Changing annual cycles of snow and sea ice also affect sources and sinks of important greenhouse gases (such as carbon dioxide and methane), further complicating feedbacks involving the global budgets of these important constituents. For instance, thawing permafrost increases the extent of tundra wetlands and lakes, releasing greater amounts of methane into the atmosphere. Variable sea ice cover may affect the hemispheric carbon budget by altering the ocean–atmosphere exchange of carbon dioxide. There is growing concern that amplification of global warming in the Arctic will have far-reaching effects on lower latitude climate through these feedback mechanisms. Despite the diverse and convincing observational evidence that the Arctic environment is changing, it remains unclear whether these changes are anthropogenically forced or result from natural variations of the climate system. A better understanding of what controls the seasonal distributions of snow and ice

  15. Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

    Science.gov (United States)

    Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

    2017-11-01

    Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

  16. Radiative forcing over the conterminous United States due to contemporary land cover land use change and sensitivity to snow and interannual albedo variability

    Science.gov (United States)

    Barnes, Christopher A.; Roy, David P.

    2010-01-01

    Satellite-derived land cover land use (LCLU), snow and albedo data, and incoming surface solar radiation reanalysis data were used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 58 ecoregions covering 69% of the conterminous United States. A net positive surface radiative forcing (i.e., warming) of 0.029 Wm−2 due to LCLU albedo change from 1973 to 2000 was estimated. The forcings for individual ecoregions were similar in magnitude to current global forcing estimates, with the most negative forcing (as low as −0.367 Wm−2) due to the transition to forest and the most positive forcing (up to 0.337 Wm−2) due to the conversion to grass/shrub. Snow exacerbated both negative and positive forcing for LCLU transitions between snow-hiding and snow-revealing LCLU classes. The surface radiative forcing estimates were highly sensitive to snow-free interannual albedo variability that had a percent average monthly variation from 1.6% to 4.3% across the ecoregions. The results described in this paper enhance our understanding of contemporary LCLU change on surface radiative forcing and suggest that future forcing estimates should model snow and interannual albedo variation.

  17. Warming, soil moisture, and loss of snow increase Bromus tectorum’s population growth rate

    Directory of Open Access Journals (Sweden)

    Aldo Compagnoni

    2014-01-01

    Full Text Available Abstract Climate change threatens to exacerbate the impacts of invasive species. In temperate ecosystems, direct effects of warming may be compounded by dramatic reductions in winter snow cover. Cheatgrass (Bromus tectorum is arguably the most destructive biological invader in basins of the North American Intermountain West, and warming could increase its performance through direct effects on demographic rates or through indirect effects mediated by loss of snow. We conducted a two-year experimental manipulation of temperature and snow pack to test whether 1 warming increases cheatgrass population growth rate and 2 reduced snow cover contributes to cheatgrass’ positive response to warming. We used infrared heaters operating continuously to create the warming treatment, but turned heaters on only during snowfalls for the snowmelt treatment. We monitored cheatgrass population growth rate and the vital rates that determine it: emergence, survival and fecundity. Growth rate increased in both warming and snowmelt treatments. The largest increases occurred in warming plots during the wettest year, indicating that the magnitude of response to warming depends on moisture availability. Warming increased both fecundity and survival, especially in the wet year, while snowmelt contributed to the positive effects of warming by increasing survival. Our results indicate that increasing temperature will exacerbate cheatgrass impacts, especially where warming causes large reductions in the depth and duration of snow cover.

  18. NOAA Global Surface Temperature (NOAAGlobalTemp)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a merged land–ocean surface temperature analysis (formerly known as MLOST) (link is external). It is...

  19. Role of snow and cold environment in the fate and effects of nanoparticles and select organic pollutants from gasoline engine exhaust.

    Science.gov (United States)

    Nazarenko, Yevgen; Kurien, Uday; Nepotchatykh, Oleg; Rangel-Alvarado, Rodrigo B; Ariya, Parisa A

    2016-02-01

    Exposure to vehicle exhaust can drive up to 70 % of excess lifetime cancer incidences due to air pollution in urban environments. Little is known about how exhaust-derived particles and organic pollutants, implicated in adverse health effects, are affected by freezing ambient temperatures and the presence of snow. Airborne particles and (semi)volatile organic constituents in dilute exhaust were studied in a novel low-temperature environmental chamber system containing natural urban snow under controlled cold environmental conditions. The presence of snow altered the aerosol size distributions of dilute exhaust in the 10 nm to 10 μm range and decreased the number density of the nanoparticulate (snow from 0.218 ± 0.014 to 0.539 ± 0.009 mg L(-1), and over 40 additional (semi)volatile organic compounds and a large number of exhaust-derived carbonaceous and likely organic particles were identified. The concentrations of benzene, toluene, ethylbenzene, and xylenes (BTEX) increased from near the detection limit to 52.48, 379.5, 242.7, and 238.1 μg kg(-1) (± 10 %), respectively, indicating the absorption of exhaust-derived toxic organic compounds by snow. The alteration of exhaust aerosol size distributions at freezing temperatures and in the presence of snow, accompanied by changes of the organic pollutant content in snow, has potential to alter health effects of human exposure to vehicle exhaust.

  20. Climate Prediction Center (CPC) U.S. Daily Snow Depth Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Observational reports of current snow depth (at 1200 UTC) are made by members of the NWS Automated Surface Observing Systems (ASOS) network and NWS Cooperative...