WorldWideScience

Sample records for ii land-surface simulations

  1. A coupled atmosphere and multi-layer land surface model for improving heavy rainfall simulation

    Directory of Open Access Journals (Sweden)

    M. Haggag

    2008-04-01

    Full Text Available A multi-layer land surface model (SOLVEG is dynamically coupled to the non-hydrostatic atmospheric model (MM5 in order to represent better spatial variations and changes in land surface characteristics compared with the land surface parameterization schemes included in the MM5. In this coupling, calculations of the atmosphere and land surface models are carried out as independent tasks of different processors; a model coupler controls these calculations and data exchanges among models using Message Passing Interface (MPI. This coupled model is applied to the record-breaking heavy rain events occurred in Kyushu Island, the southernmost of Japan's main islands, from 20 July to 25 July in 2006. The test computations are conducted by using both the developed coupled model and the original land surface parameterization of MM5. The result of these computations shows that SOLVEG reproduce higher ground temperature than land surface parameterization schemes in the MM5. This result indicates the feedback of land surface processes between MM5 and SOLVEG plays an important role in the computation. The most pronounced difference is in the rainfall simulation that shows the importance of coupling SOLVEG and MM5. The coupled model accurately reproduces the heavy rainfall events observed in Kyushu Island compared to the original MM5 from both the spatial and temporal point of view. This paper clearly shows that realistic simulation of rainfall event strongly depends on land-surface processes interacting with cloud development that depends on surface heat and moisture fluxes, which in turn are mainly determined by land surface vegetation and soil moisture storage. Soil temperature/moisture changes significantly affect the localized precipitation and modest improvement in the land surface representation can enhance the heavy rain simulation. MM5-SOLVEG coupling shows a clear image of land surface-atmosphere interactions and the dynamic feedback on

  2. Application of a land surface model for simulating river streamflow in high latitudes

    Science.gov (United States)

    Gusev, Yeugeniy; Nasonova, Olga; Dzhogan, Larissa

    2010-05-01

    Nowadays modelling runoff from the pan-Arctic river basins, which represents nearly 50% of water flow to the Arctic Ocean, is of great interest among hydrological modelling community because these regions are very sensitive to natural and anthropogenic impacts. This motivates the necessity of increase of the accuracy of hydrological estimations, runoff predictions, and water resources assessments in high latitudes. However, in these regions, observations required for model simulations (to specify model parameters and forcing inputs) are very scarce or even absent (especially this concerns land surface parameters). At the same time river discharge measurements are usually available that makes it possible to estimate model parameters by their calibration against measured discharge. Such a situation is typical of most of the northern basins of Russia. The major goal of the work is to reveal whether a physically-based land surface model (LSM) Soil Water - Atmosphere - Plants (SWAP) is able to reproduce snowmelt and rain driven daily streamflow in high latitudes (using poor input information) with the accuracy acceptable for hydrologic applications. Three river basins, located on the north of the European part of Russia, were chosen for investigation. They are the Mezen River basin (area: area: 78 000 km2), the Pechora River basin (area: 312 000 km2) and the Severnaya Dvina River basin (area: 348 000 km2). For modeling purposes the basins were presented, respectively, by 10, 57 and 62 one-degree computational grid boxes connected by river network. A priori estimation of the land surface parameters for each grid box was based on the global one-degree datasets prepared within the framework of the International Satellite Land-Surface Climatology Project Initiative II (ISLSCP) / the Second Global Soil Wetness Project (GSWP-2). Three versions of atmospheric forcing data prepared for the basins were based on: (1) NCEP/DOE reanalysis dataset; (2) NCEP/DOE reanalysis product

  3. Atmosphere-only GCM (ACCESS1.0) simulations with prescribed land surface temperatures

    Science.gov (United States)

    Ackerley, Duncan; Dommenget, Dietmar

    2016-06-01

    General circulation models (GCMs) are valuable tools for understanding how the global ocean-atmosphere-land surface system interacts and are routinely evaluated relative to observational data sets. Conversely, observational data sets can also be used to constrain GCMs in order to identify systematic errors in their simulated climates. One such example is to prescribe sea surface temperatures (SSTs) such that 70 % of the Earth's surface temperature field is observationally constrained (known as an Atmospheric Model Intercomparison Project, AMIP, simulation). Nevertheless, in such simulations, land surface temperatures are typically allowed to vary freely, and therefore any errors that develop over the land may affect the global circulation. In this study therefore, a method for prescribing the land surface temperatures within a GCM (the Australian Community Climate and Earth System Simulator, ACCESS) is presented. Simulations with this prescribed land surface temperature model produce a mean climate state that is comparable to a simulation with freely varying land temperatures; for example, the diurnal cycle of tropical convection is maintained. The model is then developed further to incorporate a selection of "proof of concept" sensitivity experiments where the land surface temperatures are changed globally and regionally. The resulting changes to the global circulation in these sensitivity experiments are found to be consistent with other idealized model experiments described in the wider scientific literature. Finally, a list of other potential applications is described at the end of the study to highlight the usefulness of such a model to the scientific community.

  4. Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

    Science.gov (United States)

    Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

    2016-07-01

    Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after

  5. Simulating Land Surface Hydrology at a 30-meter Spatial Resolution over the Contiguous United States

    Science.gov (United States)

    Wood, E. F.; Pan, M.; Cai, X.; Chaney, N.

    2016-12-01

    Big data, high performance computing, and recent advances in hydrologic similarity present a unique opportunity for macroscale hydrology: the land surface hydrology can be modeled at field scales over continental extents while ensuring computational efficiency to enable robust ensemble frameworks. In this presentation we will illustrate this potential breakthrough in macroscale hydrology by discussing results from a 30-meter simulation over the contiguous United States using the HydroBlocks land surface model. HydroBlocks is a novel land surface model that represents field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs) [Chaney et al., 2016]. The model is a coupling between the Noah-MP land surface model and the Dynamic TOPMODEL hydrologic model. The HRUs are defined by clustering proxies of the drivers of spatial heterogeneity using hyperresolution land data. For the simulations over CONUS, HydroBlocks is run at every HUC10 catchment using 100 HRUs per catchment between 2004 and 2014. The simulations are forced with the 4 km Stage IV radar rainfall product and a spatially downscaled version of NLDAS-2. We will show how this approach to macroscale hydrology ensures computational efficiency while providing field-scale hydrologic information over continental extents. We will illustrate how this approach provides a novel approach in both the application and validation of macroscale land surface and hydrologic models. Finally, using these results, we will discuss the important role that big data and high performance computing can play in providing solutions to longstanding challenges to not only flood and drought monitoring systems but also to numerical weather prediction, seasonal forecasting, and climate prediction. References Chaney, N., P. Metcalfe, and E. F. Wood (2016), HydroBlocks: A Field-scale Resolving Land Surface Model for Application Over Continental Extents, Hydrological Processes, (in press.)

  6. Study on Numerical Simulation of the Impact of the Land-Surface Process in a Meiyu Front Rainstorm

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The research aimed to carry out numerical simulation on impact of land-surface process in a Meiyu front rainstorm.[Method] Based on the meso-scale atmospheric non-hydrostatic model GRAPES-Meso which coupled with NOAH land-surface module,a Meiyu front rainstorm in Jianghuai basin during 6-8 July,2005 was simulated.Via sensitivity tests with and without land-surface process,the impact of land-surface process on Meiyu front rainstorm was studied.[Result] GRAPES-Meso which coupled with NOAH land-sur...

  7. Impact of interactive vegetation phenology on the simulated pan-Arctic land surface state

    Science.gov (United States)

    Teufel, Bernardo; Sushama, Laxmi

    2016-04-01

    The pan-Arctic land surface is undergoing rapid changes in a warming climate, with near-surface permafrost projected to degrade significantly during the 21st century. This can have important impacts on the regional climate and hydrology through various feedbacks, including vegetation-related feedbacks. In this study, the impact of interactive phenology on the land surface state, including near-surface permafrost, is assessed by comparing two simulations of the Canadian Land Surface Scheme (CLASS) - one with interactive phenology, modelled using the Canadian Terrestrial Ecosystem Model (CTEM), and the other with prescribed phenology. These simulations are performed for the 1979-2012 period, using atmospheric forcing from ECMWF's ERA-Interim reanalysis. The impact of interactive phenology on projected changes to the land surface state are also assessed by comparing two simulations of CLASS (with and without interactive phenology), spanning the 1961-2100 period, driven by atmospheric forcing from a transient climate change simulation of the 5th generation Canadian Regional Climate Model (CRCM5) for the Representative Concentration Pathway 8.5 (RCP8.5). Comparison of the CLASS coupled to CTEM simulation with available observational estimates of plant area index, primary productivity, spatial distribution of permafrost and active layer thickness suggests that the model captures reasonably well the general distribution of vegetation and permafrost. Significant differences in evapotranspiration, leading to differences in runoff, soil temperature and active layer thickness are noted when comparing CLASS simulations with and without interactive phenology. Furthermore, the CLASS simulations with and without interactive phenology for RCP8.5 show extensive near-surface permafrost degradation by the end of the 21st century, with slightly accelerated degradation of permafrost in the simulation with interactive phenology, pointing towards a positive feedback of changes in

  8. An off-line simulation of land surface processes over the northern Tibetan Plateau

    Institute of Scientific and Technical Information of China (English)

    MinHong Song; YaoMing Ma; Yu Zhang; WeiQiang Ma; SiQiong Luo

    2014-01-01

    In order to further understand the land surface processes over the northern Tibetan Plateau, this study produced an off-line simulated examination at the Bujiao site on the northern Tibetan Plateau from June 2002 to April 2004, using the Noah Land Surface Model (Noah LSM) and observed data from the CAMP/Tibet experiment. The observed data were neces-sarily corrected and the number of soil layers in the Noah LSM was changed from 4 to 10 to enable this off-line simulation and analysis. The main conclusions are as follows:the Noah LSM performed well on the northern Tibetan Plateau. The simulated net radiation, upward longwave radiation, and upward shortwave radiation demonstrated the same remarkable annual and seasonal variation as the observed data, especially the upward longwave radiation. The simulated soil tem-peratures were acceptably close to the observed temperatures, especially in the shallow soil layers. The simulated freezing and melting processes were shown to start from the surface soil layer and spread down to the deep soil layers, but they took longer than the observed processes. However, Noah LSM did not adequately simulate the soil moisture. Therefore, addi-tional high-quality, long-term observations of land surface-atmosphere processes over the Tibetan Plateau will be a key factor in proper adjustments of the model parameters in the future.

  9. Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

    Science.gov (United States)

    Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

    2016-06-01

    The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

  10. Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

    Directory of Open Access Journals (Sweden)

    J. M. Edwards

    2009-03-01

    Full Text Available Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

  11. WRF Simulation over the Eastern Africa by use of Land Surface Initialization

    Science.gov (United States)

    Sakwa, V. N.; Case, J.; Limaye, A. S.; Zavodsky, B.; Kabuchanga, E. S.; Mungai, J.

    2014-12-01

    to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. These MET tools enable KMS to monitor model forecast accuracy in near real time. This study highlights verification results of WRF runs over East Africa using the LIS land surface initialization.

  12. Simulation and validation of land surface temperature algorithms for MODIS and AATSR data

    Directory of Open Access Journals (Sweden)

    J. M. Galve

    2007-01-01

    Full Text Available A database of global, cloud-free, atmospheric radiosounding profiles was compiled with the aim of simulating radiometric measurements from satellite-borne sensors in the thermal infrared. The objective of the simulation was to use Terra/Moderate Resolution Imaging Spectroradiometer (MODIS and Envisat/Advanced Along Track Scanning Radiometer (AATSR data to generate split-window (SW and dual-angle (DA algorithms for the retrieval of land surface temperature (LST. The database contains 382 radiosounding profiles acquired from land surfaces, with an almost uniform distribution of precipitable water between 0 and 5.5 cm. Radiative transfer calculations were performed with the MODTRAN 4 code for six different viewing angles between 0 and 65º. The resulting radiance spectra were integrated with the response filter functions of MODIS bands 31 and 32 and AATSR channels at 11 and 12 μm. Using the simulation database, SW algorithms adapted for MODIS and AATSR data, and DA algorithms for AATSR data were developed. Both types of algorithms are quadratic in the brightness temperature difference, and depend explicitly on the land surface emissivity. These SW and DA algorithms were validated with actual ground measurements of LST collected concurrently with MODIS and AATSR observations in a large, flat and thermally homogeneous area of rice crops located close to the city of Valencia, Spain. The results were not bias and had a standard deviation of around ± 0.5 K for SW algorithms at the nadir of both sensors; the SW algorithm used in the forward view resulted in a bias of 0.5 K and a standard deviation of ± 0.8 K. The least accurate results were obtained in the DA algorithms with a bias close to -2.0 K and a standard deviation of almost ± 1.0 K.

  13. Wintertime land surface characteristics in climatic simulations over the western Himalayas

    Indian Academy of Sciences (India)

    A P Dimri

    2012-04-01

    Wintertime regional climate studies over the western Himalayas with ICTP-RegCM3 simulations through 22 years has shown systematic biases in precipitation and temperature fields. The model simulated precipitation shows systematically wet bias. In surface temperature simulations, positive and negative biases of 2°–4°C occurred. Experiment without (CONT) and with subBATS (SUB) shows that later scheme performs better, especially for precipitation. Apart from the role of topography and model internal variability, land surface characteristics also have profound impact on these climatic variables. Therefore, in the present study, impacts of land surface characteristics are investigated through cool/wet and warm/dry winter climate by CONT and SUB simulations to assess systematic biases. Since SUB experiment uses detailed land-use classification, systematic positive biases in temperature over higher elevation peaks are markedly reduced. The change has shown reduced excessive precipitation as well. Most of the surface characteristics show that major interplay between topography and western disturbances (WDs) takes place along the foothills rather than over the higher peaks of the western Himalayas.

  14. Spectral emissivity measurements of land-surface materials and related radiative transfer simulations

    Science.gov (United States)

    Wan, Z.; Ng, D.; Dozier, J.

    1994-01-01

    Spectral radiance measurements have been made in the laboratory and in the field for deriving spectral emissivities of some land cover samples with a spectroradiometer and an auxiliary radiation source in the wavelength range 2.5-14.5 micrometers. A easy and quick four-step method (four steps to measure the sample and a diffuse reflecting plate surface under sunshine and shadowing conditions, respectively) has been used for simultaneous determination of surface temperature and emissivity. We emphasized in-situ measurements in combination with radiative transfer simulations, and an error analysis for basic assumptions in deriving spectral emissivity of land-surface samples from thermal infrared measurements.

  15. Role of land surface processes and diffuse/direct radiation partitioning in simulating the European climate

    Directory of Open Access Journals (Sweden)

    E. L. Davin

    2012-05-01

    Full Text Available The influence of land processes and in particular of diffuse/direct radiation partitioning on surface fluxes and associated regional-scale climate feedbacks is investigated using ERA-40 driven simulations over Europe performed with the COSMO-CLM2 Regional Climate Model (RCM. Two alternative Land Surface Models (LSMs, a 2nd generation LSM (TERRA_ML and a more advanced 3rd generation LSM (Community Land Model version 3.5, and two versions of the atmospheric component are tested, as well as a revised coupling procedure allowing for variations in diffuse/direct light partitioning at the surface, and their accounting by the land surface component.

    Overall, the RCM performance for various variables (e.g., surface fluxes, temperature and precipitation is improved when using the more advanced 3rd generation LSM. These improvements are of the same order of magnitude as those arising from a new version of the atmospheric component, demonstrating the benefit of using a realistic representation of land surface processes for regional climate simulations. Taking into account the variability in diffuse/direct light partitioning at the surface further improves the model performance in terms of summer temperature variability at the monthly and daily time scales. Comparisons with observations show that the RCM realistically captures temporal variations in diffuse/direct light partitioning as well as the evapotranspiration sensitivity to these variations. Our results suggest that a modest but consistent fraction (up to 3 % of the overall variability in summer temperature can be explained by variations in the diffuse to direct ratio.

  16. Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

    Indian Academy of Sciences (India)

    C K Unnikrishnan; M Rajeevan; S Vijaya Bhaskara Rao

    2016-06-01

    The direct impact of high resolution land surface initialization on the forecast bias in a regional climatemodel in recent years over Indian summer monsoon region is investigated. Two sets of regional climatemodel simulations are performed, one with a coarse resolution land surface initial conditions and secondone used a high resolution land surface data for initial condition. The results show that all monsoonyears respond differently to the high resolution land surface initialization. The drought monsoon year2009 and extended break periods were more sensitive to the high resolution land surface initialization.These results suggest that the drought monsoon year predictions can be improved with high resolutionland surface initialization. Result also shows that there are differences in the response to the land surfaceinitialization within the monsoon season. Case studies of heat wave and a monsoon depression simulationshow that, the model biases were also improved with high resolution land surface initialization. Theseresults show the need for a better land surface initialization strategy in high resolution regional modelsfor monsoon forecasting.

  17. Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEXv5

    Science.gov (United States)

    Berckmans, Julie; Giot, Olivier; De Troch, Rozemien; Hamdi, Rafiq; Ceulemans, Reinhart; Termonia, Piet

    2017-01-01

    Dynamical downscaling in a continuous approach using initial and boundary conditions from a reanalysis or a global climate model is a common method for simulating the regional climate. The simulation potential can be improved by applying an alternative approach of reinitialising the atmosphere, combined with either a daily reinitialised or a continuous land surface. We evaluated the dependence of the simulation potential on the running mode of the regional climate model ALARO coupled to the land surface model Météo-France SURFace EXternalisée (SURFEX), and driven by the ERA-Interim reanalysis. Three types of downscaling simulations were carried out for a 10-year period from 1991 to 2000, over a western European domain at 20 km horizontal resolution: (1) a continuous simulation of both the atmosphere and the land surface, (2) a simulation with daily reinitialisations for both the atmosphere and the land surface and (3) a simulation with daily reinitialisations of the atmosphere while the land surface is kept continuous. The results showed that the daily reinitialisation of the atmosphere improved the simulation of the 2 m temperature for all seasons. It revealed a neutral impact on the daily precipitation totals during winter, but the results were improved for the summer when the land surface was kept continuous. The behaviour of the three model configurations varied among different climatic regimes. Their seasonal cycle for the 2 m temperature and daily precipitation totals was very similar for a Mediterranean climate, but more variable for temperate and continental climate regimes. Commonly, the summer climate is characterised by strong interactions between the atmosphere and the land surface. The results for summer demonstrated that the use of a daily reinitialised atmosphere improved the representation of the partitioning of the surface energy fluxes. Therefore, we recommend using the alternative approach of the daily reinitialisation of the atmosphere for

  18. [Parameter identification and validation of SWMM in simulation of impervious urban land surface runoff].

    Science.gov (United States)

    Dong, Xin; Du, Peng-fei; Li, Zhi-yi; Wang, Hao-chang

    2008-06-01

    The purpose of this paper is the application of storm water management model (SWMM) in simulating runoff hydrology and water quality. The study chose a roof as the typical impervious urban land surface, and monitored several rainfall-runoff events for parameter identification. We identified and validated hydrological and water quality parameters, using Monte Carlo sampling method and HSY algorithm, which are based on uncertainty analysis. Results show that impervious urban land surface runoff model includes 6 critical parameters, which are depression storage (S-imperv), Manning's n (N-imperv), maximum buildup possible (max buildup), buildup rate constant (rate constant), washoff coefficient (coefficient), and washoff exponent (exponent). Identification of S-imperv and N-imperv could use least square error as objectives, while others could use errors of event pollution load and peak concentration of pollutant as objectives. The identification results of the 6 parameters are N-imperv 0.012-0.025,S-imperv 0-0.7, max buildup 15-30,rate constant 0.2-0.8,coefficient 0.01-0.05, and exponent 1.0-1.2. Regional sensitivities of these parameters in non-ascending order are coefficient, S-imperv, N-imperv, max buildup, exponent, and rate constant. Identified parameters are able to be validated by SWMM model. However, current model structures still have some difficulties in simulating runoff pollutant concentration curves caused by some special rain patterns.

  19. A new method to dynamically simulate groundwater table in land surface model VIC

    Institute of Scientific and Technical Information of China (English)

    YANG Hongwei; XIE Zhenghui

    2003-01-01

    Soil moisture plays an important role in water and energy balance in land-atmospheric interaction, but is impacted directly by the groundwater table. Dynamic variation of the groundwater table can be described mathematically by a moving boundary problem. In this paper, the moving boundary problem is reduced to a fixed boundary problem through a coordinate transformation. A new model of groundwater table simulation is developed using the mass-lumped finite element method and is coupled with the land surface model of Variable Infiltration Capacity (VIC). The simulation results show that the new model not only can simulate the groundwater table dynamically, but also can evade the choice of water table depth scale in computation with a low computation cost.

  20. Sensitivity of simulated South America Climate to the Land Surface Schemes in RegCM4

    Science.gov (United States)

    Llopart, Marta; da Rocha, Rosmeri; Reboita, Michelle; Cuadra, Santiago

    2017-04-01

    This work evaluates the impact of two land surface parameterizations on the simulated climate and its variability over South America (SA). Two numerical experiments using RegCM4 coupled with Biosphere-Atmosphere Transfer Scheme (RegBATS) and Community Land Model version 3.5 (RegCLM) land surface schemes are compared. For the period 1979-2008, RegCM4 simulations used 50 km horizontal grid spacing and the ERA-Interim reanalysis as initial and boundary conditions. For the period studied, both simulations represent the main observed spatial patterns of rainfall, air temperature and low level circulation over SA. However, concerning the precipitation intensity, RegCLM values are closer to the observations than RegBATS (it is in general, wetter) over most of SA. RegCLM also provides smaller biases for air temperature. Over the Amazon basin, the amplitudes of the annual cycles of the soil moisture, evapotranspiration and sensible heat flux are higher in RegBATS than in RegCLM. This indicates that RegBATS provides large amounts of water vapor to the atmosphere and has more available energy to increase the boundary layer and make it reach the level of free convection (higher sensible heat flux values) resulting in higher precipitation rates and a large wet bias. RegCLM is closer to the observations than RegBATS, presenting smaller wet and warm biases over the Amazon basin. On an interannual scale, the magnitudes of the anomalies of the precipitation and air temperature simulated by RegCLM are closer to the observations. In general, RegBATS simulates higher magnitude for the interannual variability signal.

  1. A NUMERICAL SIMULATION OF THE EFFECT ON CHINESE REGIONAL CLIMATE DUE TO SEASONAL VARIATION OF LAND SURFACE PARAMETERS (PART I)

    Institute of Scientific and Technical Information of China (English)

    孙健; 李维亮; 周秀骥

    2001-01-01

    Sensitivity experiment is an important method to study the effect on regional climate due to seasonal variation of land surface parameters. Using China Regional Climate Model (CRCM)nested in CCM1, we first simulate Chinese regional climate, then two numerical sensitivity experiments on the effect of vegetation and roughness length are made. The results show that:(1) If the vegetation is replaced with the monthly data of 1997, precipitation and land-surface temperature are both changed clearly, precipitation decreases and land surface temperature increases, but there is no regional correspondence between these changes. And the results are much better than the results when climate average vegetation was used in the CRCM. (2) If the roughness length is replaced with the monthly data of 1997, there is significant change on land surface temperature, and there is very good regional correspondence between these changes. But the effect on precipitation is very small.

  2. Simulation of permafrost and seasonal thaw depth in the JULES land surface scheme

    Directory of Open Access Journals (Sweden)

    R. Dankers

    2011-04-01

    Full Text Available Land surface models (LSMs need to be able to simulate realistically the dynamics of permafrost and frozen ground. In this paper we evaluate the performance of the LSM JULES (Joint UK Land Environment Simulator, the stand-alone version of the land surface scheme used in Hadley Centre climate models, in simulating the large-scale distribution of surface permafrost. In particular we look at how well the model is able to simulate the seasonal thaw depth or active layer thickness (ALT. We performed a number of experiments driven by observation-based climate datasets. Visually there is a very good agreement between areas with permafrost in JULES and known permafrost distribution in the Northern Hemisphere, and the model captures 97% of the area where the permafrost coverage is at least 50% of the grid cell. However, the model overestimates the total extent as it also simulates permafrost where it occurs sporadically or only in isolated patches. Consistent with this we find a cold bias in the simulated soil temperatures, especially in winter. However, when compared with observations on end-of-season thaw depth from around the Arctic, the ALT in JULES is generally too deep. Additional runs at three sites in Alaska demonstrate how uncertainties in the precipitation input affect the simulation of soil temperatures by affecting the thickness of the snowpack and therefore the thermal insulation in winter. In addition, changes in soil moisture content influence the thermodynamics of soil layers close to freezing. We also present results from three experiments in which the standard model setup was modified to improve physical realism of the simulations in permafrost regions. Extending the soil column to a depth of 60 m and adjusting the soil parameters for organic content had relatively little effect on the simulation of permafrost and ALT. A higher vertical resolution improves the simulation of ALT, although a considerable bias still remains. Future model

  3. Simulation of permafrost and seasonal thaw depth in the JULES land surface scheme

    Directory of Open Access Journals (Sweden)

    R. Dankers

    2011-09-01

    Full Text Available Land surface models (LSMs need to be able to simulate realistically the dynamics of permafrost and frozen ground. In this paper we evaluate the performance of the LSM JULES (Joint UK Land Environment Simulator, the stand-alone version of the land surface scheme used in Hadley Centre climate models, in simulating the large-scale distribution of surface permafrost. In particular we look at how well the model is able to simulate the seasonal thaw depth or active layer thickness (ALT. We performed a number of experiments driven by observation-based climate datasets. Visually there is a very good agreement between areas with permafrost in JULES and known permafrost distribution in the Northern Hemisphere, and the model captures 97% of the area where the spatial coverage of the permafrost is at least 50%. However, the model overestimates the total extent as it also simulates permafrost where it occurs sporadically or only in isolated patches. Consistent with this we find a cold bias in the simulated soil temperatures, especially in winter. However, when compared with observations on end-of-season thaw depth from around the Arctic, the ALT in JULES is generally too deep. Additional runs at three sites in Alaska demonstrate how uncertainties in the precipitation input affect the simulation of soil temperatures by affecting the thickness of the snowpack and therefore the thermal insulation in winter. In addition, changes in soil moisture content influence the thermodynamics of soil layers close to freezing. We also present results from three experiments in which the standard model setup was modified to improve physical realism of the simulations in permafrost regions. Extending the soil column to a depth of 60 m and adjusting the soil parameters for organic content had relatively little effect on the simulation of permafrost and ALT. A higher vertical resolution improves the simulation of ALT, although a considerable bias still remains. Future model

  4. Simulating hydrology with an isotopic land surface model in western Siberia: what do we learn from water isotopes?

    Directory of Open Access Journals (Sweden)

    F. Guglielmo

    2015-09-01

    Full Text Available Improvements in the evaluation of land surface models would translate into more reliable predictions of future climate changes, as significant uncertainties persist in the quantification and representation of the relative contributions of soil and vegetation to the water and energy cycles. In this paper, we investigate the usefulness of water stable isotopes in land surface models studying land surface processes. To achieve this, we implemented 18O and 2H and the computation of the oxygen (δ18O and deuterium (δD stable isotope composition of soil and leaf water pools in a~recent version of the land surface model ORCHIDEE. We performed point-wise simulations with this new model and evaluated its performance on vertical profiles of soil water isotope ratios measured in summer 2012 at four experimental sites located in a boreal region of the Artic zone of western Siberia. The model performed relatively well in simulating some features of the δ18O soil profiles, but poorly reproduced the d-excess profiles, at all four stations. The response of the simulated δ18O profiles to variations in key hydrological parameters revealed the importance of the choice of a correct infiltration pathway in ORCHIDEE. Our results show also that the strength of the evaporative enrichment signal plays a role in shaping the profiles, too and, therefore, the relevance of the vegetation and bare soil characterization. We investigated furthermore to which extent we are able to determine the relative contribution of the evaporation to the evapotranspiration. This study's results confirm that the use of water stable isotopes measurements helps constrain the representation of key land surface processes in land surface models.

  5. Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh

    Directory of Open Access Journals (Sweden)

    Bayes Ahmed

    2013-11-01

    Full Text Available Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30 °C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth on LST and consequently to devise appropriate policy measures.

  6. How can we use MODIS land surface temperature to validate long-term urban model simulations?

    Science.gov (United States)

    Hu, Leiqiu; Brunsell, Nathaniel A.; Monaghan, Andrew J.; Barlage, Michael; Wilhelmi, Olga V.

    2014-03-01

    High spatial resolution urban climate modeling is essential for understanding urban climatology and predicting the human health impacts under climate change. Satellite thermal remote-sensing data are potential observational sources for urban climate model validation with comparable spatial scales, temporal consistency, broad coverage, and long-term archives. However, sensor view angle, cloud distribution, and cloud-contaminated pixels can confound comparisons between satellite land surface temperature (LST) and modeled surface radiometric temperature. The impacts of sensor view angles on urban LST values are investigated and addressed. Three methods to minimize the confounding factors of clouds are proposed and evaluated using 10years of Moderate Resolution Imaging Spectroradiometer (MODIS) data and simulations from the High-Resolution Land Data Assimilation System (HRLDAS) over Greater Houston, Texas, U.S. For the satellite cloud mask (SCM) method, prior to comparison, the cloud mask for each MODIS scene is applied to its concurrent HRLDAS simulation. For the max/min temperature (MMT) method, the 50 warmest days and coolest nights for each data set are selected and compared to avoid cloud impacts. For the high clear-sky fraction (HCF) method, only those MODIS scenes that have a high percentage of clear-sky pixels are compared. The SCM method is recommended for validation of long-term simulations because it provides the largest sample size as well as temporal consistency with the simulations. The MMT method is best for comparison at the extremes. And the HCF method gives the best absolute temperature comparison due to the spatial and temporal consistency between simulations and observations.

  7. Simulation Experiments of Land Surface Physical Processes and Ecological Effect over Different Underlying Surface

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    Based on the existing Land Surface Physical Process Models(Deardorff, Dickinson, LIU, Noilhan, Seller, ZHAO), a Comprehensive Land Surface Physical Process Model (CLSPPM) is developed by considering the different physical processes of the earth's surface-vegetation-atmosphere system more completely. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feas...

  8. Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

    Directory of Open Access Journals (Sweden)

    H. W. Ter Maat

    2010-08-01

    Full Text Available This paper is a case study to investigate what the main controlling factors are that determine atmospheric carbon dioxide content for a region in the centre of The Netherlands. We use the Regional Atmospheric Modelling System (RAMS, coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C, and including also submodels for urban and marine fluxes, which in principle should include the dominant mechanisms and should be able to capture the relevant dynamics of the system. To validate the model, observations are used that were taken during an intensive observational campaign in central Netherlands in summer 2002. These include flux-tower observations and aircraft observations of vertical profiles and spatial fluxes of various variables.

    The simulations performed with the coupled regional model (RAMS-SWAPS-C are in good qualitative agreement with the observations. The station validation of the model demonstrates that the incoming shortwave radiation and surface fluxes of water and CO2 are well simulated. The comparison against aircraft data shows that the regional meteorology (i.e. wind, temperature is captured well by the model. Comparing spatially explicitly simulated fluxes with aircraft observed fluxes we conclude that in general latent heat fluxes are underestimated by the model compared to the observations but that the latter exhibit large variability within all flights. Sensitivity experiments demonstrate the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same tests also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

  9. Evaluation of the JULES land surface model in simulating catchment hydrology in Southern Africa

    Directory of Open Access Journals (Sweden)

    N. C. MacKellar

    2013-08-01

    Full Text Available Land surface models (LSMs are advanced tools which can be used to estimate energy, water and biogeochemical exchanges at regional scales. The inclusion of a river flow routing module in an LSM allows for the simulation of river discharge from a catchment and offers an approach to evaluate the response of the system to variations in climate and land-use, which can provide useful information for regional water resource management. This study offers insight into some of the pragmatic considerations of applying an LSM over a regional domain in Southern Africa. The objectives are to identify key parameter sensitivities and investigate differences between two runoff production schemes in physically contrasted catchments. The Joint UK Land Environment Simulator (JULES LSM was configured for a domain covering Southern Africa at a 0.5° resolution. The model was forced with meteorological input from the WATCH Forcing Data for the period 1981–2001 and sensitivity to various model configurations and parameter settings were tested. Both the PDM and TOPMODEL sub-grid scale runoff generation schemes were tested for parameter sensitivities, with the evaluation focussing on simulated river discharge in sub-catchments of the Orange, Okavango and Zambezi rivers. It was found that three catchments respond differently to the model configurations and there is no single runoff parameterization scheme or parameter values that yield optimal results across all catchments. The PDM scheme performs well in the upper Orange catchment, but poorly in the Okavango and Zambezi, whereas TOPMODEL grossly underestimates discharge in the upper Orange and shows marked improvement over PDM for the Okavango and Zambezi. A major shortcoming of PDM is that it does not realistically represent subsurface runoff in the deep, porous soils typical of the Okavango and Zambezi headwaters. The dry-season discharge in these catchments is therefore not replicated by PDM. TOPMODEL, however

  10. The Impact of Land-Surface Parameter Properties and Resolution on the Simulated Cloud-Topped Atmospheric Boundary Layer

    Science.gov (United States)

    Gantner, Leonhard; Maurer, Vera; Kalthoff, Norbert; Kiseleva, Olga

    2017-08-01

    Sensitivity tests using the `Consortium for Small Scale Modeling' model in large-eddy simulation mode with a grid spacing of 100 m are performed to investigate the impact of the resolution of soil- and vegetation-related parameters on a cloud-topped boundary layer in a real-data environment. The reference simulation uses the highest land-surface parameter resolution available for operational purposes (300 m). The sensitivity experiments were conducted using spatial averaging of about 2.5 km× 2.5 km and 10 km × 10 km for the land-surface parameters and a completely homogeneous distribution for the whole model domain of about 70 km × 70 km . Additionally, one experiment with a higher mean soil moisture and another with six mesoscale patches of enhanced or reduced soil moisture are performed. Boundary-layer clouds developed in all simulations. To assess the deviations of cloud cover on different scales within the model domain, we calculated the root-mean-square deviation (RMSD) between the sensitivity experiments and the reference simulation. The RMSD depends strongly on the spatial resolution at which cloud fields are compared. Different spatial resolutions of the cloud fields were generated by applying a low-pass filter. For all sensitivity experiments, large RMSD values occur for cut-off wavelengths {}5 km , the RMSD is still pronounced for the simulation with higher mean soil moisture. Additionally, for cut-off wavelengths between 5 and 30 km, considerable differences can be found for the experiment with mesoscale patches and for that with homogeneous land-surface parameters. Spatial averaging of land-surface parameters for areas of 2.5 km × 2.5 km and 10 km × 10 km results in larger patch sizes but simultaneously in reduced amplitudes of land-surface parameter anomalies and shows the lowest RMSD for all cut-off wavelengths.

  11. The effect of GCM biases on global runoff simulations of a land surface model

    Science.gov (United States)

    Papadimitriou, Lamprini V.; Koutroulis, Aristeidis G.; Grillakis, Manolis G.; Tsanis, Ioannis K.

    2017-09-01

    Global climate model (GCM) outputs feature systematic biases that render them unsuitable for direct use by impact models, especially for hydrological studies. To deal with this issue, many bias correction techniques have been developed to adjust the modelled variables against observations, focusing mainly on precipitation and temperature. However, most state-of-the-art hydrological models require more forcing variables, in addition to precipitation and temperature, such as radiation, humidity, air pressure, and wind speed. The biases in these additional variables can hinder hydrological simulations, but the effect of the bias of each variable is unexplored. Here we examine the effect of GCM biases on historical runoff simulations for each forcing variable individually, using the JULES land surface model set up at the global scale. Based on the quantified effect, we assess which variables should be included in bias correction procedures. To this end, a partial correction bias assessment experiment is conducted, to test the effect of the biases of six climate variables from a set of three GCMs. The effect of the bias of each climate variable individually is quantified by comparing the changes in simulated runoff that correspond to the bias of each tested variable. A methodology for the classification of the effect of biases in four effect categories (ECs), based on the magnitude and sensitivity of runoff changes, is developed and applied. Our results show that, while globally the largest changes in modelled runoff are caused by precipitation and temperature biases, there are regions where runoff is substantially affected by and/or more sensitive to radiation and humidity. Global maps of bias ECs reveal the regions mostly affected by the bias of each variable. Based on our findings, for global-scale applications, bias correction of radiation and humidity, in addition to that of precipitation and temperature, is advised. Finer spatial-scale information is also provided

  12. Evaluation of streamflow simulation results of land surface models in GLDAS on the Tibetan plateau

    Science.gov (United States)

    Bai, Peng; Liu, Xiaomang; Yang, Tiantian; Liang, Kang; Liu, Changming

    2016-10-01

    The Global Land Data Assimilation System (GLDAS) project estimates long-term runoff based on land surface models (LSMs) and provides a potential way to solve the issue of nonexistent streamflow data in gauge-sparse regions such as the Tibetan Plateau (TP). However, the reliability of GLDAS runoff data must be validated before being practically applied. In this study, the streamflows simulated by four LSMs (CLM, Noah, VIC, and Mosaic) in GLDAS coupled with a river routing model are evaluated against observed streamflows in five river basins on the TP. The evaluation criteria include four aspects: monthly streamflow value, seasonal cycle of streamflow, annual streamflow trend, and streamflow component partitioning. The four LSMs display varying degrees of biases in monthly streamflow simulations: systematic overestimations are found in the Noah (1.74 ≤ bias ≤ 2.75) and CLM (1.22 ≤ bias ≤ 2.53) models, whereas systematic underestimations are observed in the VIC (0.36 ≤ bias ≤ 0.85) and Mosaic (0.34 ≤ bias ≤ 0.66) models. The Noah model shows the best performance in capturing the temporal variation in monthly streamflow and the seasonal cycle of streamflow, while the VIC model performs the best in terms of bias statistics. The Mosaic model provides the best performance in modeling annual runoff trends and runoff component partitioning. The possible reasons for the different performances of the LSMs are discussed in detail. In order to achieve more accurate streamflow simulations from the LSMs in GLDAS, suggestions are made to further improve the accuracy of the forcing data and parameterization schemes in all models.

  13. 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

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

    Science.gov (United States)

    Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

    2015-01-01

    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 magnitude of

  15. A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations

    Directory of Open Access Journals (Sweden)

    J. Ryder

    2014-12-01

    Full Text Available In Earth system modelling, a description of the energy budget of the vegetated surface layer is fundamental as it determines the meteorological conditions in the planetary boundary layer and as such contributes to the atmospheric conditions and its circulation. The energy budget in most Earth system models has long been based on a "big-leaf approach", with averaging schemes that represent in-canopy processes. Such models have difficulties in reproducing consistently the energy balance in field observations. We here outline a newly developed numerical model for energy budget simulation, as a component of the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems – CANopy. This new model implements techniques from single-site canopy models in a practical way. It includes representation of in-canopy transport, a multilayer longwave radiation budget, height-specific calculation of aerodynamic and stomatal conductance, and interaction with the bare soil flux within the canopy space. Significantly, it avoids iterations over the height of tha canopy and so maintains implicit coupling to the atmospheric model LMDz. As a first test, the model is evaluated against data from both an intensive measurement campaign and longer term eddy covariance measurements for the intensively studied Eucalyptus stand at Tumbarumba, Australia. The model performs well in replicating both diurnal and annual cycles of fluxes, as well as the gradients of sensible heat fluxes. However, the model overestimates sensible heat flux against an underestimate of the radiation budget. Improved performance is expected through the implementation of a more detailed calculation of stand albedo and a more up-to-date stomatal conductance calculation.

  16. Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

    OpenAIRE

    2013-01-01

    Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and t...

  17. Improved meteorology and ozone air quality simulations using MODIS land surface parameters in the Yangtze River Delta urban cluster, China

    Science.gov (United States)

    Li, Mengmeng; Wang, Tijian; Xie, Min; Zhuang, Bingliang; Li, Shu; Han, Yong; Song, Yu; Cheng, Nianliang

    2017-03-01

    Land surface parameters play an important role in the land-atmosphere coupling and thus are critical to the weather and dispersion of pollutants in the atmosphere. This work aims at improving the meteorology and air quality simulations for a high-ozone (O3) event in the Yangtze River Delta urban cluster of China, through incorporation of satellite-derived land surface parameters. Using Moderate Resolution Imaging Spectroradiometer (MODIS) input to specify the land cover type, green vegetation fraction, leaf area index, albedo, emissivity, and deep soil temperature provides a more realistic representation of surface characteristics. Preliminary evaluations reveal clearly improved meteorological simulation with MODIS input compared with that using default parameters, particularly for temperature (from -2.5 to -1.7°C for mean bias) and humidity (from 9.7% to 4.3% for mean bias). The improved meteorology propagates through the air quality system, which results in better estimates for surface NO2 (from 11.5 to 8.0 ppb for mean bias) and nocturnal O3 low-end concentration values (from -18.8 to -13.6 ppb for mean bias). Modifications of the urban land surface parameters are the main reason for model improvement. The deeper urban boundary layer and intense updraft induced by the urban heat island are favorable for pollutant dilution, thus contributing to lower NO2 and elevated nocturnal O3. Furthermore, the intensified sea-land breeze circulation may exacerbate O3 pollution at coastal cities through pollutant recirculation. Improvement of mesoscale meteorology and air quality simulations with satellite-derived land surface parameters will be useful for air pollution monitoring and forecasting in urban areas.

  18. Simulation of snow microwave radiance observations using a coupled land surface- radiative transfer models

    Science.gov (United States)

    Toure, A. M.; Rodell, M.; Hoar, T. J.; Kwon, Y.; Yang, Z.; Zhang, Y.; Beaudoing, H.

    2013-12-01

    Radiance assimilation (RA) has been used in operational numerical weather forecasting for generating realistic initial and boundary conditions for the last two decades. Previous studies have shown that the same approach can be used to characterize seasonal snow. Since the penetration depth of microwaves depends essentially on snow physical properties, studies have also shown that for RA to be successful, it is crucial that the land surface model (LSM) represents with great fidelity snow physical properties such as the effective grain size, the temperature, the stratigraphy, the densification and the melt/refreeze processes. The Community Land Model version 4 (CLM4), the land model component of the Community Earth System Model (CESM), describes the physical, chemical, biological, and hydrological processes by which terrestrial ecosystems interact with climate across a variety of spatial and temporal scales. Sub-grid heterogeneity of the CLM4 is represented by fractional coverage of glacier, lake, wetland, urban, and vegetation land cover types. The vegetation portion is further divided into mosaic of plant functional types (pfts) each with its own leaf and stem area index and canopy height. Processes such as snow accumulation, depletion, densification, metamorphism, percolation, and refreezing of water are represented by a state-of-the-art multi-layer (up to five layers) snow model. Each snow layer is characterized by its thickness, ice mass, liquid water content, temperature, and effective grain radius. The model is considered to be one of the most sophisticated snow models ever within a general circulation model. One of the main challenges in simulating the radiance observed by a radiometer on-board a satellite is the spatial heterogeneity of the land within the footprint of the radiometer. Since CLM4 has the capability to represent the sub-grid heterogeneity, it is perfect candidate for a model operator for simulating the observed brightness temperature (Tb). The

  19. Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

    Science.gov (United States)

    Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

    2010-01-01

    Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

  20. Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

    Science.gov (United States)

    Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

    2010-01-01

    Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

  1. The role of land surface processes on the mesoscale simulation of the July 26, 2005 heavy rain event over Mumbai, India

    Science.gov (United States)

    Chang, Hsin-I.; Kumar, Anil; Niyogi, Dev; Mohanty, U. C.; Chen, Fei; Dudhia, Jimy

    2009-05-01

    A record-breaking heavy rain event occurred over Mumbai, India on July 26th, 2005 with 24-h rainfall exceeding 944 mm. Operational weather forecast models failed to predict the intensity and amount of heavy rainfall. The objective of this study was to test the impact of the three different land surface models when coupled to the Weather Research Forecasting (WRF), and also to investigate the ability of the WRF model to simulate the Mumbai heavy rain event. Numerical experiments were designed using the WRF model, with three nested domains (30, 10, and 3.3 km grid spacing). Results confirmed that the simulated rainfall is sensitive to the grid spacing (with finer grids leading to higher rainfall). Results also suggest that simulated precipitation amounts are sensitive to the choice of cumulus parameterization (with Grell-Devenyi cumulus scheme performing relatively best). To reduce the confounding impact of cumulus parameterization in studying the impacts of land surface models, we evaluated results for the 3.3 km grid spacing domain with explicit convection. Simulations were performed from 12Z, July 25th to 00Z, July 27th with identical boundary conditions and model configurations for three different land surface models (the Slab, the Noah, and a modified version with photosynthesis module—the Noah-GEM). The model results were compared with observed rainfall, surface temperature, and operational soundings over three locations: Mumbai, Bangalore and Bhopal. Model results showed that: (i) The simulated rainfall was sensitive to the chosen land surface model. The rainfall spatial distributions, as well as their temporal characteristics, were different for each of the three WRF runs with different LSMs. (ii) In contrast to the findings over mid-latitudes, the relatively simpler Slab model had a relatively better performance than the modestly complex Noah and Noah-GEM LSMs. For example, the highest observed rainfall over Mumbai was 944 mm and the simulated amounts for

  2. Integrated Water Flow Model (IWFM), A Tool For Numerically Simulating Linked Groundwater, Surface Water And Land-Surface Hydrologic Processes

    Science.gov (United States)

    Dogrul, E. C.; Brush, C. F.; Kadir, T. N.

    2006-12-01

    The Integrated Water Flow Model (IWFM) is a comprehensive input-driven application for simulating groundwater flow, surface water flow and land-surface hydrologic processes, and interactions between these processes, developed by the California Department of Water Resources (DWR). IWFM couples a 3-D finite element groundwater flow process and 1-D land surface, lake, stream flow and vertical unsaturated-zone flow processes which are solved simultaneously at each time step. The groundwater flow system is simulated as a multilayer aquifer system with a mixture of confined and unconfined aquifers separated by semiconfining layers. The groundwater flow process can simulate changing aquifer conditions (confined to unconfined and vice versa), subsidence, tile drains, injection wells and pumping wells. The land surface process calculates elemental water budgets for agricultural, urban, riparian and native vegetation classes. Crop water demands are dynamically calculated using distributed soil properties, land use and crop data, and precipitation and evapotranspiration rates. The crop mix can also be automatically modified as a function of pumping lift using logit functions. Surface water diversions and groundwater pumping can each be specified, or can be automatically adjusted at run time to balance water supply with water demand. The land-surface process also routes runoff to streams and deep percolation to the unsaturated zone. Surface water networks are specified as a series of stream nodes (coincident with groundwater nodes) with specified bed elevation, conductance and stage-flow relationships. Stream nodes are linked to form stream reaches. Stream inflows at the model boundary, surface water diversion locations, and one or more surface water deliveries per location are specified. IWFM routes stream flows through the network, calculating groundwater-surface water interactions, accumulating inflows from runoff, and allocating available stream flows to meet specified or

  3. Integrating satellite retrieved leaf chlorophyll into land surface models for constraining simulations of water and carbon fluxes

    KAUST Repository

    Houborg, Rasmus

    2013-07-01

    In terrestrial biosphere models, key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types although in reality significant spatial and temporal variability exists. Satellite remote sensing can support modeling efforts by offering distributed information on important land surface characteristics, which would be very difficult to obtain otherwise. This study investigates the utility of satellite based retrievals of leaf chlorophyll for estimating leaf photosynthetic capacity and for constraining model simulations of water and carbon fluxes. © 2013 IEEE.

  4. Observed and simulated effect of plant physiology and structure on land surface energy fluxes and soil conditions

    Science.gov (United States)

    Lu, Yen-Sen; Rihani, Jehan; Langensiepen, Matthias; Simmer, Clemens

    2016-04-01

    The parameterization of stomatal conductance and leaf area index (LAI) in land surface models largely influence simulated terrestrial system states. While stomatal conductance mainly controls transpiration, latent heat flux, and root-water-uptake, LAI impacts additionally the radiative energy exchange. Thus both affect canopy evaporation and transpiration and land surface energy and water fluxes as a whole. Common parameterizations of stomatal conductance follow either semi-mechanistic forms based on photosynthesis (Ball-Berry Type (BB)) or forms which consider environmental factors such as impact of light, temperature, humidity and soil moisture (Jarvis-Stewart Type (JS)). Both approaches differ also in the interpretation of humidity effects and light-use efficiency. While soil moisture plays an important role for root-water-uptake there is no clear conclusion yet about how soil moisture interacts with stomata activity. Values for LAI can be obtained from field measurements, satellite estimates or modelling and are used as an essential model input. While field measurements are very time consuming and only represent single points, satellite estimates may have biases caused by variable albedo and sensor limitations. Representing LAI within land surface models requires complex schemes in order to represent all processes contributing to plant growth. We use the Terrestrial System Modelling Platform (TerrSysMP) over the Rur watershed in Germany for studying the influence of plant physiology and structure on the state of the terrestrial system. The Transregional Collaborative Research Center 32 (TR32) extensively monitors this catchment for almost a decade. The land surface (CLM3.5) and the subsurface (ParFlow) modules of TerrSysMP are conditioned based on satellite-retrieved land cover and the soil map from FAO and forced with a high-resolution reanalysis by DWD. For studying the effect of plant physiology, the Ball-Berry-Leuning, and Jarvis-Stewart stomatal

  5. Sensitivity of a regional climate model to land surface parameterization schemes for East Asian summer monsoon simulation

    Science.gov (United States)

    Li, Wenkai; Guo, Weidong; Xue, Yongkang; Fu, Congbin; Qiu, Bo

    2016-10-01

    Land surface processes play an important role in the East Asian Summer Monsoon (EASM) system. Parameterization schemes of land surface processes may cause uncertainties in regional climate model (RCM) studies for the EASM. In this paper, we investigate the sensitivity of a RCM to land surface parameterization (LSP) schemes for long-term simulation of the EASM. The Weather Research and Forecasting (WRF) Model coupled with four different LSP schemes (Noah-MP, CLM4, Pleim-Xiu and SSiB), hereafter referred to as Sim-Noah, Sim-CLM, Sim-PX and Sim-SSiB respectively, have been applied for 22-summer EASM simulations. The 22-summer averaged spatial distributions and strengths of downscaled large-scale circulation, 2-m temperature and precipitation are comprehensively compared with ERA-Interim reanalysis and dense station observations in China. Results show that the downscaling ability of RCM for the EASM is sensitive to LSP schemes. Furthermore, this study confirms that RCM does add more information to the EASM compared to reanalysis that imposes the lateral boundary conditions (LBC) because it provides 2-m temperature and precipitation that are with higher resolution and more realistic compared to LBC. For 2-m temperature and monsoon precipitation, Sim-PX and Sim-SSiB simulations are more consistent with observation than simulations of Sim-Noah and Sim-CLM. To further explore the physical and dynamic mechanisms behind the RCM sensitivity to LSP schemes, differences in the surface energy budget between simulations of Ens-Noah-CLM (ensemble mean averaging Sim-Noah and Sim-CLM) and Ens-PX-SSiB (ensemble mean averaging Sim-PX and Sim-SSiB) are investigated and their subsequent impacts on the atmospheric circulation are analyzed. It is found that the intensity of simulated sensible heat flux over Asian continent in Ens-Noah-CLM is stronger than that in Ens-PX-SSiB, which induces a higher tropospheric temperature in Ens-Noah-CLM than in Ens-PX-SSiB over land. The adaptive

  6. Improving the Vegetation Dynamic Simulation in a Land Surface Model by Using a Statistical-dynamic Canopy Interception Scheme

    Institute of Scientific and Technical Information of China (English)

    LIANG Miaoling; XIE Zhenghui

    2008-01-01

    Canopy interception of incident precipitation, as a critical component of a forest's water budget, can affect the amount of water available to the soil, and ultimately vegetation distribution and function. In this paper, a statistical-dynamic approach based on leaf area index and statistical canopy interception is used to parameterize the canopy interception process. The statistical-dynamic canopy interception scheme is implemented into the Community Land Model with dynamic global vegetation model (CLM-DGVM) to improve its dynamic vegetation simulation. The simulation for continental China by the land surface model with the new canopy interception scheme shows that the new one reasonably represents the precipitation intercepted by the canopy. Moreover, the new scheme enhances the water availability in the root zone for vegetation growth, especially in the densely vegetated and semi-arid areas, and improves the model's performance of potential vegetation simulation.

  7. Numerical simulations of land surface physical processes and land-atmosphere interactions over oasis-desert/Gobi region

    Institute of Scientific and Technical Information of China (English)

    LIU ShuHua; LIU HePing; HU Yu; ZHANG ChengYi; LIANG FuMing; WANG JianHua

    2007-01-01

    A land-surface physical process model was coupled with a mesoscale atmospheric model. This coupled model was then used to simulate the interactions between land and the atmosphere, including surface temperature, net radiation, sensible heat flux and latent heat flux over a desert/Gobi with an oasis in northwestern semiarid regions in China. Comparisons between observations and simulations were made over the oasis and the desert/Gobi, respectively. Both cold island effect and wet island effect, the so-called oasis effect, were observed and simulated. Lower temperature, higher specific humidity and weaker turbulent transfer were present over the oasis than the desert/Gobi. A subsidence occurred over the oasis, leading to a thermally-generated mesoscale circulation.

  8. The fan of influence of streams and channel feedbacks to simulated land surface water and carbon dynamics

    Science.gov (United States)

    Shen, Chaopeng; Riley, William J.; Smithgall, Kurt R.; Melack, John M.; Fang, Kuai

    2016-02-01

    Large-scale land models assume unidirectional land-to-river hydrological interactions, without considering feedbacks between channels and land. Using a tested, physically based model with explicit multiway interactions between overland, channel, wetland, and groundwater flows, we assessed how the representation and properties of channels influence simulated land surface hydrologic, biogeochemical, and ecosystem dynamics. A zone near the channels where various fluxes and states are significantly influenced by the channels, referred to as the fan of influence (FoI) of channels, has been identified. We elucidated two mechanisms inducing the model-derived FoI: the base flow mechanism, in which incised, gaining streams lower the water table and induce more base flow, and the relatively more efficient conveyance of the channel network compared to overland flow. We systematically varied drainage density and grid resolution to quantify the size of the FoI, which is found to span a large fraction of the watershed (25-50%) for hydrologic variables including depth to water table and recharge, etc. The FoI is more pronounced with low-resolution simulations but remains noticeable in hyperresolution (25 m) subbasin simulations. The FoI and the channel influence on basin-average fluxes are also similar in simulations with alternative parameter sets. We found that high-order, entrenched streams cause larger FoI. In addition, removing the simulated channels has disproportionally large influence on modeled wetland areas and inundation duration, which has implications for coupled biogeochemical or ecological modeling. Our results suggest that explicit channel representation provides important feedbacks to land surface dynamics which should be considered in meso or large-scale simulations. Since grid refinement incurs prohibitive computational cost, subgrid channel parameterization has advantages in efficiency over grid-based representations that do not distinguish between overland

  9. Global water balances reconstructed by multi-model offline simulations of land surface models under GSWP3 (Invited)

    Science.gov (United States)

    Oki, T.; KIM, H.; Ferguson, C. R.; Dirmeyer, P.; Seneviratne, S. I.

    2013-12-01

    As the climate warms, the frequency and severity of flood and drought events is projected to increase. Understanding the role that the land surface will play in reinforcing or diminishing these extremes at regional scales will become critical. In fact, the current development path from atmospheric (GCM) to coupled atmosphere-ocean (AOGCM) to fully-coupled dynamic earth system models (ESMs) has brought new awareness to the climate modeling community of the abundance of uncertainty in land surface parameterizations. One way to test the representativeness of a land surface scheme is to do so in off-line (uncoupled) mode with controlled, high quality meteorological forcing. When multiple land schemes are run in-parallel (with the same forcing data), an inter-comparison of their outputs can provide the basis for model confidence estimates and future model refinements. In 2003, the Global Soil Wetness Project Phase 2 (GSWP2) provided the first global multi-model analysis of land surface state variables and fluxes. It spanned the decade of 1986-1995. While it was state-of-the art at the time, physical schemes have since been enhanced, a number of additional processes and components in the water-energy-eco-systems nexus can now be simulated, , and the availability of global, long-term observationally-based datasets that can be used for forcing and validating models has grown. Today, the data exists to support century-scale off-line experiments. The ongoing follow-on to GSWP2, named GSWP3, capitalizes on these new feasibilities and model functionalities. The project's cornerstone is its century-scale (1901-2010), 3-hourly, 0.5° meteorological forcing dataset that has been dynamically downscaled from the Twentieth Century Reanalysis and bias-corrected using monthly Climate Research Unit (CRU) temperature and Global Precipitation Climatology Centre (GPCC) precipitation data. However, GSWP3 also has an important long-term future climate component that spans the 21st century

  10. Impacts of snow and organic soils parameterization on northern Eurasian soil temperature profiles simulated by the ISBA land surface model

    Science.gov (United States)

    Decharme, Bertrand; Brun, Eric; Boone, Aaron; Delire, Christine; Le Moigne, Patrick; Morin, Samuel

    2016-04-01

    In this study we analyzed how an improved representation of snowpack processes and soil properties in the multilayer snow and soil schemes of the Interaction Soil-Biosphere-Atmosphere (ISBA) land surface model impacts the simulation of soil temperature profiles over northern Eurasian regions. For this purpose, we refine ISBA's snow layering algorithm and propose a parameterization of snow albedo and snow compaction/densification adapted from the detailed Crocus snowpack model. We also include a dependency on soil organic carbon content for ISBA's hydraulic and thermal soil properties. First, changes in the snowpack parameterization are evaluated against snow depth, snow water equivalent, surface albedo, and soil temperature at a 10 cm depth observed at the Col de Porte field site in the French Alps. Next, the new model version including all of the changes is used over northern Eurasia to evaluate the model's ability to simulate the snow depth, the soil temperature profile, and the permafrost characteristics. The results confirm that an adequate simulation of snow layering and snow compaction/densification significantly impacts the snowpack characteristics and the soil temperature profile during winter, while the impact of the more accurate snow albedo computation is dominant during the spring. In summer, the accounting for the effect of soil organic carbon on hydraulic and thermal soil properties improves the simulation of the soil temperature profile. Finally, the results confirm that this last process strongly influences the simulation of the permafrost active layer thickness and its spatial distribution.

  11. Simulations of seasonal variations of stable water isotopes in land surface process model CLM

    Institute of Scientific and Technical Information of China (English)

    ZHANG XinPing; WANG XiaoYun; YANG ZongLiang; NIU GuoYue; Xie ZiChu

    2009-01-01

    In this study, we simulated and analyzed the monthly variations of stable water isotopes in different reservoirs at Manaus, Brazil, using the Community Land Model (CLM) that incorporates stable isotopic effects as a diagnostic tool for understanding stable water isotopic processes, filling the observational data gaps and predicting hydrometeorological processes. The simulation results show that the δO values in precipitation, vapor and surface runoff have distinct seasonality with the marked negative correlations with corresponding water amount. Compared with the survey results by the International Atomic Energy Agency (IAEA) in co-operation with the World Meteorological Organization (WMO), the simulations by CLM reveal the similar temporal distributions of the δO in precipitation. Moreover, the simulated amount effect between monthly δO and monthly precipitation amount, and MWL (meteoric water line) are all close to the measured values. However, the simulated seasonal difference in the δO in precipitation is distinctly smaller than observed one, and the simulated temporal distribution of the 8180 in precipitation displays the ideal bimodal seasonality rather than the observed single one. These mismatches are possibly related to the simulation capacity and the veracity in forcing data.

  12. Impact of Rain Snow Threshold Temperature on Snow Depth Simulation in Land Surface and Regional Atmospheric Models

    Institute of Scientific and Technical Information of China (English)

    WEN Lijuan; Nidhi NAGABHATLA; L(U) Shihua; Shih-Yu WANG

    2013-01-01

    This study investigates the impact of rain snow threshold (RST) temperatures on snow depth simulation using the Community Land Model (CLM) and the Weather Research and Forecasting model (WRF coupled with the CLM and hereafter referred to as WRF_CLM),and the difference in impacts.Simulations were performed from 17 December 1994 to 30 May 1995 in the French Alps.Results showed that both the CLM and the WRF_CLM were able to represent a fair simulation of snow depth with actual terrain height and 2.5℃ RST temperature.When six RST methods were applied to the simulation using WRF_CLM,the simulated snow depth was the closest to observations using 2.5℃ RST temperature,followed by that with Pipes',USACE,Kienzle's,Dai's,and 0℃ RST temperature methods.In the case of using CLM,simulated snow depth was the closest to the observation with Dai's method,followed by with USACE,Pipes',2.5℃ RST temperature,Kienzle's,and 0℃ RST temperature method.The snow depth simulation using the WRF_CLM was comparatively sensitive to changes in RST temperatures,because the RST temperature was not only the factor to partition snow and rainfall.In addition,the simulated snow related to RST temperature could induce a significant feedback by influencing the meteorological variables forcing the land surface model in WRF_CLM.In comparison,the above variables did not change with changes in RST in CLM.Impacts of RST temperatures on snow depth simulation could also be influenced by the patterns of temperature and precipitation,spatial resolution,and input terrain heights.

  13. Land Surface Model and Particle Swarm Optimization Algorithm Based on the Model-Optimization Method for Improving Soil Moisture Simulation in a Semi-Arid Region.

    Directory of Open Access Journals (Sweden)

    Qidong Yang

    Full Text Available Improving the capability of land-surface process models to simulate soil moisture assists in better understanding the atmosphere-land interaction. In semi-arid regions, due to limited near-surface observational data and large errors in large-scale parameters obtained by the remote sensing method, there exist uncertainties in land surface parameters, which can cause large offsets between the simulated results of land-surface process models and the observational data for the soil moisture. In this study, observational data from the Semi-Arid Climate Observatory and Laboratory (SACOL station in the semi-arid loess plateau of China were divided into three datasets: summer, autumn, and summer-autumn. By combing the particle swarm optimization (PSO algorithm and the land-surface process model SHAW (Simultaneous Heat and Water, the soil and vegetation parameters that are related to the soil moisture but difficult to obtain by observations are optimized using three datasets. On this basis, the SHAW model was run with the optimized parameters to simulate the characteristics of the land-surface process in the semi-arid loess plateau. Simultaneously, the default SHAW model was run with the same atmospheric forcing as a comparison test. Simulation results revealed the following: parameters optimized by the particle swarm optimization algorithm in all simulation tests improved simulations of the soil moisture and latent heat flux; differences between simulated results and observational data are clearly reduced, but simulation tests involving the adoption of optimized parameters cannot simultaneously improve the simulation results for the net radiation, sensible heat flux, and soil temperature. Optimized soil and vegetation parameters based on different datasets have the same order of magnitude but are not identical; soil parameters only vary to a small degree, but the variation range of vegetation parameters is large.

  14. 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.

  15. NUMERICAL SIMULATIONS OF EFFECTS OF LAND SURFACE PROCESSES ON CLIMATE——IMPLEMENTING OF SSiB IN IAP/LASG AGCM AND ITS PERFORMANCE

    Institute of Scientific and Technical Information of China (English)

    孙岚; 吴国雄; 孙菽芬

    2001-01-01

    This is an investigation of exchanges of energy and water between the atmosphere and the vegetated continents, and the impact of and mechanisms for land surface-atmosphere interactions on hydrological cycle and general circulation by implementing the Simplified Simple Biosphere (SSiB) model in a modified version of IAP/LASG global spectral general model (L9R15 AGCM).This study reveals that the SSiB model produces a better partitioning of the land surface heat and moisture fluxes and its diurnal variations, and also gives the transport of energy and water among atmosphere, vegetation and soil explicitly and realistically. Thus the coupled SSiB-AGCM runs lead to the more conspicuous improvement in the simulated circulation, precipitation, mean water vapor content and its transport, particularly in the Asian monsoon region in the real world than CTL-AGCM runs. It is also pointed out that both the implementation of land surface parameterizations and the variations in land surface into the GOALS model have greatly improved hydrological balance over continents and have a significant impact on the simulated climate,particularly over the massive continents.Improved precipitation recycling model was employed to verify the mechanisms for land surface hydrology parameterizations on hydrological cycle and precipitation climatology in AGCM.It can be argued that the recycling precipitation rate is significantly reduced, particularly in the arid and semi-arid region of the boreal summer hemisphere, coincident with remarkable reduction in evapotranspiration over the continental area. Therefore the coupled SSiB-AGCM runs reduce the bias of too much precipitation over land surface in most AGCMs, thereby bringing the simulated precipitation closer to observations in many continental regions of the world than CTL-AGCM runs.

  16. Hydrogeology and simulation of groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas, 1891-2009

    Science.gov (United States)

    Kasmarek, Mark C.

    2012-01-01

    In cooperation with the Harris–Galveston Subsidence District, Fort Bend Subsidence District, and Lone Star Groundwater Conservation District, the U.S. Geological Survey developed and calibrated the Houston Area Groundwater Model (HAGM), which simulates groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system in Texas from predevelopment (before 1891) through 2009. Withdrawal of groundwater since development of the aquifer system has resulted in potentiometric surface (hydraulic head, or head) declines in the Gulf Coast aquifer system and land-surface subsidence (primarily in the Houston area) from depressurization and compaction of clay layers interbedded in the aquifer sediments.

  17. Can simulations of flux exchanges between the land surface and the atmosphere be improved by a more complex description of soil and plant processes?

    Science.gov (United States)

    Klein, Christian

    2013-04-01

    Can simulations of flux exchanges between the land surface and the atmosphere be improved by a more complex description of soil and plant processes? Christian Klein, Christian Biernath, Peter Hoffmann and Eckart Priesack Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Soil Ecology, Oberschleissheim, Germany christian.klein@helmholtz-muenchen.de, ++ 49 89 3187 3015 Recent studies show, that uncertainties in regional and global climate simulations are partly caused by inadequate descriptions of soil-plant-atmosphere. Therefore, we coupled the soil-plant model system Expert-N to the regional climate and weather forecast model WRF. Key features of the Expert-N model system are the simulation of water flow, heat transfer and solute transport in soils and the transpiration of grassland and forest stands. Particularly relevant for the improvement of regional weather forecast are simulations of the feedback between the land surface and atmosphere, which influences surface temperature, surface pressure and precipitation. The WRF model was modified to optionally select either the land surface model Expert-N or NOAH to simulate the exchange of water and energy fluxes between the land surface and the atmosphere for every single grid cell within the simulation domain. Where the standard land surface model NOAH interpolates monthly LAI input values to simulate interactions between plant and atmosphere Expert-N simulates a dynamic plant growth with respect to water and nutrient availability in the soil. In this way Expert-N can be applied to study the effect of dynamic vegetation growth simulation on regional climate simulation results. For model testing Expert-N was used with two different soil parameterizations. The first parametrization used the USGS soil texture classification and simplifies the soil profile to one horizon (similar to the NOAH model). The second parameterization is based on the German soil texture classification

  18. Geothermal Heat Flux Assessment Using Remote Sensing Land Surface Temperature and Simulated Data. Case Studies at the Kenyan Rift and Yellowstone Geothermal Areas

    Science.gov (United States)

    Romaguera, M.; Vaughan, R. G.; Ettema, J.; Izquierdo-Verdiguier, E.; Hecker, C.; van der Meer, F. D.

    2015-12-01

    In this work we propose an innovative approach to assess the geothermal heat flux anomalies in the regions of the Kenyan Rift and the Yellowstone geothermal areas. The method is based on the land surface temperature (LST) differences obtained between remote sensing data and land surface model simulations. The hypothesis is that the model simulations do not account for the subsurface geothermal heat source in the formulation. Remote sensing of surface emitted radiances is able to detect at least the radiative portion of the geothermal signal that is not in the models. Two methods were proposed to assess the geothermal component of LST (LSTgt) based on the aforementioned hypothesis: a physical model and a data mining approach. The LST datasets were taken from the Land Surface Analysis Satellite Application Facilities products over Africa and the Copernicus Programme for North America, at a spatial resolution of 3-5 km. These correspond to Meteosat Second Generation and Geostationary Operational Environmental Satellite system satellites data respectively. The Weather Research and Forecasting model was used to simulate LST based on atmospheric and surface characteristics using the Noah land surface model. The analysis was carried out for a period of two months by using nighttime acquisitions. Higher spatial resolution images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer data were also used on the Kenyan area to produce similar outputs employing existing methods. The comparison of the results from both methods and areas illustrated the potential of the data and methodologies for geothermal applications.

  19. A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

    Science.gov (United States)

    Peylin, Philippe; Bacour, Cédric; MacBean, Natasha; Leonard, Sébastien; Rayner, Peter; Kuppel, Sylvain; Koffi, Ernest; Kane, Abdou; Maignan, Fabienne; Chevallier, Frédéric; Ciais, Philippe; Prunet, Pascal

    2016-09-01

    Large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model-data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The

  20. Impact of model developments on present and future simulations of permafrost in a global land-surface model

    Science.gov (United States)

    Chadburn, S. E.; Burke, E. J.; Essery, R. L. H.; Boike, J.; Langer, M.; Heikenfeld, M.; Cox, P. M.; Friedlingstein, P.

    2015-08-01

    There is a large amount of organic carbon stored in permafrost in the northern high latitudes, which may become vulnerable to microbial decomposition under future climate warming. In order to estimate this potential carbon-climate feedback it is necessary to correctly simulate the physical dynamics of permafrost within global Earth system models (ESMs) and to determine the rate at which it will thaw. Additional new processes within JULES, the land-surface scheme of the UK ESM (UKESM), include a representation of organic soils, moss and bedrock and a modification to the snow scheme; the sensitivity of permafrost to these new developments is investigated in this study. The impact of a higher vertical soil resolution and deeper soil column is also considered. Evaluation against a large group of sites shows the annual cycle of soil temperatures is approximately 25 % too large in the standard JULES version, but this error is corrected by the model improvements, in particular by deeper soil, organic soils, moss and the modified snow scheme. A comparison with active layer monitoring sites shows that the active layer is on average just over 1 m too deep in the standard model version, and this bias is reduced by 70 cm in the improved version. Increasing the soil vertical resolution allows the full range of active layer depths to be simulated; by contrast, with a poorly resolved soil at least 50 % of the permafrost area has a maximum thaw depth at the centre of the bottom soil layer. Thus all the model modifications are seen to improve the permafrost simulations. Historical permafrost area corresponds fairly well to observations in all simulations, covering an area between 14 and 19 million km2. Simulations under two future climate scenarios show a reduced sensitivity of permafrost degradation to temperature, with the near-surface permafrost loss per degree of warming reduced from 1.5 million km2 °C-1 in the standard version of JULES to between 1.1 and 1.2 million km2 °C-1

  1. Evaluation of land surface model simulations of evapotranspiration over a 12 year crop succession: impact of the soil hydraulic properties

    Directory of Open Access Journals (Sweden)

    S. Garrigues

    2014-10-01

    Full Text Available Evapotranspiration has been recognized as one of the most uncertain term in the surface water balance simulated by land surface models. In this study, the SURFEX/ISBA-A-gs simulations of evapotranspiration are assessed at local scale over a 12 year Mediterranean crop succession. The model is evaluated in its standard implementation which relies on the use of the ISBA pedotransfer estimates of the soil properties. The originality of this work consists in explicitly representing the succession of crop cycles and inter-crop bare soil periods in the simulations and assessing its impact on the dynamic of simulated and measured evapotranspiration over a long period of time. The analysis focuses on key soil parameters which drive the simulation of evapotranspiration, namely the rooting depth, the soil moisture at saturation, the soil moisture at field capacity and the soil moisture at wilting point. The simulations achieved with the standard values of these parameters are compared to those achieved with the in situ values. The portability of the ISBA pedotransfer functions is evaluated over a typical Mediterranean crop site. Various in situ estimates of the soil parameters are considered and distinct parametrization strategies are tested to represent the evapotranspiration dynamic over the crop succession. This work shows that evapotranspiration mainly results from the soil evaporation when it is continuously simulated over a Mediterranean crop succession. The evapotranspiration simulated with the standard surface and soil parameters of the model is largely underestimated. The deficit in cumulative evapotranspiration amounts to 24% over 12 years. The bias in daily daytime evapotranspiration is −0.24 mm day−1. The ISBA pedotransfer estimates of the soil moisture at saturation and at wilting point are overestimated which explains most of the evapotranspiration underestimation. The overestimation of the soil moisture at wilting point causes the

  2. Evaluation of land surface model simulations of evapotranspiration over a 12 year crop succession: impact of the soil hydraulic properties

    Science.gov (United States)

    Garrigues, S.; Olioso, A.; Calvet, J.-C.; Martin, E.; Lafont, S.; Moulin, S.; Chanzy, A.; Marloie, O.; Desfonds, V.; Bertrand, N.; Renard, D.

    2014-10-01

    Evapotranspiration has been recognized as one of the most uncertain term in the surface water balance simulated by land surface models. In this study, the SURFEX/ISBA-A-gs simulations of evapotranspiration are assessed at local scale over a 12 year Mediterranean crop succession. The model is evaluated in its standard implementation which relies on the use of the ISBA pedotransfer estimates of the soil properties. The originality of this work consists in explicitly representing the succession of crop cycles and inter-crop bare soil periods in the simulations and assessing its impact on the dynamic of simulated and measured evapotranspiration over a long period of time. The analysis focuses on key soil parameters which drive the simulation of evapotranspiration, namely the rooting depth, the soil moisture at saturation, the soil moisture at field capacity and the soil moisture at wilting point. The simulations achieved with the standard values of these parameters are compared to those achieved with the in situ values. The portability of the ISBA pedotransfer functions is evaluated over a typical Mediterranean crop site. Various in situ estimates of the soil parameters are considered and distinct parametrization strategies are tested to represent the evapotranspiration dynamic over the crop succession. This work shows that evapotranspiration mainly results from the soil evaporation when it is continuously simulated over a Mediterranean crop succession. The evapotranspiration simulated with the standard surface and soil parameters of the model is largely underestimated. The deficit in cumulative evapotranspiration amounts to 24% over 12 years. The bias in daily daytime evapotranspiration is -0.24 mm day-1. The ISBA pedotransfer estimates of the soil moisture at saturation and at wilting point are overestimated which explains most of the evapotranspiration underestimation. The overestimation of the soil moisture at wilting point causes the underestimation of

  3. ORCHIDEE-SRC v1.0: an extension of the land surface model ORCHIDEE for simulating short rotation coppice poplar plantations

    OpenAIRE

    De Groote, T.; D. Zona; Broeckx, L. S.; Verlinden, M. S.; Luyssaert, S.; Bellassen, V.; Vuichard, N.; R. Ceulemans; Gobin, A.; Janssens, I. A.

    2015-01-01

    Modelling biomass production and the environmental impact of short rotation coppice (SRC) plantations is necessary for planning their deployment, as they are becoming increasingly important for global energy production. This paper describes the modification of the widely used land surface model ORCHIDEE for stand-scale simulations of SRC plantations. The model uses weather data, soil texture and species-specific parameters to predict the aboveground (harvestable) biomass...

  4. Using a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to Simulate the Interaction between Land Surface Processes and Atmospheric Boundary Layer in Semi-Arid Regions

    Institute of Scientific and Technical Information of China (English)

    刘树华; 乐旭; 胡非; 刘辉志

    2004-01-01

    This paper uses a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to study the interaction between land surface and atmospheric boundary layer processes. The scheme is composed of two main parts:atmospheric boundary layer processes and land surface processes. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feasibility of the model is well proved in this paper. The numerical simulation results from MSPAS show good agreement with reality. The scheme is used to obtain reasonable simulations for diurnal variations of heat balance, potential temperature of boundary layer, and wind field, and spatial distributions of temperature, specific humidity, vertical velocity,turbulence kinetic energy, and turbulence exchange coefficient over desert and oasis. In addition, MSPAS is used to simulate the interaction between desert and oasis at night, and again it obtains reasonable results.This indicates that MSPAS can be used to study the interaction between land surface processes and the atmospheric boundary layer over various underlying surfaces and can be extended for regional climate and numerical weather prediction study.

  5. Simulating the carbon, water, energy budgets and greenhouse gas emissions of arctic soils with the ISBA land surface model

    Science.gov (United States)

    Morel, Xavier; Decharme, Bertrand; Delire, Christine

    2017-04-01

    Permafrost soils and boreal wetlands represent an important challenge for future climate simulations. Our aim is to be able to correctly represent the most important thermal, hydrologic and carbon cycle related processes in boreal areas with our land surface model ISBA (Masson et al, 2013). This is particularly important since ISBA is part of the CNRM-CM Climate Model (Voldoire et al, 2012), that is used for projections of future climate changes. To achieve this goal, we replaced the one layer original soil carbon module based on the CENTURY model (Parton et al, 1987) by a multi-layer soil carbon module that represents C pools and fluxes (CO2 and CH4), organic matter decomposition, gas diffusion (Khvorostyanov et al., 2008), CH4 ebullition and plant-mediated transport, and cryoturbation (Koven et al., 2009). The carbon budget of the new model is closed. The soil carbon module is tightly coupled to the ISBA energy and water budget module that solves the one-dimensional Fourier law and the mixed-form of the Richards equation explicitly to calculate the time evolution of the soil energy and water budgets (Boone et al., 2000; Decharme et al. 2011). The carbon, energy and water modules are solved using the same vertical discretization. Snowpack processes are represented by a multi-layer snow model (Decharme et al, 2016). We test this new model on a pair of monitoring sites in Greenland, one in a permafrost area (Zackenberg Ecological Research Operations, Jensen et al, 2014) and the other in a region without permafrost (Nuuk Ecological Research Operations, Jensen et al, 2013); both sites are established within the GeoBasis part of the Greenland Ecosystem Monitoring (GEM) program. The site of Chokurdakh, in a permafrost area of Siberia is is our third studied site. We test the model's ability to represent the physical variables (soil temperature and water profiles, snow height), the energy and water fluxes as well as the carbon dioxyde and methane fluxes. We also test the

  6. The groundwater-land-surface-atmosphere connection: soil moisture effects on the atmospheric boundary layer in fully-coupled simulations

    Energy Technology Data Exchange (ETDEWEB)

    Maxwell, R M; Chow, F K; Kollet, S J

    2007-02-02

    This study combines a variably-saturated groundwater flow model and a mesoscale atmospheric model to examine the effects of soil moisture heterogeneity on atmospheric boundary layer processes. This parallel, integrated model can represent spatial variations in land-surface forcing driven by three-dimensional (3D) atmospheric and subsurface components. The development of atmospheric flow is studied in a series of idealized test cases with different initial soil moisture distributions generated by an offline spin-up procedure or interpolated from a coarse-resolution dataset. These test cases are performed with both the fully-coupled model (which includes 3D groundwater flow and surface water routing) and the uncoupled atmospheric model. The effects of the different soil moisture initializations and lateral subsurface and surface water flow are seen in the differences in atmospheric evolution over a 36-hour period. The fully-coupled model maintains a realistic topographically-driven soil moisture distribution, while the uncoupled atmospheric model does not. Furthermore, the coupled model shows spatial and temporal correlations between surface and lower atmospheric variables and water table depth. These correlations are particularly strong during times when the land surface temperatures trigger shifts in wind behavior, such as during early morning surface heating.

  7. Modelling land surface - atmosphere interactions

    DEFF Research Database (Denmark)

    Rasmussen, Søren Højmark

    related to inaccurate land surface modelling, e.g. enhanced warm bias in warm dry summer months. Coupling the regional climate model to a hydrological model shows the potential of improving the surface flux simulations in dry periods and the 2 m air temperature in general. In the dry periods......The study is investigates modelling of land surface – atmosphere interactions in context of fully coupled climatehydrological model. With a special focus of under what condition a fully coupled model system is needed. Regional climate model inter-comparison projects as ENSEMBLES have shown bias...... representation of groundwater in the hydrological model is found to important and this imply resolving the small river valleys. Because, the important shallow groundwater is found in the river valleys. If the model does not represent the shallow groundwater then the area mean surface flux calculation...

  8. Study on a Dynamic Vegetation Model for Simulating Land Surface Flux Exchanges at Lien-Hua-Chih Flux Observation Site in Taiwan

    Science.gov (United States)

    Yeh, T. Y.; Li, M. H.; Chen, Y. Y.; Ryder, J.; McGrath, M.; Otto, J.; Naudts, K.; Luyssaert, S.; MacBean, N.; Bastrikov, V.

    2016-12-01

    Dynamic vegetation model ORCHIDEE (Organizing Carbon and Hydrology In Dynamic EcosystEms) is a state of art land surface component of the IPSL (Institute Pierre Simon Laplace) Earth System Model. It has been used world-wide to investigate variations of water, carbon, and energy exchanges between the land surface and the atmosphere. In this study we assessed the applicability of using ORCHIDEE-CAN, a new feature with 3-D CANopy structure (Naudts et al., 2015; Ryder et al., 2016), to simulate surface fluxes measured at tower-based eddy covariance fluxes at the Lien-Hua-Chih experimental watershed in Taiwan. The atmospheric forcing including radiation, air temperature, wind speed, and the dynamics of vertical canopy structure for driving the model were obtained from the observations site. Suitable combinations of default plant function types were examined to meet in-situ observations of soil moisture and leaf area index from 2009 to 2013. The simulated top layer soil moisture was ranging from 0.1 to 0.4 and total leaf area was ranging from 2.2 to 4.4, respectively. A sensitivity analysis was performed to investigate the sensitive of model parameters and model skills of ORCHIDEE-CAN on capturing seasonal variations of surface fluxes. The most sensitive parameters were suggested and calibrated by an automatic data assimilation tool ORCHDAS (ORCHIDEE Data Assimilation Systems; http://orchidas.lsce.ipsl.fr/). Latent heat, sensible heat, and carbon fluxes simulated by the model were compared with long-term observations at the site. ORCHIDEE-CAN by making use of calibrated surface parameters was used to study variations of land-atmosphere interactions on a variety of temporal scale in associations with changes in both land and atmospheric conditions. Ref: Naudts, K., et al.,: A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes, Geoscientific Model Development, 8, 2035-2065, doi:10.5194/gmd-8

  9. A GRACE-Streamflow Land Surface Model Calibration Approach for Improved Baseflow and Water Table Simulations over the Highly Managed Upper-Nile Basin of East Africa

    Science.gov (United States)

    Nanteza, J.; Lo, M. H.; Wu, R. J.; Thomas, B. F.; Famiglietti, J. S.

    2015-12-01

    Land surface models (LSMs) are useful tools for understanding behaviors of land hydrologic variables at different time and spatial scales. LSM outputs, however, are marked with great uncertainties resulting from the simplified assumptions on the parameterization and processes of the land surface and a poor representation of both the natural and anthropogenic controls on the system. The Upper-Nile basin, over Uganda, Kenya and Tanzania, is one region that is characteristic of significant human controls on streamflow, including Lake Victoria releases. The river Nile flow from Lake Victoria follows apriori rating curves that are not simulated by LSMs. Apart from management practices; the huge storage volume of Lake Victoria also modifies the seasonal characteristics of the Upper-Nile discharge, creating small seasonal variations in stream flow. In this study we calibrate several critical parameters in the Community Land Model (CLM.v4) in a multiobjective framework using total water storage anomalies (∆TWS) from GRACE, observed total runoff (Q) and estimated baseflow (BF) over the Upper-Nile basin. The goal is to improve the CLM parameters so that the model simulates the agreed curve (apriori) streamflow and baseflow with a better accuracy. We demonstrate the significance of improved parametrization by comparing model results of ∆TWS, Q and BF with a combination of insitu and estimated observations. Preliminary results based on RMSE statistics show that with calibration, simulations of ∆TWS, Q and BF achieve higher performance. Further, an improvement in the model's capacity to simulate the water table depth is also evident with the calibration. Such results provide a basis for using CLM for other hydrologic experiments that could guide water resources management in this highly managed basin.

  10. ORCHIDEE-SRC v1.0: an extension of the land surface model ORCHIDEE for simulating short rotation coppice poplar plantations

    Science.gov (United States)

    De Groote, T.; Zona, D.; Broeckx, L. S.; Verlinden, M. S.; Luyssaert, S.; Bellassen, V.; Vuichard, N.; Ceulemans, R.; Gobin, A.; Janssens, I. A.

    2015-05-01

    Modelling biomass production and the environmental impact of short rotation coppice (SRC) plantations is necessary for planning their deployment, as they are becoming increasingly important for global energy production. This paper describes the modification of the widely used land surface model ORCHIDEE for stand-scale simulations of SRC plantations. The model uses weather data, soil texture and species-specific parameters to predict the aboveground (harvestable) biomass production, as well as carbon and energy fluxes of an SRC plantation. Modifications to the model were made to the management, growth, and allocation modules of ORCHIDEE. The modifications presented in this paper were evaluated using data from two Belgian poplar-based SRC sites, for which multiple measurements and meteorological data were available. Biomass yield data were collected from 23 other sites across Europe and compared to 22 simulations across a comparable geographic range. The simulations show that the model predicts very well aboveground (harvestable) biomass production (within measured ranges), ecosystem photosynthesis (R2 = 0.78, NRMSE = 0.064, PCC = 0.89) and ecosystem respiration (R2 = 0.95, NRMSE = 0.078 PCC = 0.91). Also soil temperature and soil moisture are simulated adequately, but due to the simplicity of the soil moisture simulation, there are some discrepancies, which also influence the simulation of the latent heat flux. Overall, the extended model, ORCHIDEE-SRC, proved to be a tool suitable for predicting biomass production of SRC plantations.

  11. The Role of Surface Energy Exchange for Simulating Wind Inflow: An Evaluation of Multiple Land Surface Models in WRF for the Southern Great Plains Site Field Campaign Report

    Energy Technology Data Exchange (ETDEWEB)

    Wharton, Sonia [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Simpson, Matthew [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Osuna, Jessica [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Newman, Jennifer [National Renewable Energy Lab. (NREL), Golden, CO (United States); Biraud, Sebastien [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-05-01

    The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. The LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.

  12. A reduced-order modeling approach to represent subgrid-scale hydrological dynamics for land-surface simulations: application in a polygonal tundra landscape

    Science.gov (United States)

    Pau, G. S. H.; Bisht, G.; Riley, W. J.

    2014-09-01

    Existing land surface models (LSMs) describe physical and biological processes that occur over a wide range of spatial and temporal scales. For example, biogeochemical and hydrological processes responsible for carbon (CO2, CH4) exchanges with the atmosphere range from the molecular scale (pore-scale O2 consumption) to tens of kilometers (vegetation distribution, river networks). Additionally, many processes within LSMs are nonlinearly coupled (e.g., methane production and soil moisture dynamics), and therefore simple linear upscaling techniques can result in large prediction error. In this paper we applied a reduced-order modeling (ROM) technique known as "proper orthogonal decomposition mapping method" that reconstructs temporally resolved fine-resolution solutions based on coarse-resolution solutions. We developed four different methods and applied them to four study sites in a polygonal tundra landscape near Barrow, Alaska. Coupled surface-subsurface isothermal simulations were performed for summer months (June-September) at fine (0.25 m) and coarse (8 m) horizontal resolutions. We used simulation results from three summer seasons (1998-2000) to build ROMs of the 4-D soil moisture field for the study sites individually (single-site) and aggregated (multi-site). The results indicate that the ROM produced a significant computational speedup (> 103) with very small relative approximation error (constructed at different scales together hierarchically, this method has the potential to efficiently increase the resolution of land models for coupled climate simulations to spatial scales consistent with mechanistic physical process representation.

  13. Evaluation of global continental hydrology as simulated by the Land-surface Processes and eXchanges Dynamic Global Vegetation Model

    Directory of Open Access Journals (Sweden)

    S. J. Murray

    2011-01-01

    Full Text Available Global freshwater resources are sensitive to changes in climate, land cover and population density and distribution. The Land-surface Processes and eXchanges Dynamic Global Vegetation Model is a recent development of the Lund-Potsdam-Jena model with improved representation of fire-vegetation interactions. It allows simultaneous consideration of the effects of changes in climate, CO2 concentration, natural vegetation and fire regime shifts on the continental hydrological cycle. Here the model is assessed for its ability to simulate large-scale spatial and temporal runoff patterns, in order to test its suitability for modelling future global water resources. Comparisons are made against observations of streamflow and a composite dataset of modelled and observed runoff (1986–1995 and are also evaluated against soil moisture data and the Palmer Drought Severity Index. The model captures the main features of the geographical distribution of global runoff, but tends to overestimate runoff in much of the Northern Hemisphere (where this can be somewhat accounted for by freshwater consumption and the unrealistic accumulation of the simulated winter snowpack in permafrost regions and the southern tropics. Interannual variability is represented reasonably well at the large catchment scale, as are seasonal flow timings and monthly high and low flow events. Further improvements to the simulation of intra-annual runoff might be achieved via the addition of river flow routing. Overestimates of runoff in some basins could likely be corrected by the inclusion of transmission losses and direct-channel evaporation.

  14. Hydrological land surface modelling

    DEFF Research Database (Denmark)

    Ridler, Marc-Etienne Francois

    to imperfect model forecasts. It remains a crucial challenge to account for system uncertainty, so as to provide model outputs accompanied by a quantified confidence interval. Properly characterizing and reducing uncertainty opens-up the opportunity for risk-based decision-making and more effective emergency...... and disaster management. The objective of this study is to develop and investigate methods to reduce hydrological model uncertainty by using supplementary data sources. The data is used either for model calibration or for model updating using data assimilation. Satellite estimates of soil moisture and surface...... temperature are explored in a multi-objective calibration experiment to optimize the parameters in a SVAT model in the Sahel. The two satellite derived variables were effective at constraining most land-surface and soil parameters. A data assimilation framework is developed and implemented with an integrated...

  15. ORCHIDEE-SRC v1.0: an extension of the land surface model ORCHIDEE for simulating short rotation coppice poplar plantations

    Directory of Open Access Journals (Sweden)

    T. De Groote

    2014-06-01

    Full Text Available Modelling biomass production and the environmental impact of short rotation coppice (SRC plantations is necessary for planning their deployment, as they are becoming increasingly important for global energy production. This paper describes the modification of the widely used land surface model ORCHIDEE for stand scale simulations of SRC plantations. The model uses weather data, soil texture and species-specific parameters to predict the aboveground (harvestable biomass production, as well as carbon and energy fluxes of an SRC plantation. Modifications to the model were made to the management, growth, and allocation modules of ORCHIDEE. The modifications presented in this paper were evaluated using data from two poplar based SRC sites. The simulations show that the model performs very well to predict aboveground (harvestable biomass production (within measured ranges, ecosystem photosynthesis (R2 = 0.78, NRMSE = 0.064, PCC = 0.89 and ecosystem respiration (R2 = 0.95, NRMSE = 0.081, PCC = 0.91. Overall, the extended model, ORCHIDEE-SRC, proved to be a tool suitable for predicting biomass production of SRC plantations.

  16. A hydrological prediction system based on the SVS land-surface scheme: efficient calibration of GEM-Hydro for streamflow simulation over the Lake Ontario basin

    Directory of Open Access Journals (Sweden)

    É. Gaborit

    2017-09-01

    Full Text Available This work explores the potential of the distributed GEM-Hydro runoff modeling platform, developed at Environment and Climate Change Canada (ECCC over the last decade. More precisely, the aim is to develop a robust implementation methodology to perform reliable streamflow simulations with a distributed model over large and partly ungauged basins, in an efficient manner. The latest version of GEM-Hydro combines the SVS (Soil, Vegetation and Snow land-surface scheme and the WATROUTE routing scheme. SVS has never been evaluated from a hydrological point of view, which is done here for all major rivers flowing into Lake Ontario. Two established hydrological models are confronted to GEM-Hydro, namely MESH and WATFLOOD, which share the same routing scheme (WATROUTE but rely on different land-surface schemes. All models are calibrated using the same meteorological forcings, objective function, calibration algorithm, and basin delineation. GEM-Hydro is shown to be competitive with MESH and WATFLOOD: the NSE  √  (Nash–Sutcliffe criterion computed on the square root of the flows is for example equal to 0.83 for MESH and GEM-Hydro in validation on the Moira River basin, and to 0.68 for WATFLOOD. A computationally efficient strategy is proposed to calibrate SVS: a simple unit hydrograph is used for routing instead of WATROUTE. Global and local calibration strategies are compared in order to estimate runoff for ungauged portions of the Lake Ontario basin. Overall, streamflow predictions obtained using a global calibration strategy, in which a single parameter set is identified for the whole basin of Lake Ontario, show accuracy comparable to the predictions based on local calibration: the average NSE  √  in validation and over seven subbasins is 0.73 and 0.61, respectively for local and global calibrations. Hence, global calibration provides spatially consistent parameter values, robust performance at gauged locations, and reduces the

  17. Effect of explicit urban land surface representation on the simulation of the 26 July 2005 heavy rain event over Mumbai, India

    Directory of Open Access Journals (Sweden)

    M. Lei

    2008-05-01

    Full Text Available We investigate whether explicit representation of the urban land surface improves the simulation of the record-breaking 24-h heavy rain event that occurred over Mumbai, India on 26 July 2005 as the event has been poorly simulated by operational weather forecasting models. We coupled and conducted experiments using the Regional Atmosphere modeling system (RAMS 4.3, with and without an explicit urban energy balance model-town energy budget (TEB to study the role of urban land – atmosphere interactions in modulating the heavy rain event over the Indian monsoon region. The impact of including an explicit urban energy balance on surface thermodynamic, boundary layer, and circulation changes are analyzed. The results indicate that even for this synoptically active rainfall event, the vertical wind and precipitation are significantly influenced by urbanization, and the effect is more significant during the storm initiation. Interestingly, precipitation in the upwind region of Mumbai city is increased in the simulation, possibly as a feedback from the sea breeze – urban landscape convergence. We find that even with the active monsoon, the representation of urbanization contributes to local heavy precipitation and mesoscale precipitation distribution over the Indian monsoon region. Additional experiments within a statistical dynamical framework show that an urban model by itself is not the dominant factor for the enhanced rainfall for Mumbai heavy rain event; the combination of updated SST fields using Tropical Rainfall Measurement Mission (TRMM data with the detailed representation of urban heat island (UHI simulated by the TEB/urban model created realistic gradients that successfully maintained the convergence zone over Mumbai. Further research will require more detailed morphology data for simulating weather events in such urban regions. The results suggest that urbanization can significantly contribute to extremes in monsoonal rain events that

  18. Effect of explicit urban land surface representation on the simulation of the 26 July 2005 heavy rain event over Mumbai, India

    Directory of Open Access Journals (Sweden)

    M. Lei

    2008-10-01

    Full Text Available We investigate whether explicit representation of the urban land surface improves the simulation of the record-breaking 24-h heavy rain event that occurred over Mumbai, India on 26 July 2005 as the event has been poorly simulated by operational weather forecasting models. We conducted experiments using the Regional Atmosphere modeling system (RAMS 4.3, coupled with and without explicit urban energy balance model-town energy budget (TEB to study the role of urban land – atmosphere interactions in modulating the heavy rain event over the Indian monsoon region. The impact of including an explicit urban energy balance on surface thermodynamic, boundary layer, and circulation changes are analyzed. The results indicate that even for this synoptically active rainfall event, the vertical wind and precipitation are significantly influenced by heterogeneity in surface temperatures due to urbanization, and the effect is more significant during the storm initiation. Interestingly, precipitation in the upwind region of Mumbai city is increased in the simulation, possibly as a feedback from the sea breeze – urban landscape convergence. We find that even with the active monsoon, the representation of urbanization contributes to local heavy precipitation and mesoscale precipitation distribution over the Indian monsoon region. Additional experiments within a statistical dynamical framework show that an urban model by itself is not the dominant factor for the enhanced rainfall for a Mumbai heavy rain event; the combination of updated SST fields using Tropical Rainfall Measurement Mission (TRMM data with the detailed representation of urban effects simulated by the TEB model created realistic gradients that successfully maintained the convergence zone over Mumbai. Further research will require more detailed morphology data for simulating weather events in such urban regions. The results suggest that urbanization can significantly contribute to extremes in

  19. Comparison of Satellite-Derived TOA Shortwave Clear-Sky Fluxes to Estimates from GCM Simulations Constrained by Satellite Observations of Land Surface Characteristics

    Science.gov (United States)

    Anantharaj, Valentine G.; Nair, Udaysankar S.; Lawrence, Peter; Chase, Thomas N.; Christopher, Sundar; Jones, Thomas

    2010-01-01

    Clear-sky, upwelling shortwave flux at the top of the atmosphere (S(sub TOA raised arrow)), simulated using the atmospheric and land model components of the Community Climate System Model 3 (CCSM3), is compared to corresponding observational estimates from the Clouds and Earth's Radiant Energy System (CERES) sensor. Improvements resulting from the use of land surface albedo derived from Moderate Resolution Imaging Spectroradiometer (MODIS) to constrain the simulations are also examined. Compared to CERES observations, CCSM3 overestimates global, annual averaged S(sub TOA raised arrow) over both land and oceans. However, regionally, CCSM3 overestimates S(sub TOA raised arrow) over some land and ocean areas while underestimating it over other sites. CCSM3 underestimates S(sub TOA raised arrow) over the Saharan and Arabian Deserts and substantial differences exist between CERES observations and CCSM3 over agricultural areas. Over selected sites, after using groundbased observations to remove systematic biases that exist in CCSM computation of S(sub TOA raised arrow), it is found that use of MODIS albedo improves the simulation of S(sub TOA raised arrow). Inability of coarse resolution CCSM3 simulation to resolve spatial heterogeneity of snowfall over high altitude sites such as the Tibetan Plateau causes overestimation of S(sub TOA raised arrow) in these areas. Discrepancies also exist in the simulation of S(sub TOA raised arrow) over ocean areas as CCSM3 does not account for the effect of wind speed on ocean surface albedo. This study shows that the radiative energy budget at the TOA is improved through the use of MODIS albedo in Global Climate Models.

  20. Improved simulation of fire-vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX-Mv1)

    Science.gov (United States)

    Kelley, D. I.; Harrison, S. P.; Prentice, I. C.

    2014-10-01

    The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed

  1. Impact of Spin-up Forcing on Vegetation States Simulated by a Dynamic Global Vegetation Model Coupledwith a Land Surface Model

    Institute of Scientific and Technical Information of China (English)

    LI Fang; ZENG Xiaodong; SONG Xiang; TIAN Dongxiao; SHAO Pu; ZHANG Dongling

    2011-01-01

    A dynamic global vegetation model (DGVM) coupled with a land surface model (LSM) is generally initialized using a spin-up process to derive a physically-consistent initial condition. Spin-up forcing, which is the atmospheric forcing used to drive the coupled model to equilibrium solutions in the spin-up process,varies across earlier studies. In the present study, the impact of the spin-up forcing in the initialization stage on the fractional coverages (FCs) of plant functional type (PFT) in the subsequent simulation stage are assessed in seven classic climate regions by a modified Community Land Model's Dynamic Global Vegetation Model (CLM-DGVM). Results show that the impact of spin-up forcing is considerable in all regions except the tropical rainforest climate region (TR) and the wet temperate climate region (WM). In the tropical monsoon climate region (TM), the TR and TM transition region (TR-TM), the dry temperate climate region (DM), the highland climate region (H), and the boreal forest climate region (BF), where FCs are affected by climate non-negligibly, the discrepancies in initial FCs, which represent long-term cumulative response of vegetation to different climate anomalies, are large. Moreover, the large discrepancies in initial FCs usually decay slowly because there are trees or shrubs in the five regions. The intrinsic growth timescales of FCs for tree PFTs and shrub PFTs are long, and the variation of FCs of tree PFTs or shrub PFTs can affect that of grass PFTs.

  2. Evaluation of land surface model simulations of evapotranspiration over a 12-year crop succession: impact of soil hydraulic and vegetation properties

    Science.gov (United States)

    Garrigues, S.; Olioso, A.; Calvet, J. C.; Martin, E.; Lafont, S.; Moulin, S.; Chanzy, A.; Marloie, O.; Buis, S.; Desfonds, V.; Bertrand, N.; Renard, D.

    2015-07-01

    Evapotranspiration has been recognized as one of the most uncertain terms in the surface water balance simulated by land surface models. In this study, the SURFEX/ISBA-A-gs (Interaction Sol-Biosphere-Atmosphere) simulations of evapotranspiration are assessed at the field scale over a 12-year Mediterranean crop succession. The model is evaluated in its standard implementation which relies on the use of the ISBA pedotransfer estimates of the soil properties. The originality of this work consists in explicitly representing the succession of crop cycles and inter-crop bare soil periods in the simulations and assessing its impact on the dynamics of simulated and measured evapotranspiration over a long period of time. The analysis focuses on key parameters which drive the simulation of ET, namely the rooting depth, the soil moisture at saturation, the soil moisture at field capacity and the soil moisture at wilting point. A sensitivity analysis is first conducted to quantify the relative contribution of each parameter on ET simulation over 12 years. The impact of the estimation method used to retrieve the soil parameters (pedotransfer function, laboratory and field methods) on ET is then analysed. The benefit of representing the variations in time of the rooting depth and wilting point is evaluated. Finally, the propagation of uncertainties in the soil parameters on ET simulations is quantified through a Monte Carlo analysis and compared with the uncertainties triggered by the mesophyll conductance which is a key above-ground driver of the stomatal conductance. This work shows that evapotranspiration mainly results from the soil evaporation when it is continuously simulated over a Mediterranean crop succession. This results in a high sensitivity of simulated evapotranspiration to uncertainties in the soil moisture at field capacity and the soil moisture at saturation, both of which drive the simulation of soil evaporation. Field capacity was proved to be the most

  3. 中国地表太阳辐射资源空间化模拟%Spatial Simulation of China's Land Surface Solar Radiation Resources

    Institute of Scientific and Technical Information of China (English)

    刘玉洁; 潘韬

    2012-01-01

    Based on observed solar radiation and daily range of temperature data from 122 stations during 1981-2010,the Bristow-Campbell radiation model was validated and calibrated in China's eight natural regions separately.Spatial pattern of the astronomical radiation was calculated by meteorological model through geographic information platform.Gridded maximum and minimum average temperature data was achieved using PRISM model.Then the astronomical radiation and temperature data were inputted into the parameterized Bristow-Campbell model,and the spatialization process was realized.Based on Stefan-Boltzmann Law,the national long-wave radiation balance was calculated,and then inputted into the solar radiation balance equation.After that,the spatial pattern of China's land surface solar radiation balance was simulated.Results show that Bristow-Campbell model can be well used to estimate China's solar radiation after calibration and validation.Bristow-Campbell solar radiation estimation model coupling with gridded meteorological data is an effective way for the spatial simulation of solar radiation resources.The spatial pattern of China's land surface solar radiation balance shows that the high-value area is in the Tibetan Plateau with over 9000 MJ·m^-2 each year.The total radiation balance in the eastern region is lower than the western where the northeastern region is slightly higher than Zhejiang and Fujian provinces.Sichuan and Guizhou are the low areas where the average radiation balance is about 2000 MJ·m^-2.%基于1981—2010年全国122个气象台站的太阳辐射和气温日较差观测数据,将Bristow-Campbell太阳辐射估算模型在中国八大自然区分别进行了参数校正和验证;利用地理信息空间分析平台,采用PRISM模型对中国区域平均最高与最低气温空间化的结果,将其输入Bristow-Campbell模型,实现太阳总辐射的空间栅格化模拟;通过斯忒藩-玻耳兹曼定律计算全国地表长波辐射平

  4. Comment on "Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics"

    Science.gov (United States)

    A recently published meteorology and air quality modeling study has several serious deficiencies deserving comment. The study uses the weather research and forecasting/chemistry (WRF/Chem) model to compare and evaluate boundary layer and land surface modeling options. The most se...

  5. Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3

    Science.gov (United States)

    Westermann, S.; Langer, M.; Boike, J.; Heikenfeld, M.; Peter, M.; Etzelmüller, B.; Krinner, G.

    2016-02-01

    Thawing of permafrost in a warming climate is governed by a complex interplay of different processes of which only conductive heat transfer is taken into account in most model studies. However, observations in many permafrost landscapes demonstrate that lateral and vertical movement of water can have a pronounced influence on the thaw trajectories, creating distinct landforms, such as thermokarst ponds and lakes, even in areas where permafrost is otherwise thermally stable. Novel process parameterizations are required to include such phenomena in future projections of permafrost thaw and subsequent climatic-triggered feedbacks. In this study, we present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes. We document the model physics and employed parameterizations for the basis module CryoGrid 3, and compare model results with in situ observations of surface energy balance, surface temperatures, and ground thermal regime from the Samoylov permafrost observatory in NE Siberia. The comparison suggests that CryoGrid 3 can not only model the evolution of the ground thermal regime in the last decade, but also consistently reproduce the chain of energy transfer processes from the atmosphere to the ground. In addition, we demonstrate a simple 1-D parameterization for thaw processes in permafrost areas rich in ground ice, which can phenomenologically reproduce both formation of thermokarst ponds and subsidence of the ground following thawing of ice-rich subsurface layers. Long-term simulation from 1901 to 2100 driven by reanalysis data and climate model output demonstrate that the hydrological regime can both accelerate and delay permafrost thawing. If meltwater from thawed ice-rich layers can drain, the ground subsides, as well as the formation of a talik, are delayed. If the meltwater pools at the surface, a pond is formed that enhances heat

  6. Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

    Science.gov (United States)

    Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

    2014-01-01

    Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

  7. Effects of Crop Growth and Development on Land Surface Fluxes

    Institute of Scientific and Technical Information of China (English)

    CHEN Feng; XIE Zhenghui

    2011-01-01

    In this study, the Crop Estimation through Resource and Environment Synthesis model (CERES3.0) was coupled into the Biosphere-Atmosphere Transfer Scheme (BATS), which is called BATS_CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 n2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes.For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China: one by BATS_CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.

  8. Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

    2011-01-01

    Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  9. Land surface Verification Toolkit (LVT – a generalized framework for land surface model evaluation

    Directory of Open Access Journals (Sweden)

    S. V. Kumar

    2012-02-01

    Full Text Available Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS, it supports hydrological data products from non-LIS environments as well. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  10. Land surface Verification Toolkit (LVT – a generalized framework for land surface model evaluation

    Directory of Open Access Journals (Sweden)

    S. V. Kumar

    2012-06-01

    Full Text Available Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS, it supports hydrological data products from non-LIS environments as well. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

  11. Sensitivity Simulation of Heavy Rainfall to Land Surface Characteristics and Ensemble Forecast Test%陆面特征量初始扰动的敏感性及集合预报试验

    Institute of Scientific and Technical Information of China (English)

    王洋; 曾新民; 葛洪彬; 张长卫

    2014-01-01

    The simulation of a heavy rainfall event that occurred in the middle and lower reaches of Yangtze River was conducted to examine the effects of perturbations of land surface variables (soil moisture and soil temperature)and land surface parameter (vegetation fraction)in the ensemble forecast using the Weather Research and Forecasting Model (WRF)Version 3 .2 .1 and National Centers for Environmental Prediction (NCEP)reanalysis data.The results showed that land surface variable (or parameter)perturbations have a large impact on short-term simulation of rainstorm.The time scale that the land surface variable (or pa-rameter)perturbation affects precipitation is lower than 10 h and the smallest time scale is lower than 6 h. From the point of influence mechanism,disturbance of the land surface variables (parameters)changes the surface latent heat flux and sensible heat flux firstly,which has great impact on the local atmospheric tem-perature,pressure,humidity and wind field by the land-atmosphere interaction,and thus affects the inten-sity and distribution of the heavy rainfall.The ensemble average result is better than the control forecast, which is more stable and credible than the single ensemble members.The analysis of the precipitation probability forecast can provide some useful information about the precipitation forecast especially to heavy rainfall.Overall,the initial perturbation of land surface variables and land surface parameter perturbations are significant to the initial ensemble forecast.%提文章利用中尺度模式 Weather Research and Forecasting Model(WRF)3.2.1版本及National Centers for Environ-mental Prediction(NCEP)分析资料,研究了陆面变量(土壤湿度、土壤温度)和陆面参数(植被覆盖率)初始场随机扰动对长江中下游暴雨预报的影响并进行了集合预报试验。试验结果表明,短期暴雨过程对陆面变量(参数)扰动是敏感的;陆面变量(参数)初始场扰

  12. Toward Transfer Functions for Land Surface Phenologies

    Science.gov (United States)

    Henebry, G. M.

    2010-12-01

    A key problem in projecting future landscapes is simulating the associated land surface phenologies (or LSPs). A recent study of land surface models concluded that the representations of crop phenologies among the models diverged sufficiently to impede a useful intercomparison of simulation results from their associated climate models. Grassland phenologies are far more complicated than cropland phenologies due to multiple forcing factors, photosynthetic pathways (C3 vs C4), and spatial heterogeneities in both resource availabilities and land management practices. Furthermore, many tallgrass species (such as switchgrass) are widely distributed across temperature, but not moisture, gradients, resulting in significant ecotypic variation across the species' geographic range. Thus, how feasible is "transplanting" tallgrass LSPs across isotherms—but along isohyets—to simulate a shift in cultivation from maize-soy to switchgrass? Prior work has shown a quadratic model can provide a parsimonious link between a Normalized Difference Vegetation Index (or NDVI) time series and thermal time, measured in terms of accumulated growing degree-days (or AGDD). Moreover, the thermal time to peak NDVI (or TTP) is a simple function of the parameter coefficients of fitted model. I fitted quadratic models to MODIS NDVI and weather station data at multiple sites across the Northern Great Plains over ten growing seasons, 2000-2009. There is a strong latitudinal gradient in TTP that results in part from a quasi-linear gradient in accumulated daylight hours (or ADH) between 30 and 50 degrees north. However, AGDD improves upon ADH by providing sensitivity to the variability of growing season weather. In the quadratic parameter coefficients there is a geographic pattern apparent as a function of TTP, although it is more variable at shorter TTPs. Using these patterns, an LSP transfer function was implemented along a latitudinal transect to simulate switchgrass cultivation in areas now

  13. Integrative inversion of land surface component temperature

    Institute of Scientific and Technical Information of China (English)

    FAN Wenjie; XU Xiru

    2005-01-01

    In this paper, the row winter wheat was selected as the example to study the component temperature inversion method of land surface target in detail. The result showed that the structural pattern of row crop can affect the inversion precision of component temperature evidently. Choosing appropriate structural pattern of row crop can improve the inversion precision significantly. The iterative method combining inverse matrix was a stable method that was fit for inversing component temperature of land surface target. The result of simulation and field experiment showed that the integrative method could remarkably improve the inversion accuracy of the lighted soil surface temperature and the top layer canopy temperature, and enhance inversion stability of components temperature. Just two parameters were sufficient for accurate atmospheric correction of multi-angle and multi-spectral thermal infrared data: atmospheric transmittance and the atmospheric upwelling radiance. If the atmospheric parameters and component temperature can be inversed synchronously, the really and truly accurate atmospheric correction can be achieved. The validation using ATSRII data showed that the method was useful.

  14. On The Reproducibility of Seasonal Land-surface Climate

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J

    2004-10-22

    The sensitivity of the continental seasonal climate to initial conditions is estimated from an ensemble of decadal simulations of an atmospheric general circulation model with the same specifications of radiative forcings and monthly ocean boundary conditions, but with different initial states of atmosphere and land. As measures of the ''reproducibility'' of continental climate for different initial conditions, spatio-temporal correlations are computed across paired realizations of eleven model land-surface variables in which the seasonal cycle is either included or excluded--the former case being pertinent to climate simulation, and the latter to seasonal anomaly prediction. It is found that the land-surface variables which include the seasonal cycle are impacted only marginally by changes in initial conditions; moreover, their seasonal climatologies exhibit high spatial reproducibility. In contrast, the reproducibility of a seasonal land-surface anomaly is generally low, although it is substantially higher in the Tropics; its spatial reproducibility also markedly fluctuates in tandem with warm and cold phases of the El Nino/Southern Oscillation. However, the overall degree of reproducibility depends strongly on the particular land-surface anomaly considered. It is also shown that the predictability of a land-surface anomaly implied by its reproducibility statistics is consistent with what is inferred from more conventional predictability metrics. Implications of these results for climate model intercomparison projects and for operational forecasts of seasonal continental climate also are elaborated.

  15. ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models

    Directory of Open Access Journals (Sweden)

    S. Faroux

    2013-04-01

    Full Text Available The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo. Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover and GLC2000 (Global Land Cover by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography. The leaf area index (LAI from MODIS and normalized difference vegetation index (NDVI from SPOT/Vegetation (a global monitoring system of vegetation yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas and, inside the nature tile, fractions of 12 plant functional types (PFTs representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of

  16. TANGO ARRAY II: Simulations

    Science.gov (United States)

    Bauleo, P.; Bonifazi, C.; Filevich, A.

    The angular and energy resolution of the TANGO Array has been obtained using Monte Carlo simulations. The AIRES code, with the SYBILL hadronic collision package, was used to simulate Extended Air Showers produced by primary cosmic rays (protons and iron nuclei), with energies ranging from 1014 eV to 1018 eV. These data were fed into a realistic code which simulates the response of the detector stations (water ˇCerenkov detectors), including the electronics, pick up noise, and the signal attenuation in the connecting cabling. The trigger stage is taken into account in order to produce estimates of the trigger efficiency of the array and to check the accuracy of the reconstruction codes. This paper describes the simulations performed to obtain the expected behavior of the array, and presents the simulated data. These simulations indicate that the accuracy of the cosmic ray primary energy determination is expected to be ˜ 60 % and the precision in the measurement of the direction of arrival can be estimated as ˜ 4 degrees.

  17. 基于GIS的自适应三维古海面-地面演变模型研究%The study of the adaptive 3D Old Sea Level-Land Surface Change Simulation Model based on GIS

    Institute of Scientific and Technical Information of China (English)

    钟鹤翔; 谢志仁; 闾国年; 袁林旺; 信忠保

    2011-01-01

    本文设计了基于GIS的具有"自适应"功能的三维古海面-地面演变模型.该模型可以动态演绎沿海地区"沧海桑田"的变化景象,并且可以运用历史资料及专家知识,对海面-地面变化模拟结果进行检验,根据检验结果来对模型的一系列控制参数进行自动半自动的修订,然后重新进行海面-地面演变的动态模拟,直到更趋近于真实的历史演变过程,从而实现模型的"自适应"调整.与其他模型相比,该模型具有计算控制相对准确,能够方便的进行反复模拟、验证计算,模型能自动、半自动地控制调整计算参数等的特点.运用该模型对长江三角洲地区一万年来的海面-地面系统的变化进行了反演模拟,取得了较好的模拟结果.%The expression and recognition of geographical environment, the recovery and reappearance of ancient geographical environment have been the focus in some research fields such as geography, cartography, cognitive science and artificial intelligence. As well, virtual geographical environment and the expression of multidimensional spatio-temporal information have become important research directions with the development of GIS. The reconstruction of sea surface change has long been a focus of geography, and in the past years the prediction of sea surface change has also received considerable interest. The recent development of GIS provides the opportunity for the dynamical simulations of sea surface change as well as for its visualizations. It is also an important research direction in the development situation to build the model with functions of forecast, influence and countermeasure, based on the research of the sea level historical change. This model can provide an effective method for sea level change research.In this paper we present an adaptive 3D Old Sea Level-Land Surface Change Simulation Model based on GIS for the above purpose. This model can be used to simulate the old sea levelland

  18. Assessing the influence of groundwater and land surface scheme in the modelling of land surface-atmosphere feedbacks over the FIFE area in Kansas, USA

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Højmark Rasmussen, Søren; Drews, Martin

    2016-01-01

    experiments include five simulations. First MIKE SHE is forced by observed climate data in two versions i) with groundwater at a fixed uniform depth, and ii) with a dynamical groundwater component simulating shallow groundwater conditions in river valleys. iii) In a third simulation MIKE SHE is forced......The land surface-atmosphere interaction is described differently in large scale surface schemes of regional climate models and small scale spatially distributed hydrological models. In particular, the hydrological models include the influence of shallow groundwater on evapotranspiration during dry...... periods where soils are depleted and groundwater is the only water supply. These mechanisms are analysed by combining a distributed hydrological model (MIKE SHE) and a regional climate model (HIRHAM) and comparing simulation results to the FIFE area observation data in Kansas, USA. The numerical...

  19. Advanced microwave forward model for the land surface data assimilation

    Science.gov (United States)

    Park, Chang-Hwan; Pause, Marion; Gayler, Sebastian; Wollschlaeger, Ute; Jackson, Thomas J.; LeDrew, Ellsworth; Behrendt, Andreas; Wulfmeyer, Volker

    2015-04-01

    From local to global scales, microwave remote-sensing techniques can provide temporally and spatially highly resolved observations of land surface properties including soil moisture and temperature as well as the state of vegetation. These variables are critical for agricultural productivity and water resource management. Furthermore, having accurate information of these variables allows us to improve the performances of numerical weather forecasts and climate prediction models. However, it is challenging to translate a measured brightness temperature into the multiple land surface properties because of the inherent inversion problem. In this study, we introduce a novel forward model for microwave remote sensing to resolve this inversion problem and to close the gap between land surface modeling and observations. It is composed of the Noah-MP land surface model as well as new models for the dielectric mixing and the radiative transfer. For developing a realistic forward operator, the land surface model must simulate soil and vegetation processes properly. The Noah-MP land surface model provides an excellent starting point because it contains already a sophisticated soil texture and land cover data set. Soil moisture transport is derived using the Richards equation in combination with a set of soil hydraulic parameters. Vegetation properties are considered using several photosynthesis models with different complexity. The energy balance is closed for the top soil and the vegetation layers. The energy flux becomes more realistic due to including not only the volumetric ratio of land surface properties but also their surface fraction as sub-grid scale information (semitile approach). Dielectric constant is the fundamental link to quantify the land surface properties. Our physical based new dielectric-mixing model is superior to previous calibration and semi-empirical approaches. Furthermore, owing to the consideration of the oversaturated surface dielectric behaviour

  20. Relative Humidity as an Indicator for Cloud Formation over Heterogeneous land surfaces

    NARCIS (Netherlands)

    Heerwaarden, van C.C.; Vilà-Guerau de Arellano, J.

    2008-01-01

    The influence of land surface heterogeneity on potential cloud formation is investigated using relative humidity as an indicator. This is done by performing numerical experiments using a large-eddy simulation model (LES). The land surface in the model was divided into two patches that had the same s

  1. Research on Land Surface Thermal-Hydrologic Exchange in Southern China under Future Climate and Land Cover Scenarios

    Directory of Open Access Journals (Sweden)

    Jianwu Yan

    2013-01-01

    Full Text Available Climate change inevitably leads to changes in hydrothermal circulation. However, thermal-hydrologic exchanging caused by land cover change has also undergone ineligible changes. Therefore, studying the comprehensive effects of climate and land cover changes on land surface water and heat exchanges enables us to well understand the formation mechanism of regional climate and predict climate change with fewer uncertainties. This study investigated the land surface thermal-hydrologic exchange across southern China for the next 40 years using a land surface model (ecosystem-atmosphere simulation scheme (EASS. Our findings are summarized as follows. (i Spatiotemporal variation patterns of sensible heat flux (H and evapotranspiration (ET under the land cover scenarios (A2a or B2a and climate change scenario (A1B are unanimous. (ii Both H and ET take on a single peak pattern, and the peak occurs in June or July. (iii Based on the regional interannual variability analysis, H displays a downward trend (10% and ET presents an increasing trend (15%. (iv The annual average H and ET would, respectively, increase and decrease by about 10% when woodland converts to the cultivated land. Through this study, we recognize that land surface water and heat exchanges are affected greatly by the future climate change as well as land cover change.

  2. Enhancing the representation of subgrid land surface characteristics in land surface models

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2013-03-01

    intensity (Nclass = 18 as it explained the most PFTs and elevation variability among the three subgrid methods. Spatially, the SGC method explained more elevation variability in topography-complex areas and more vegetation variability in flat areas. Furthermore, the variability of both elevation and vegetation explained by the new method was more spatially homogeneous regardless of the model resolutions and computational burdens. The SGC method will be implemented in CLM over the NA continent to assess its impacts on simulating land surface processes.

  3. Toward hyper-resolution land-surface modeling: The effects of fine-scale topography and soil texture on CLM4.0 simulations over the Southwestern U.S.

    Science.gov (United States)

    Singh, R. S.; Reager, J. T.; Miller, N. L.; Famiglietti, J. S.

    2015-04-01

    Increasing computational efficiency and the need for improved accuracy are currently driving the development of "hyper-resolution" land-surface models that can be implemented at continental scales with resolutions of 1 km or finer. Here we report research incorporating fine-scale grid resolutions into the NCAR Community Land Model (CLM v4.0) for simulations at 1, 25, and 100 km resolution using 1 km soil and topographic information. Multiyear model runs were performed over the Southwestern U.S., including the entire state of California and the Colorado River basin. The results show changes in the total amount of CLM-modeled water storage, and changes in the spatial and temporal distributions of water in snow and soil reservoirs, as well as changes in surface fluxes and the energy balance. To inform future model progress and continued development needs and weaknesses, we compare simulation outputs to station and gridded observations of model fields. Although the higher grid-resolution model is not driven by high-resolution forcing, grid resolution changes alone yield significant improvement (reduction in error) between model outputs and observations, where the RMSE decreases by more than 35%, 36%, 34%, and 12% for soil moisture, terrestrial water storage anomaly, sensible heat, and snow water equivalent, respectively. As an additional exercise, we performed a 100 m resolution simulation over a spatial subdomain. Those results indicate that parameters such as drainage, runoff, and infiltration are significantly impacted when hillslope scales of ˜100 m or finer are considered, and we show the ways in which limitations of the current model physics, including no lateral flow between grid cells, may affect model simulation accuracy.

  4. Evaluating the impacts of cumulus, land surface and ocean surface schemes on summertime rainfall simulations over East-to-southeast Asia and the western north Pacific by RegCM4

    Science.gov (United States)

    Li, Yu-Bin; Tam, Chi-Yung; Huang, Wan-Ru; Cheung, Kevin K. W.; Gao, Zhiqiu

    2016-04-01

    This study evaluates the sensitivity of summertime rainfall simulations over East-to-southeast Asia and the western north Pacific in the regional climate model version 4 (RegCM4) to cumulus (including Grell with Arakawa-Schubert type closure, Grell with Fritsch-Chappell type closure, and Emanuel), land surface (Biosphere-atmosphere transfer scheme or BATS, and the community land model or CLM) and ocean surface (referred to as Zeng1, Zeng2 and BATS1e in the model) schemes by running the model with different combinations of these parameterization packages. For each of these experiments, ensemble integration of the model was carried out in the extended boreal summer of May-October from 1998 to 2007. The simulated spatial distribution, intensity and inter-annual variation of the precipitation, latent heat flux, position of the subtropical high and tropical cyclone genesis patterns from these numerical experiments were analyzed. Examinations show that the combination of Emanuel, CLM and Zeng2 (E-C-Z2) yields the best overall results, consistent with the fact that physical mechanisms considered in E-C-Z2 tend to be more comprehensive in comparison with the others. Additionally, the rainfall quantity is found very sensitive to sea surface roughness length, and the reduction of the roughness length constant (from 2 × 10-4 to 5 × 10-5 m) in our modified BATS1e mitigates the drastic overestimation of latent heat flux and rainfall, and is therefore preferable to the default value for simulations in the western north Pacific region in RegCM4.

  5. Improving land surface models with FLUXNET data

    Directory of Open Access Journals (Sweden)

    Y. -P. Wang

    2009-07-01

    Full Text Available There is a growing consensus that land surface models (LSMs that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covariance technique, is a prime source of data for model improvement. Here we outline a multi-stage process for "fusing" (i.e. linking LSMs with FLUXNET data to generate better models with quantifiable uncertainty. First, we describe FLUXNET data availability, and its random and systematic biases. We then introduce methods for assessing LSM model runs against FLUXNET observations in temporal and spatial domains. These assessments are a prelude to more formal model-data fusion (MDF. MDF links model to data, based on error weightings. In theory, MDF produces optimal analyses of the modelled system, but there are practical problems. We first discuss how to set model errors and initial conditions. In both cases incorrect assumptions will affect the outcome of the MDF. We then review the problem of equifinality, whereby multiple combinations of parameters can produce similar model output. Fusing multiple independent and orthogonal data provides a means to limit equifinality. We then show how parameter probability density functions (PDFs from MDF can be used to interpret model validity, and to propagate errors into model outputs. Posterior parameter distributions are a useful way to assess the success of MDF, combined with a determination of whether model residuals are Gaussian. If the MDF scheme provides evidence for temporal variation in parameters, then that is indicative of a critical missing dynamic process. A comparison of parameter PDFs generated with the same model from multiple FLUXNET sites can provide insights into the concept and validity of plant functional types (PFT – we would expect similar parameter

  6. Improving land surface models with FLUXNET data

    Directory of Open Access Journals (Sweden)

    M. Williams

    2009-03-01

    Full Text Available There is a growing consensus that land surface models (LSMs that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covariance technique, is a prime source of data for model improvement. Here we outline a multi-stage process for fusing LSMs with FLUXNET data to generate better models with quantifiable uncertainty. First, we describe FLUXNET data availability, and its random and systematic biases. We then introduce methods for assessing LSM model runs against FLUXNET observations in temporal and spatial domains. These assessments are a prelude to more formal model-data fusion (MDF. MDF links model to data, based on error weightings. In theory, MDF produces optimal analyses of the modelled system, but there are practical problems. We first discuss how to set model errors and initial conditions. In both cases incorrect assumptions will affect the outcome of the MDF. We then review the problem of equifinality, whereby multiple combinations of parameters can produce similar model output. Fusing multiple independent data provides a means to limit equifinality. We then show how parameter probability density functions (PDFs from MDF can be used to interpret model process validity, and to propagate errors into model outputs. Posterior parameter distributions are a useful way to assess the success of MDF, combined with a determination of whether model residuals are Gaussian. If the MDF scheme provides evidence for temporal variation in parameters, then that is indicative of a critical missing dynamic process. A comparison of parameter PDFs generated with the same model from multiple FLUXNET sites can provide insights into the concept and validity of plant functional types (PFT – we would expect similar parameter estimates among sites

  7. Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

    Science.gov (United States)

    Liu, Yongqiang; Mamtimin, Ali; He, Qing

    2014-05-01

    Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

  8. Revising Hydrology of a Land Surface Model

    Science.gov (United States)

    Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

    2015-04-01

    Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.

  9. Modeling Land Surface Phenology Using Earthlight

    Science.gov (United States)

    Henebry, G. M.

    2005-12-01

    Microwave radiometers have long been used in earth observation, but the coarse spatial resolution of the data has discouraged its use in investigations of the vegetated land surface. The Advanced Microwave Scanning Radiometer (AMSR-E) on the Aqua satellite acquires multifrequency observations twice daily (1:30 and 13:30). From these brightness temperatures come two data products relevant to land surface phenology: soil moisture and vegetation water content. Although the nominal spatial resolution of these products is coarse (25 km), the fine temporal sampling allows characterization of the diel variation in surface moisture as contained in the uppermost soil layer and bound in the vegetation canopy. The ephermal dynamics of surficial soil moisture are difficult to validate due to the scale discrepancy between the 625 sq km coverage of a single pixel and the sparse network of weather stations. In contrast, canopy dynamics are more readily validated using finer spatial resolution data products and/or ecoregionalizations. For sites in the North American Great Plains and Northern Eurasia dominated by herbaceous vegetation, I will present land surface phenologies modeled using emitted earthlight and compare them with land surface phenologies modeled using reflected sunlight. I will also explore whether some key climate modes have a significant effect on the microwave-retrieved land surface phenologies.

  10. Remote sensing of land surface phenology

    Science.gov (United States)

    Meier, G.A.; Brown, J.F.

    2014-01-01

    Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

  11. On the Potential Predictability of Seasonal Land-Surface Climate

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J

    2001-10-01

    The chaotic behavior of the continental climate of an atmospheric general circulation model is investigated from an ensemble of decadal simulations with common specifications of radiative forcings and monthly ocean boundary conditions, but different initial states of atmosphere and land. The variability structures of key model land-surface processes appear to agree sufficiently with observational estimates to warrant detailed examination of their predictability on seasonal time scales. This predictability is inferred from several novel measures of spatio-temporal reproducibility applied to eleven model variables. The reproducibility statistics are computed for variables in which the seasonal cycle is included or excluded, the former case being most pertinent to climate model simulations, and the latter to predictions of the seasonal anomalies. Because the reproducibility metrics in the latter case are determined in the context of a ''perfectly'' known ocean state, they are properly viewed as estimates of the potential predictability of seasonal climate. Inferences based on these reproducibility metrics are shown to be in general agreement with those derived from more conventional measures of potential predictability. It is found that the land-surface variables which include the seasonal cycle are impacted only marginally by changes in initial conditions; moreover, their seasonal climatologies exhibit high spatial reproducibility. In contrast, the reproducibility of a seasonal land-surface anomaly is generally low, although it is considerably higher in the Tropics; its spatial reproducibility also fluctuates in tandem with warm and cold phases of the El Nino/Southern Oscillation phenomenon. However, the detailed sensitivities to initial conditions depend somewhat on the land-surface process: pressure and temperature anomalies exhibit the highest temporal reproducibilities, while hydrological and turbulent flux anomalies show the highest spatial

  12. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  13. Intercomparison of the Performance of CLM3, NOAH, RUC, and STD Land Surface Schemes in the Weather and Research Forecasting Model

    Science.gov (United States)

    Jin, J.; Miller, N.

    2007-12-01

    The Community Land Model version 3 (CLM3) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 2.2. The performance of WRF-CLM3 in predicting regional climate was quantitatively compared with that of WRF coupled to the soil thermal diffusion (STD), Rapid Update Cycle, and NOAH Land Surface Schemes. These land surface schemes represent a range of complexity within land-surface schemes. CLM3 is the most sophisticated model, with detailed snow and vegetation processes. The STD scheme is oversimplified, which only calculates soil temperature and neglects vegetation and snow physics. The RUC and NOAH schemes are intermediate in the detail, and the major deference between them is that RUC has a multi-layer snow scheme, and Noah has a single snow layer lumped with the topmost soil layer. WRF was driven by the National Centers for Environmental Prediction Reanalysis data II with each of these land surface schemes for one-year simulations over the period, 1 October 1995 to 30 September 1996, resulting in four one-year simulations for intercomparison. Each simulation has 30km-10km two-way nested domains. The 30 km domain includes the western U.S. and eastern Pacific, and the inner domain includes California and parts of Nevada, Oregon, and the eastern Pacific. Our analysis shows that WRF-CLM3 outperforms WRF-RUC, WRF-NOAH, and WRF-STD in simulating temperature and snow when compared with observations. The WRF-STD scheme, which does not include snow and vegetation processes resulted in the poorest results, with a dramatic overestimation of surface air temperature. However, regardless of the land surface scheme chosen, WRF reasonably well reproduces the winter precipitation, a major water resource for California, suggesting that the linkage between land surface processes and precipitation is not explicit. In general, land surface schemes play a significant role in the simulation of regional

  14. A test of an optimal stomatal conductance scheme within the CABLE land surface model

    Science.gov (United States)

    De Kauwe, M. G.; Kala, J.; Lin, Y.-S.; Pitman, A. J.; Medlyn, B. E.; Duursma, R. A.; Abramowitz, G.; Wang, Y.-P.; Miralles, D. G.

    2015-02-01

    Stomatal conductance (gs) affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model (LSM). In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT), but instead only in relation to photosynthetic pathway. We constrained the key model parameter "g1", which represents plant water use strategy, by PFT, based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960-1990) bioclimatic variables: (i) temperature and (ii) an indirect estimate of annual plant water availability. The new stomatal model, in conjunction with PFT parameterisations, resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations) across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance against upscaled data products was not degraded, but did not noticeably reduce existing model-data biases. We identified assumptions relating to the coupling of the vegetation to the atmosphere and the parameterisation of the minimum stomatal conductance as areas requiring further investigation in both CABLE and potentially other LSMs. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.

  15. A test of an optimal stomatal conductance scheme within the CABLE Land Surface Model

    Directory of Open Access Journals (Sweden)

    M. G. De Kauwe

    2014-10-01

    Full Text Available Stomatal conductance (gs affects the fluxes of carbon, energy and water between the vegetated land surface and the atmosphere. We test an implementation of an optimal stomatal conductance model within the Community Atmosphere Biosphere Land Exchange (CABLE land surface model (LSM. In common with many LSMs, CABLE does not differentiate between gs model parameters in relation to plant functional type (PFT, but instead only in relation to photosynthetic pathway. We therefore constrained the key model parameter "g1" which represents a plants water use strategy by PFT based on a global synthesis of stomatal behaviour. As proof of concept, we also demonstrate that the g1 parameter can be estimated using two long-term average (1960–1990 bioclimatic variables: (i temperature and (ii an indirect estimate of annual plant water availability. The new stomatal models in conjunction with PFT parameterisations resulted in a large reduction in annual fluxes of transpiration (~ 30% compared to the standard CABLE simulations across evergreen needleleaf, tundra and C4 grass regions. Differences in other regions of the globe were typically small. Model performance when compared to upscaled data products was not degraded, though the new stomatal conductance scheme did not noticeably change existing model-data biases. We conclude that optimisation theory can yield a simple and tractable approach to predicting stomatal conductance in LSMs.

  16. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.

    2006-01-01

    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches, ......, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed....

  17. Land-surface modelling in hydrological perspective

    DEFF Research Database (Denmark)

    Overgaard, Jesper; Rosbjerg, Dan; Butts, M.B.

    2006-01-01

    The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches......, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed....

  18. Terrestrial Ecosystems - Land Surface Forms of the Conterminous United States

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The U.S. Geological Survey (USGS) has generated land surface form classes for the contiguous United States. These land surface form classes were created as part of...

  19. Modeling the impact of land surface feedbacks on post landfall tropical cyclones

    Science.gov (United States)

    Subramanian, Subashini

    The land surface is an important component of numerical models. The land surface models are modules that control energy partitioning, compute surface exchange coefficients and form the only physical boundary in a regional scale numerical model. Thus, an accurate representation of land surface is critical to compute surface fluxes, represent the boundary layer evolution and affect changes in weather systems. Land surface can affect landfalling tropical cyclones in two ways: (i) when the cyclone is offshore and land can influence cyclones by introducing dry (or moist) air that can weaken (or strengthen) the organized convective structure of cyclones, and (ii) land can affect the evolution of cyclones post landfall by modifying the surface heat fluxes and introducing additional surface drag. In this dissertation, the hypothesis that improved representation of land surface conditions will improve the prediction of landfalling tropical cyclones is tested. To that effect, a comprehensive review of land surface effects on tropical cyclones was undertaken and an idealized study was conducted to study the impact of antecedent soil temperature on the sustenance/reintensification of tropical cyclones over land. Rainfall verification for cyclone events over the Atlantic Ocean was conducted and a comparison study between land models--GFDL Slab and Noah, also considers the sensitivity of tropical cyclone models to land surface parameterizations. The recent adoption of Noah land model with hydrology products in HWRF offers a unique opportunity to couple a river routing model to HWRF to provide streamflow estimations from the HWRF model and this dissertation has outlined techniques to real time predict streamflow for United States with HWRF forcing. Results from this dissertation research indicate antecedent land surface conditions can affect tropical cyclone evolution post landfall and high soil temperature and thermally diffusive soil texture of land surface are critical factors

  20. Assessment of Noah land surface model with various runoff parameterizations over a Tibetan river

    Science.gov (United States)

    Zheng, Donghai; Van Der Velde, Rogier; Su, Zhongbo; Wen, Jun; Wang, Xin

    2017-02-01

    Runoff parameterizations currently adopted by the (i) Noah-MP model, (ii) Community Land Model (CLM), and (iii) CLM with variable infiltration capacity hydrology (CLM-VIC) are incorporated into the structure of Noah land surface model, and the impact of these parameterizations on the runoff simulations is investigated for a Tibetan river. Four numerical experiments are conducted with the default Noah and three aforementioned runoff parameterizations. Each experiment is forced with the same set of atmospheric forcing, vegetation, and soil parameters. In addition, the Community Earth System Model database provides the maximum surface saturated area parameter for the Noah-MP and CLM parameterizations. A single-year recurrent spin-up is adopted for the initialization of each model run to achieve equilibrium states. Comparison with discharge measurements shows that each runoff parameterization produces significant differences in the separation of total runoff into surface and subsurface components and that the soil water storage-based parameterizations (Noah and CLM-VIC) outperform the groundwater table-based parameterizations (Noah-MP and CLM) for the seasonally frozen and high-altitude Tibetan river. A parameter sensitivity experiment illustrates that this underperformance of the groundwater table-based parameterizations cannot be resolved through calibration. Further analyses demonstrate that the simulations of other surface water and energy budget components are insensitive to the selected runoff parameterizations, due to the strong control of the atmosphere on simulated land surface fluxes induced by the diurnal dependence of the roughness length for heat transfer and the large water retention capacity of the highly organic top soils over the plateau.

  1. Land surface processes and Sahel climate

    Science.gov (United States)

    Nicholson, Sharon

    2000-02-01

    This paper examines the question of land surface-atmosphere interactions in the West African Sahel and their role in the interannual variability of rainfall. In the Sahel, mean rainfall decreased by 25-40% between 1931-1960 and 1968-1997; every year in the 1950s was wet, and nearly every year since 1970 has been anomalously dry. Thus the intensity and multiyear persistence of drought conditions are unusual and perhaps unique features of Sahel climate. This article presents arguments for the role of land surface feedback in producing these features and reviews research relevant to land surface processes in the region, such as results from the 1992 Hydrologic Atmospheric Pilot Experiment (HAPEX)-Sahel experiment and recent studies on aerosols and on the issue of desertification in the region, a factor implicated by some as a cause of the changes in rainfall. Included also is a summary of evidence of feedback on meteorological processes, presented from both model results and observations. The reviewed studies demonstrate numerous ways in which the state of the land surface can influence interactions with the atmosphere. Surface hydrology essentially acts to delay and prolong the effects of meteorological drought. Each evaporative component of the surface water balance has its own timescale, with the presence of vegetation affecting the process both by delaying and prolonging the return of soil moisture to the atmosphere but at the same time accelerating the process through the evaporation of canopy-intercepted water. Hence the vegetation structure, including rooting depth, can modulate the land-atmosphere interaction. Such processes take on particular significance in the Sahel, where there is a high degree of recycling of atmospheric moisture and where the meteorological processes from the scale of boundary layer development to mesoscale disturbance generation are strongly influenced by moisture. Simple models of these feedback processes and their various timescales

  2. A New Approach for Parameter Optimization in Land Surface Model

    Institute of Scientific and Technical Information of China (English)

    LI Hongqi; GUO Weidong; SUN Guodong; ZHANG Yaocun; FU Congbin

    2011-01-01

    In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation (CNOP) in a land surface model (LSM) using long-term enhanced field observations at Tongyn station in Jilin Province,China,combined with a sophisticated LSM (common land model,CoLM).Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project (CEOP) that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments:First,a single-parameter optimization was performed,while the second and third experiments performed triple- and six-parameter optinizations,respectively.Notable improvements in simulating sensible heat flux (SH),latent heat flux (LH),soil temperature (TS),and moisture (MS) at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.

  3. MEaSUREs Land Surface Temperature from GOES Satellites

    Science.gov (United States)

    Pinker, Rachel T.; Chen, Wen; Ma, Yingtao; Islam, Tanvir; Borbas, Eva; Hain, Chris; Hulley, Glynn; Hook, Simon

    2017-04-01

    Information on Land Surface Temperature (LST) can be generated from observations made from satellites in low Earth orbit (LEO) such as MODIS and ASTER and by sensors in geostationary Earth orbit (GEO) such as GOES. Under a project titled: "A Unified and Coherent Land Surface Temperature and Emissivity Earth System Data Record for Earth Science" led by Jet Propulsion Laboratory, an effort is underway to develop long term consistent information from both such systems. In this presentation we will describe an effort to derive LST information from GOES satellites. Results will be presented from two approaches: 1) based on regression developed from a wide range of simulations using MODTRAN, SeeBor Version 5.0 global atmospheric profiles and the CAMEL (Combined ASTER and MODIS Emissivity for Land) product based on the standard University of Wisconsin 5 km emissivity values (UWIREMIS) and the ASTER Global Emissivity Database (GED) product; 2) RTTOV radiative transfer model driven with MERRA-2 reanalysis fields. We will present results of evaluation of these two methods against various products, such as MOD11, and ground observations for the five year period of (2004-2008).

  4. Complex land surface phenologies of moisture status

    Science.gov (United States)

    Henebry, G. M.; Doubkova, M.

    2006-12-01

    Making cross-scale linkages from experimental plots or flux tower footprints to regional and continental extents is made difficult by disparate spatial and temporal scales between process and observation. While exchanges between the vegetated land surface and the atmospheric boundary layer are continual, sampling and observations are typically intermittent in time and limited across space. Remote sensing of reflected sunlight has proven useful to track ecological dynamics. These observations are, however, restricted to daytime and often obscured by cloud cover, necessitating production of multi-date composites. The current generation of passive microwave radiometers can observe the land surface both day and night regardless of cloudiness, albeit at a spatial resolution coarser than typically used in ecological remote sensing. Datastreams from the AMSR-E (Advanced Microwave Scanning Radiometer-EOS) onboard NASA's Aqua platform are processed daily at the National Snow and Ice Data Center (NSIDC) into various products, including global retrievals of surficial soil moisture and vegetation water content based on microwave brightness temperatures observed at multiple frequencies. Due to sensor orbit and swath width, gaps occur at the lower latitudes in daily products. We have further processed the product-streams from the descending (01:30) and ascending (13:30) orbits into separate smoothed daily composites using an 8-day retrospective moving average. Of particular interest for synoptic ecology is the diel difference in vegetation water content. When the difference between the pre-dawn and the early afternoon values is positive, it suggests that the supply of moisture from the root zone is not able to keep pace with evapotranspiration during the day, but the soil and canopy moisture equalize overnight. Time series of the diel difference show rapid changes in moisture status in response to precipitation events and dry spells. What constitutes the appropriate baseline

  5. Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

    Science.gov (United States)

    Chen, Xuelong; Su, Bob

    2017-04-01

    Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

  6. Automation of SimSphere Land Surface Model Use as a Standalone Application and Integration With EO Data for Deriving Key Land Surface Parameters

    Science.gov (United States)

    Petropoulos, George P.; Konstas, Ioannis; Carlson, Toby N.

    2013-04-01

    Use of simulation process models has played a key role in extending our abilities to study Earth system processes and enhancing our understanding on how different components of it interplay. Use of such models combined with Earth Observation (EO) data provides a promising direction towards deriving accurately spatiotemporal estimates of key parameters characterising land surface interactions, by combining the horizontal coverage and spectral resolution of remote sensing data with the vertical coverage and fine temporal continuity of those models. SimSphere is such a software toolkit written in Java for simulating the interactions of soil, vegetation and atmosphere layers of the Earth's land surface. Its use is at present continually expanding worldwide both as an educational and as a research tool for scientific investigations. It is being used either as a stand-alone application or synergistically with EO data. Herein we present recent advancements introduced to SimSphere in different aspects of the model aiming to make its use more robust when used both as a standalone application and synergistically with EO data. We have extensively tested and updated the model code, as well as enhanced it with new functionalities. These included for example taking into account the thermal inertia variation in soil moisture, simulating additional parameters characterising land surface interactions, automating the model use when integrating it with EO data via the "triangle" method and developing batch processing operations. Use of these recently introduced to the model functionalities are illustrated herein using a variety of examples. Our work is significant to the users' community of the model and very timely, given the potential use of SimSphere in an EO-based method being under development for deriving operationally regional estimates of energy fluxes and soil moisture from EO data provided by non-commercial vendors. KEYWORDS: land surface interactions, land surface process

  7. Sensitivity of a general circulation model to land surface parameters in African tropical deforestation experiments

    Energy Technology Data Exchange (ETDEWEB)

    Maynard, K.; Royer, J.F. [Meteo-France CNRM, 42 Avenue G. Coriolis, 31057, Toulouse Cedex 1 (France)

    2004-06-01

    During the last two decades, several land surface schemes for use in climate, regional and/or mesoscale, hydrological and ecological models have been designed. Incorrect parametrization of land-surface processes and prescription of the surface parameters in atmospheric modeling, can result in artificial changes of the horizontal gradient of the sensible heat flux. Thus, an error in horizontal temperature gradient within the lower atmosphere may be introduced. The reliability of the model depends on the quality of boundary layer scheme implemented and its sensitivity to the bare soil and vegetation parameters. In this study, a series of sensitivity experiments has been conducted over broad time scales, using a version of the ARPEGE Climate Model coupled to the ISBA land surface scheme in order to investigate model sensitivity to separate changes in land surface parameters over Africa. Effects of perturbing vegetation cover, distribution of soil depth, albedo of vegetation, roughness length, leaf area index and minimum stomatal resistance were explored by using a simple statistical analysis. Identifying which parameters are important in controlling turbulent energy fluxes, temperature and soil moisture is dependent on which variables are used to determine sensibility, which type of vegetation and climate regime is being simulated and the magnitude and sign of the parameter change. This study does not argue that a particular parameter is important in ISBA, rather it shows that no general ranking of parameters is possible. So, it is essential to specify all land surface parameters with greater precision when attempting to determine the climate response to modification of the land surface. The implication of ISBA being sensitive to parameters that cannot be validated suggests that there will always be considerable doubt over the predictive quality of land-surface schemes. (orig.)

  8. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  9. A protocol for validating Land Surface Temperature from Sentinel-3

    Science.gov (United States)

    Ghent, D.

    2015-12-01

    One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC).Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. The Sentinel-3 Cal-Val Plan for evaluating the level-2 SL_2_LST product builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities, and is rapidly gaining international recognition. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for SLSTR which is designed around biome-based coefficients, thus emphasizing the importance of

  10. Modeling the land surface reflectance for optical remote sensing data in rugged terrain

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented.Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively,the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model.A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper.The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.

  11. Modeling the land surface reflectance for optical remote sensing data in rugged terrain

    Institute of Scientific and Technical Information of China (English)

    WEN JianGuang; LIU QinHuo; XIAO Qing; LIU Qiang; LI XiaoWen

    2008-01-01

    A model for topographic correction and land surface reflectance estimation for optical remote sensing data in rugged terrian is presented. Considering a directional-directional reflectance that is used for direct solar irradiance correction and a hemispheric-directional reflectance that is used for atmospheric diffuse irradiance and terrain background reflected irradiance correction respectively, the directional reflectance-based model for topographic effects removing and land surface reflectance calculation is developed by deducing the directional reflectance with topographic effects and using a radiative transfer model. A canopy reflectance simulated by GOMS model and Landsat/TM raw data covering Jiangxi rugged area were taken to validate the performance of the model presented in the paper. The validation results show that the model presented here has a remarkable ability to correct topography and estimate land surface reflectance and also provides a technique method for sequently quantitative remote sensing application in terrain area.

  12. A land surface model incorporated with soil freeze/thaw and its application in GAME/Tibet

    Institute of Scientific and Technical Information of China (English)

    HU Heping; YE Baisheng; ZHOU Yuhua; TIAN Fuqiang

    2006-01-01

    Land surface process is of great importance in global climate change,moisture and heat exchange in the interface of the earth and atmosphere,human impacts on the environment and ecosystem,etc.Soil freeze/thaw plays an important role in cold land surface processes.In this work the diurnal freeze/thaw effects on energy partition in the context of GAME/Tibet are studied.A sophisticated land surface model is developed,the particular aspect of which is its physical consideration of soil freeze/thaw and vapor flux.The simultaneous water and heat transfer soil sub-model not only reflects the water flow from unfrozen zone to frozen fringe in freezing/thawing soil,but also demonstrates the change of moisture and temperature field induced by vapor flux from high temperature zone to low temperature zone,which makes the model applicable for various circumstances.The modified Picard numerical method is employed to help with the water balance and convergence of the numerical scheme.Finally,the model is applied to analyze the diurnal energy and water cycle characteristics over the Tibetan Plateau using the Game/Tibet datasets observed in May and July of 1998.Heat and energy transfer simulation shows that: (i) There exists a negative feedback mechanism between soil freeze/thaw and soil temperature/ground heat flux; (ii) during freezing period all three heat fluxes do not vary apparently,in spite of the fact that the negative soil temperature is higher than that not considering soil freeze; (iii) during thawing period,ground heat flux increases,and sensible heat flux decreases,but latent heat flux does not change much; and (iv) during freezing period,soil temperature decreases,though ground heat flux increases.

  13. SLUDGE BATCH 6 PHASE II FLOWSHEET SIMULATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Koopman, D.; Best, D.

    2010-03-30

    Two Sludge Receipt and Adjustment Tank (SRAT) runs were used to demonstrate that a fairly wide window of acid stoichiometry was available for processing SB6 Phase II flowsheet simulant (Tank 40 simulant) while still meeting the dual goals of acceptable nitrate destruction and controlled hydrogen generation. Phase II was an intermediate flowsheet study for the projected composition of Tank 40 after transfer of SB6/Tank 51 sludge to the heel of SB5. The composition was based on August 2009 projections. A window of about 50% in total acid was found between acceptable nitrite destruction and excessive hydrogen generation.

  14. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; Velde, van der R.; Vekerdy, Z.; Su, Z.

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  15. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park

  16. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  17. Towards an improved land surface scheme for prairie landscapes

    Science.gov (United States)

    Mekonnen, M. A.; Wheater, H. S.; Ireson, A. M.; Spence, C.; Davison, B.; Pietroniro, A.

    2014-04-01

    The prairie region of Canada and the United States is characterized by millions of small depressions of glacial origin called prairie potholes. The transfer of surface runoff in this landscape is mainly through a “fill and spill” mechanism among neighboring potholes. While non-contributing areas, that is small internally drained basins, are common on this landscape, during wet periods these areas can become hydrologically connected to larger regional drainage systems. Accurate prediction of prairie surface runoff generation and streamflow thus requires realistic representation of the dynamic threshold-mediated nature of these contributing areas. This paper presents a new prairie surface runoff generation algorithm for land surface schemes and large scale hydrological models that conceptualizes a hydrologic unit as a combination of variable and interacting storage elements. The proposed surface runoff generation algorithm uses a probability density function to represent the spatial variation of pothole storages and assumes a unique relationship between storage and the fractional contributing area for runoff (and hence amount of direct runoff generated) within a grid cell. In this paper the parameters that define this relationship are obtained by calibration against streamflow. The model was compared to an existing hydrology-land surface scheme (HLSS) applied to a typical Canadian prairie catchment, the Assiniboine River. The existing configuration is based on the Canadian Land Surface Scheme (CLASS) and WATROF (a physically-based overland and interflow scheme). The new configuration consists of CLASS coupled with the new PDMROF model. Results showed that the proposed surface runoff generation algorithm performed better at simulating streamflow, and appears to capture the dynamic nature of contributing areas in an effective and parsimonious manner. A pilot evaluation based on 1 m LiDAR data from a small (10 km2) experimental area suggests that the shape of the

  18. Impact of land surface conditions on 2004 North American monsoon in GCM experiments

    Science.gov (United States)

    Feng, X.; Bosilovich, M.; Houser, P.; Chern, J.-D.

    2013-01-01

    In this study, two sets of six-member ensemble simulations were performed for the boreal summer of 2004 using the Finite Volume General Circulation model to investigate the sensitivity of the North American monsoon (NAM) system to land surface conditions and further to identify the mechanisms by which land surface processes control the NAM precipitation. The control simulation uses a fully interactive land surface model, whereas the sensitivity experiment uses prescribed land surface fields from the Global Land Data Assimilation System.The response of the monsoon precipitation to land surface changes varies over different regions modulated by two different soil moisture-precipitation feedbacks. The vast northern NAM region, including most of Arizona and New Mexico, as well as the northwestern Mexico shows that soil moisture has a positive feedback with precipitation primarily due to local recycling mechanisms. The reduction of soil moisture decreases latent heat flux and increases sensible heat flux and consequently increases the Bowen ratio and surface temperature, leading to a deep (warm and dry) boundary layer, which suppresses convection and hence reduces precipitation. Over the west coast of Mexico near Sinaloa, a negative soil moisture-precipitation relationship is noted to be associated with a large-scale mechanism. The reduced soil moisture changes surface fluxes and hence boundary layer instability and ultimately low-level circulation. As a result, the changes in surface pressure and large scale wind field increase moisture flux convergence and consequently moisture content, leading to increased atmospheric instability and in turn enhancing convection and accordingly precipitation. These results further reinforce the important role of land surface conditions on surface process, boundary structure, atmospheric circulation, and rainfall during the NAM development.

  19. Studying the Effect of Runoff Parameterization and Interaction between Atmosphere and Land Surface in Land Surface Schemes Used in NWP Models

    Science.gov (United States)

    Khodamorad Poor, M.; Irannejad, P.

    2009-04-01

    Land Surface Schemes that is one of the most important components in climate and numerical weather prediction models (NWP) has concentrated on surface energy and water budgets. Water budget is the hydrologic core of the land surface schemes and it is presented as the precipitation which is divided into evapotranspiration, runoff and changing in soil moisture. It is also introduced by different parameterizations among land surface schemes. Since Runoff is the major component of the water budget, unrealistic simulation of it can have some effects on the other components used in water budget and hence on the laten heat flux between atmosphere and land surface. Different representations of runoff in NWP models are relatively simple because runoff is conceptually difficult to be parameterized. Regarding that topography has a major control on the distribution of soil moisture and runoff, the main objective in this study is to find the parameterization runoff which is better to be introduced in NWP models. The algorithm used in Simple TOP Model (SIMTOP) for runoff parameterization is put in NOAH LSM utilized in Weather Research and Forecasting model (WRF). In SIMTOP, surface and subsurface runoff are considered as exponential functions of water table depth, but in NOAH LSM runoff is produced by extra maximum soil infiltration. The SIMTOP is like TOPMODEL that implemented topographic information (expressed by topographic index) and the nature of soil (indicated by reducing hydraulic conductivity with soil depth). The SIMTOP is simpler than TOPMODEL because of reducing in parameters that are needed to be calibrated. The surface runoff is the sum of two components, the first generated by infiltration excess (Horton mechanism) and the second, referring to variable contributed area, by saturation excess (Dunn mechanism). The subsurface runoff is represented by topographic control, bottom drainage and saturation excess. Although the river routing is very important for

  20. Classes of land-surface form in the United States

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This digital dataset describes classes of land-surface form in the conterminous United States. The source of the data is the map of land-surface form in the 1970...

  1. Angiotensin II during Experimentally Simulated Central Hypovolemia

    DEFF Research Database (Denmark)

    Jensen, Theo Walther; Olsen, Niels Vidiendal

    2016-01-01

    Central hypovolemia, defined as diminished blood volume in the heart and pulmonary vascular bed, is still an unresolved problem from a therapeutic point of view. The development of pharmaceutical agents targeted at specific angiotensin II receptors, such as the non-peptidergic AT2-receptor agonist...... of these agents in a hypovolemic setting. We argue that the latest debates on the effect of angiotensin II during hypovolemia might guide for future studies, investigating the effect of such agents during experimentally simulated central hypovolemia. The purpose of this review is to examine the role...... of angiotensin II during episodes of central hypovolemia. To examine this, we reviewed results from studies with three experimental models of simulated hypovolemia: head up tilt table test, lower body negative pressure, and hemorrhage of animals. A systemic literature search was made with the use of Pub...

  2. Mycorrhizal fungi and global land surface models?

    Science.gov (United States)

    Brzostek, E. R.; Fisher, J. B.; Shi, M.; Phillips, R.

    2013-12-01

    In the current generation of Land Surface Models (LSMs), the representation of coupled carbon (C) and nutrient cycles does not account for allocation of C by plants to mycorrhizal fungi in exchange for limiting nutrients. Given that the amount of C transferred to mycorrhizae can exceed 20% of net primary production (NPP), mycorrhizae can supply over half of the nitrogen (N) needed to support NPP, and that large majority of plants form associations with mycorrhizae; integrating these mechanisms into LSMs may significantly alter our understanding of the role of the terrestrial biosphere in mitigating climate change. Here, we present results from the integration of a mycorrhizal framework into a cutting-edge global plant nitrogen model -- Fixation & Uptake of Nitrogen (FUN; Fisher et al., 2010) -- that can be coupled into existing LSMs. In this mycorrhizal framework, the C cost of N acquisition varies as a function of mycorrhizal type with: (1) plants that support arbuscular mycorrhizae (AM) benefiting when N is plentiful and (2) plants that support ectomycorrhizae (ECM) benefiting when N is limiting. At the plot scale (15 x 15m), the My-FUN model improved predictions of retranslocation, N uptake, and the amount of C transferred into the soil relative to the base model across 45 plots that vary in mycorrhizal type in Indiana, USA. At the ecosystem scale, when we coupled this new framework into the Community Land Model (CLM-CN), the model estimated lower C uptake than the base model and more accurately predicted C uptake at the Morgan Monroe State Forest AmeriFlux site. These results suggest that the inclusion of a mycorrhizal framework into LSMs will enhance our ability to predict feedbacks between global change and the terrestrial biosphere.

  3. Semi-analytical analysis of the response of the air temperature over the land surface to the global vegetation distribution

    Institute of Scientific and Technical Information of China (English)

    LIU Fei; CHAO JiPing

    2009-01-01

    Response of the air temperature over the land surface to the global vegetation distribution is investigated, using a three-dimensional governing equation to simulate the steady, large-scale, limited amplitude perturbation of the free, inviscid and adiabatic atmosphere. The adoption of the static equation leads to a temperature governing equation in the terrain following coordinate. With the prescribed temperature as the upper boundary condition and the radiation balance as the lower boundary condition, the semi-analytical solution of the global circulation temperature can be calculated. In this article, only the air temperature (at 2 m height) over the land surface is analyzed, and the result suggests that this model can simulate the air temperature pattern over the land surface reasonably. A better simulation occurs when a simple feedback of the albedo on the temperature is included. Two sensitivity experiments are analyzed through this model. One suggests that the air temperature over the land surface descends obviously when the land surface is covered with ice all over, while another suggests that the air temperature rises a little when the land surface is covered with forest except the ice-covered area. This model appears to be a good tool to study the response of the air temperature to the vegetation distribution. Limitations of the model are also discussed.

  4. Exploring new topography-based subgrid spatial structures for improving land surface modeling

    Energy Technology Data Exchange (ETDEWEB)

    Tesfa, Teklu K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Leung, Lai-Yung Ruby [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2017-02-22

    Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation, slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Overall the local

  5. Exploring new topography-based subgrid spatial structures for improving land surface modeling

    Science.gov (United States)

    Tesfa, Teklu K.; Leung, Lai-Yung Ruby

    2017-02-01

    Topography plays an important role in land surface processes through its influence on atmospheric forcing, soil and vegetation properties, and river network topology and drainage area. Land surface models with a spatial structure that captures spatial heterogeneity, which is directly affected by topography, may improve the representation of land surface processes. Previous studies found that land surface modeling, using subbasins instead of structured grids as computational units, improves the scalability of simulated runoff and streamflow processes. In this study, new land surface spatial structures are explored by further dividing subbasins into subgrid structures based on topographic properties, including surface elevation, slope and aspect. Two methods (local and global) of watershed discretization are applied to derive two types of subgrid structures (geo-located and non-geo-located) over the topographically diverse Columbia River basin in the northwestern United States. In the global method, a fixed elevation classification scheme is used to discretize subbasins. The local method utilizes concepts of hypsometric analysis to discretize each subbasin, using different elevation ranges that also naturally account for slope variations. The relative merits of the two methods and subgrid structures are investigated for their ability to capture topographic heterogeneity and the implications of this on representations of atmospheric forcing and land cover spatial patterns. Results showed that the local method reduces the standard deviation (SD) of subgrid surface elevation in the study domain by 17 to 19 % compared to the global method, highlighting the relative advantages of the local method for capturing subgrid topographic variations. The comparison between the two types of subgrid structures showed that the non-geo-located subgrid structures are more consistent across different area threshold values than the geo-located subgrid structures. Overall the local method

  6. Development of high resolution land surface parameters for the Community Land Model

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2012-06-01

    Full Text Available There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0 are at 0.5° or coarser resolutions, released with the model from the National Center for Atmospheric Research (NCAR. Plant Functional Types (PFTs, vegetation properties such as Leaf Area Index (LAI, Stem Area Index (SAI, and non-vegetated land covers were developed using remotely-sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM applied to the western US to demonstrate their use in high-resolution modeling. Future work will include global offline CLMsimulations to examine the impacts of source data resolution and subsequent land parameter changes on simulated land surface processes.

  7. Assimilation of freeze-thaw observations into the NASA Catchment land surface model

    Science.gov (United States)

    Farhadi, L.; Reichle, R. H.; Delannoy, G.

    2012-12-01

    The land surface freeze-thaw (F/T) state controls hydrological and carbon cycling and thus affects water and energy exchanges at land surface. In this research an Observing System Simulation Experiment experiment is conducted using synthetically generated measurements of the F/T state for a region in North America (90-110oW longitude, 45-55oN latitude). The synthetic "truth" is generated using the NASA Catchment land surface model forced with surface meteorological fields from the Modern-Era Retrospective Reanalysis for Research and Applications (MERRA). To generate synthetic measurements, the true categorical F/T state is corrupted with a prescribed amount of F/T classification error. The assimilation experiment employs the same Catchment model except that forcing errors (relative to truth) are introduced via the application of meteorological forcing fields from the Global Land Data Assimilation System (GLDAS). A rule-based approach that incorporates model and observational errors is developed and used for assimilating the categorical F/T measurements into the land surface model (F/T analysis). The effect of the F/T analysis on land surface temperature, soil temperature and soil moisture is examined. In a real-world experiment, the synthetic F/T observations are replaced with F/T observations from the Advanced Microwave Scanning Radiometer Enhanced (AMSR-E). The ultimate goal of this project is to provide a framework for the assimilation of SMAP (Soil Moisture Active Passive) F/T observations into the NASA Catchment land surface model.

  8. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

    Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land

  9. Spatial Aggregation of Land Surface Characteristics: Impact of resolution of remote sensing data on land surface modelling

    NARCIS (Netherlands)

    Pelgrum, H.

    2000-01-01

    Land surface models describe the exchange of heat, moisture and momentum between the land surface and the atmosphere. These models can be solved regionally using remote sensing measurements as input. Input variables which can be derived from remote sensing measurements are surface albedo, surface te

  10. Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Chun; Huang, Maoyi; Fast, Jerome D.; Berg, Larry K.; Qian, Yun; Guenther , A.; Gu, Dasa; Shrivastava, ManishKumar B.; Liu, Ying; Walters, Stacy; Pfister, G.; Jin, Jiming; Shilling, John E.; Warneke, Carsten

    2016-05-27

    Current climate models still have large uncertainties 24 in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land-surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature MEGAN (MEGAN v2.1) is coupled within the land surface parameterization CLM4 in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implement, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a standalone vegetation map that differs from what is used by land surface parameterizations. This improved modeling framework is used to investigate the impact of two land surface parameterizations, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted during June of 2010 provide an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface parameterizations do influence the simulated BVOCs, but that impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover datasets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry, and consequently secondary organic aerosol formation.

  11. A Modeling Study of Land Surface Process Impacts on Inland Behavior of Typhoon Rananim (2004)

    Institute of Scientific and Technical Information of China (English)

    WEI Na; LI Ying

    2013-01-01

    On 12 August 2004,Typhoon Rananim (0414) moved inland over China and stagnated over the Poyang Lake area,resulting in torrential rainfall and severe geologic hazards.The Advanced Weather Research and Forecasting (ARW-WRF) model and its different land surface models (LSMs) were employed to study the impacts of land surface process on the inland behavior of Typhoon Rananim.Results show that simulations,coupled with LSMs or not,have no significant differences in predicting typhoon track,intensity,and largescale circulation.However,the simulations of mesoscale structure,rainfall rate,and rainfall distribution of typhoon are more reasonable with LSMs than without LSMs.Although differences are slight among LSMs,NOAH is better than the others.Based on outputs using the NOAH scheme,the interaction between land surface and typhoon was explored in this study.Notably,typhoon rainfall and cloud cover can cool land surface,but rainfall expands the underlying saturated wetland area,which exacerbates the asymmetric distribution of surface heat fluxes.Accordingly,an energy frontal zone may form in the lower troposphere that enhances ascending motion and local convection,resulting in heavier rainfall.Moreover,the expanded underlying saturated wetlands provide plentiful moisture and unstable energy for the maintenance of Typhoon Rananim and increased rainfall in return.

  12. Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

    Science.gov (United States)

    Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

    2010-01-01

    Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

  13. Automated Distributed Simulation in Ptolemy II

    DEFF Research Database (Denmark)

    Lázaro Cuadrado, Daniel; Ravn, Anders Peter; Koch, Peter

    2007-01-01

    the ensuing communication and synchronization problems. Very often the designer has to explicitly specify extra information concerning distribution for the framework to make an effort to exploit parallelism. This paper presents Automated Distributed Simulation (ADS), which allows the designer to forget about......Despite the well known advantages of distributed processing for intensive computations like simulation, frameworks often fail to exploit them. A distributed simulation is harder to develop than a sequential one, because it is necessary to interface and map activities to processors and handle...... distribution concerns while benefiting from the advantages. ADS relies on the actor formalism. It is realized as an open source implementation for the Ptolemy II simulation framework. Experiments compare different topologies, granularities and number of blocks, achieving linear speedups for practical cases. We...

  14. Fuel moisture content estimation: a land-surface modelling approach applied to African savannas

    Science.gov (United States)

    Ghent, D.; Spessa, A.; Kaduk, J.; Balzter, H.

    2009-04-01

    Despite the importance of fire to the global climate system, in terms of emissions from biomass burning, ecosystem structure and function, and changes to surface albedo, current land-surface models do not adequately estimate key variables affecting fire ignition and propagation. Fuel moisture content (FMC) is considered one of the most important of these variables (Chuvieco et al., 2004). Biophysical models, with appropriate plant functional type parameterisations, are the most viable option to adequately predict FMC over continental scales at high temporal resolution. However, the complexity of plant-water interactions, and the variability associated with short-term climate changes, means it is one of the most difficult fire variables to quantify and predict. Our work attempts to resolve this issue using a combination of satellite data and biophysical modelling applied to Africa. The approach we take is to represent live FMC as a surface dryness index; expressed as the ratio between the Normalised Difference Vegetation Index (NDVI) and land-surface temperature (LST). It has been argued in previous studies (Sandholt et al., 2002; Snyder et al., 2006), that this ratio displays a statistically stronger correlation to FMC than either of the variables, considered separately. In this study, simulated FMC is constrained through the assimilation of remotely sensed LST and NDVI data into the land-surface model JULES (Joint-UK Land Environment Simulator). Previous modelling studies of fire activity in Africa savannas, such as Lehsten et al. (2008), have reported significant levels of uncertainty associated with the simulations. This uncertainty is important because African savannas are among some of the most frequently burnt ecosystems and are a major source of greenhouse trace gases and aerosol emissions (Scholes et al., 1996). Furthermore, regional climate model studies indicate that many parts of the African savannas will experience drier and warmer conditions in future

  15. Software and Physics Simulation at Belle II

    CERN Document Server

    Kim, Doris Yangsoo

    2015-01-01

    The Belle II experiment at the SuperKEKB collider in Tsukuba, Japan, will start physics data taking in 2018. It is planned to accumulate an e+ e- collision data set of 50 /ab, about 50 times larger than that of the earlier Belle experiment. The software library for the new detector will use GEANT4 for Monte Carlo simulation and is an entirely new software and reconstruction system based on modern computing tools. Examples of physics simulation including beam background overlays will be described.

  16. Angiotensin II during experimentally simulated central hypovolemia

    Directory of Open Access Journals (Sweden)

    Theo Walther Jensen

    2016-03-01

    Full Text Available Abstract:Central hypovolemia, defined as diminished blood volume in the heart and pulmonary vascular bed, is still an unresolved problem from a therapeutic point of view. The development of pharmaceutical agents targeted at specific angiotensin II receptors, like the non-peptidergic AT2-receptor agonist compound 21, is yielding many opportunities to uncover more knowledge about angiotensin II receptor profiles and possible therapeutic use. Cardiovascular, anti-inflammatory and neuroprotective therapeutic use of compound 21 have been suggested. However, there has not yet been a focus on the use of these agents in a hypovolemic setting. We argue that the latest debates on the effect of angiotensin II during hypovolemia might guide for future studies investigating the effect of such agents during experimentally simulated central hypovolemia. The purpose of this review is to examine the role of angiotensin II during episodes of central hypovolemia.To examine this, we reviewed results from studies with three experimental models of simulated hypovolemia: head up tilt table test, lower body negative pressure, and hemorrhage of animals. A systemic literature search was made with the use of PubMed/MEDLINE for studies that measured variables of the renin-angiotensin system or its effect during simulated hypovolemia. 12 articles, using one of the three models, were included and showed a possible organ protective effect and an effect on the sympathetic system of angiotensin II during hypovolemia. The results support the possible organ protective vasodilatory role for the AT2-receptor during hypovolemia on both the kidney and the splanchnic tissue.

  17. Forest biomass allometry in global land surface models

    Science.gov (United States)

    Wolf, Adam; Ciais, Philippe; Bellassen, Valentin; Delbart, Nicolas; Field, Christopher B.; Berry, Joseph A.

    2011-09-01

    A number of global land surface models simulate photosynthesis, respiration, and disturbance, important flows in the carbon cycle that are widely tested against flux towers and CO2 concentration gradients. The resulting forest biomass is examined in this paper for its resemblance to realistic stands, which are characterized using allometric theory. The simulated biomass pools largely do not conform to widely observed allometry, particularly for young stands. The best performing models had an explicit treatment of stand-thinning processes, which brought the slope of the allometry of these models closer to observations. Additionally, models that had relatively shorter wood turnover times performed were generally closer to observed allometries. The discrepancy between the pool distribution between models and data suggests estimates of NEE have biases when integrated over the long term, as compared to observed biomass data, and could therefore compromise long-term predictions of land carbon sources and sinks. We think that this presents a practical obstacle for improving models by informing them better with data. The approach taken in this paper, examining biomass pools allometrically, offers a simple approach to improving the characteristic behaviors of global models with the relatively sparse data that is available globally by forest inventory.

  18. An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

    Science.gov (United States)

    Kim, Edward J.; Tedesco, Marco

    2006-01-01

    Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. 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. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. 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 at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

  19. eMODIS Global Land Surface Temperature Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The EROS Moderate Resolution Imaging Spectroradiometer (eMODIS) Aqua Land Surface Temperature (LST) product is similar to the Land Processes Distributed Active...

  20. An Estimation of Land Surface Temperatures from Landsat ETM+ ...

    African Journals Online (AJOL)

    Dr-Adeline

    2 National Authority for Remote Sensing and Space Sciences, Cairo, Egypt. 3University of ... Keywords: Urban growth, urban heat Island, land surface temperatures, satellite remote sensing .... observed target includes green vegetation or not.

  1. Determination of Land Surface Temperature (LST) and Potential ...

    African Journals Online (AJOL)

    Determination of Land Surface Temperature (LST) and Potential Urban Heat Island Effect in Parts of Lagos State using Satellite ... Changes in temperature appear to be closely related to concentrations of atmospheric carbon dioxide.

  2. Towards scale-independent land-surface flux estimates in Noah-MP

    Science.gov (United States)

    Thober, Stephan; Mizukami, Naoki; Samaniego, Luis; Attinger, Sabine; Clark, Martyn; Cuntz, Matthias

    2017-04-01

    Land-surface models use a variety of process representations to calculate terrestrial energy, water and biogeochemical fluxes. These process descriptions are usually derived from point measurements which are, in turn, scaled to much larger resolutions ranging from 1 km in catchment hydrology to 100 km in climate modelling. Both, hydrologic and climate models are nowadays run on different spatial resolutions, using the exactly same land surface representations. A fundamental criterion for the physical consistency of land-surface simulations across scales is that a flux estimated over a given area is independent of the spatial model resolution (i.e., the flux-matching criterion). The Noah-MP land surface model considers only one soil and land cover type per model grid cell without any representation of their subgrid variability, implying a weak flux-matching. A fractional approach simulates the subgrid variability but it requires a higher computational demand than using effective parameters and it is used only for land cover in current land surface schemes. A promising approach to derive scale-independent parameters is the Multiscale Parameter Regionalization (MPR) technique, which consists of two steps: first, it applies transfer functions directly to high-resolution data (such as 100 m soil maps) to derive high-resolution model parameter fields, acknowledging the full subgrid variability. Second, it upscales these high-resolution parameter fields to the model resolution by using appropriate upscaling operators. MPR has shown to improve substantially the scalability of the mesoscale Hydrologic Models mHM (Samaniego et al., 2010 WRR). Here, we apply the MPR technique to the Noah-MP land-surface model for a large sample of basins distributed across the contiguous USA. Specifically, we evaluate the flux-matching criterion for several hydrologic fluxes such as evapotranspiration and drainage at scales ranging from 3 km to 48 km. We investigate the impact of different

  3. Incorporation of water vapor transfer in the JULES land surface model: Implications for key soil variables and land surface fluxes

    Science.gov (United States)

    Garcia Gonzalez, Raquel; Verhoef, Anne; Luigi Vidale, Pier; Braud, Isabelle

    2012-05-01

    This study focuses on the mechanisms underlying water and heat transfer in upper soil layers, and their effects on soil physical prognostic variables and the individual components of the energy balance. The skill of the JULES (Joint UK Environment Simulator) land surface model (LSM) to simulate key soil variables, such as soil moisture content and surface temperature, and fluxes such as evaporation, is investigated. The Richards equation for soil water transfer, as used in most LSMs, was updated by incorporating isothermal and thermal water vapor transfer. The model was tested for three sites representative of semiarid and temperate arid climates: the Jornada site (New Mexico, USA), Griffith site (Australia), and Audubon site (Arizona, USA). Water vapor flux was found to contribute significantly to the water and heat transfer in the upper soil layers. This was mainly due to isothermal vapor diffusion; thermal vapor flux also played a role at the Jornada site just after rainfall events. Inclusion of water vapor flux had an effect on the diurnal evolution of evaporation, soil moisture content, and surface temperature. The incorporation of additional processes, such as water vapor flux among others, into LSMs may improve the coupling between the upper soil layers and the atmosphere, which in turn could increase the reliability of weather and climate predictions.

  4. Analysis of Anomaly in Land Surface Temperature Using MODIS Products

    Science.gov (United States)

    Yorozu, K.; Kodama, T.; Kim, S.; Tachikawa, Y.; Shiiba, M.

    2011-12-01

    Atmosphere-land surface interaction plays a dominant role on the hydrologic cycle. Atmospheric phenomena cause variation of land surface state and land surface state can affect on atmosphereic conditions. Widely-known article related in atmospheric-land interaction was published by Koster et al. in 2004. The context of this article is that seasonal anomaly in soil moisture or soil surface temperature can affect summer precipitation generation and other atmospheric processes especially in middle North America, Sahel and south Asia. From not only above example but other previous research works, it is assumed that anomaly of surface state has a key factor. To investigate atmospheric-land surface interaction, it is necessary to analyze anomaly field in land surface state. In this study, soil surface temperature should be focused because it can be globally and continuously observed by satellite launched sensor. To land surface temperature product, MOD11C1 and MYD11C1 products which are kinds of MODIS products are applied. Both of them have 0.05 degree spatial resolution and daily temporal resolution. The difference of them is launched satellite, MOD11C1 is Terra and MYD11C1 is Aqua. MOD11C1 covers the latter of 2000 to present and MYD11C1 covers the early 2002 to present. There are unrealistic values on provided products even if daily product was already calibrated or corrected. For pre-analyzing, daily data is aggregated into 8-days data to remove irregular values for stable analysis. It was found that there are spatial and temporal distribution of 10-years average and standard deviation for each 8-days term. In order to point out extreme anomaly in land surface temperature, standard score for each 8-days term is applied. From the analysis of standard score, it is found there are large anomaly in land surface temperature around north China plain in early April 2005 and around Bangladesh in early May 2009.

  5. 2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2013-05-01

    Full Text Available Most land surface hydrological models (LSHMs consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2 and the atmospheric part of the RCM MM5 (45 × 45 km2. The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both

  6. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    MAO KeBiao; SHI JianCheng; LI ZhaoLiang; QIN ZhiHao; LI ManChun; XU Bin

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface temperature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM, the difference of different frequencies can eliminate the influence of water in soil and atmosphere, and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately, the land surface should be at least classified into three types: water covered surface, snow covered surface, and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm, we built different equations for different ranges of temperature. The average land surface temperature error is about 2-3℃ relative to the MODIS LST product.

  7. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface tem-perature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM,the difference of different frequen-cies can eliminate the influence of water in soil and atmosphere,and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately,the land surface should be at least classified into three types:water covered surface,snow covered surface,and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm,we built different equations for different ranges of temperature. The average land surface temperature er-ror is about 2―3℃ relative to the MODIS LST product.

  8. Physically plausible prescription of land surface model soil moisture

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia

    2016-04-01

    Land surface hydrology is an important control of surface weather and climate, especially under extreme dry or wet conditions where it can amplify heat waves or floods, respectively. Prescribing soil moisture in land surface models is a valuable technique to investigate this link between hydrology and climate. It has been used for example to assess the influence of soil moisture on temperature variability, mean and extremes (Seneviratne et al. 2006, 2013, Lorenz et al., 2015). However, perturbing the soil moisture content artificially can lead to a violation of the energy and water balances. Here we present a new method for prescribing soil moisture which ensures water and energy balance closure by using only water from runoff and a reservoir term. If water is available, the method prevents soil moisture decrease below climatological values. Results from simulations with the Community Land Model (CLM) indicate that our new method allows to avoid soil moisture deficits in many regions of the world. We show the influence of the irrigation-supported soil moisture content on mean and extreme temperatures and contrast our findings with that of earlier studies. Additionally, we will assess how long into the 21st century the new method will be able to maintain present-day climatological soil moisture levels for different regions. Lorenz, R., Argüeso, D., Donat, M.G., Pitman, A.J., den Hurk, B.V., Berg, A., Lawrence, D.M., Chéruy, F., Ducharne, A., Hagemann, S. and Meier, A., 2015. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. Journal of Geophysical Research: Atmospheres. Seneviratne, S.I., Lüthi, D., Litschi, M. and Schär, C., 2006. Land-atmosphere coupling and climate change in Europe. Nature, 443(7108), pp.205-209. Seneviratne, S.I., Wilhelm, M., Stanelle, T., Hurk, B., Hagemann, S., Berg, A., Cheruy, F., Higgins, M.E., Meier, A., Brovkin, V. and Claussen, M., 2013. Impact of soil moisture

  9. Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

    Science.gov (United States)

    Case. Jonathan; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

    2014-01-01

    ) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

  10. Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

    Science.gov (United States)

    Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

    2012-01-01

    Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

  11. Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm

    Directory of Open Access Journals (Sweden)

    Offer Rozenstein

    2014-03-01

    Full Text Available Land surface temperature (LST is one of the most important variables measured by satellite remote sensing. Public domain data are available from the newly operational Landsat-8 Thermal Infrared Sensor (TIRS. This paper presents an adjustment of the split window algorithm (SWA for TIRS that uses atmospheric transmittance and land surface emissivity (LSE as inputs. Various alternatives for estimating these SWA inputs are reviewed, and a sensitivity analysis of the SWA to misestimating the input parameters is performed. The accuracy of the current development was assessed using simulated Modtran data. The root mean square error (RMSE of the simulated LST was calculated as 0.93 °C. This SWA development is leading to progress in the determination of LST by Landsat-8 TIRS.

  12. Towards an improved and more flexible representation of water stress in coupled photosynthesis-stomatal conductance models; implications for simulated land surface fluxes and variables at various spatiotemporal scales

    Science.gov (United States)

    Egea, G.; Verhoef, A.; Vidale, P. L.; Black, E.; Van den Hoof, C.

    2012-04-01

    Coupled photosynthesis-stomatal conductance (A-gs) models are commonly used in ecosystem models to represent the exchange rate of CO2 and H2O between vegetation and the atmosphere. The ways these models account for water stress differ greatly among modelling schemes. This study provides insight into the impact of contrasting model configurations of water stress on the simulated leaf-level values of net photosynthesis (A), stomatal conductance (gs), the functional relationship among them and their ratio, the intrinsic water use efficiency (A/gs), as soil dries. A simple, yet versatile, normalized soil moisture dependent function was used to account for the effects of water stress on gs, on mesophyll conductance (gm ) and on the biochemical capacity (Egea et al., 2011). Model output was compared to leaf-level values obtained from the literature. The sensitivity analyses emphasized the necessity to combine both stomatal and non-stomatal limitations of A in coupled A-gs models to accurately capture the observed functional relationships A vs. gs and A/gs vs. gs in response to drought. Accounting for water stress in coupled A-gs models by imposing either stomatal or biochemical limitations of A, as commonly practiced in most ecosystem models, failed to reproduce the observed functional relationship between key leaf gas exchange attributes. A quantitative limitation analysis revealed that the general pattern of C3 photosynthetic response to water stress can be represented in coupled A-gs models by imposing the highest limitation strength to mesophyll conductance, then to stomatal conductance and finally to the biochemical capacity. This more realistic representation of soil water stress on the simulated leaf-level values of A and gs was embedded in the JULES (Joint UK Land Environment Simulator; Best et al., 2011), model and tested for a number of vegetation types, for which driving and flux verification data were available. These simulations provide an insight into the

  13. Impacts on the regional climate modeling and improvements of modern land surface model over the Tibet Plateau

    Science.gov (United States)

    Gao, Yanhong; Xiao, Linhong; Chen, Fei; Chen, Deliang

    2017-04-01

    Three WRF dynamical downscaling simulations were designed and conducted with two different GCM forcings and two land-surface schemes (Noah versus Noah-MP). Two of them used the same forcing (ERA) and two of them shared the same land-surface model physics (Noah-MP). Simulated surface air temperature and precipitation were assessed in terms of seasonal and annual mean Climatology, and spatial characteristics and linear trends over the TP for the period 1980-2005. Major findings are summarized in the following: 1) A common cold and wet bias exists in all three simulations regardless the type of large-scale forcing or land-surface model being used. This is especially true in the western TP during the cold season, indicating that the WRF model is still deficient in capturing cold-season processes at high elevations. However, such biases in DDM were greatly constrained compared to these in forcing GCM. The land-surface model impacts the surface air temperature and precipitation climatology and spatial distribution significantly more than the large -scale forcing. Large-scale forcing has more influence on the trends rather than on the spatial characteristics in DDM. 2) The land-surface model affects precipitation over the TP through including the surface heating differential over the TP. The heating differential caused surface heat fluxes differences resulting in a stronger or weaker upward vertical motion and divergence (convergence) at upper (low) levels. This in turn brings different moist air from the ocean.

  14. Improvements of modern land surface model and impacts on the regional climate modeling in the Tibet Plateau

    Science.gov (United States)

    Gao, Y.; Linhong, X., Sr.; Chen, F.

    2016-12-01

    Three WRF dynamical downscaling simulations were designed and conducted with two different GCM forcings and two land-surface schemes (Noah versus Noah-MP). Two of them used the same forcing (ERA) and two of them shared the same land-surface model physics (Noah-MP). Simulated surface air temperature and precipitation were assessed in terms of seasonal and annual mean climatology, and spatial characteristics and linear trends over the TP for the period 1980-2005. Major findings are summarized in the following: 1) A common cold and wet bias exists in all three simulations regardless the type of large-scale forcing or land-surface model being used. This is especially true in the western TP during the cold season, indicating that the WRF model is still deficient in capturing cold-season processes at high elevations. However, such biases in DDM were greatly constrained compared to these in forcing GCM. The land-surface model impacts the surface air temperature and precipitation climatology and spatial distribution significantly more than the large -scale forcing. Large-scale forcing has more influence on the trends rather than on the spatial characteristics in DDM. 2) The land-surface model affects precipitation over the TP through including the surface heating differential over the TP. The heating differential caused surface heat fluxes differences resulting in a stronger or weaker upward vertical motion and divergence (convergence) at upper (low) levels. This in turn brings different moist air from the ocean.

  15. Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) dynamic vegetation-land surface model

    Science.gov (United States)

    Landry, Jean-Sébastien; Price, David T.; Ramankutty, Navin; Parrott, Lael; Damon Matthews, H.

    2016-04-01

    Insects defoliate and kill plants in many ecosystems worldwide. The consequences of these natural processes on terrestrial ecology and nutrient cycling are well established, and their potential climatic effects resulting from modified land-atmosphere exchanges of carbon, energy, and water are increasingly being recognized. We developed a Marauding Insect Module (MIM) to quantify, in the Integrated BIosphere Simulator (IBIS), the consequences of insect activity on biogeochemical and biogeophysical fluxes, also accounting for the effects of altered vegetation dynamics. MIM can simulate damage from three different insect functional types: (1) defoliators on broadleaf deciduous trees, (2) defoliators on needleleaf evergreen trees, and (3) bark beetles on needleleaf evergreen trees, with the resulting impacts being estimated by IBIS based on the new, insect-modified state of the vegetation. MIM further accounts for the physical presence and gradual fall of insect-killed dead standing trees. The design of MIM should facilitate the addition of other insect types besides the ones already included and could guide the development of similar modules for other process-based vegetation models. After describing IBIS-MIM, we illustrate the usefulness of the model by presenting results spanning daily to centennial timescales for vegetation dynamics and cycling of carbon, energy, and water in a simplified setting and for bark beetles only. More precisely, we simulated 100 % mortality events from the mountain pine beetle for three locations in western Canada. We then show that these simulated impacts agree with many previous studies based on field measurements, satellite data, or modelling. MIM and similar tools should therefore be of great value in assessing the wide array of impacts resulting from insect-induced plant damage in the Earth system.

  16. Development of high resolution land surface parameters for the Community Land Model

    Directory of Open Access Journals (Sweden)

    Y. Ke

    2012-11-01

    Full Text Available There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0 are at 0.5° or coarser resolutions, released with the Community Earth System Model (CESM. Plant Functional Types (PFTs, vegetation properties such as Leaf Area Index (LAI, Stem Area Index (SAI, and non-vegetated land covers were developed using remotely sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. Advantages and disadvantages of each dataset were discussed in order to provide guidance on the use of the data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM applied to the western US to demonstrate their use in high-resolution modeling. A remapping method from the latitude/longitude grid of the CLM data to the WRF grids with map projection was also demonstrated. Future work will include global offline CLM simulations to examine the impacts of source data resolution and subsequent land

  17. Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo

    Science.gov (United States)

    Wang, Rong; Chen, Jing M.; Pavlic, Goran; Arain, Altaf

    2016-09-01

    Winter leaf area index (LAI) of evergreen coniferous forests exerts strong control on the interception of snow, snowmelt and energy balance. Simulation of winter LAI and associated winter processes in land surface models is challenging. Retrieving winter LAI from remote sensing data is difficult due to cloud contamination, poor illumination, lower solar elevation and higher radiation reflection by snow background. Underestimated winter LAI in evergreen coniferous forests is one of the major issues limiting the application of current remote sensing LAI products. It has not been fully addressed in past studies in the literature. In this study, we used needle lifespan to correct winter LAI in a remote sensing product developed by the University of Toronto. For the validation purpose, the corrected winter LAI was then used to calculate land surface albedo at five FLUXNET coniferous forests in Canada. The RMSE and bias values for estimated albedo were 0.05 and 0.011, respectively, for all sites. The albedo map over coniferous forests across Canada produced with corrected winter LAI showed much better agreement with the GLASS (Global LAnd Surface Satellites) albedo product than the one produced with uncorrected winter LAI. The results revealed that the corrected winter LAI yielded much greater accuracy in simulating land surface albedo, making the new LAI product an improvement over the original one. Our study will help to increase the usability of remote sensing LAI products in land surface energy budget modeling.

  18. Climatic change due to land surface alterations

    Energy Technology Data Exchange (ETDEWEB)

    Franchito, S.H.; Rao, V.B.

    1992-01-01

    A primitive equations global zonally averaged climate model is developed. The model includes biofeedback mechanisms. For the Northern Hemisphere the parameterization of biofeedback mechanisms is similar to that used by Gutman et al. For the Southern Hemisphere new parameterizations are derived. The model simulates reasonably well the mean annual zonally averaged climate and geobotanic zones. Deforestation, desertification, and irrigation experiments are performed. In the case of deforestation and desertification there is a reduction in the surface net radiation, evaporation, and precipitation and an increase in the surface temperature. In the case of irrigation experiment opposite changes occurred. In all the cases considered the changes in evapotranspiration overcome the effect of surface albedo modification. In all the experiments changes are smaller in the Southern Hemisphere.

  19. A comprehensive approach to analyze discrepancies between land surface models and in-situ measurements: a case study over US and Illinois with SECHIBA forced by NLDAS

    OpenAIRE

    Guimberteau, M.; Perrier, A.; K. Laval; Polcher, J.

    2012-01-01

    The purpose of this study is to test the ability of the Land Surface Model SECHIBA to simulate water budget and particularly soil moisture at two different scales: regional and mesoscale. The model is forced by NLDAS data set at eighth degree resolution over the 1997–1999 period. SECHIBA gives satisfying results in terms of evapotranspiration and runoff over US compared with four other land surface models, all forced by NLDAS data set for a common time period. The simulated soil moisture...

  20. Real Time Land-Surface Hydrologic Modeling Over Continental US

    Science.gov (United States)

    Houser, Paul R.

    1998-01-01

    The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

  1. Bayesian Estimation for Land Surface Temperature Retrieval: The Nuisance of Emissivities

    CERN Document Server

    Morgan, J A

    2004-01-01

    An approach to the remote sensing of land surface temperature is developed using the methods of Bayesian inference. The starting point is the maximum entropy estimate for the posterior distribution of radiance in multiple bands. In order to convert this quantity to an estimator for surface temperature and emissivity with Bayes' theorem, it is necessary to obtain the joint prior probability for surface temperature and emissivity, given available prior knowledge. The requirement that any pair of distinct observers be able to relate their descriptions of radiance under arbitrary Lorentz transformations uniquely determines the prior probability. Perhaps surprisingly, surface temperature acts as a scale parameter, while emissivity acts as a location parameter, giving the prior probability P(T,emissivity|K)=const./T dT d(emissivity). Given this result, it is a simple matter to construct estimators for surface temperature and emssivity. Monte Carlo simulations of land surface temeprature retrieval in selected MODIS ...

  2. High resolution land surface response of inland moving Indian monsoon depressions over Bay of Bengal

    Science.gov (United States)

    Rajesh, P. V.; Pattnaik, S.

    2016-05-01

    During Indian summer monsoon (ISM) season, nearly about half of the monsoonal rainfall is brought inland by the low pressure systems called as Monsoon Depressions (MDs). These systems bear large amount of rainfall and frequently give copious amount of rainfall over land regions, therefore accurate forecast of these synoptic scale systems at short time scale can help in disaster management, flood relief, food safety. The goal of this study is to investigate, whether an accurate moisture-rainfall feedback from land surface can improve the prediction of inland moving MDs. High Resolution Land Data Assimilation System (HRLDAS) is used to generate improved land state .i.e. soil moisture and soil temperature profiles by means of NOAH-MP land-surface model. Validation of the model simulated basic atmospheric parameters at surface layer and troposphere reveals that the incursion of high resolution land state yields least Root Mean Squared Error (RMSE) with a higher correlation coefficient and facilitates accurate depiction of MDs. Rainfall verification shows that HRLDAS simulations are spatially and quantitatively in more agreement with the observations and the improved surface characteristics could result in the realistic reproduction of the storm spatial structure, movement as well as intensity. These results signify the necessity of investigating more into the land surface-rainfall feedbacks through modifications in moisture flux convergence within the storm.

  3. On the Representation of Heterogeneity in Land-Surface-Atmosphere Coupling

    Science.gov (United States)

    de Vrese, Philipp; Schulz, Jan-Peter; Hagemann, Stefan

    2016-07-01

    A realistic representation of processes that are not resolved by the model grid is one of the key challenges in Earth-system modelling. In particular, the non-linear nature of processes involved makes a representation of the link between the atmosphere and the land surface difficult. This is especially so when the land surface is horizontally strongly heterogeneous. In the majority of present day Earth system models two strategies are pursued to couple the land surface and the atmosphere. In the first approach, surface heterogeneity is not explicitly accounted for, instead effective parameters are used to represent the entirety of the land surface in a model's grid box (parameter-aggregation). In the second approach, subgrid-scale variability at the surface is explicitly represented, but it is assumed that the blending height is located below the lowest atmospheric model level (simple flux-aggregation). Thus, in both approaches the state of the atmosphere is treated as being horizontally homogeneous within a given grid box. Based upon the blending height concept, an approach is proposed that allows for a land-surface-atmosphere coupling in which horizontal heterogeneity is considered not only at the surface, but also within the lowest layers of the atmosphere (the VERTEX scheme). Below the blending height, the scheme refines the turbulent mixing process with respect to atmospheric subgrid fractions, which correspond to different surface features. These subgrid fractions are not treated independently of each other, since an explicit horizontal component is integrated into the turbulent mixing process. The scheme was implemented into the JSBACH model, the land component of the Max Planck Institute for Meteorology's Earth-system model, when coupled to the atmospheric general circulation model ECHAM. The single-column version of the Earth system model is used in two example cases in order to demonstrate how the effects of surface heterogeneity are transferred into the

  4. The retrieval of land surface albedo in rugged terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2012-01-01

    Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed s

  5. Determining Land-Surface Parameters from the ERS Wind Scatterometer

    NARCIS (Netherlands)

    Woodhouse, I.H.; Hoekman, D.H.

    2000-01-01

    The ERS-1 wind scatterometer (WSC) has a resolution cell of about 50 km but provides a high repetition rate (less than four days) and makes measurements at multiple incidence angles. In order to retrieve quantitative geophysical parameters over land surfaces using this instrument, a method is presen

  6. estimation of land surface temperature of kaduna metropolis, nigeria

    African Journals Online (AJOL)

    Zaharaddeen et. al

    Understanding the spatial variation of Land Surface Temperature. (LST), will be ... positive correlation between mean of surface emissivity with date and ... deviation of 1.92 of LST and coefficient determinant R2 (0.46) show a ... (LST), as the prime and basic physical parameter of the earth's ..... thorough review of the paper.

  7. DISAGGREGATION OF GOES LAND SURFACE TEMPERATURES USING SURFACE EMISSIVITY

    Science.gov (United States)

    Accurate temporal and spatial estimation of land surface temperatures (LST) is important for modeling the hydrological cycle at field to global scales because LSTs can improve estimates of soil moisture and evapotranspiration. Using remote sensing satellites, accurate LSTs could be routine, but unfo...

  8. The retrieval of land surface albedo in rugged terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2012-01-01

    Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed s

  9. The retrieval of land surface albedo in rugged terrain

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Menenti, M.

    2012-01-01

    Land surface albedo may be derived from the satellite data through the estimation of a bidirectional reflectance distribution function (BRDF) model and angular integration. However many BRDF models do not consider explicitly the topography. In rugged terrain, the topography influences the observed

  10. Simultaneous inversion of multiple land surface parameters from MODIS optical-thermal observations

    Science.gov (United States)

    Ma, Han; Liang, Shunlin; Xiao, Zhiqiang; Shi, Hanyu

    2017-06-01

    Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface variables usually focus on individual parameters separately even from the same satellite observations, resulting in inconsistent products. Moreover, no efforts have been made to generate global products from integrated observations from the optical to Thermal InfraRed (TIR) spectrum. Particularly, Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal, which contains both reflected and emitted radiation. In this paper, we propose a unified algorithm for simultaneously retrieving six land surface parameters - Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Emissivity (LSE), Land Surface Temperature (LST), and Upwelling Longwave radiation (LWUP) by exploiting MODIS visible-to-TIR observations. We incorporate a unified physical radiative transfer model into a data assimilation framework. The MODIS visible-to-TIR time series datasets include the daily surface reflectance product and MIR-to-TIR surface radiance, which are atmospherically corrected from the MODIS data using the Moderate Resolution Transmittance program (MODTRAN, ver. 5.0). LAI was first estimated using a data assimilation method that combines MODIS daily reflectance data and a LAI phenology model, and then the LAI was input to the unified radiative transfer model to simulate spectral surface reflectance and surface emissivity for calculating surface broadband albedo and emissivity, and FAPAR. LST was estimated from the MIR-TIR surface radiance data and the simulated emissivity, using an iterative optimization procedure. Lastly, LWUP was estimated using the LST and surface emissivity. The retrieved six parameters were extensively validated across six representative sites with

  11. Land surface parameter optimisation through data assimilation: the adJULES system

    Science.gov (United States)

    Raoult, Nina; Jupp, Tim; Cox, Peter

    2017-04-01

    Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. We present adJULES in a data assimilation framework and demonstrate its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85% of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

  12. Passive remote sensing of the atmospheric water vapour content above land surfaces

    Science.gov (United States)

    Bartsch, B.; Bakan, S.; Fischer, J.

    The global distribution of the atmospheric water vapour content plays an important role in the weather forecast and climate research. Nowadays there exist various methods dealing with remote sensing of the atmospheric water vapour content. Unfortunately, most of them are restricted to ocean areas, since, in general, the emission of land surfaces is not known well enough. Therefore, a new method is developed which allows the detection of the atmospheric total water vapour content from aircraft or satellite with the aid of backscattered solar radiation in the near infrared above land surfaces. The Matrix-Operator-Method has been used to simulate backscattered solar radiances, including various atmospheric profiles of temperature, pressure, water vapour, and aerosols of various types, several sun zenith angles, and different types of land surfaces. From these calculations it can be concluded, that the detection of water vapour content in cloudless atmospheres is possible with an error of < 10 % even for higher aerosol contents. In addition to the theoretical results first comparisons with aircraft measurements of the backscattered solar radiances are shown. These measurements have been carried out with the aid of OVID (Optical Visible and near Infrared Detector), a new multichannel array spectrometer, in 1993.

  13. Object-based Dimensionality Reduction in Land Surface Phenology Classification

    Directory of Open Access Journals (Sweden)

    Brian E. Bunker

    2016-11-01

    Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

  14. Stable water isotopes in the coupled atmosphere–land surface model ECHAM5-JSBACH

    Directory of Open Access Journals (Sweden)

    B. Haese

    2012-10-01

    Full Text Available In this study we present first results of a new model development, ECHAM5-JSBACH-wiso, where we have incorporated the stable water isotopes H218O and HDO as tracers in the hydrological cycle of the coupled atmosphere–land surface model ECHAM5-JSBACH. The ECHAM5-JSBACH-wiso model was run under present-day climate conditions at two different resolutions (T31L19, T63L31. A comparison between ECHAM5-JSBACH-wiso and ECHAM5-wiso shows that the coupling has a strong impact on the simulated temperature and soil wetness. Caused by these changes of temperature and the hydrological cycle, the δ18O in precipitation also shows variations from −4.5‰ up to 4.5‰. One of the clearest anomalies is shown over North-East Asia where, depending on an increase of temperature, the δ18O in precipitation increases as well. In order to analyze the sensitivity of the fractionation processes over land, we compare a set of simulations with various implementations of water isotope fractionation processes over the land surface. The simulations allow us to distinguish between no fractionation, fractionation included in the evaporation flux (from bare soil and also fractionation included in both evaporation and transpiration (from water transport through plants fluxes. The simulated δ18O and δD in precipitation of these setups generally fit well with the observations and the best agreement between observation and simulation is given in the case where no fractionation over land surface is assumed.

  15. SGP Cloud and Land Surface Interaction Campaign (CLASIC): Measurement Platforms

    Energy Technology Data Exchange (ETDEWEB)

    MA Miller; R Avissar; LK Berg; SA Edgerton; ML Fischer; TJ Jackson; B. Kustas; PJ Lamb; G McFarquhar; Q Min; B Schmid; MS Torn; DD Tuner

    2007-06-01

    The Cloud and Land Surface Interaction Campaign (CLASIC) will be conducted from June 8 to June 30, 2007, at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. Data will be collected using eight aircraft equipped with a variety of specialized sensors, four specially instrumented surface sites, and two prototype surface radar systems. The architecture of CLASIC includes a high-altitude surveillance aircraft and enhanced vertical thermodynamic and wind profile measurements that will characterize the synoptic scale structure of the clouds and the land surface within the ACRF SGP site. Mesoscale and microscale structures will be sampled with a variety of aircraft, surface, and radar observations. An overview of the measurement platforms that will be used during the CLASIC are described in this report. The coordination of measurements, especially as it relates to aircraft flight plans, will be discussed in the CLASIC Implementation Plan.

  16. Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

    Science.gov (United States)

    Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Zavodsky, Bradley T.; Srikishen, Jayanthi; Limaye, Ashutosh; Blankenship, Clay B.

    2016-01-01

    into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

  17. Understanding land surface response to changing South Asian monsoon in a warming climate

    Directory of Open Access Journals (Sweden)

    M. V. S. Ramarao

    2015-05-01

    Full Text Available Recent studies have drawn attention to a significant weakening trend of the South Asian monsoon circulation and an associated decrease in regional rainfall during the last few decades. While surface temperatures over the region have steadily risen during this period, most of the CMIP (Coupled Model Intercomparison Project global climate models have difficulties in capturing the observed decrease of monsoon precipitation, thus limiting our understanding of the regional land surface response to monsoonal changes. This problem is investigated by performing two long-term simulation experiments, with and without anthropogenic forcing, using a variable resolution global climate model having high-resolution zooming over the South Asian region. The present results indicate that anthropogenic effects have considerably influenced the recent weakening of the monsoon circulation and decline of precipitation. It is seen that the simulated increase of surface temperature over the Indian region during the post-1950s is accompanied by a significant decrease of monsoon precipitation and soil moisture. Our analysis further reveals that the land surface response to decrease of soil moisture is associated with significant reduction in evapotranspiration over the Indian land region. A future projection, based on the representative concentration pathway 4.5 (RCP4.5 scenario of the Intergovernmental panel on Climate Change (IPCC, using the same high-resolution model indicates the possibility for detecting the summer-time soil drying signal over the Indian region during the 21st century, in response to climate change. While these monsoon hydrological changes have profound socioeconomic implications, the robustness of the high-resolution simulations provides deeper insights and enhances our understanding of the regional land surface response to the changing South Asian monsoon.

  18. Land-surface studies with a directional neutron detector.

    Energy Technology Data Exchange (ETDEWEB)

    Desilets, Darin (Sandia National Laboratories, Albuquerque, NM); Brennan, James S.; Mascarenhas, Nicholas; Marleau, Peter

    2009-09-01

    Direct measurements of cosmic-ray neutron intensity were recorded with a neutron scatter camera developed at SNL. The instrument used in this work is a prototype originally designed for nuclear non-proliferation work, but in this project it was used to characterize the response of ambient neutrons in the 0.5-10 MeV range to water located on or above the land surface. Ambient neutron intensity near the land surface responds strongly to the presence of water, suggesting the possibility of an indirect method for monitoring soil water content, snow water equivalent depth, or canopy intercepted water. For environmental measurements the major advantage of measuring neutrons with the scatter camera is the limited (60{sup o}) field of view that can be obtained, which allows observations to be conducted at a previously unattainable spatial scales. This work is intended to provide new measurements of directional fluxes which can be used in the design of new instruments for passively and noninvasively observing land-surface water. Through measurements and neutron transport modeling we have demonstrated that such a technique is feasible.

  19. Photosynthesis sensitivity to climate change in land surface models

    Science.gov (United States)

    Manrique-Sunen, Andrea; Black, Emily; Verhoef, Anne; Balsamo, Gianpaolo

    2016-04-01

    Accurate representation of vegetation processes within land surface models is key to reproducing surface carbon, water and energy fluxes. Photosynthesis determines the amount of CO2 fixated by plants as well as the water lost in transpiration through the stomata. Photosynthesis is calculated in land surface models using empirical equations based on plant physiological research. It is assumed that CO2 assimilation is either CO2 -limited, radiation -limited ; and in some models export-limited (the speed at which the products of photosynthesis are used by the plant) . Increased levels of atmospheric CO2 concentration tend to enhance photosynthetic activity, but the effectiveness of this fertilization effect is regulated by environmental conditions and the limiting factor in the photosynthesis reaction. The photosynthesis schemes at the 'leaf level' used by land surface models JULES and CTESSEL have been evaluated against field photosynthesis observations. Also, the response of photosynthesis to radiation, atmospheric CO2 and temperature has been analysed for each model, as this is key to understanding the vegetation response that climate models using these schemes are able to reproduce. Particular emphasis is put on the limiting factor as conditions vary. It is found that while at present day CO2 concentrations export-limitation is only relevant at low temperatures, as CO2 levels rise it becomes an increasingly important restriction on photosynthesis.

  20. Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals

    Science.gov (United States)

    Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

    2012-01-01

    Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 14% (312 K) over desert and 17% (320 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.52% (26 K). In particular, at 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 1017 K under the most severe conditions.

  1. Simulation of CO2 and sensible/latent heat fluxes exchange between land surface and atmosphere over cropland and grassland in semi-arid region, China%半干旱区农田和草地与大气间二氧化碳和水热通量的模拟研究

    Institute of Scientific and Technical Information of China (English)

    姜纪峰; 延晓冬; 黄耀; 郭维栋; 刘辉志

    2007-01-01

    集成生物圈模型(IBIS)是目前最复杂的基于动态植被模型的陆面生物物理模型之一.应用该模型对国际CEOP计划半干旱区基准站之一的吉林通榆观测站(44°25'N , 122°52'E)草地和农田生态系统2003年全年的CO2和水、热通量变化进行模拟,并将结果与涡度相关法测定的观测值进行了对比分析,以检验IBIS模型在半干旱区的模拟能力.对比结果表明:除CO2通量模拟结果不够理想外,IBIS模型较好地模拟了通榆观测站的感热通量和潜热通量.总体上看,该模型对农田生态系统模拟的偏差小于对退化草地的模拟.%A comparison between simulated land surface fluxes and observed eddy covariance (EC) measurements was conducted to validate Integrated Biosphere Simulator (IBIS) at Tongyu field observation station (44°25'N, 122°52'E) in Jilin Province, China. Results showed that the IBIS model could reproduce net ecosystem CO2 exchange (NEE), sensible and latent heat fluxes reasonably, as indicated by correlation coefficients exceeding the significant level of 0.05. It was also evident that the NEE and sensible heat fluxes were characterized by diurnal and seasonal variation both in the grassland and the cropland ecosystems, while the latent heat fluxes correlated with evapotranspiration, only took on the diurnal variation during the growing season. Moreover, both sensible heat fluxes and the latent heat fluxes were larger in the cropland ecosystem than that in the degraded grassland ecosystem. This different characteristic was possibly correlated with vegetation growing situation in the two kinds of ecosystems. A close agreement between observation and simulation on NEE, sensible heat fluxes and latent heat flux was obtained both in the degraded grassland and the cropland ecosystems. In addition, the annual NEE in the model was overestimated by 23.21% at the grassland and 27.43% at the cropland, sensible heat flux with corresponding 9.90% and 11

  2. Simulation in Wood Industry. Part II

    Directory of Open Access Journals (Sweden)

    Mihály Varga

    2010-03-01

    Full Text Available The goal of this simulation is to introduce and realize a part of material flow of an international furniture manufacturing company. This simulation was made with a special process-simulation software, called SIMUL8. With SIMUL8 we could simulate the whole process under real circumstances, and obtain the actual values of specific parameters relevant for the company. This opportunity helped the company to develop its strategy - to maximize the production efficiency and to find out the possibble bottle-necks without making any investment, and to rearrange the workcenters effectively.

  3. Safety Assessment of Advanced Imaging Sequences II: Simulations

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2016-01-01

    An automatic approach for simulating the emitted pressure, intensity, and MI of advanced ultrasound imaging sequences is presented. It is based on a linear simulation of pressure fields using Field II, and it is hypothesized that linear simulation can attain the needed accuracy for predicting...

  4. How much does weather-driven vegetation dynamics matter in land surface modelling?

    Science.gov (United States)

    Ingwersen, Joachim; Streck, Thilo

    2016-04-01

    Land surface models (LSM) are an essential part of weather and climate models as they provide the lower boundary condition for the atmospheric models. In state-of-the-art LSMs the seasonal vegetation dynamics is "frozen". The seasonal variation of vegetation state variables, such as leaf area index or green vegetation fraction, are prescribed in lookup tables. Hence, a year-by-year variation in the development of vegetation due to changing weather conditions cannot be considered. For climate simulations, this is obviously a severe drawback. The objective of the present study was to quantify the potential error in the simulation of land surface exchange processes resulting from "frozen" vegetation dynamics. For this purpose we simulated energy and water fluxes from a winter wheat stand and a maize stand in Southwest Germany. In a first set of simulations, six years (2010 to 2015) were simulated considering weather-driven vegetation dynamics. For this purpose, we coupled the generic crop growth model GECROS with the NOAH-MP model (NOAHMP-GECROS). In a second set of simulations all vegetation-related state variables of the 2010 simulation were written to an external file and were used to overwrite the vegetation-related state variables of the simulations of the years 2011-2015. The difference between both sets was taken as a measure for the potential error introduced to the LSM due to the assumption of a "frozen" vegetation dynamics. We will present first results and discuss the impact of "frozen" vegetation dynamics on climate change simulations.

  5. Variational assimilation of land surface temperature within the ORCHIDEE Land Surface Model Version 1.2.6

    Science.gov (United States)

    Benavides Pinjosovsky, Hector Simon; Thiria, Sylvie; Ottlé, Catherine; Brajard, Julien; Badran, Fouad; Maugis, Pascal

    2017-01-01

    The SECHIBA module of the ORCHIDEE land surface model describes the exchanges of water and energy between the surface and the atmosphere. In the present paper, the adjoint semi-generator software called YAO was used as a framework to implement a 4D-VAR assimilation scheme of observations in SECHIBA. The objective was to deliver the adjoint model of SECHIBA (SECHIBA-YAO) obtained with YAO to provide an opportunity for scientists and end users to perform their own assimilation. SECHIBA-YAO allows the control of the 11 most influential internal parameters of the soil water content, by observing the land surface temperature or remote sensing data such as the brightness temperature. The paper presents the fundamental principles of the 4D-VAR assimilation, the semi-generator software YAO and a large number of experiments showing the accuracy of the adjoint code in different conditions (sites, PFTs, seasons). In addition, a distributed version is available in the case for which only the land surface temperature is observed.

  6. The Contribution of Reservoirs to Global Land Surface Water Storage Variations

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Tian; Nijssen, Bart; Gao, Huilin; Lettenmaier, Dennis P.

    2016-12-21

    Man-made reservoirs play a key role in the terrestrial water system. They alter water fluxes at the land surface and impact surface water storage through water management regulations for diverse purposes such as irrigation, municipal water supply, hydropower generation, and flood control. Although most developed countries have established sophisticated observing systems for many variables in the land surface water cycle, long-term and consistent records of reservoir storage are much more limited and not always shared. Furthermore, most land surface hydrological models do not represent the effects of water management activities. Here, the contribution of reservoirs to seasonal water storage variations is investigated using a large-scale water management model to simulate the effects of reservoir management at basin and continental scales. The model was run from 1948 to 2010 at a spatial resolution of 0.258 latitude–longitude. A total of 166 of the largest reservoirs in the world with a total capacity of about 3900 km3 (nearly 60%of the globally integrated reservoir capacity) were simulated. The global reservoir storage time series reflects the massive expansion of global reservoir capacity; over 30 000 reservoirs have been constructed during the past half century, with a mean absolute interannual storage variation of 89 km3. The results indicate that the average reservoir-induced seasonal storage variation is nearly 700 km3 or about 10%of the global reservoir storage. For some river basins, such as the Yellow River, seasonal reservoir storage variations can be as large as 72%of combined snow water equivalent and soil moisture storage.

  7. The Effect of Errors in Snow Assimilation on Land Surface Modeling

    Science.gov (United States)

    Cosgrove, Brian A.; Houser, Paul R.; Atlas, Robert (Technical Monitor)

    2001-01-01

    The accurate portrayal of the hydrological cycle is extremely important in land surface modeling. Central to this effort is the treatment of snow, as errors in the representation of this quantity can impact practically all other modeled quantities through alterations in the water and energy balances. Although land surface model (LSM) simulations can benefit from the assimilation of snow cover and snow depth observations, they can be negatively impacted if such observations contain errors or if a model bias exists in the simulation of surface or soil temperatures. Both cases may lead to excessive melting or growth of snow packs, and to large alterations in both the energy and water balances. Such problems in the snow assimilation process, made evident by the repeated melting and replenishing of snow pack over significant areas of the United States, exists in the Eta Data Assimilation System and is a product of the EDAS system's direct insertion assimilation of snow data. Occurring on a 24 hour cycle, the repeated melting infuses the soil column with a large quantity of water that upsets the hydrological cycle. In an effort to quantify the impacts of such errors in snow assimilation on water and energy budgets, a series of Mosaic LSM simulations were performed over the 12 month period covering October 1998 to October 1999.

  8. High-resolution Continental Scale Land Surface Model incorporating Land-water Management in United States

    Science.gov (United States)

    Shin, S.; Pokhrel, Y. N.

    2016-12-01

    Land surface models have been used to assess water resources sustainability under changing Earth environment and increasing human water needs. Overwhelming observational records indicate that human activities have ubiquitous and pertinent effects on the hydrologic cycle; however, they have been crudely represented in large scale land surface models. In this study, we enhance an integrated continental-scale land hydrology model named Leaf-Hydro-Flood to better represent land-water management. The model is implemented at high resolution (5km grids) over the continental US. Surface water and groundwater are withdrawn based on actual practices. Newly added irrigation, water diversion, and dam operation schemes allow better simulations of stream flows, evapotranspiration, and infiltration. Results of various hydrologic fluxes and stores from two sets of simulation (one with and the other without human activities) are compared over a range of river basin and aquifer scales. The improved simulations of land hydrology have potential to build consistent modeling framework for human-water-climate interactions.

  9. Developing a synergy algorithm for land surface temperature: the SEN4LST project

    Science.gov (United States)

    Sobrino, Jose A.; Jimenez, Juan C.; Ghent, Darren J.

    2013-04-01

    Land surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. An adequate characterization of LST distribution and its temporal evolution requires measurements with detailed spatial and temporal frequencies. With the advent of the Sentinel 2 (S2) and 3 (S3) series of satellites a unique opportunity exists to go beyond the current state of the art of single instrument algorithms. The Synergistic Use of The Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST) project aims at developing techniques to fully utilize synergy between S2 and S3 instruments in order to improve LST retrievals. In the framework of the SEN4LST project, three LST retrieval algorithms were proposed using the thermal infrared bands of the Sea and Land Surface Temperature Retrieval (SLSTR) instrument on board the S3 platform: split-window (SW), dual-angle (DA) and a combined algorithm using both split-window and dual-angle techniques (SW-DA). One of the objectives of the project is to select the best algorithm to generate LST products from the synergy between S2/S3 instruments. In this sense, validation is a critical step in the selection process for the best performing candidate algorithm. A unique match-up database constructed at University of Leicester (UoL) of in situ observations from over twenty ground stations and corresponding brightness temperature (BT) and LST match-ups from multi-sensor overpasses is utilised for validating the candidate algorithms. Furthermore, their performance is also evaluated against the standard ESA LST product and the enhanced offline UoL LST product. In addition, a simulation dataset is constructed using 17 synthetic images of LST and the radiative transfer model MODTRAN carried under 66 different atmospheric conditions. Each candidate LST

  10. Achieving scale-independent land-surface flux estimates - Application of the Multiscale Parameter Regionalization (MPR) to the Noah-MP land-surface model across the contiguous USA

    Science.gov (United States)

    Thober, S.; Mizukami, N.; Samaniego, L. E.; Attinger, S.; Clark, M. P.; Cuntz, M.

    2016-12-01

    Land-surface models use a variety of process representations to calculate terrestrial energy, water and biogeochemical fluxes. These process descriptions are usually derived from point measurements but are scaled to much larger resolutions in applications that range from about 1 km in catchment hydrology to 100 km in climate modelling. Both, hydrologic and climate models are nowadays run on different spatial resolutions, using the exact same land surface representations. A fundamental criterion for the physical consistency of land-surface simulations across scales is that a flux estimated over a given area is independent of the spatial model resolution (i.e., the flux-matching criterion). The Noah-MP land surface model considers only one soil and land cover type per model grid cell without any representation of subgrid variability, implying a weak flux-matching. A fractional approach simulates subgrid variability but it requires a higher computational demand than using effective parameters and it is used only for land cover in current land surface schemes. A promising approach to derive scale-independent parameters is the Multiscale Parameter Regionalization (MPR) technique, which consists of two steps: first, it applies transfer functions directly to high-resolution data (such as 100 m soil maps) to derive high-resolution model parameter fields, acknowledging the full subgrid variability. Second, it upscales these high-resolution parameter fields to the model resolution by using appropriate upscaling operators. MPR has shown to improve substantially the scalability of hydrologic models. Here, we apply the MPR technique to the Noah-MP land-surface model for a large sample of basins distributed across the contiguous USA. Specifically, we evaluate the flux-matching criterion for several hydrologic fluxes such as evapotranspiration and total runoff at scales ranging from 3 km to 48 km. We also investigate a p-norm scaling operator that goes beyond the current

  11. Coupled atmospheric, land surface, and subsurface modeling: Exploring water and energy feedbacks in three-dimensions

    Science.gov (United States)

    Davison, Jason H.; Hwang, Hyoun-Tae; Sudicky, Edward A.; Lin, John C.

    2015-12-01

    Human activities amplified by climate change pose a significant threat to the sustainability of water resources. Coupled climate-hydrologic simulations commonly predict these threats by combining shallow 1-D land surface models (LSMs) with traditional 2-D and 3-D hydrology models. However, these coupled models limit the moisture and energy-feedback dynamics to the shallow near-surface. This paper presents a novel analysis by applying an integrated variably-saturated subsurface/surface hydrology and heat transport model, HydroGeoSphere (HGS), as a land surface model (LSM). Furthermore, this article demonstrates the coupling of HGS to a simple 0-D atmospheric boundary layer (ABL) model. We then applied our coupled HGS-ABL model to three separate test cases and reproduced the strong correlation between the atmospheric energy balance to the depth of the groundwater table. From our simulations, we found that conventional LSMs may overestimate surface temperatures for extended drought periods because they underestimate the heat storage in the groundwater zone. Our final test case of the atmospheric response to drought conditions illustrated that deeper roots buffered the atmosphere better than shallow roots by maintaining higher latent heat fluxes, lower sensible heat fluxes, and lower surface and atmospheric temperatures.

  12. A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms

    Directory of Open Access Journals (Sweden)

    João P. A. Martins

    2016-09-01

    Full Text Available Land surface temperature (LST is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This study analyzes calibration strategies while considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere, indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis—Satellite Application Facility to calibrate its LST algorithms, applied both for current and forthcoming sensors.

  13. Geostatistical Solutions for Downscaling Remotely Sensed Land Surface Temperature

    Science.gov (United States)

    Wang, Q.; Rodriguez-Galiano, V.; Atkinson, P. M.

    2017-09-01

    Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.

  14. Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

    Science.gov (United States)

    Farhadi, Leila; Reichle, Rolf H.; DeLannoy, Gabrielle J. M.; Kimball, John S.

    2014-01-01

    The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

  15. Land Surface Models Evaluation for Two Different Land-Cover Types: Cropland and Forest

    Directory of Open Access Journals (Sweden)

    Daeun Kim

    2016-02-01

    Full Text Available Land Surface Model (LSM is an important tool used to understand the complicated hydro-meteorological flux interaction systems between the land surface and atmosphere in hydrological cycles. Over the past few decades, LSMs have further developed to more accurately estimate weather and climate hydrological processes. Common Land Model (CLM and Noah Land Surface Model (Noah LSM are used in this paper to estimate the hydro-meteorological fluxes for model applicability assessment at two different flux tower sites in Korea during the summer monsoon season. The estimated fluxes such as net radiation (RN, sensible heat flux (H, latent heat flux (LE, ground heat flux (G, and soil temperature (Ts were compared with the observed data from flux towers. The simulated RN from both models corresponded well with the in situ data. The root-mean-square error (RMSE values were 39 - 44 W m-2 for the CLM and 45 - 50 W m-2 for the Noah LSM while the H and LE showed relatively larger discrepancies with each observation. The estimated Ts from the CLM corresponded comparatively well with the observed soil temperature. The CLM estimations generally showed better statistical results than those from the Noah LSM, even though the estimated hydro-meteorological fluxes from both models corresponded reasonably with the observations. A sensitivity test indicated that differences according to different locations between the estimations from models and observations were caused by field conditions including the land-cover type and soil texture. In addition the estimated RN, H, LE, and G were more sensitive than the estimated Ts in both models.

  16. Water balance in the Amazon basin from a land surface model ensemble

    Energy Technology Data Exchange (ETDEWEB)

    Getirana, Augusto; Dutra, Emanuel; Guimberteau, Matthieu; Kam, Jonghun; Li, Hongyi; Decharme, Bertrand; Zhang, Zhengqiu J.; Ducharne, Agnes; Boone, Aaron; Balsamo, Gianpaolo; Rodell, Matthew; Mounirou Toure, Ally; Xue, Yongkang; Peters-Lidard, Christa D.; Kumar, Sujay V.; Arsenault, Kristi Rae; Drapeau, Guillaume; Leung, Lai-Yung R.; Ronchail, Josyane; Sheffield, Justin

    2014-12-06

    Despite recent advances in modeling and remote sensing of land surfaces, estimates of the global water budget are still fairly uncertain. The objective of this study is to evaluate the water budget of the Amazon basin based on several state-of-the-art land surface model (LSM) outputs. Water budget variables [total water storage (TWS), evapotranspiration (ET), surface runoff (R) and baseflow (B)] are evaluated at the basin scale using both remote sensing and in situ data. Fourteen LSMs were run using meteorological forcings at a 3-hourly time step and 1-degree spatial resolution. Three experiments are performed using precipitation which has been rescaled to match monthly global GPCP and GPCC datasets and the daily HYBAM dataset for the Amazon basin. R and B are used to force the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration, and GRACE TWS estimates in different catchments. At the basin scale, simulated ET ranges from 2.39mm.d-1 to 3.26mm.d-1 and a low spatial correlation between ET and P indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget variables vary significantly as a function of both the LSM and precipitation used, but simulated TWS generally agree at the basin scale. The best water budget simulations resulted from experiments using the HYBAM dataset, mostly explained by a denser rainfall gauge network the daily rescaling.

  17. Application of the GERTS II simulator in the industrial environment.

    Science.gov (United States)

    Whitehouse, G. E.; Klein, K. I.

    1971-01-01

    GERT was originally developed to aid in the analysis of stochastic networks. GERT can be used to graphically model and analyze complex systems. Recently a simulator model, GERTS II, has been developed to solve GERT Networks. The simulator language used in the development of this model was GASP II A. This paper discusses the possible application of GERTS II to model and analyze (1) assembly line operations, (2) project management networks, (3) conveyor systems and (4) inventory systems. Finally, an actual application dealing with a job shop loading problem is presented.

  18. Land surface changes enhanced drought over the Loess Plateau

    Science.gov (United States)

    Xu, Xianli; Liu, Meixian

    2017-04-01

    In order to prevent the severe soil-water erosion over the Loess Plateau (LP), the Chinese Government initiated large scale ecological restoration (ER) in the past half century. The ER had successfully reduced soil erosion however also changed the land surface and altered the regional water-energy balance and consequently the dryness/wetness conditions, which in turn affects the vegetation. Knowledge of the impacts of the ER on dryness/wetness conditions is essential for developing future effective ER measures. For this purpose, a new drought index, the standardized wetness index (SWI), was proposed. The SWI can represent the dryness/wetness brought by solely climate change (denoted as SWIf in this case), and the dryness/wetness brought by the joint effects of climate change and land surface change (SWI_m). A total of 13 main catchments were selected to investigate the effects of ER on dryness/wetness conditions during 1961-2009 over LP. Results showed that the overall increasing parameter n (a parameter of the Budyko formulae) could be well explained by the ER measures (R^2=1) in these catchments. The SWIf and SWIm had similar fluctuating features and exhibited downward trends. However, the SWIm had larger negative trends than the SWI_f, implying that ER actions enhanced the drought conditions over the drying LP in the past decades. Therefore, we suggest that the government should manage and maintain the existing achievements but not further expand revegetation because of unintended consequences on drought vulnerability.

  19. The international surface temperature initiative's global land surface databank

    Science.gov (United States)

    Lawrimore, J. H.; Rennie, J.; Gambi de Almeida, W.; Christy, J.; Flannery, M.; Gleason, B.; Klein-Tank, A.; Mhanda, A.; Ishihara, K.; Lister, D.; Menne, M. J.; Razuvaev, V.; Renom, M.; Rusticucci, M.; Tandy, J.; Thorne, P. W.; Worley, S.

    2013-09-01

    The International Surface Temperature Initiative (ISTI) consists of an end-to-end process for land surface air temperature analyses. The foundation is the establishment of a global land surface Databank. This builds upon the groundbreaking efforts of scientists in the 1980s and 1990s. While using many of their principles, a primary aim is to improve aspects including data provenance, version control, openness and transparency, temporal and spatial coverage, and improved methods for merging disparate sources. The initial focus is on daily and monthly timescales. A Databank Working Group is focused on establishing Stage-0 (original observation forms) through Stage-3 data (merged dataset without quality control). More than 35 sources of data have already been added and efforts have now turned to development of the initial version of the merged dataset. Methods have been established for ensuring to the extent possible the provenance of all data from the point of observation through all intermediate steps to final archive and access. Databank submission procedures were designed to make the process of contributing data as easy as possible. All data are provided openly and without charge. We encourage the use of these data and feedback from interested users.

  20. Derived Land Surface Emissivity From Suomi NPP CrIS

    Science.gov (United States)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

    2012-01-01

    Presented here is the land surface IR spectral emissivity retrieved from the Cross-track Infrared Sounder (CrIS) measurements. The CrIS is aboard the Suomi National Polar-orbiting Partnership (NPP) satellite launched on October 28, 2011. We describe the retrieval algorithm, demonstrate the surface emissivity retrieved with CrIS measurements, and inter-comparison with the Infrared Atmospheric Sounding Interferometer (IASI) emissivity. We also demonstrate that surface emissivity from satellite measurements can be used in assistance of monitoring global surface climate change, as a long-term measurement of IASI and CrIS will be provided by the series of EUMETSAT MetOp and US Joint Polar Satellite System (JPSS) satellites. Monthly mean surface properties are produced using last 5-year IASI measurements. A temporal variation indicates seasonal diversity and El Nino/La Nina effects not only shown on the water but also on the land. Surface spectral emissivity and skin temperature from current and future operational satellites can be utilized as a means of long-term monitoring of the Earth's environment. CrIS spectral emissivity are retrieved and compared with IASI. The difference is small and could be within expected retrieval error; however it is under investigation.

  1. Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

    Science.gov (United States)

    Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

    2013-01-01

    Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

  2. Huntington II Simulation Program-POLUT. Teacher's Guide.

    Science.gov (United States)

    Braun, L.; And Others

    This teacher's guide is written to accompany the Huntington II Simulation Program - POLUT. POLUT is a program written in BASIC which provides simulation of the interaction between water and waste. It creates a context within which the user can control specific variables which effect the quality of a water resource. The teacher's guide provides…

  3. Utilization of satellite-derived estimates of meteorological and land surface characteristics in the Land Surface Model for vast agricultural region territory

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena

    2015-04-01

    The method has been elaborated to evaluate the water and heat regime characteristics of the territory on a regional scale for the vegetation season based on a physical-mathematical model of water and heat exchange between vegetation covered land surface and atmosphere (LSM, Land Surface Model) appropriate for using satellite information on land surface and meteorological conditions. The developed model is intended for calculating soil water content, evapotranspiration (evaporation from bare soil and transpiration by vegetation), vertical water and heat fluxes as well as land surface and vegetation cover temperatures and vertical distributions of temperature and moisture in the active soil layer. Parameters of the model are soil and vegetation characteristics and input variables are meteorological characteristics. Their values have been obtained from ground-based observations at agricultural meteorological stations and satellite-based measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua and SEVIRI (geostationary satellites Meteosat-9, -10). The AVHRR data have been used to build the estimates of three types of land surface temperature (LST): land skin temperature Tsg, air temperature at a level of vegetation cover Ta and efficient radiation temperature Tseff, emissivity E, normalized vegetation index NDVI, vegetation cover fraction B, leaf area index LAI, and precipitation. The set of estimates derived from MODIS data has comprised values of LST Tls, E, NDVI and LAI. The SEVIRI-based retrievals have included Tls, Ta, Е at daylight and nighttime, LAI (daily) and precipitation. The case study has been carried out for agricultural Central Black Earth region of the European Russia of 227,300 sq.km containing 7 regions of the Russian Federation for years 2009-2013 vegetation seasons. Estimates of described characteristics have been built with the help of the developed original and improved pre-existing methods and technologies of thematic processing

  4. Widespread land surface wind decline in the Northern Hemisphere partly attributed to land surface changes

    Science.gov (United States)

    Thepaut, J.; Vautard, R.; Cattiaux, J.; Yiou, P.; Ciais, P.

    2010-12-01

    pressure gradients, and modeled winds from weather re-analyses do not exhibit any comparable stilling trends than at surface stations. For instance, large-scale circulation changes captured in the most recent European Centre for Medium Range Weather Forecast re-analysis (ERA-interim) can only explain only up to 10-50% of the wind stilling, depending on the region. In addition, a significant amount of the slow-down could originate from a generalized increase in surface roughness, due for instance to forest growth and expansion, and urbanization. This hypothesis, which could explain up to 60% of the decline, is supported by remote sensing observations and theoretical calculations combined with meso-scale model simulations. For future wind power energy resource, the part of wind decline due to land cover changes is easier to cope with than that due to global atmospheric circulation slow down.

  5. Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

    Science.gov (United States)

    Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

    2017-04-01

    Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM

  6. Stable water isotopes in the coupled atmosphere–land surface model ECHAM5-JSBACH

    Directory of Open Access Journals (Sweden)

    B. Haese

    2013-09-01

    Full Text Available In this study we present first results of a new model development, ECHAM5-JSBACH-wiso, where we have incorporated the stable water isotopes H218O and HDO as tracers in the hydrological cycle of the coupled atmosphere–land surface model ECHAM5-JSBACH. The ECHAM5-JSBACH-wiso model was run under present-day climate conditions at two different resolutions (T31L19, T63L31. A comparison between ECHAM5-JSBACH-wiso and ECHAM5-wiso shows that the coupling has a strong impact on the simulated temperature and soil wetness. Caused by these changes of temperature and the hydrological cycle, the δ18O in precipitation also shows variations from −4‰ up to 4‰. One of the strongest anomalies is shown over northeast Asia where, due to an increase of temperature, the δ18O in precipitation increases as well. In order to analyze the sensitivity of the fractionation processes over land, we compare a set of simulations with various implementations of these processes over the land surface. The simulations allow us to distinguish between no fractionation, fractionation included in the evaporation flux (from bare soil and also fractionation included in both evaporation and transpiration (from water transport through plants fluxes. While the isotopic composition of the soil water may change for δ18O by up to +8&permil:, the simulated δ18O in precipitation shows only slight differences on the order of ±1‰. The simulated isotopic composition of precipitation fits well with the available observations from the GNIP (Global Network of Isotopes in Precipitation database.

  7. Defects and diffusion, theory & simulation II

    CERN Document Server

    Fisher, David J

    2010-01-01

    This second volume in a new series covering entirely general results in the fields of defects and diffusion includes 356 abstracts of papers which appeared between the end of 2009 and the end of 2010. As well as the abstracts, the volume includes original papers on theory/simulation, semiconductors and metals: ""Predicting Diffusion Coefficients from First Principles ..."" (Mantina, Chen & Liu), ""Gouge Assessment for Pipes ..."" (Meliani, Pluvinage & Capelle), ""Simulation of the Impact Behaviour of ... Hollow Sphere Structures"" (Ferrano, Speich, Rimkus, Merkel & Öchsner), ""Elastic-Plastic

  8. On the potential application of land surface models for drought monitoring in China

    Science.gov (United States)

    Zhang, Liang; Zhang, Huqiang; Zhang, Qiang; Li, Yaohui; Zhao, Jianhua

    2017-05-01

    The potential of using land surface models (LSMs) to monitor near-real-time drought has not been fully assessed in China yet. In this study, we analyze the performance of such a system with a land surface model (LSM) named the Australian Community Atmosphere Biosphere Land Exchange model (CABLE). The meteorological forcing datasets based on reanalysis products and corrected by observational data have been extended to near-real time for semi-operational trial. CABLE-simulated soil moisture (SM) anomalies are used to characterize drought spatial and temporal evolutions. One outstanding feature in our analysis is that with the same meteorological data, we have calculated a range of drought indices including Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI). We have assessed the similarity among these indices against observed SM over a number of regions in China. While precipitation is the dominant factor in the drought development, relationships between precipitation, evaporation, and soil moisture anomalies vary significantly under different climate regimes, resulting in different characteristics of droughts in China. The LSM-based trial system is further evaluated for the 1997/1998 drought in northern China and 2009/2010 drought in southwestern China. The system can capture the severities and temporal and spatial evolutions of these drought events well. The advantage of using a LSM-based drought monitoring system is further demonstrated by its potential to monitor other consequences of drought impacts in a more physically consistent manner.

  9. On the potential application of land surface models for drought monitoring in China

    Science.gov (United States)

    Zhang, Liang; Zhang, Huqiang; Zhang, Qiang; Li, Yaohui; Zhao, Jianhua

    2016-01-01

    The potential of using land surface models (LSMs) to monitor near-real-time drought has not been fully assessed in China yet. In this study, we analyze the performance of such a system with a land surface model (LSM) named the Australian Community Atmosphere Biosphere Land Exchange model (CABLE). The meteorological forcing datasets based on reanalysis products and corrected by observational data have been extended to near-real time for semi-operational trial. CABLE-simulated soil moisture (SM) anomalies are used to characterize drought spatial and temporal evolutions. One outstanding feature in our analysis is that with the same meteorological data, we have calculated a range of drought indices including Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI). We have assessed the similarity among these indices against observed SM over a number of regions in China. While precipitation is the dominant factor in the drought development, relationships between precipitation, evaporation, and soil moisture anomalies vary significantly under different climate regimes, resulting in different characteristics of droughts in China. The LSM-based trial system is further evaluated for the 1997/1998 drought in northern China and 2009/2010 drought in southwestern China. The system can capture the severities and temporal and spatial evolutions of these drought events well. The advantage of using a LSM-based drought monitoring system is further demonstrated by its potential to monitor other consequences of drought impacts in a more physically consistent manner.

  10. Improving the Fit of a Land-Surface Model to Data Using its Adjoint

    Science.gov (United States)

    Raoult, Nina; Jupp, Tim; Cox, Peter; Luke, Catherine

    2016-04-01

    Land-surface models (LSMs) are crucial components of the Earth System Models (ESMs) which are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. In this study, JULES is automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. We present an introduction to the adJULES system and demonstrate its ability to improve the model-data fit using eddy covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the 5 Plant Functional Types (PFTS) in JULES. The optimised PFT-specific parameters improve the performance of JULES over 90% of the FLUXNET sites used in the study. These reductions in error are shown and compared to reductions found due to site-specific optimisations. Finally, we show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

  11. Practical split-window algorithm for retrieving land surface temperature over agricultural areas from ASTER data

    Science.gov (United States)

    Wang, Songhan; He, Longhua

    2014-01-01

    A practical split-window algorithm which involves two parameters (transmittance and emissivity) utilized to retrieve land-surface temperature over agricultural areas from the Advanced Spaceborne Thermal Emission and Reflection Radiometer data is presented. First, by calculating the relationship between thermal radiation intensity and temperature, the Planck function is simplified using exponential function which is applied to deduce the split-window algorithm. Second, how to obtain transmittance from water vapor content and the method for estimating emissivity using normalized difference vegetation index are discussed in detail. Sensitivity analysis demonstrates that the algorithm is not sensitive to these two parameters. Finally, a standard atmospheric simulation method has been used to validate the proposed algorithm, and comparison between the algorithm and the prior study has been carried out. The results indicate that the average accuracy is 0.32 K for the case without error in both transmittance and emissivity, which is better than the prior algorithm. The accuracy is also 0.32 K when the transmittance is computed from the water content by piecewise cubic polynomial fit. The accuracy is about 0.30 K˜0.33 K corresponding to different Pv (Pv is the proportion of vegetation) values, which indicates that this algorithm is suitable for different land surface types over agricultural areas.

  12. PEP-II RF feedback system simulation

    Energy Technology Data Exchange (ETDEWEB)

    Tighe, R. [Stanford Linear Accelerator Center, Menlo Park, CA (United States)

    1996-08-01

    A model containing the fundamental impedance of the PEP-II cavity along with the longitudinal beam dynamics and RF feedback system components is in use. It is prepared in a format allowing time-domain as well as frequency-domain analysis and full graphics capability. Matlab and Simulink are control system design and analysis programs (widely available) with many built-in tools. The model allows the use of compiled C-code modules for compute intensive portions. We desire to represent as nearly as possible the components of the feedback system including all delays, sample rates and applicable nonlinearities. (author)

  13. Machine Learning and Cosmological Simulations II: Hydrodynamical Simulations

    CERN Document Server

    Kamdar, Harshil M; Brunner, Robert J

    2015-01-01

    We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations. In this work, we show that ML is a promising technique to study galaxy formation in the backdrop of a hydrodynamical simulation. We use the Illustris Simulation to train and test various sophisticated machine learning algorithms. By using only essential dark matter halo physical properties and no merger history, our model predicts the gas mass, stellar mass, black hole mass, star formation rate, $g-r$ color, and stellar metallicity fairly robustly. Our results provide a unique and powerful phenomenological framework to explore the galaxy-halo connection that is built upon a solid hydrodynamical simulation. The promising reproduction of the listed galaxy properties demonstrably place ML as a promising and a significantly more computationally efficient tool to study small-scale structure formation. We find that ML mimics a full-blown hydro...

  14. Machine learning and cosmological simulations - II. Hydrodynamical simulations

    Science.gov (United States)

    Kamdar, Harshil M.; Turk, Matthew J.; Brunner, Robert J.

    2016-04-01

    We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations. In this work, we show that ML is a promising technique to study galaxy formation in the backdrop of a hydrodynamical simulation. We use the Illustris simulation to train and test various sophisticated ML algorithms. By using only essential dark matter halo physical properties and no merger history, our model predicts the gas mass, stellar mass, black hole mass, star formation rate, g - r colour, and stellar metallicity fairly robustly. Our results provide a unique and powerful phenomenological framework to explore the galaxy-halo connection that is built upon a solid hydrodynamical simulation. The promising reproduction of the listed galaxy properties demonstrably place ML as a promising and a significantly more computationally efficient tool to study small-scale structure formation. We find that ML mimics a full-blown hydrodynamical simulation surprisingly well in a computation time of mere minutes. The population of galaxies simulated by ML, while not numerically identical to Illustris, is statistically robust and physically consistent with Illustris galaxies and follows the same fundamental observational constraints. ML offers an intriguing and promising technique to create quick mock galaxy catalogues in the future.

  15. Four-stream Radiative Transfer Parameterization Scheme in a Land Surface Process Model

    Institute of Scientific and Technical Information of China (English)

    ZHOU Wenyan; GUO Pinwen; LUO Yong; Kuo-Nan LIOU; Yu GU; Yongkang XUE

    2009-01-01

    Accurate estimates of albedos are required in climate modeling. Accurate and simple schemes for radiative transfer within canopy are required for these estimates, but severe limitations exist. This paper developed a four-stream solar radiative transfer model and coupled it with a land surface process model. The radiative model uses a four-stream approximation method as in the atmosphere to obtain analytic solutions of the basic equation of canopy radiative transfer. As an analytical model, the four-stream radiative transfer model can be easily applied efficiently to improve the parameterization of land surface radiation in climate models. Our four-stream solar radiative transfer model is based on a two-stream short wave radiative transfer model. It can simulate short wave solar radiative transfer within canopy according to the relevant theory in the atmosphere. Each parameter of the basic radiative transfer equation of canopy has special geometry and optical characters of leaves or canopy. The upward or downward radiative fluxes are related to the diffuse phase function, the G-function, leaf reflectivity and transmission, leaf area index, and the solar angle of the incident beam.The four-stream simulation is compared with that of the two-stream model. The four-stream model is proved successful through its consistent modeling of canopy albedo at any solar incident angle. In order to compare and find differences between the results predicted by the four-and two-stream models, a number of numerical experiments are performed through examining the effects of different leaf area indices, leaf angle distributions, optical properties of leaves, and ground surface conditions on the canopy albcdo. Parallel experiments show that the canopy albedos predicted by the two models differ significantly when the leaf angle distribution is spherical and vertical. The results also show that the difference is particularly great for different incident solar beams.One additional

  16. An integrated modelling framework for regulated river systems in Land Surface Hydrological Models

    Science.gov (United States)

    Rehan Anis, Muhammad; razavi, Saman; Wheater, Howard

    2017-04-01

    Many of the large river systems around the world are highly regulated with numerous physical flow control and storage structures as well as a range of water abstraction rules and regulations. Most existing Land Surface Models (LSM) do not represent the modifications to the hydrological regimes introduced by water management (reservoirs, irrigation diversions, etc.). The interactions between natural hydrological processes and changes in water and energy fluxes and storage due to human interventions are important to the understanding of how these systems may respond to climate change amongst other drivers for change as well as to the assessment of their feedbacks to the climate system at regional and global scales. This study presents an integrated modelling approach to include human interventions within natural hydrological systems using a fully coupled modelling platform. The Bow River Basin in Alberta (26,200 km2), one of the most managed Canadian rivers, is used to demonstrate the approach. We have dynamically linked the MESH modelling system, which embeds the Canadian Land Surface Scheme (CLASS), with the MODSIM-DSS water management modelling tool. MESH models the natural hydrology while MODSIM optimizes the reservoir operation of 4 simulated reservoirs to satisfy demands within the study basin. MESH was calibrated for the catchments upstream the reservoirs and gave good performance (NSE = 0.81) while BIAS was only 2.3% at the catchment outlet. Without coupling with MODSIM (i.e. no regulation), simulated hydrographs at the catchment outlet were in complete disagreement with observations (NSE = 0.28). The coupled model simulated the optimization introduced by the operation of the multi-reservoir system in the Bow river basin and shows excellent agreement between observed and simulated hourly flows (NSE = 0.98). Irrigation demands are fully satisfied during summer, however, there are some shortages in winter demand from industries, which can be rectified by

  17. Improved in-situ methods for determining land surface emissivity

    Science.gov (United States)

    Göttsche, Frank; Olesen, Folke; Hulley, Glynn

    2014-05-01

    The accurate validation of LST satellite products, such as the operational LST retrieved by the Land Surface Analysis - Satellite Application Facility (LSA-SAF), requires accurate knowledge of emissivity for the areas observed by the ground radiometers as well as for the area observed by the satellite sensor. Especially over arid regions, the relatively high uncertainty in land surface emissivity (LSE) limits the accuracy with which land surface temperature (LST) can be retrieved from thermal infrared (TIR) radiance measurements. LSE uncertainty affects LST obtained from satellite measurements and in-situ radiance measurements alike. Furthermore, direct comparisons between satellite sensors and ground based sensors are complicated by spatial scale mismatch: ground radiometers usually observe some 10 m2, whereas satellite sensors typically observe between 1 km2 and 100 km2. Therefore, validation sites have to be carefully selected and need to be characterised on the scale of the ground radiometer as well as on the scale of the satellite pixel. The permanent stations near Gobabeb (Namibia; hyper-arid desert climate) and Dahra (Senegal; hot-arid steppe-prairie climate) are two of KIT's four dedicated LST validation stations. Gobabeb station is located on vast and flat gravel plains (several 100 km2), which are mainly covered by coarse gravel, sand, and desiccated grass. The gravel plains are highly homogeneous in space and time, which makes them ideal for validating a broad range of satellite-derived products. Dahra station is located in so called 'tiger bush' and is covered by strongly seasonal grass (95%) and sparse, evergreen trees (dominantly acacia trees) with a background of reddish sand. The strong seasonality is caused by a pronounced rainy season, during which LST retrieval is highly challenging. Outside the rainy season, both sites have relatively large fractions of bare ground and desiccated vegetation: therefore, they are particularly prone to be

  18. An Open and Transparent Databank of Global Land Surface Temperature

    Science.gov (United States)

    Rennie, J.; Thorne, P.; Lawrimore, J. H.; Gleason, B.; Menne, M. J.; Williams, C.

    2013-12-01

    The International Surface Temperature Initiative (ISTI) consists of an effort to create an end-to-end process for land surface air temperature analyses. The foundation of this process is the establishment of a global land surface databank. The databank builds upon the groundbreaking efforts of scientists who led efforts to construct global land surface datasets in the 1980's and 1990's. A primary aim of the databank is to improve aspects including data provenance, version control, temporal and spatial coverage, and improved methods for bringing dozens of source data together into an integrated dataset. The databank consists of multiple stages, with each successive stage providing a higher level of processing, quality and integration. Currently more than 50 sources of data have been added to the databank. An automated algorithm has been developed that merges these sources into one complete dataset by removing duplicate station records, identifying two or more station records that can be merged into a single record, and incorporating new and unique stations. The program runs iteratively through all the sources which are ordered based upon criteria established by the ISTI. The highest preferred source, known as the target, runs through all the candidate sources, calculating station comparisons that are acceptable for merging. The process is probabilistic in approach, and the final fate of a candidate station is based upon metadata matching and data equivalence criteria. If there is not enough information, the station is withheld for further investigation. The algorithm has been validated using a pseudo-source of stations with a known time of observation bias, and correct matches have been made nearly 95% of the time. The final product, endorsed and recommended by ISTI, contains over 30,000 stations, however slight changes in the algorithm can perturb results. Subjective decisions, such as the ordering of the sources, or changing metadata and data matching thresholds

  19. Land Surface Modeling Applications for Famine Early Warning

    Science.gov (United States)

    McNally, A.; Verdin, J. P.; Peters-Lidard, C. D.; Arsenault, K. R.; Wang, S.; Kumar, S.; Shukla, S.; Funk, C. C.; Pervez, M. S.; Fall, G. M.; Karsten, L. R.

    2015-12-01

    AGU 2015 Fall Meeting Session ID#: 7598 Remote Sensing Applications for Water Resources Management Land Surface Modeling Applications for Famine Early Warning James Verdin, USGS EROS Christa Peters-Lidard, NASA GSFC Amy McNally, NASA GSFC, UMD/ESSIC Kristi Arsenault, NASA GSFC, SAIC Shugong Wang, NASA GSFC, SAIC Sujay Kumar, NASA GSFC, SAIC Shrad Shukla, UCSB Chris Funk, USGS EROS Greg Fall, NOAA Logan Karsten, NOAA, UCAR Famine early warning has traditionally required close monitoring of agro-climatological conditions, putting them in historical context, and projecting them forward to anticipate end-of-season outcomes. In recent years, it has become necessary to factor in the effects of a changing climate as well. There has also been a growing appreciation of the linkage between food security and water availability. In 2009, Famine Early Warning Systems Network (FEWS NET) science partners began developing land surface modeling (LSM) applications to address these needs. With support from the NASA Applied Sciences Program, an instance of the Land Information System (LIS) was developed to specifically support FEWS NET. A simple crop water balance model (GeoWRSI) traditionally used by FEWS NET took its place alongside the Noah land surface model and the latest version of the Variable Infiltration Capacity (VIC) model, and LIS data readers were developed for FEWS NET precipitation forcings (NOAA's RFE and USGS/UCSB's CHIRPS). The resulting system was successfully used to monitor and project soil moisture conditions in the Horn of Africa, foretelling poor crop outcomes in the OND 2013 and MAM 2014 seasons. In parallel, NOAA created another instance of LIS to monitor snow water resources in Afghanistan, which are an early indicator of water availability for irrigation and crop production. These successes have been followed by investment in LSM implementations to track and project water availability in Sub-Saharan Africa and Yemen, work that is now underway. Adoption of

  20. Towards a simple representation of chalk hydrology in land surface modelling

    Science.gov (United States)

    Rahman, Mostaquimur; Rosolem, Rafael

    2017-01-01

    Modelling and monitoring of hydrological processes in the unsaturated zone of chalk, a porous medium with fractures, is important to optimize water resource assessment and management practices in the United Kingdom (UK). However, incorporating the processes governing water movement through a chalk unsaturated zone in a numerical model is complicated mainly due to the fractured nature of chalk that creates high-velocity preferential flow paths in the subsurface. In general, flow through a chalk unsaturated zone is simulated using the dual-porosity concept, which often involves calibration of a relatively large number of model parameters, potentially undermining applications to large regions. In this study, a simplified parameterization, namely the Bulk Conductivity (BC) model, is proposed for simulating hydrology in a chalk unsaturated zone. This new parameterization introduces only two additional parameters (namely the macroporosity factor and the soil wetness threshold parameter for fracture flow activation) and uses the saturated hydraulic conductivity from the chalk matrix. The BC model is implemented in the Joint UK Land Environment Simulator (JULES) and applied to a study area encompassing the Kennet catchment in the southern UK. This parameterization is further calibrated at the point scale using soil moisture profile observations. The performance of the calibrated BC model in JULES is assessed and compared against the performance of both the default JULES parameterization and the uncalibrated version of the BC model implemented in JULES. Finally, the model performance at the catchment scale is evaluated against independent data sets (e.g. runoff and latent heat flux). The results demonstrate that the inclusion of the BC model in JULES improves simulated land surface mass and energy fluxes over the chalk-dominated Kennet catchment. Therefore, the simple approach described in this study may be used to incorporate the flow processes through a chalk unsaturated

  1. Impact of land surface processes on the South American warm season climate

    Energy Technology Data Exchange (ETDEWEB)

    Ma, H.-Y.; Mechoso, C.R.; Xiao, H.; Wu, C.-M. [University of California Los Angeles, Department of Atmospheric and Oceanic Sciences, Los Angeles, CA (United States); Xue, Y. [University of California Los Angeles, Department of Atmospheric and Oceanic Sciences, Los Angeles, CA (United States); University of California Los Angeles, Department of Geography, Los Angeles, CA (United States); Li, J.-L. [California Institute of Technology, Jet Propulsion Laboratory, Pasadena, CA (United States); Sales, F.De [University of California Los Angeles, Department of Geography, Los Angeles, CA (United States)

    2011-07-15

    The present study demonstrates that (1) the simulation of the South American warm season (December-February) climate by an atmospheric general circulation model (AGCM) is sensitive to the representation of land surface processes, (2) the sensitivity is not confined to the ''hot spot'' in Amazonia, and (3) upgrading the representation of those processes can produce a significant improvement in AGCM performance. The reasons for sensitivity and higher success are investigated based on comparisons between observational datasets and simulations by the AGCM coupled to either a simple land scheme that specifies soil moisture availability or to the Simplified Simple Biosphere Model (SSiB) that allows for consideration of soil and vegetation biophysical process. The context for the study is the UCLA AGCM. The most notable simulation improvements are along the lee of the Andes in the lower troposphere, where poleward flow transports abundant moisture from the Amazon basin to high latitudes, and in the monsoon region where the intensity and pattern of precipitation and upper level ice water content are more realistic. It is argued that a better depiction of the Chaco Low, which is controlled by local effects of land surface processes, decisively contributes to the superior model performance with low-level flows in central South America. The better representation of the atmospheric column static stability and large-scale moisture convergence in tropical South America contribute to more realistic precipitation over the monsoon region. The overall simulation improvement is, therefore, due to a combination of different regional processes. This finding is supported by idealized AGCM experiments. (orig.)

  2. Calibration plan for the sea and land surface temperature radiometer

    Science.gov (United States)

    Smith, David L.; Nightingale, Tim J.; Mortimer, Hugh; Middleton, Kevin; Edeson, Ruben; Cox, Caroline V.; Mutlow, Chris T.; Maddison, Brian J.

    2013-10-01

    The Sea and Land Surface Temperature Radiometer (SLSTR) to be flown on ESA's Sentinel-3 mission is a multichannel scanning radiometer that will continue the 21-year datasets of the Along Track Scanning Radiometer (ATSR) series. As its name implies, measurements from SLSTR will be used to retrieve global sea surface temperatures to an uncertainty of SLSTR instrument, infrared calibration sources and alignment equipment. The calibration rig has been commissioned and results of these tests will be presented. Finally the authors will present the planning for the on-orbit monitoring and calibration activities to ensure that calibration is maintained. These activities include vicarious calibration techniques that have been developed through previous missions, and the deployment of ship-borne radiometers.

  3. A comparison of all-weather land surface temperature products

    Science.gov (United States)

    Martins, Joao; Trigo, Isabel F.; Ghilain, Nicolas; Goettche, Frank-M.; Ermida, Sofia; Olesen, Folke-S.; Gellens-Meulenberghs, Françoise; Arboleda, Alirio

    2017-04-01

    The Satellite Application Facility on Land Surface Analysis (LSA-SAF, http://landsaf.ipma.pt) has been providing land surface temperature (LST) estimates using SEVIRI/MSG on an operational basis since 2006. The LSA-SAF service has since been extended to provide a wide range of satellite-based quantities over land surfaces, such as emissivity, albedo, radiative fluxes, vegetation state, evapotranspiration, and fire-related variables. Being based on infra-red measurements, the SEVIRI/MSG LST product is limited to clear-sky pixels only. Several all-weather LST products have been proposed by the scientific community either based on microwave observations or using Soil-Vegetation-Atmosphere Transfer models to fill the gaps caused by clouds. The goal of this work is to provide a nearly gap-free operational all-weather LST product and compare these approaches. In order to estimate evapotranspiration and turbulent energy fluxes, the LSA-SAF solves the surface energy budget for each SEVIRI pixel, taking into account the physical and physiological processes occurring in vegetation canopies. This task is accomplished with an adapted SVAT model, which adopts some formulations and parameters of the Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) model operated at the European Center for Medium-range Weather Forecasts (ECMWF), and using: 1) radiative inputs also derived by LSA-SAF, which includes surface albedo, down-welling fluxes and fire radiative power; 2) a land-surface characterization obtained by combining the ECOCLIMAP database with both LSA-SAF vegetation products and the H(ydrology)-SAF snow mask; 3) meteorological fields from ECMWF forecasts interpolated to SEVIRI pixels, and 4) soil moisture derived by the H-SAF and LST from LSA-SAF. A byproduct of the SVAT model is surface skin temperature, which is needed to close the surface energy balance. The model skin temperature corresponds to the radiative temperature of the interface between soil and atmosphere

  4. A map of radon flux at the Australian land surface

    Directory of Open Access Journals (Sweden)

    A. D. Griffiths

    2010-06-01

    Full Text Available A time-dependent map of radon-222 flux density at the Australian land surface has been constructed with a spatial resolution of 0.05° and temporal resolution of one month. Radon flux density was calculated from a simple model utilising data from national gamma-ray aerial surveys, modelled soil moisture, and maps of soil properties. The model was calibrated against a large data set of accumulation-chamber measurements, thereby constraining it with experimental data. A notable application of the map is in atmospheric mixing and transport studies which use radon as a tracer, where it is a clear improvement on the common assumption of uniform radon flux density.

  5. A map of radon flux at the Australian land surface

    Directory of Open Access Journals (Sweden)

    A. D. Griffiths

    2010-09-01

    Full Text Available A time-dependent map of radon-222 flux density at the Australian land surface has been constructed with a spatial resolution of 0.05° and temporal resolution of one month. Radon flux density was calculated from a simple model utilising data from national gamma-ray aerial surveys; modelled soil moisture, available from 1900 in near real-time; and maps of soil properties. The model was calibrated against a data set of accumulation chamber measurements, thereby constraining it with experimental data. A notable application of the map is in atmospheric mixing and transport studies which use radon as a tracer, where it is a clear improvement on the common assumption of uniform radon flux density.

  6. A New Estimate of the Earth's Land Surface Temperature History

    Science.gov (United States)

    Muller, R. A.; Curry, J. A.; Groom, D.; Jacobsen, B.; Perlmutter, S.; Rohde, R. A.; Rosenfeld, A.; Wickham, C.; Wurtele, J.

    2011-12-01

    The Berkeley Earth Surface Temperature team has re-evaluated the world's atmospheric land surface temperature record using a linear least-squares method that allow the use of all the digitized records back to 1800, including short records that had been excluded by prior groups. We use the Kriging method to estimate an optimal weighting of stations to give a world average based on uniform weighting of the land surface. We have assembled a record of the available data by merging 1.6 billion temperature reports from 16 pre-existing data archives; this data base will be made available for public use. The former Global Historic Climatology Network (GHCN) monthly data base shows a sudden drop in the number of stations reporting monthly records from 1980 to the present; we avoid this drop by calculating monthly averages from the daily records. By using all the data, we reduce the effects of potential data selection bias. We make an independent estimate of the urban heat island effect by calculating the world land temperature trends based on stations chosen to be far from urban sites. We calculate the effect of poor station quality, as documented in the US by the team led by Anthony Watts by estimating the temperature trends based solely on the stations ranked good (1,2 or 1,2,3 in the NOAA ranking scheme). We avoid issues of homogenization bias by using raw data; at times when the records are discontinuous (e.g. due to station moves) we break the record into smaller segments and analyze those, rather than attempt to correct the discontinuity. We estimate the uncertainties in the final results using the jackknife procedure developed by J. Tukey. We calculate spatial uncertainties by measuring the effects of geographical exclusion on recent data that have good world coverage. The results we obtain are compared to those published by the groups at NOAA, NASA-GISS, and Hadley-CRU in the UK.

  7. The Land Surface Temperature Impact to Land Cover Types

    Science.gov (United States)

    Ibrahim, I.; Abu Samah, A.; Fauzi, R.; Noor, N. M.

    2016-06-01

    Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R2 = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

  8. 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

  9. Hydrologic Remote Sensing and Land Surface Data Assimilation

    Directory of Open Access Journals (Sweden)

    Hamid Moradkhani

    2008-05-01

    Full Text Available 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

  10. Global observation-based diagnosis of soil moisture control on land surface flux partition

    Science.gov (United States)

    Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Veal, Karen L.; Folwell, Sonja S.

    2016-04-01

    Soil moisture plays a central role in the partition of available energy at the land surface between sensible and latent heat flux to the atmosphere. As soils dry out, evapotranspiration becomes water-limited ("stressed"), and both land surface temperature (LST) and sensible heat flux rise as a result. This change in surface behaviour during dry spells directly affects critical processes in both the land and the atmosphere. Soil water deficits are often a precursor in heat waves, and they control where feedbacks on precipitation become significant. State-of-the-art global climate model (GCM) simulations for the Coupled Model Intercomparison Project Phase 5 (CMIP5) disagree on where and how strongly the surface energy budget is limited by soil moisture. Evaluation of GCM simulations at global scale is still a major challenge owing to the scarcity and uncertainty of observational datasets of land surface fluxes and soil moisture at the appropriate scale. Earth observation offers the potential to test how well GCM land schemes simulate hydrological controls on surface fluxes. In particular, satellite observations of LST provide indirect information about the surface energy partition at 1km resolution globally. Here, we present a potentially powerful methodology to evaluate soil moisture stress on surface fluxes within GCMs. Our diagnostic, Relative Warming Rate (RWR), is a measure of how rapidly the land warms relative to the overlying atmosphere during dry spells lasting at least 10 days. Under clear skies, this is a proxy for the change in sensible heat flux as soil dries out. We derived RWR from MODIS Terra and Aqua LST observations, meteorological re-analyses and satellite rainfall datasets. Globally we found that on average, the land warmed up during dry spells for 97% of the observed surface between 60S and 60N. For 73% of the area, the land warmed faster than the atmosphere (positive RWR), indicating water stressed conditions and increases in sensible heat flux

  11. Modelling Hydrological Processes in Presence of Uncertain or Unreliable Forcing Data and Land Surface Parameters

    Science.gov (United States)

    Gusev, Ye. M.; Nasonova, O. N.; Dzhogan, L. Ya.

    2009-04-01

    Construction of a model for simulating hydrological processes, to our opinion, should be based on mathematical description of the real physical heat and water exchange processes occurring in a soil - vegetation/snow cover - atmosphere system rather than on available data. This allows one to create more universal model, which can be applied at different temporal and spatial scales and under different natural conditions. More than that, such a model can be applied for poorly-gauged basins and in the presence of uncertain/unreliable forcing data and land surface parameters, provided that reliable runoff measurements are available at least for several years. The latter is necessary for model calibration to reduce the impact of uncertainties in input data on model results. The present work is intended to confirm the above statements using the land surface model SWAP (Soil Water - Atmosphere - Plants). SWAP is a physically-based model describing the processes of heat and water exchange within a soil-vegetation/snow cover-atmosphere system (SVAS). The model can be applied both for point (or grid cell) simulations of vertical fluxes and state variables of SVAS in atmospheric science applications, and for simulating streamflow on different scales — from small catchments to continental scale river basins. The results of model validations have demonstrated that SWAP is able to reproduce (without calibration) heat and water exchange processes (in particular, hydrological processes) adequately, provided that input data of high quality are available. In poorly-gauged basins, alternative sources of information should be used. Here, the global data sets on forcing data and land surface parameters were used for simulating streamflow from two pan-Arctic river basins (the Mezen and the Pechora basins with an area of 78 000 and 324 000 sq.km, respectively), located in the northeast part of the European Russia. The Mezen and the Pechora basins were represented for modeling purposes

  12. Safety Assessment of Advanced Imaging Sequences II: Simulations

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2016-01-01

    An automatic approach for simulating the emitted pressure, intensity, and MI of advanced ultrasound imaging sequences is presented. It is based on a linear simulation of pressure fields using Field II, and it is hypothesized that linear simulation can attain the needed accuracy for predicting...... and Ita.3 closely matches that for the measurement, and simulations can therefore be used to select the region for measuring the intensities, resulting in a significant reduction in measurement time. It can validate emission sequences by showing symmetry of emitted pressure fields, focal position...

  13. Computer simulation of a magnetohydrodynamic dynamo. II

    Science.gov (United States)

    Kageyama, Akira; Sato, Tetsuya; Complexity Simulation Group

    1995-05-01

    A computer simulation of a magnetohydrodynamic dynamo in a rapidly rotating spherical shell is performed. Extensive parameter runs are carried out changing electrical resistivity. When resistivity is sufficiently small, total magnetic energy can grow more than ten times larger than total kinetic energy of convection motion which is driven by an unlimited external energy source. When resistivity is relatively large and magnetic energy is comparable or smaller than kinetic energy, the convection motion maintains its well-organized structure. However, when resistivity is small and magnetic energy becomes larger than kinetic energy, the well-organized convection motion is highly irregular. The magnetic field is organized in two ways. One is the concentration of component parallel to the rotation axis and the other is the concentration of perpendicular component. The parallel component tends to be confined inside anticyclonic columnar convection cells, while the perpendicular component is confined outside convection cells.

  14. Collisionless microinstabilities in stellarators II - numerical simulations

    CERN Document Server

    Proll, Josefine Henriette Elise; Helander, Per

    2013-01-01

    Microinstabilities exhibit a rich variety of behavior in stellarators due to the many degrees of freedom in the magnetic geometry. It has recently been found that certain stellarators (quasi-isodynamic ones with maximum-$J$ geometry) are partly resilient to trapped-particle instabilities, because fast-bouncing particles tend to extract energy from these modes near marginal stability. In reality, stellarators are never perfectly quasi-isodynamic, and the question thus arises whether they still benefit from enhanced stability. Here the stability properties of Wendelstein 7-X and a more quasi-isodynamic configuration, QIPC, are investigated numerically and compared with the National Compact Stellarator Experiment (NCSX) and the DIII-D tokamak. In gyrokinetic simulations, performed with the gyrokinetic code GENE in the electrostatic and collisionless approximation, ion-temperature-gradient modes, trapped-electron modes and mixed-type instabilities are studied. Wendelstein 7-X and QIPC exhibit significantly reduce...

  15. Developing first time-series of land surface temperature from AATSR with uncertainty estimates

    Science.gov (United States)

    Ghent, Darren; Remedios, John

    2013-04-01

    Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Earth Observation satellites provide the opportunity to obtain global coverage of LST approximately every 3 days or less. One such source of satellite retrieved LST has been the Advanced Along-Track Scanning Radiometer (AATSR); with LST retrieval being implemented in the AATSR Instrument Processing Facility in March 2004. Here we present first regional and global time-series of LST data from AATSR with estimates of uncertainty. Mean changes in temperature over the last decade will be discussed along with regional patterns. Although time-series across all three ATSR missions have previously been constructed (Kogler et al., 2012), the use of low resolution auxiliary data in the retrieval algorithm and non-optimal cloud masking resulted in time-series artefacts. As such, considerable ESA supported development has been carried out on the AATSR data to address these concerns. This includes the integration of high resolution auxiliary data into the retrieval algorithm and subsequent generation of coefficients and tuning parameters, plus the development of an improved cloud mask based on the simulation of clear sky conditions from radiance transfer modelling (Ghent et al., in prep.). Any inference on this LST record is though of limited value without the accompaniment of an uncertainty estimate; wherein the Joint Committee for Guides in Metrology quote an uncertainty as "a parameter associated with the result of a measurement that characterizes the dispersion of the values that could reasonably be attributed to the measurand that is the value of the particular quantity to be measured". Furthermore, pixel level uncertainty fields are a mandatory requirement in the on-going preparation of the LST product for the upcoming Sea and Land Surface Temperature (SLSTR) instrument on-board Sentinel-3

  16. Spatial validation of large scale land surface models against monthly land surface temperature patterns using innovative performance metrics.

    Science.gov (United States)

    Koch, Julian; Siemann, Amanda; Stisen, Simon; Sheffield, Justin

    2016-04-01

    Land surface models (LSMs) are a key tool to enhance process understanding and to provide predictions of the terrestrial hydrosphere and its atmospheric coupling. Distributed LSMs predict hydrological states and fluxes, such as land surface temperature (LST) or actual evapotranspiration (aET), at each grid cell. LST observations are widely available through satellite remote sensing platforms that enable comprehensive spatial validations of LSMs. In spite of the availability of LST data, most validation studies rely on simple cell to cell comparisons and thus do not regard true spatial pattern information. This study features two innovative spatial performance metrics, namely EOF- and connectivity-analysis, to validate predicted LST patterns by three LSMs (Mosaic, Noah, VIC) over the contiguous USA. The LST validation dataset is derived from global High-Resolution-Infrared-Radiometric-Sounder (HIRS) retrievals for a 30 year period. The metrics are bias insensitive, which is an important feature in order to truly validate spatial patterns. The EOF analysis evaluates the spatial variability and pattern seasonality, and attests better performance to VIC in the warm months and to Mosaic and Noah in the cold months. Further, more than 75% of the LST variability can be captured by a single pattern that is strongly driven by air temperature. The connectivity analysis assesses the homogeneity and smoothness of patterns. The LSMs are most reliable at predicting cold LST patterns in the warm months and vice versa. Lastly, the coupling between aET and LST is investigated at flux tower sites and compared against LSMs to explain the identified LST shortcomings.

  17. The Land Surface Temperature Synergistic Processor in BEAM: A Prototype towards Sentinel-3

    OpenAIRE

    Ruescas, Ana Belen; Danne, Olaf; Fomferra, Norman; Brockmann, Carsten

    2016-01-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temp...

  18. Numerically Test of Influence of Incorporation of TOPMODEL into Land Surface Model SSiB on Hydrological Simulation at Basin Scale%陆面模式SSiB耦合TOPMODEL对流域水文模拟影响的数值试验

    Institute of Scientific and Technical Information of China (English)

    刘惠民; 邓慧平; 孙菽芬; 肖燕

    2013-01-01

    为了检验陆面模式SSiB耦合TOPMODEL模型对流域水量平衡模拟结果的影响,用原始SSiB与TOPMODEL按饱和区和非饱和区两种方案耦合的耦合模型(下称SSiBT)进行长江下游青弋江流域水文的数值试验,通过耦合模型与原始SSiB模式模拟结果的比较,并利用流域实测逐日流量和水量平衡资料,揭示了流域水文模拟结果对SSiB耦合TOPMODEL的响应和原因.结果表明:(1)与原始SSiB的模拟结果相比,SSiBT增加了土壤湿度的模拟结果和各层土壤湿度之间的差异,流域蒸散发增加而总径流减小.(2)原始SSiB不能准确地将径流在地表径流和基流之间分配,对于较小的土壤饱和导水率,原始SSiB产生过多的地表径流和洪峰流量;对于较大的土壤饱和导水率又产生过多的基流和明显偏小的洪峰流量.(3)即使土壤饱和导水率大到不会产生超渗产流,由于饱和区的存在,SSiBT在洪水期间也能产生足够大的地表径流,从而形成洪峰流量.由于考虑了地形引起的土壤湿度空间非均匀形成的饱和区产流,SSiBT改善了雨季逐日流量的模拟结果.%In order to examine and analyze the effects of integration of land surface model SSiB with TOPMODEL on hydrological simulations,the coupled model (hereinafter SSiBT) which partitions the catchment into saturated and unsaturated zones is used to conduct hydrological simulations at basin scale using data from the Qingyijiang basin.By assessing SSiBT outputs against original SSiB outputs and using observational data sets of daily runoff and water balance of the basin the responses of hydrological simulations to incorporation of TOPMODEL into original SSiB are analyzed and the reasons for such responses are investigated.The study shows that comparing with the results from original SSiB simulations,the coupled model SSiBT predicts more strong vertical changes in soil wetness,higher soil wetness and evaporation and lower total runoff

  19. Sensitivity of snow cover to horizontal resolution in a land surface model

    Science.gov (United States)

    Dutra, E.; Kotlarski, S.; Viterbo, P.; Balsamo, G.; Miranda, P. M. A.; Schär, C.

    2010-09-01

    Snow cover is a highly variable land surface condition that exerts a strong control on the heat and moisture budget of the overlying atmosphere. Modeling studies based on long integrations of global circulation models (GCM) are normally carried out at very low resolution (typically coarser than 100 km) due to their high computational demand. On local scales, snow cover plays an important socioeconomic role, ranging from water management applications to outdoor recreation. These latter applications vary in horizontal resolution from a few hundred meters to a few kilometers, where small scale topography, land cover and local circulation effects play a significant role. In this study our focus will be on horizontal scales ranging from typical GCM global climate modeling to high resolution global weather forecasts. In the land surface component of a GCM (land surface model - LSM), snow cover temporal and spatial variability is mainly determined by the overlying atmospheric conditions. However, once snowfall settles on the ground, the sub-grid scale variability associated with complex terrain and land cover variability (not resolved at the model resolution) is parameterized following simple physical and/or empirical relations. The present study intends to access the impact of horizontal resolution in the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface model (HTESSEL). HTESSEL is forced by the ECMWF operational weather forecasts since March 2006 to December 2009 (runs in offline/stand-alone mode). The control run is carried out at the horizontal resolution of the forecasts at TL799 (gaussian reduced grid N400 -about 25 km). Two lower horizontal resolutions are then tested: TL255 (gaussian reduced grid - about 80 km, same as the ERA-Interim reanalysis), and TL95 (gaussian reduced grid N48 - about 200 km). The length of the simulations is rather small (only 46 months), however global meteorological forcing at 25 km can only be accessed through the

  20. Submodeling Simulations in Fusion Welds: Part II

    Science.gov (United States)

    Bonifaz, E. A.

    2013-11-01

    In part I, three-dimensional transient non-linear sub modeling heat transfer simulations were performed to study the thermal histories and thermal cycles that occur during the welding process at the macro, meso and micro scales. In the present work, the corresponding non-uniform temperature changes were imposed as load conditions on structural calculations to study the evolution of localized plastic strains and residual stresses at these sub-level scales. To reach the goal, a three-dimensional finite element elastic-plastic model (ABAQUS code) was developed. The sub-modeling technique proposed to be used in coupling phase-field (and/or digital microstructures) codes with finite element codes, was used to mesh a local part of the model with a refined mesh based on interpolation of the solution from an initial, relatively coarse, macro global model. The meso-sub-model is the global model for the subsequent micro sub-model. The strategy used to calculate temperatures, strains and residual stresses at the macro, meso and micro scale level, is very flexible to be used to any number of levels. The objective of this research was to initiate the development of microstructural models to identify fusion welding process parameters for preserving the single crystal nature of gas turbine blades during repair procedures. The multi-scale submodeling approach can be used to capture weld pool features at the macro-meso scale level, and micro residual stress and secondary dendrite arm spacing features at the micro scale level.

  1. 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.

  2. Information-Theoretic Benchmarking of Land Surface Models

    Science.gov (United States)

    Nearing, Grey; Mocko, David; Kumar, Sujay; Peters-Lidard, Christa; Xia, Youlong

    2016-04-01

    Benchmarking is a type of model evaluation that compares model performance against a baseline metric that is derived, typically, from a different existing model. Statistical benchmarking was used to qualitatively show that land surface models do not fully utilize information in boundary conditions [1] several years before Gong et al [2] discovered the particular type of benchmark that makes it possible to *quantify* the amount of information lost by an incorrect or imperfect model structure. This theoretical development laid the foundation for a formal theory of model benchmarking [3]. We here extend that theory to separate uncertainty contributions from the three major components of dynamical systems models [4]: model structures, model parameters, and boundary conditions describe time-dependent details of each prediction scenario. The key to this new development is the use of large-sample [5] data sets that span multiple soil types, climates, and biomes, which allows us to segregate uncertainty due to parameters from the two other sources. The benefit of this approach for uncertainty quantification and segregation is that it does not rely on Bayesian priors (although it is strictly coherent with Bayes' theorem and with probability theory), and therefore the partitioning of uncertainty into different components is *not* dependent on any a priori assumptions. We apply this methodology to assess the information use efficiency of the four land surface models that comprise the North American Land Data Assimilation System (Noah, Mosaic, SAC-SMA, and VIC). Specifically, we looked at the ability of these models to estimate soil moisture and latent heat fluxes. We found that in the case of soil moisture, about 25% of net information loss was from boundary conditions, around 45% was from model parameters, and 30-40% was from the model structures. In the case of latent heat flux, boundary conditions contributed about 50% of net uncertainty, and model structures contributed

  3. Quantification of the relative role of land-surface processes and large-scale forcing in dynamic downscaling over the Tibetan Plateau

    Science.gov (United States)

    Gao, Yanhong; Xiao, Linhong; Chen, Deliang; Chen, Fei; Xu, Jianwei; Xu, Yu

    2017-03-01

    Dynamical downscaling modeling (DDM) is important to understand regional climate change and develop local mitigation strategies, and the accuracy of DDM depends on the physical processes involved in the regional climate model as well as the forcing datasets derived from global models. This study investigates the relative role of the land surface schemes and forcing datasets in the DDM over the Tibet Plateau (TP), a region complex in topography and vulnerable to climate change. Three Weather Research and Forecasting model dynamical downscaling simulations configured with two land surface schemes [Noah versus Noah with multiparameterization (Noah-MP)] and two forcing datasets are performed over the period of 1980-2005. The downscaled temperature and precipitation are evaluated with observations and inter-compared regarding temporal trends, spatial distributions, and climatology. Results show that the temporal trends of the temperature and precipitation are determined by the forcing datasets, and the forcing dataset with the smallest trend bias performs the best. Relative to the forcing datasets, land surface processes play a more critical role in the DDM over the TP due to the strong heating effects on the atmospheric circulation from a vast area at exceptionally high elevations. By changing the vertical profiles of temperature in the atmosphere and the horizontal patterns of moisture advection during the monsoon seasons, the land surface schemes significantly regulate the downscaled temperature and precipitation in terms of climatology and spatial patterns. This study emphasizes the selection of land surface schemes is of crucial importance in the successful DDM over the TP.

  4. Simulation of cusp formation in mode II delamination

    NARCIS (Netherlands)

    Sluys, L.J.; Van der Meer, F.P.

    2014-01-01

    On the microlevel, cusps are formed during delamination crack growth under mode II loading conditions. In this work, two different approaches to simulate this process are presented. Firstly a cohesive zone method where cohesive segments are introduced between a pair of neighbouring elements when the

  5. Parametrization of the Tidal Effect for Use in the Noah Land-Surface Model: Development and Validation

    Science.gov (United States)

    Lee, Young-Hee; Ahn, Kwang-Deuk; Lee, Yong Hee

    2016-12-01

    We have developed a parametrization of tidal effects for use in the Noah land-surface model and have validated the land-surface model using observations taken over a tidal flat of the western coast of South Korea. The parametrization is based on the energy budget of a water layer with varying thickness above the soil. During flood tide, heat transfer by the moving water is considered in addition to the surface energy budget. In addition, partial penetration of solar radiation through the water layer is considered in the surface energy budget, and the water thickness varying with time is used as an additional input. Seven days with clear-sky conditions and westerly winds during the daytime are selected for validation of the model. Two simulations are performed in an offline mode: a control simulation without the tidal effect (CONTROL) and a simulation with the tidal effect (TIDE). Comparisons of results have been made with eddy-covariance measurements and soil temperature data for the tidal flats. Observations show that inundation significantly reduces both sensible and latent heat fluxes during daytime, which is well simulated in the TIDE simulation. The diurnal variation and magnitude of soil temperature are better simulated in the TIDE than in the CONTROL simulation. Some underestimation of the latent heat flux over the water surface is partly attributed to the use of one layer of water and the underestimated roughness length at this site. In addition, other model deficiencies are discussed.

  6. Parametrization of the Tidal Effect for Use in the Noah Land-Surface Model: Development and Validation

    Science.gov (United States)

    Lee, Young-Hee; Ahn, Kwang-Deuk; Lee, Yong Hee

    2016-06-01

    We have developed a parametrization of tidal effects for use in the Noah land-surface model and have validated the land-surface model using observations taken over a tidal flat of the western coast of South Korea. The parametrization is based on the energy budget of a water layer with varying thickness above the soil. During flood tide, heat transfer by the moving water is considered in addition to the surface energy budget. In addition, partial penetration of solar radiation through the water layer is considered in the surface energy budget, and the water thickness varying with time is used as an additional input. Seven days with clear-sky conditions and westerly winds during the daytime are selected for validation of the model. Two simulations are performed in an offline mode: a control simulation without the tidal effect (CONTROL) and a simulation with the tidal effect (TIDE). Comparisons of results have been made with eddy-covariance measurements and soil temperature data for the tidal flats. Observations show that inundation significantly reduces both sensible and latent heat fluxes during daytime, which is well simulated in the TIDE simulation. The diurnal variation and magnitude of soil temperature are better simulated in the TIDE than in the CONTROL simulation. Some underestimation of the latent heat flux over the water surface is partly attributed to the use of one layer of water and the underestimated roughness length at this site. In addition, other model deficiencies are discussed.

  7. Validation of Multibody Program to Optimize Simulated Trajectories II Parachute Simulation with Interacting Forces

    Science.gov (United States)

    Raiszadeh, Behzad; Queen, Eric M.; Hotchko, Nathaniel J.

    2009-01-01

    A capability to simulate trajectories of multiple interacting rigid bodies has been developed, tested and validated. This capability uses the Program to Optimize Simulated Trajectories II (POST 2). The standard version of POST 2 allows trajectory simulation of multiple bodies without force interaction. In the current implementation, the force interaction between the parachute and the suspended bodies has been modeled using flexible lines, allowing accurate trajectory simulation of the individual bodies in flight. The POST 2 multibody capability is intended to be general purpose and applicable to any parachute entry trajectory simulation. This research paper explains the motivation for multibody parachute simulation, discusses implementation methods, and presents validation of this capability.

  8. Assessing the influence of groundwater and land surface scheme in the modelling of land surface-atmosphere feedbacks over the FIFE area in Kansas, USA

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Højmark Rasmussen, Søren; Drews, Martin;

    2016-01-01

    experiments include five simulations. First MIKE SHE is forced by observed climate data in two versions i) with groundwater at a fixed uniform depth, and ii) with a dynamical groundwater component simulating shallow groundwater conditions in river valleys. iii) In a third simulation MIKE SHE is forced...

  9. Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models

    Science.gov (United States)

    Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

    2017-04-01

    Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates

  10. On the (in)consistency of a multi-model ensemble of the past 30 years land surface state.

    Science.gov (United States)

    Dutra, Emanuel; Schellekens, Jaap; Beck, Hylke; Balsamo, Gianpaolo

    2016-04-01

    Global land-surface and hydrological models are a fundamental tool in understanding the land-surface state and evolution either coupled to atmospheric models for climate and weather predictions or in stand-alone mode. In this study we take a recently developed dataset consisting in stand-alone simulations by 10 global hydrological and land surface models sharing the same atmospheric forcing for the period 1979-2012 (the eart2Observe dataset). This multi-model ensemble provides the first freely available dataset with such a spatial/temporal scale that allows for a characterization of the multi-model characteristics such as inter-model consistency and error-spread relationship. We will present a metric for the ensemble consistency using the concept of potential predictability, that can be interpreted as a proxy for the multi-model agreement. Initial results point to regions of low inter-model agreement in the polar and tropical regions, the latter also present when comparing globally available precipitation datasets. In addition to this, the discharge ensemble spread around the ensemble mean was compared to the error of the ensemble mean for several large-scale and small scale basins. This showed a general under-estimation of the ensemble spread, particularly in tropical basins, suggesting that the current dataset lacks the representation of the precipitation uncertainty in the input meteorological data.

  11. Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

    Science.gov (United States)

    Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; Luke, Catherine M.

    2016-08-01

    Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

  12. Scale-consistent two-way coupling of land-surface and atmospheric models

    Science.gov (United States)

    Schomburg, A.; Venema, V.; Ament, F.; Simmer, C.

    2009-04-01

    Processes at the land surface and in the atmosphere act on different spatial scales. While in the atmosphere small-scale heterogeneity is smoothed out quickly by turbulent mixing, this is not the case at the land surface where small-scale variability of orography, land cover, soil texture, soil moisture etc. varies only slowly in time. For the modelling of the fluxes between the land-surface and the atmosphere it is consequently more scale consistent to model the surface processes at a higher spatial resolution than the atmospheric processes. The mosaic approach is one way to deal with this problem. Using this technique the Soil Vegetation Atmosphere Transfer (SVAT) scheme is solved on a higher resolution than the atmosphere, which is possible since a SVAT module generally demands considerably less computation time than the atmospheric part. The upscaling of the turbulent fluxes of sensible and latent heat at the interface to the atmosphere is realized by averaging, due to the nonlinearities involved this is a more sensible approach than averaging the soil properties and computing the fluxes in a second step. The atmospheric quantities are usually assumed to be homogeneous for all soil-subpixels pertaining to one coarse atmospheric grid box. In this work, the aim is to develop a downscaling approach in which the atmospheric quantities at the lowest model layer are disaggregated before they enter the SVAT module at the higher mosaic resolution. The overall aim is a better simulation of the heat fluxes which play an important role for the energy and moisture budgets at the surface. The disaggregation rules for the atmospheric variables will depend on high-resolution surface properties and the current atmospheric conditions. To reduce biases due to nonlinearities we will add small-scale variability according to such rules as well as noise for the variability we can not explain. The model used in this work is the COSMO-model, the weather forecast model (and regional

  13. mRM - multiscale Routing Model for Land Surface and Hydrologic Models

    Science.gov (United States)

    Cuntz, M.; Thober, S.; Mai, J.; Samaniego, L. E.; Gochis, D. J.; Kumar, R.

    2015-12-01

    Routing streamflow through a river network is a basic step within any distributed hydrologic model. It integrates the generated runoff and allows comparison with observed discharge at the outlet of a catchment. The Muskingum routing is a textbook river routing scheme that has been implemented in Earth System Models (e.g., WRF-HYDRO), stand-alone routing schemes (e.g., RAPID), and hydrologic models (e.g., the mesoscale Hydrologic Model). Most implementations suffer from a high computational demand because the spatial routing resolution is fixed to that of the elevation model irrespective of the hydrologic modeling resolution. This is because the model parameters are scale-dependent and cannot be used at other resolutions without re-estimation. Here, we present the multiscale Routing Model (mRM) that allows for a flexible choice of the routing resolution. mRM exploits the Multiscale Parameter Regionalization (MPR) included in the open-source mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) that relates model parameters to physiographic properties and allows to estimate scale-independent model parameters. mRM is currently coupled to mHM and is presented here as stand-alone Free and Open Source Software (FOSS). The mRM source code is highly modular and provides a subroutine for internal re-use in any land surface scheme. mRM is coupled in this work to the state-of-the-art land surface model Noah-MP. Simulation results using mRM are compared with those available in WRF-HYDRO for the Red River during the period 1990-2000. mRM allows to increase the routing resolution from 100m to more than 10km without deteriorating the model performance. Therefore, it speeds up model calculation by reducing the contribution of routing to total runtime from over 80% to less than 5% in the case of WRF-HYDRO. mRM thus makes discharge data available to land surface modeling with only little extra calculations.

  14. Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

    Science.gov (United States)

    Al-Hamdan, M. Z.; Crosson, W. L.; Estes, M. G., Jr.; Estes, S. M.; Quattrochi, D. A.; Johnson, D.

    2013-12-01

    This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heat-related mortality data. The current HWWS do not take into account intra-urban spatial variations in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with land surface temperature (LST) estimates derived from thermal remote sensing data. In order to further improve the assessment of intra-urban variations in risk from extreme heat, we developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. We will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

  15. Daily monitoring of the land surface of the Earth

    Science.gov (United States)

    Mascaro, J.

    2016-12-01

    Planet is an integrated aerospace and data analytics company that operates the largest fleet of Earth-imaging satellites. With more than 140 cube-sats successfully launched to date, Planet is now collecting approximately 10 million square kilometers of imagery per day (3-5m per pixel, in red, green, blue and near infrared spectral bands). By early 2017, Planet's constellation will image the entire land surface of the Earth on a daily basis. Due to investments in cloud storage and computing, approximately 75% of imagery collected is available to Planet's partners within 24 hours of capture through an Application Program Interface. This unique dataset has enormous applications for monitoring the status of Earth's natural ecosystems, as well as human settlements and agricultural welfare. Through our Ambassadors Program, Planet has made data available for researchers in areas as disparate as human rights monitoring in refugee camps, to assessments of the impact of hydroelectric installations, to tracking illegal gold mining in Amazon forests, to assessing the status of the cryosphere. Here, we share early results from Planet's research partner network, including enhanced spatial and temporal resolution of NDVI data for agricultural health in Saudi Arabia, computation of rates of illegal deforestation in Southern Peru, estimates of tropical forest carbon stocks based on data integration with active sensors, and estimates of glacial flow rates. We synthesize the potentially enormous research and scientific value of Planet's persistent monitoring capability, and discuss methods by which the data will be disseminated into the scientific community.

  16. Afforestation in China cools local land surface temperature.

    Science.gov (United States)

    Peng, Shu-Shi; Piao, Shilong; Zeng, Zhenzhong; Ciais, Philippe; Zhou, Liming; Li, Laurent Z X; Myneni, Ranga B; Yin, Yi; Zeng, Hui

    2014-02-25

    China has the largest afforested area in the world (∼62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 ± 0.5 °C (mean ± 1 SD) and to increase nighttime LST by about 0.2 ± 0.5 °C, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.

  17. Land surface temperature shaped by urban fractions in megacity region

    Science.gov (United States)

    Zhang, Xiaoxuan; Hu, Yonghong; Jia, Gensuo; Hou, Meiting; Fan, Yanguo; Sun, Zhongchang; Zhu, Yuxiang

    2017-02-01

    Large areas of cropland and natural vegetation have been replaced by impervious surfaces during the recent rapid urbanization in China, which has resulted in intensified urban heat island effects and modified local or regional warming trends. However, it is unclear how urban expansion contributes to local temperature change. In this study, we investigated the relationship between land surface temperature (LST) change and the increase of urban land signals. The megacity of Tianjin was chosen for the case study because it is representative of the urbanization process in northern China. A combined analysis of LST and urban land information was conducted based on an urban-rural transect derived from Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectrometer (MODIS), and QuickBird images. The results indicated that the density of urban land signals has intensified within a 1-km2 grid in the urban center with an impervious land fraction >60 %. However, the construction on urban land is quite different with low-/mid-rise buildings outnumbering high-rise buildings in the urban-rural transect. Based on a statistical moving window analysis, positive correlation ( R 2 > 0.9) is found between LST and urban land signals. Surface temperature change (ΔLST) increases by 0.062 °C, which was probably caused by the 1 % increase of urbanized land (ΔIF) in this case region.

  18. Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

    Science.gov (United States)

    Zhou, D. K.; Larar, A. M.; Liu, Xu; Smith, W. L.; Strow, L. L.; Yang, Ping; Schlussel, P.; Calbet, X.

    2011-01-01

    Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spaceborne IR soundings. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral IR sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme has been applied to the Infrared Atmospheric Sounding Interferometer (IASI). Rapidly produced SSE is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. Initial validation of retrieved emissivity spectra is conducted with Namib and Kalahari desert laboratory measurements. Seasonal products of global land SSE and surface skin temperature retrieved with IASI are presented to demonstrate seasonal variation of SSE.

  19. A New Global Climatology of Annual Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Benjamin Bechtel

    2015-03-01

    Full Text Available Land surface temperature (LST is an important parameter in various fields including hydrology, climatology, and geophysics. Its derivation by thermal infrared remote sensing has long tradition but despite substantial progress there remain limited data availability and challenges like emissivity estimation, atmospheric correction, and cloud contamination. The annual temperature cycle (ATC is a promising approach to ease some of them. The basic idea to fit a model to the ATC and derive annual cycle parameters (ACP has been proposed before but so far not been tested on larger scale. In this study, a new global climatology of annual LST based on daily 1 km MODIS/Terra observations was processed and evaluated. The derived global parameters were robust and free of missing data due to clouds. They allow estimating LST patterns under largely cloud-free conditions at different scales for every day of year and further deliver a measure for its accuracy respectively variability. The parameters generally showed low redundancy and mostly reflected real surface conditions. Important influencing factors included climate, land cover, vegetation phenology, anthropogenic effects, and geology which enable numerous potential applications. The datasets will be available at the CliSAP Integrated Climate Data Center pending additional processing.

  20. Land surface phenology from SPOT VEGETATION time series

    Directory of Open Access Journals (Sweden)

    A. Verger

    2016-12-01

    Full Text Available Land surface phenology from time series of satellite data are expected to contribute to improve the representation of vegetation phenology in earth system models. We characterized the baseline phenology of the vegetation at the global scale from GEOCLIM-LAI, a global climatology of leaf area index (LAI derived from 1-km SPOT VEGETATION time series for 1999-2010. The calibration with ground measurements showed that the start and end of season were best identified using respectively 30% and 40% threshold of LAI amplitude values. The satellite-derived phenology was spatially consistent with the global distributions of climatic drivers and biome land cover. The accuracy of the derived phenological metrics, evaluated using available ground observations for birch forests in Europe, cherry in Asia and lilac shrubs in North America showed an overall root mean square error lower than 19 days for the start, end and length of season, and good agreement between the latitudinal gradients of VEGETATION LAI phenology and ground data.

  1. Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

    Science.gov (United States)

    Al-Hamdan, Mohammad; Crosson, William; Estes, Maurice, Jr.; Estes, Sue; Quattrochi, Dale; Johnson, Daniel

    2013-01-01

    This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

  2. Simulating Capacitive Micromachined Ultrasonic Transducers (CMUTs) using Field II

    DEFF Research Database (Denmark)

    Bæk, David; Oralkan, Omer; Kupnik, Mario;

    2010-01-01

    Field II has been a recognized simulation tool for piezoceramic medical transducer arrays for more than a decade. The program has its strength in doing fast computations of the spatial impulse response (SIR) from array elements by dividing the elements into smaller mathematical elements (ME)s from...... which it calculates the SIR responses. The program features predefined models for classical transducer geometries, but currently none for the fast advancing CMUTs. This work addresses the assumptions required for modeling CMUTs with Field II. It is shown that rectangular array elements, populated...

  3. A land surface scheme for atmospheric and hydrologic models: SEWAB (Surface Energy and Water Balance)

    Energy Technology Data Exchange (ETDEWEB)

    Mengelkamp, H.T.; Warrach, K.; Raschke, E. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Atmosphaerenphysik

    1997-12-31

    A soil-vegetation-atmosphere-transfer scheme is presented here which solves the coupled system of the Surface Energy and Water Balance (SEWAB) equations considering partly vegetated surfaces. It is based on the one-layer concept for vegetation. In the soil the diffusion equations for heat and moisture are solved on a multi-layer grid. SEWAB has been developed to serve as a land-surface scheme for atmospheric circulation models. Being forced with atmospheric data from either simulations or measurements it calculates surface and subsurface runoff that can serve as input to hydrologic models. The model has been validated with field data from the FIFE experiment and has participated in the PILPS project for intercomparison of land-surface parameterization schemes. From these experiments we feel that SEWAB reasonably well partitions the radiation and precipitation into sensible and latent heat fluxes as well as into runoff and soil moisture Storage. (orig.) [Deutsch] Ein Landoberflaechenschema wird vorgestellt, das den Transport von Waerme und Wasser zwischen dem Erdboden, der Vegetation und der Atmosphaere unter Beruecksichtigung von teilweise bewachsenem Boden beschreibt. Im Erdboden werden die Diffusionsgleichungen fuer Waerme und Feuchte auf einem Gitter mit mehreren Schichten geloest. Das Schema SEWAB (Surface Energy and Water Balance) beschreibt die Landoberflaechenprozesse in atmosphaerischen Modellen und berechnet den Oberflaechenabfluss und den Basisabfluss, die als Eingabedaten fuer hydrologische Modelle genutzt werden koennen. Das Modell wurde mit Daten des FIFE-Experiments kalibriert und hat an Vergleichsexperimenten fuer Landoberflaechen-Schemata im Rahmen des PILPS-Projektes teilgenommen. Dabei hat sich gezeigt, dass die Aufteilung der einfallenden Strahlung und des Niederschlages in den sensiblen und latenten Waermefluss und auch in Abfluss und Speicherung der Bodenfeuchte in SEWAB den beobachteten Daten recht gut entspricht. (orig.)

  4. Impact of land surface degradation in northern China and southern Mongolia on regional climate

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jingyong; DONG Wenjie; FU Congbin

    2005-01-01

    Clear evidence provided by the singular value decomposition (SVD) analysis to the normalized difference vegetation index (NDVI) and precipitation data identifies that there exists a sensitive region of vegetation-climate interaction located in the transitional zone over northern China and its surrounding areas, where the vegetation cover change has the most significant influence on summer precipitation over China. Comparison of reanalysis data with station data provides a good method to assess the impacts of land use change on surface temperature, and the most obvious contribution of land use change may be to lead to notable warming over northern China in the interdecadal time scale. Based on the new statistical results, a high-resolution regional integrated environmental model system (RIEMS) is employed to investigate the effects of land surface degradation over the transitional zone and its surrounding areas (northern China and southern Mongolia) on the regional climate. Land degradation results in the decreases in precipitation over northern and southern China, and the increase in between, and increased and decreased temperature over vegetation change areas and the adjacent area to the south, respectively. Not only would it change the surface climate, but also bring the significant influence on the atmospheric circulation. Both the surface climate and circulation changes generally agree to the observed interdecadal anomalies over the last five decades. These integrated statistical and simulated results imply that land surface degradation over the transitional zone in northern China and its surrounding areas could be one of the main causes responsible for the climate anomalies over China, especially the drought over northern China.

  5. How you cannot find rain with changes in land surface temperature

    Science.gov (United States)

    Wanders, Niko

    2017-04-01

    Estimating precipitation from space-born sensors is valuable source of observation in poorly-gauged regions. For example, hydrological modelling and monitoring greatly benefits from the increased near-real time data availability for improved accuracy in the simulations of water resources. As is true for all satellite product, precipitation estimated from space are far from perfect and scientist have used many techniques to improve their accuracy. In this study, I tried to improve the space-born precipitation estimates by using remotely sensed soil moisture to observe sudden increases in soil wetness as a result of precipitation. After a month of massaging the data and applied methodology I realized that the gain was very marginal and I was drilling a dry hole. Driven by these disappointing results I tried some random other satellite products to see if they showed correlation with the precipitation signal. There I found a causality that I had not expected at the start of this study, linking land surface temperature to precipitation. It seemed that using changes in land surface temperature strongly correlated with precipitation totals, driven by a cooling of the soil as a result of increase wetness. This link could not only be modelled, but more surprisingly it could be observed from space and used to improve the satellite precipitation estimates. The reduction in the precipitation uncertainty was far better than for any of the three soil moisture products, contrary to what one might expect. This was far from the anticipated result but it showed me that sometimes you should think out of the box and not only use observations for their intended purpose. This experience has motivated me to not only use the obvious observation or method and try techniques and methods from other disciplines to see if we can improve our understanding of the hydrological cycle.

  6. Evaluation of a photosyntheses-based canopy resistance formulation in the Noah Land-surface model

    Science.gov (United States)

    Accurately representing complex land-surface processes balancing complexity and realism remains one challenge that the weather modelling community is facing nowadays. In this study, a photosynthesis-based Gas-exchange Evapotranspiration Model (GEM) is integrated into the Noah land-surface model repl...

  7. The sand extraction potential of embedded land surface lowering in the Netherlands

    NARCIS (Netherlands)

    Meulen, M.J. van der; Kleine, M.P.E. de; Veldkamp, J.G.; Dubelaar, C.W.; Pietersen, H.S.

    2004-01-01

    In the Netherlands, mineral extraction by means of dredging or quarrying meets with considerable societal resistance. Land surface lowering prior to large land reconstruction projects may raise fewer objections. We have calculated the potential yields of sand and gravel from land surface lowering

  8. The sand extraction potential of embedded land surface lowering in the Netherlands

    NARCIS (Netherlands)

    Van der Meulen, M.J.; De Kleine, M.P.E.; Veldkamp, J.G.; Dubbelaar, C.W.; Pietersen, H.S.

    2004-01-01

    In the Netherlands, mineral extraction by means of dredging or quarrying meets with considerable societal resistance. Land surface lowering prior to large land reconstruction projects may raise fewer objections. We have calculated the potential yields of sand and gravel form land surface lowering

  9. Long-term change in surface air temperature over Eurasian continent and possible contribution from land-surface conditions.

    Science.gov (United States)

    Kim, K.; Jeong, J. H.; Shim, T.

    2015-12-01

    Summertime heat wave over Eurasia is induced by various climatic factors. As internal and external factors are changing under an abrupt climate change, the variability of heat waves exhibits radical changes. In this study, the long-term change in heat wave characteristics over Eurasia for the last several decades was examined and the impact of land-atmosphere interaction modulated by soil moisture variability on the change was investigated. Through the empirical orthogonal functions(EOF) analysis, the principle spatio-temporal pattern of Eurasian heat wave during July-August was objectively detected. The leading pattern (1st EOF mode) of the variability was found be an overall increase in heat waves over eastern Europe and east Asia (Mongol to northern part of China), which seems to be associated mainly with the global warming signal but with interannual variability as well. Through performing JULES(Joint UK Land Environment Simulator) land surface model simulation forced with observational atmospheric forcings, soil moisture and energy flux at surface were estimated, and the impacts of land-atmosphere interaction on the heat wave variability was investigated based on the estimated land surface variables and temperature observations. It is found that there is a distinct dry soil condition accompanying with East Asian heat waves. The dry condition leads to an increase in sensible heat flux from land surface to atmosphere and resulting near-surface warming, which is followed by warm-core high - a typical characteristics of a heatwave sustained by land-atmosphere interaction. This result is consistent with an distinct increase in heatwave in recent years. By using the hindcast of long-range prediction model of KMA, GloSea5, the seasonal predictability of heatwave was examined. GloSea5 reasonably well simulates the spatial pattern of Eurasian heatwaves variability found in observations but shows modest skill in simulating accurate year-to-year variability. This result

  10. Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets

    Science.gov (United States)

    Lawston, Patricia M.; Santanello, Joseph A., Jr.; Franz, Trenton E.; Rodell, Matthew

    2017-06-01

    Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASA's Land Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high-resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily timescales. In addition, this study uses point and gridded soil moisture observations from fixed and roving cosmic-ray neutron probes and co-located human-practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation for accurate simulation of water and energy states and fluxes over cropland.

  11. Assimilation of neural network soil moisture in land surface models

    Science.gov (United States)

    Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias

    2017-04-01

    In this study a set of land surface data assimilation (DA) experiments making use of satellite derived soil moisture (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of soil moisture for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and Soil Moisture and Ocean Salinity (SMOS) data were used. The SMOS soil moisture dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and soil-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests

  12. Impact of Land Surface Heterogeneity on Mesoscale Atmospheric Dispersion

    Science.gov (United States)

    Wu, Yuling; Nair, Udaysankar S.; Pielke, Roger A., Sr.; McNider, Richard T.; Christopher, Sundar A.; Anantharaj, Valentine G.

    2009-01-01

    Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities, but past studies do not consider the impact of a realistic distribution of surface heterogeneities on mesoscale atmospheric dispersion. While these focussed on dispersion in the convective boundary layer, the present work also considers dispersion in the nocturnal boundary layer and above. Using a Lagrangian particle dispersion model (LPDM) coupled to the Eulerian Regional Atmospheric Modeling System (RAMS), the impact of topographic, vegetation, and soil moisture heterogeneities on daytime and nighttime atmospheric dispersion is examined. In addition, the sensitivity to the use of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived spatial distributions of vegetation characteristics on atmospheric dispersion is also studied. The impact of vegetation and terrain heterogeneities on atmospheric dispersion is strongly modulated by soil moisture, with the nature of dispersion switching from non-Gaussian to near- Gaussian behaviour for wetter soils (fraction of saturation soil moisture content exceeding 40%). For drier soil moisture conditions, vegetation heterogeneity produces differential heating and the formation of mesoscale circulation patterns that are primarily responsible for non-Gaussian dispersion patterns. Nighttime dispersion is very sensitive to topographic, vegetation, soil moisture, and soil type heterogeneity and is distinctly non-Gaussian for heterogeneous land-surface conditions. Sensitivity studies show that soil type and vegetation heterogeneities have the most dramatic impact on atmospheric dispersion. To provide more skillful dispersion calculations, we recommend the utilisation of satellite-derived vegetation characteristics coupled with data assimilation techniques that constrain soil-vegetation-atmosphere transfer (SVAT) models to generate realistic spatial distributions of surface energy fluxes.

  13. Reconstruction of MODIS daily land surface temperature under clouds

    Science.gov (United States)

    Sun, L.; Gao, F.; Chen, Z.; Song, L.; Xie, D.

    2015-12-01

    Land surface temperature (LST), generally defined as the skin temperature of the Earth's surface, controls the process of evapotranspiration, surface energy balance, soil moisture change and climate change. Moderate Resolution Imaging Spectrometer (MODIS) is equipped with 1km resolution thermal sensor andcapable of observing the earth surface at least once per day.Thermal infrared bands cannot penetrate cloud, which means we cannot get consistency drought monitoring condition at one area. However, the cloudy-sky conditions represent more than half of the actual day-to-day weather around the global. In this study, we developed an LST filled model based on the assumption that under good weather condition, LST difference between two nearby pixels are similar among the closest 8 days. We used all the valid pixels covered by a 9*9 window to reconstruct the gap LST. Each valid pixel is assigned a weight which is determined by the spatial distance and the spectral similarity. This model is applied in the Middle-East of China including Gansu, Ningxia, Shaanxi province. The terrain is complicated in this area including plain and hill. The MODIS daily LST product (MOD11A3) from 2000 to 2004 is tested. Almost all the gap pixels are filled, and the terrain information is reconstructed well and smoothly. We masked two areas in order to validate the model, one located in the plain, another located in the hill. The correlation coefficient is greater than 0.8, even up to 0.92 in a few days. We also used ground measured day maximum and mean surface temperature to valid our model. Although both the temporal and spatial scale are different between ground measured temperature and MODIS LST, they agreed well in all the stations. This LST filled model is operational because it only needs LST and reflectance, and does not need other auxiliary information such as climate factors. We will apply this model to more regions in the future.

  14. Evaluation and Monitoring of Jpss Land Surface Temperature Data

    Science.gov (United States)

    Yu, Y.; Yu, P.; Liu, Y.; Csiszar, I. A.

    2016-12-01

    Land Surface Temperature (LST) is one of environmental data records (EDRs) produced operationally through the U.S. Joint Polar Satellite System (JPSS) mission. LST is an important parameter for understanding climate change, modeling the hydrological and biogeochemical cycles, and is a prime candidate for Numerical Weather Prediction (NWP) assimilation models. Recently, the international LST and Emissivity Working Ggroup (ILSTE-WG) is promoting to the inclusion of the LST as essential climate variable (ECV) in the Global Climate Observation System (GCOS) of the Word Meteorological Organization (WMO). At the Center for Satellite Applications and Research (STAR) of National Atmospheric and Oceanic Administration (NOAA), we, are as a science team, are responsible to for the science of JPSS LST production. In this work, we present our activities and accomplishments on the JPSS LST evaluation and monitoring since the launch of the first JPSS satellite, i.e. S-NPP, satellite. Beta version, provisional version, and validated stage 1 version of the S-NPP LST products which were announced in May 2013, July 2014, and March 2015, respectively. Evaluation of the LST products have been performed versus ground measurements and other polar-orbiting satellite LST data (e,g. MODIS LSTs); some results will be illustrated. A daily monitoring system of the JPSS LST production has been developed, which presents daily, weekly and monthly global LST maps and inter-comparison results on the STAR JPSS program website. Further, evaluation of the enterprise LST algorithm for JPSS mission which is in development at STAR currently are presented in this work. Finally, evaluation and monitoring plan of the LST production for the JPSS-1 satellite are also presented.

  15. Estimation of Land Surface Temperature from 1-km AVHRR data

    Science.gov (United States)

    Frey, Corinne

    2016-04-01

    In order to re-process DLRs 1km AVHRR data archive to different geophysical and descriptive parameters of the land surface and the atmosphere, a series of scientific data processors are being developed in the framework of the TIMELINE project. The archive of DLR ranges back to the 80ies. One of the data processors is SurfTemp, which processes L2 LST and emissivity datasets from AVHRR L1b data. The development of the data processor included the selection of statistical procedures suitable for time series processing, including four mono-window and six split window algorithms. For almost all of these algorithms, new constants were generated, which better account for different atmospheric and geometric acquisition situations. The selection of optimal algorithms for SurfTemp is based on a round robin approach, in which the selected mono-window and split window algorithms are tested on the basis of a large number of TOA radiance/LST pairs, which were generated using a radiative transfer model and the SeeBorV5 profile database. The original LSTs are thereby compared to the LSTs derived from the TOA radiances using the mono- and split window algorithms. The algorithm comparison includes measures of precision, as well as the sensitivity of a method to the accuracy of its input data. The results of the round robin are presented, as well as the implementation of selected algorithms into SurfTemp. Further, first cross-validation results between the AVHRR LST and MODIS LST are shown.

  16. Roughness Length of Water Vapor over Land Surfaces and Its Influence on Latent Heat Flux

    Directory of Open Access Journals (Sweden)

    Sang-Jong Park

    2010-01-01

    Full Text Available Latent heat flux at the surface is largely dependent on the roughness length for water vapor (z0q. The determination of z0q is still uncertain because of its multifaceted characteristics of surface properties, atmospheric conditions and insufficient observations. In this study, observed values from the Fluxes Over Snow Surface II field experiment (FLOSS-II from November 2002 to March 2003 were utilized to estimate z0q over various land surfaces: bare soil, snow, and senescent grass. The present results indicate that the estimated z0q over bare soil is much smaller than the roughness length of momentum (z0m; thus, the ratio z0m/z0q is larger than those of previous studies by a factor of 20 - 150 for the available flow regime of the roughness Reynolds number, Re* > 0.1. On the snow surface, the ratio is comparable to a previous estimation for the rough flow (Re* > 1, but smaller by a factor of 10 - 50 as the flow became smooth (Re* < 1. Using the estimated ratio, an optimal regression equation of z0m/z0q is determined as a function of Re* for each surface type. The present parameterization of the ratio is found to greatly reduce biases of latent heat flux estimation compared with that estimated by the conventional method, suggesting the usefulness of current parameterization for numerical modeling.

  17. Implementing surface parameter aggregation rules in the CCM3 global climate model: regional responses at the land surface

    Directory of Open Access Journals (Sweden)

    M. A. Arain

    1999-01-01

    Full Text Available The land-surface parameters required as input to a GCM grid box (typically a few degrees are often set to be those of the dominant vegetation type within the grid box. This paper discusses the use and effect of aggregation rules for specifying effective values of these land cover parameters by taking into account the relative proportion of each land-cover type within each individual grid box. Global land-cover classification data at 1 km resolution were used to define Biosphere Atmosphere Transfer Scheme (BATS specific aggregate (using aggregation rules land-cover parameters. Comparison of the values of the aggregate parameters and those defined using the single dominant vegetation type (default parameters shows significant differences in some regions, particularly in the semi-desert and in forested regions, e.g. the Sahara Desert and the tropical forest of South America. These two different sets of parameters were used as input data for two 10-year simulations of the NCAR CCM3 model coupled to the BATS land-surface scheme. Statistical analyses comparing the results of the two model runs showed that the resulting effects on the land-surface diagnostics are significant only in specific regions. For example, the sensible heat flux in the Sahara Desert calculated for the aggregate parameter run increased due to the marked increase in the minimum stomatal resistance and the decrease in fractional vegetation cover in the aggregate parameters over the default parameters. The modelled global precipitation and surface air temperature fields were compared to observations: there is a general improvement in the performance of the aggregate parameter run over the default parameter run in areas where the differences between the aggregate and default parameter run are significant. However, most of the difference between the modelled and observed fields is attributable to other model deficiencies. It can be concluded that the use of aggregation rules to derive

  18. On improving cold region hydrological processes in the Canadian Land Surface Scheme

    Science.gov (United States)

    Ganji, Arman; Sushama, Laxmi; Verseghy, Diana; Harvey, Richard

    2017-01-01

    Regional and global climate model simulated streamflows for high-latitude regions show systematic biases, particularly in the timing and magnitude of spring peak flows. Though these biases could be related to the snow water equivalent and spring temperature biases in models, a good part of these biases is due to the unaccounted effects of non-uniform infiltration capacity of the frozen ground and other related processes. In this paper, the treatment of frozen water in the Canadian Land Surface Scheme (CLASS), which is used in the Canadian regional and global climate models, is modified to include fractional permeable area, supercooled liquid water and a new formulation for hydraulic conductivity. The impact of these modifications on the regional hydrology, particularly streamflow, is assessed by comparing three simulations performed with the original and two modified versions of CLASS, driven by atmospheric forcing data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis (ERA-Interim) for the 1990-2001 period over a northeast Canadian domain. The two modified versions of CLASS differ in the soil hydraulic conductivity and matric potential formulations, with one version being based on formulations from a previous study and the other one is newly proposed. Results suggest statistically significant decreases in infiltration and therefore soil moisture during the snowmelt season for the simulation with the new hydraulic conductivity and matric potential formulations and fractional permeable area concept compared to the original version of CLASS, which is also reflected in the increased spring surface runoff and streamflows in this simulation with modified CLASS over most of the study domain. The simulated spring peaks and their timing in this simulation are also in better agreement to those observed. This study thus demonstrates the importance of treatment of frozen water for realistic simulation of streamflows.

  19. A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Yongmin Yang

    2017-01-01

    Full Text Available The partitioning of available energy between sensible heat and latent heat is important for precise water resources planning and management in the context of global climate change. Land surface temperature (LST is a key variable in energy balance process and remotely sensed LST is widely used for estimating surface heat fluxes at regional scale. However, the inequality between LST and aerodynamic surface temperature (Taero poses a great challenge for regional heat fluxes estimation in one-source energy balance models. To address this issue, we proposed a One-Source Model for Land (OSML to estimate regional surface heat fluxes without requirements for empirical extra resistance, roughness parameterization and wind velocity. The proposed OSML employs both conceptual VFC/LST trapezoid model and the electrical analog formula of sensible heat flux (H to analytically estimate the radiometric-convective resistance (rae via a quartic equation. To evaluate the performance of OSML, the model was applied to the Soil Moisture-Atmosphere Coupling Experiment (SMACEX in United States and the Multi-Scale Observation Experiment on Evapotranspiration (MUSOEXE in China, using remotely sensed retrievals as auxiliary data sets at regional scale. Validated against tower-based surface fluxes observations, the root mean square deviation (RMSD of H and latent heat flux (LE from OSML are 34.5 W/m2 and 46.5 W/m2 at SMACEX site and 50.1 W/m2 and 67.0 W/m2 at MUSOEXE site. The performance of OSML is very comparable to other published studies. In addition, the proposed OSML model demonstrates similar skills of predicting surface heat fluxes in comparison to SEBS (Surface Energy Balance System. Since OSML does not require specification of aerodynamic surface characteristics, roughness parameterization and meteorological conditions with high spatial variation such as wind speed, this proposed method shows high potential for routinely acquisition of latent heat flux estimation

  20. Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

    Science.gov (United States)

    Yu, Miao; Wang, Guiling; Chen, Haishan

    2016-03-01

    Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In this study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, a process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081-2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981-2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. These uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the

  1. Modifications in the land surface model ORCHIDEE and application in the Tarim basin

    Science.gov (United States)

    Zhou, Xudong; Polcher, Jan; Yang, Tao; Nguyen Quang, Trung; Hirabayashi, Yukiko

    2017-04-01

    Land surface modeling in regions mixing high mountains and arid deserts remains a great challenge due to the inadequate representations of physical processes in atmospheric forcings , runoff generation, evaporation and river routing. A few key improvements were analyzed within ORCHIDEE (Organising Carbon and Hydrology in Dynamic Ecosystems) to better understand these limitations as well as quantify their influence on the water cycle over Tarim basin (TRB). The TRB is a representative endorheic basin in center Asia, with glacier and snow melting, limited precipitation but strong evaporation, high spatial heterogeneity and intensive human interference, thus challenging any land surface model. National observations on daily precipitation from China Meteorological Administration (CMA) were used to correct precipitation inputs on the basis of WATCH forcing datasets. The independent glacier melting simulation by HYOGA2 was added to the forcing to overcome the lack of glacier module in ORCHIDEE. Improvements in the snow scheme provided more accurate simulations of the soil temperature which restrict the infiltration process when the soil is frozen. In addition, a novel routing scheme with finer spatial resolution from 50km to 1km was developed based on HydroSHED map. It improves the descriptions of catchments boundaries, the flow direction and the water residence time within sub-basins that make significant difference especially for the mountainous area and flat plains. Model results with these modifications were compared through various atmospheric and hydrological variables (i.e. evaporation, soil moisture, runoff and discharge). In conclusion, the correction by the precipitation observations and involvement of glacier melting simulations increase the water input to the basin by 37.2% and 8.4% respectively, which in turn increases evaporation, soil moisture and runoff to different extents. The new snow and soil freezing scheme advance in time the spring high-water in

  2. The effects of land surface process perturbations in a global ensemble forecast system

    Science.gov (United States)

    Deng, Guo; Zhu, Yuejian; Gong, Jiandong; Chen, Dehui; Wobus, Richard; Zhang, Zhe

    2016-10-01

    Atmospheric variability is driven not only by internal dynamics, but also by external forcing, such as soil states, SST, snow, sea-ice cover, and so on. To investigate the forecast uncertainties and effects of land surface processes on numerical weather prediction, we added modules to perturb soil moisture and soil temperature into NCEP's Global Ensemble Forecast System (GEFS), and compared the results of a set of experiments involving different configurations of land surface and atmospheric perturbation. It was found that uncertainties in different soil layers varied due to the multiple timescales of interactions between land surface and atmospheric processes. Perturbations of the soil moisture and soil temperature at the land surface changed sensible and latent heat flux obviously, as compared to the less or indirect land surface perturbation experiment from the day-to-day forecasts. Soil state perturbations led to greater variation in surface heat fluxes that transferred to the upper troposphere, thus reflecting interactions and the response to atmospheric external forcing. Various verification scores were calculated in this study. The results indicated that taking the uncertainties of land surface processes into account in GEFS could contribute a slight improvement in forecast skill in terms of resolution and reliability, a noticeable reduction in forecast error, as well as an increase in ensemble spread in an under-dispersive system. This paper provides a preliminary evaluation of the effects of land surface processes on predictability. Further research using more complex and suitable methods is needed to fully explore our understanding in this area.

  3. Water Balance in the Amazon Basin from a Land Surface Model Ensemble

    Science.gov (United States)

    Getirana, Augusto C. V.; Dutra, Emanuel; Guimberteau, Matthieu; Kam, Jonghun; Li, Hong-Yi; Decharme, Bertrand; Zhang, Zhengqiu; Ducharne, Agnes; Boone, Aaron; Balsamo, Gianpaolo; Rodell, Matthew; Toure, Ally M.; Xue, Yongkang; Peters-Lidard, Christa D.; Kumar, Sujay V.; Arsenault, Kristi; Drapeau, Guillaume; Leung, L. Ruby; Ronchail, Josyane; Sheffield, Justin

    2014-01-01

    Despite recent advances in land surfacemodeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-ofthe- art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 18 spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to matchmonthly Global Precipitation Climatology Project (GPCP) andGlobal Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l'Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets andGravity Recovery and ClimateExperiment (GRACE)TWSestimates in two subcatchments of main tributaries (Madeira and Negro Rivers).At the basin scale, simulated ET ranges from 2.39 to 3.26 mm day(exp -1) and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.

  4. Towards a public, standardized, diagnostic benchmarking system for land surface models

    Directory of Open Access Journals (Sweden)

    G. Abramowitz

    2012-02-01

    Full Text Available We examine different conceptions of land surface model benchmarking and illustrate the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. We additionally show how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and give an example of how these expectations might be quantified. Finally, we introduce the Protocol for the Analysis of Land Surface models (PALS, a free, online land surface model benchmarking application, and show how it is structured to meet both of these goals.

  5. Towards a public, standardized, diagnostic benchmarking system for land surface models

    Directory of Open Access Journals (Sweden)

    G. Abramowitz

    2012-06-01

    Full Text Available This work examines different conceptions of land surface model benchmarking and the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. It additionally demonstrates how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and gives an example of how these expectations might be quantified. Finally, the Protocol for the Analysis of Land Surface models (PALS is introduced – a free, online land surface model benchmarking application that is structured to meet both of these goals.

  6. Particle Simulations of DARHT-II Transport System

    Energy Technology Data Exchange (ETDEWEB)

    Poole, B; Chen, Y J

    2001-06-11

    The DARHT-II beam line utilizes a fast stripline kicker to temporally chop a high current electron beam from a single induction LINAC and deliver multiple temporal electron beam pulses to an x-ray converter target. High beam quality needs to be maintained throughout the transport line from the end of the accelerator through the final focus lens to the x-ray converter target to produce a high quality radiographic image. Issues that will affect beam quality such as spot size and emittance at the converter target include dynamic effects associated with the stripline kicker as well as emittance growth due to the nonlinear forces associated with the kicker and various focusing elements in the transport line. In addition, dynamic effects associated with transverse resistive wall instability as well as gas focusing will affect the beam transport. A particle-in-cell code is utilized to evaluate beam transport in the downstream transport line in DARHT-II. External focusing forces are included utilizing either analytic expressions or field maps. Models for wakefields from the beam kicker, transverse resistive wall instability, and gas focusing are included in the simulation to provide a more complete picture of beam transport in DARHT-II. From these simulations, for various initial beam loads based on expected accelerator performance the temporally integrated target spot size and emittance can be estimated.

  7. Particle Simulations of DARHT-II Transport System

    Energy Technology Data Exchange (ETDEWEB)

    Poole, B; Chen, Y J

    2001-06-11

    The DARHT-II beam line utilizes a fast stripline kicker to temporally chop a high current electron beam from a single induction LINAC and deliver multiple temporal electron beam pulses to an x-ray converter target. High beam quality needs to be maintained throughout the transport line from the end of the accelerator through the final focus lens to the x-ray converter target to produce a high quality radiographic image. Issues that will affect beam quality such as spot size and emittance at the converter target include dynamic effects associated with the stripline kicker as well as emittance growth due to the nonlinear forces associated with the kicker and various focusing elements in the transport line. In addition, dynamic effects associated with transverse resistive wall instability as well as gas focusing will affect the beam transport. A particle-in-cell code is utilized to evaluate beam transport in the downstream transport line in DARHT-II. External focusing forces are included utilizing either analytic expressions or field maps. Models for wakefields from the beam kicker, transverse resistive wall instability, and gas focusing are included in the simulation to provide a more complete picture of beam transport in DARHT-II. From these simulations, for various initial beam loads based on expected accelerator performance the temporally integrated target spot size and emittance can be estimated.

  8. Practical retrieval of land surface emissivity spectra in 8-14 μm from hyperspectral thermal infrared data.

    Science.gov (United States)

    Wu, Hua; Wang, Ning; Ni, Li; Tang, Bo-Hui; Li, Zhao-Liang

    2012-10-22

    A practical physics-based regression method was developed and evaluated for nearly real time estimate of land surface emissivity spectra in 8-14 μm from hyperspectral thermal infrared data. Two spectral emissivity libraries and one atmospheric profile database fully covering all the possible situations for clear sky conditions were elaborately selected to simulate the radiances at the top of the atmosphere (TOA). The regression coefficients were determined by the main principal components of emissivity spectra and those of simulated brightness temperature at TOA using a ridge regression method. The experience with the simulated Interferometer Atmospheric Sounding Instrument (IASI) data showed that the emissivity spectra could be retrieved under clear sky conditions with root mean square errors of 0.015 and 0.03 for 714-970 cm(-1) (10.3-14.0 μm) and 970-1250 cm(-1) (8.0-10.3 μm), respectively, for various land surface and atmospheric conditions. This indicates the proposed method may be robust and applicable for all hyperspectral infrared sensors.

  9. Multi-objective calibration of the land surface scheme TERRA/LM using LITFASS-2003 data

    Directory of Open Access Journals (Sweden)

    K.-P. Johnsen

    2005-01-01

    Full Text Available The turbulent sensible and latent heat fluxes simulated in the operational weather forecast model LM have been checked with data from the field experiment LITFASS 2003 (Lindenberg Inhomogeneous Terrain - Fluxes between Atmosphere and Surface: a Long-term Study using both single site measurements and grid box aggregated fluxes. SCE-UA (single objective and MOSCEM-UA (multi-objective approaches were applied to calibrate the land-surface scheme TERRA/LM for 11 single sites and for the aggregated fluxes. A large variation is seen among the parameter sets found by calibration but no typical classification according to vegetation type is obvious. This is attributed to the calibrated parameter sets correcting for model deficiencies and data errors rather than describing the physical characteristics of the measurement site. The measured fluxes were combined into a time series of aggregated fluxes by the tile method. Calibration of TERRA/LM with respect to the averaged fluxes resulted in a range of parameter sets which all simulated the area-averaged fluxes in much better agreement with the observed fluxes than the standard parameter set of the operational model. A modified Nash-Sutcliffe measure as a coincidence criterion fell from 0.3 to a range between 0.15 and 0.28 for the latent heat flux and from 0.43 to between 0.26 and 0.36 for the sensible heat flux when the calibrated parameter sets were used instead of the standard parameters.

  10. An enhanced single-channel algorithm for retrieving land surface temperature from Landsat series data

    Science.gov (United States)

    Wang, Mengmeng; Zhang, Zhaoming; He, Guojin; Wang, Guizhou; Long, Tengfei; Peng, Yan

    2016-10-01

    Land surface temperature (LST) is a critical parameter in the physics of Earth surface processes and is required for many applications related to ecology and environment. Landsat series satellites have provided more than 30 years of thermal information at medium spatial resolution. This paper proposes an enhanced single-channel algorithm (SCen) for retrieving LST from Landsat series data (Landsat 4 to Landsat 8). The SCen algorithm includes three atmospheric functions (AFs), and the latitude and acquisition month of Landsat image were added to the AF models to improve LST retrieval. Performance of the SCen algorithm was assessed with both simulated and in situ data, and accuracy of three single-channel algorithms (including the monowindow algorithm developed by Qin et al., SCQin, and the generalized single-channel algorithm developed by Jiménez-Muñoz and Sobrino, SCJ&S) were compared. The accuracy assessments with simulated data had root-mean-square deviations (RMSDs) for the SCen, SCJ&S, and SCQin algorithms of 1.363 K, 1.858 K, and 2.509 K, respectively. Validation with in situ data showed RMSDs for the SCen and SCJ&S algorithms of 1.04 K and 1.49 K, respectively. It was concluded that the SCen algorithm is very operational, has good precision, and can be used to develop an LST product for Landsat series data.

  11. Land surface albedo and vegetation feedbacks enhanced the millennium drought in south-east Australia

    Science.gov (United States)

    Evans, Jason P.; Meng, Xianhong; McCabe, Matthew F.

    2017-01-01

    In this study, we have examined the ability of a regional climate model (RCM) to simulate the extended drought that occurred throughout the period of 2002 through 2007 in south-east Australia. In particular, the ability to reproduce the two drought peaks in 2002 and 2006 was investigated. Overall, the RCM was found to reproduce both the temporal and the spatial structure of the drought-related precipitation anomalies quite well, despite using climatological seasonal surface characteristics such as vegetation fraction and albedo. This result concurs with previous studies that found that about two-thirds of the precipitation decline can be attributed to the El Niño-Southern Oscillation (ENSO). Simulation experiments that allowed the vegetation fraction and albedo to vary as observed illustrated that the intensity of the drought was underestimated by about 10 % when using climatological surface characteristics. These results suggest that in terms of drought development, capturing the feedbacks related to vegetation and albedo changes may be as important as capturing the soil moisture-precipitation feedback. In order to improve our modelling of multi-year droughts, the challenge is to capture all these related surface changes simultaneously, and provide a comprehensive description of land surface-precipitation feedback during the droughts development.

  12. Comparing potential recharge estimates from three Land Surface Models across the western US

    Science.gov (United States)

    Niraula, Rewati; Meixner, Thomas; Ajami, Hoori; Rodell, Matthew; Gochis, David; Castro, Christopher L.

    2017-02-01

    Groundwater is a major source of water in the western US. However, there are limited recharge estimates in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01% to 15% for Mosaic, 3.2% to 42% for Noah, and 6.7% to 31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge in data limited regions.

  13. Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds

    Directory of Open Access Journals (Sweden)

    Xiwei Fan

    2015-04-01

    Full Text Available Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST retrieval error of 11.0 K when using the generalized split-window (GSW algorithm with a cirrus optical depth (COD at 0.55 μm of 0.4 and in nadir view. A correction term in the COD linear function was added to the GSW algorithm to extend the GSW algorithm to cirrus cloudy conditions. The COD was acquired by a look up table of the isolated cirrus bidirectional reflectance at 0.55 μm. Additionally, the slope k of the linear function was expressed as a multiple linear model of the top of the atmospheric brightness temperatures of MODIS channels 31–34 and as the difference between split-window channel emissivities. The simulated data showed that the LST error could be reduced from 11.0 to 2.2 K. The sensitivity analysis indicated that the total errors from all the uncertainties of input parameters, extension algorithm accuracy, and GSW algorithm accuracy were less than 2.5 K in nadir view. Finally, the Great Lakes surface water temperatures measured by buoys showed that the retrieval accuracy of the GSW algorithm was improved by at least 1.5 K using the proposed extension algorithm for cirrus skies.

  14. Cross-validation of satellite products over France through their integration into a land surface model

    Science.gov (United States)

    Calvet, Jean-Christophe; Barbu, Alina; Carrer, Dominique; Meurey, Catherine

    2014-05-01

    Long (more than 30 years) time series of satellite-derived products over land are now available. They concern Essential Climate Variables (ECV) such as LAI, FAPAR, surface albedo, and soil moisture. The direct validation of such Climate Data Records (CDR) is not easy, as in situ observations are limited in space and time. Therefore, indirect validation has a key role. It consists in comparing the products with similar preexisting products derived from satellite observations or from land surface model (LSM) simulations. The most advanced indirect validation technique consists in integrating the products into a LSM using a data assimilation scheme. The obtained reanalysis accounts for the synergies of the various upstream products and provides statistics which can be used to monitor the quality of the assimilated observations. Meteo-France develops the ISBA-A-gs generic LSM able to represent the diurnal cycle of the surface fluxes together with the seasonal, interannual and decadal variability of the vegetation biomass. The LSM is embedded in the SURFEX modeling platform together with a simplified extended Kalman filter. These tools form a Land Data Assimilation System (LDAS). The current version of the LDAS assimilates SPOT-VGT LAI and ASCAT surface soil moisture (SSM) products over France (8km x 8km), and a passive monitoring of albedo, FAPAR and Land Surface temperature (LST) is performed (i.e., the simulated values are compared with the satellite products). The LDAS-France system is used in the European Copernicus Global Land Service (http://land.copernicus.eu/global/) to monitor the quality of upstream products. The LDAS generates statistics whose trends can be analyzed in order to detect possible drifts in the quality of the products: (1) for LAI and SSM, metrics derived from the active monitoring (i.e. assimilation) such as innovations (observations vs. model forecast), residuals (observations vs. analysis), and increments (analysis vs. model forecast) ; (2

  15. Calibration of the Distributed Hydrological Model mHM using Satellite derived Land Surface Temperature

    Science.gov (United States)

    Zink, M.; Samaniego, L. E.; Cuntz, M.

    2012-12-01

    A combined investigation of the water and energy balance in hydrologic models can lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on information of few points within a catchment. This procedure does not take into account any spatio-temporal variability of fluxes or state variables. Satellite data are a useful source of information to account for this spatial distributions. The objective of this study is to calibrate the distributed hydrological model mHM with satellite derived Land Surface Temperature (LST) fields provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). LST is preferred to other satellite products such as soil moisture or evapotranspiration due to its higher precision. LST is obtained by solving the energy balance by assuming that the soil heat flux and the storage term are negligible on a daily time step. The evapotranspiration is determined by closing the water balance in mHM. The net radiation is calculated by using the incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is used to determine the aerodynamic resistance among other parameters. The optimization is performed within the time period 2008-2010 using three objective functions that consider 1) only discharge, 2) only LST, and 3) a combination of both. The proposed method is applied to seven major German river basins: Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The annual coefficient of correlation between LSA-SAF incoming shortwave radiation and 28 meteorological stations operated by the German Weather Service (DWD) is 0.94 (RMSE = 29 W m-2) in 2009. LSA-SAF incoming longwave radiation could be further evaluated at two eddy covariance stations with a very similar

  16. On the development of a coupled land surface and groundwater model

    Energy Technology Data Exchange (ETDEWEB)

    Maxwell, R.M.; Miller, N.L.

    2004-05-04

    Management of surface water quality is often complicated by interactions between surface water and groundwater. Traditional Land-Surface Models (LSM) used for numerical weather prediction, climate projection, and as inputs to water management decision support systems, do not treat the LSM lower boundary in a fully process-based fashion. LSMs have evolved from a leaky bucket to more sophisticated land surface water and energy budget models that typically have a so-called basement term to depict the bottom model layer exchange with deeper aquifers. Nevertheless, the LSM lower boundary is often assumed zero flux or the soil moisture content is set to a constant value; an approach that while mass conservative, ignores processes that can alter surface fluxes, runoff, and water quantity and quality. Conversely, groundwater models (GWM) for saturated and unsaturated water flow, while addressing important features such as subsurface heterogeneity and three-dimensional flow, often have overly simplified upper boundary conditions that ignore soil heating, runoff, snow and root-zone uptake. In the present study, a state-of-the-art LSM (CLM) and a variably-saturated GWM (ParFlow) have been coupled as a single column model. A set of simulations based on synthetic data and data from the Project for Intercomparison of Landsurface Parameterization Schemes (PILPS), version 2(d), 18-year dataset from Valdai, Russia demonstrate the temporal dynamics of this coupled modeling system. Changes in soil moisture and movement of the water table are used as indicators of mass conservation between the LSM and GWM. This study demonstrates the affect of aquifer storage and a dynamic water table on predicted watershed flow. The model's ability to capture certain cold processes such as frozen soil and freeze/thaw processes are discussed. Comparisons of the uncoupled and coupled modes are presented and the differences in simulations of soil moisture and shallow and deeper ground processes are

  17. Influences of biomass heat and biochemical energy storages on the land surface fluxes and radiative temperature

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Lianhong [ORNL; Meyers, T. P. [NOAA ATDD; Pallardy, Stephen G. [University of Missouri; Hanson, Paul J [ORNL; Yang, Bai [ORNL; Heuer, Mark [ATDD, NOAA; Hosman, K. P. [University of Missouri; Liu, Qing [ORNL; Riggs, Jeffery S [ORNL; Sluss, Daniel Wayne [ORNL; Wullschleger, Stan D [ORNL

    2007-01-01

    We conducted observations and modeling at a forest site to assess importance of biomass heat and biochemical energy storages for land-atmosphere interactions. We used the terrestrial ecosystem Fluxes And Pools Integrated Simulator (FAPIS). We first examined FAPIS performance by testing its predictions with and without biomass energy storages against measurements of surface energy and CO2 fluxes. We then evaluated the magnitudes and temporal patterns of the calculated biomass energy storages. Effects of energy storages on flux exchanges and variations of radiative temperature were investigated by contrasting FAPIS simulations with and without the storages. We found that with the storages, FAPIS predictions agreed with measurements well; without them, FAPIS performance deteriorated for all surface energy fluxes. The biomass heat storage and biochemical energy storage had clear diurnal patterns with typical ranges from -50 to 50 and -3 to 20 Wm-2, respectively; these typical ranges were exceeded substantially when there were sudden changes in atmospheric conditions. Without-storage simulations produced larger sensible and latent heat fluxes during the day but smaller fluxes (more negative values) at night as compared with with-storage simulations. Similarly, without-storage simulations had higher surface radiative temperature during the day but lower radiative temperature at night, indicating that the biomass energy storages act to dampen diurnal temperature range. Therefore, biomass heat and biochemical energy storages are an integral and substantial part of the surface energy budget and play a role in modulating land surface temperatures and must be considered in studies of land - atmosphere interactions and climate modeling.

  18. STIR Proposal For Research Area 2.1.2 Surface Energy Balance: Transient Soil Density Impacts Land Surface Characteristics and Characterization

    Science.gov (United States)

    2015-12-22

    SECURITY CLASSIFICATION OF: Soil density is commonly treated as static in studies on land surface property dynamics. Magnitudes of errors associated...properties, and ii) evaluate impact of changing soil density on surface energy balance and heat and water transfer. Six soil properties were...ABSTRACT 2. REPORT TYPE 17. LIMITATION OF ABSTRACT 15. NUMBER OF PAGES 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 5c. PROGRAM ELEMENT

  19. Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Q.; Minnis, P.; daSilva, A. M., Jr.; Palikonda, R.; Yost, C. R.

    2012-01-01

    Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

  20. Computer simulation study of hexokinase II from Ehrlich ascites cells.

    Science.gov (United States)

    Garfinkel, L

    1975-02-21

    A study of the mechanism of hexokinase II from ascites cells the effects of its binding to mitochondrial membranes has been carried out by computer simulation. This is based on experimental data of Kosow and Rose and of Gumaa and McLean, and the theoretical methods of cleveland. For the soluble enzyme the mechanism is random with ternary produce-inhibition complexes; when bound to mitochondria, the mechanism becomes ordered-on, random-off, as the binding of ATP to the free enzymes becomes negligibly slow. The requirements of experimental data for mechanistic studies are discussed.

  1. Recent Achievements in Simulated Moving Bed (SMB Technology. Part II

    Directory of Open Access Journals (Sweden)

    Roje, M.

    2010-09-01

    Full Text Available Progress in the method of simulated moving bed (SMB technology and some important achievements in separation of specific classes of racemic compounds of therapeutic interest are reported in the Part I of this review. Part II describes novel methods of SMB technology. Complex technologies,such as the combination of SMB and biocatalytic reactions, and SMB with crystallization process, are presented. VariCol variant of SMB, and its application in the separation of the racemic mixtures of commercial and academic interest are discussed. In the conclusive section, comments are given concerning the economic dimension and the market of enantiomerically pure compounds.

  2. Simulations, Diagnostics and Recent Results of the VISA II Experiment

    CERN Document Server

    Andonian, G; Pellegrini, C; Reiche, S; Rosenzweig, J B; Travish, G

    2005-01-01

    The VISA II experiment entails use of a chirped beam to drive a high gain SASE FEL. The output radiation is diagnosed with a modified frequency resolved optical gating (FROG) technique. Sextupoles are implemented to correct the lonigtudinal aberrations affecting the high energy spread chirped beam during transport to the undulator. The double differential energy spectrum is measured with a pair of slits and a set of gratings. In this paper, we report on start-to-end simulations, radiation diagnostics, as well as intial experimental results; experimental methods are described.

  3. Physics Detector Simulation Facility Phase II system software description

    Energy Technology Data Exchange (ETDEWEB)

    Scipioni, B.; Allen, J.; Chang, C.; Huang, J.; Liu, J.; Mestad, S.; Pan, J.; Marquez, M.; Estep, P.

    1993-05-01

    This paper presents the Physics Detector Simulation Facility (PDSF) Phase II system software. A key element in the design of a distributed computing environment for the PDSF has been the separation and distribution of the major functions. The facility has been designed to support batch and interactive processing, and to incorporate the file and tape storage systems. By distributing these functions, it is often possible to provide higher throughput and resource availability. Similarly, the design is intended to exploit event-level parallelism in an open distributed environment.

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. Simulation of PEP-II Accelerator Backgrounds Using TURTLE

    CERN Document Server

    Barlow, Roger J; Kozanecki, Witold; Majewski, Stephanie; Roudeau, Patrick; Stocchi, Achille

    2005-01-01

    We present studies of accelerator-induced backgrounds in the BaBar detector at the SLAC B-Factory, carried out using a modified version ofthe DECAY TURTLE simulation package. Lost-particle backgrounds in PEP-II are dominated by a combination of beam-gas bremstrahlung, beam-gas Coulomb scattering, radiative-Bhabha events and beam-beam blow-up. The radiation damage and detector occupancy caused by the associated electromagnetic shower debris can limit the usable luminosity. In order to understand and mitigate such backgrounds, we have performed a full programme of beam-gas and luminosity-background simulations, that include the effects of the detector solenoidal field, detailed modelling of limiting apertures in both collider rings, and optimization of the betatron collimation scheme in the presence of large transverse tails.

  10. Quality and Reliability of Large-Eddy Simulations II

    CERN Document Server

    Salvetti, Maria Vittoria; Meyers, Johan; Sagaut, Pierre

    2011-01-01

    The second Workshop on "Quality and Reliability of Large-Eddy Simulations", QLES2009, was held at the University of Pisa from September 9 to September 11, 2009. Its predecessor, QLES2007, was organized in 2007 in Leuven (Belgium). The focus of QLES2009 was on issues related to predicting, assessing and assuring the quality of LES. The main goal of QLES2009 was to enhance the knowledge on error sources and on their interaction in LES and to devise criteria for the prediction and optimization of simulation quality, by bringing together mathematicians, physicists and engineers and providing a platform specifically addressing these aspects for LES. Contributions were made by leading experts in the field. The present book contains the written contributions to QLES2009 and is divided into three parts, which reflect the main topics addressed at the workshop: (i) SGS modeling and discretization errors; (ii) Assessment and reduction of computational errors; (iii) Mathematical analysis and foundation for SGS modeling.

  11. Remote Sensing and Synchronous Land Surface Measurements of Soil Moisture and Soil Temperature in the Field

    Science.gov (United States)

    Kolev, N. V.; Penev, K. P.; Kirkova, Y. M.; Krustanov, B. S.; Nazarsky, T. G.; Dimitrov, G. K.; Levchev, C. P.; Prodanov, H. I.; Kraleva, L. H.

    1998-01-01

    The paper presents the results of remote sensing and synchronous land surface measurements for estimation of soil (surface and profile) water content and soil temperature for different soil types in Bulgaria. The relationship between radiometric temperature and soil surface water content is shown. The research is illustrated by some results from aircraft and land surface measurements carried out over three test areas near Pleven, Sofia and Plovdiv, respectively, during the period 1988-1990.

  12. Noah-MP-Crop: Introducing dynamic crop growth in the Noah-MP land surface model

    Science.gov (United States)

    Liu, Xing; Chen, Fei; Barlage, Michael; Zhou, Guangsheng; Niyogi, Dev

    2016-12-01

    Croplands are important in land-atmosphere interactions and in the modification of local and regional weather and climate; however, they are poorly represented in the current version of the coupled Weather Research and Forecasting/Noah with multiparameterization (Noah-MP) land surface modeling system. This study introduced dynamic corn (Zea mays) and soybean (Glycine max) growth simulations and field management (e.g., planting date) into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at field scales using crop biomass data sets, surface heat fluxes, and soil moisture observations. Compared to the generic dynamic vegetation and prescribed-leaf area index (LAI)-driven methods in Noah-MP, the Noah-MP-Crop showed improved performance in simulating leaf area index (LAI) and crop biomass. This model is able to capture the seasonal and annual variability of LAI and to differentiate corn and soybean in peak values of LAI as well as the length of growing seasons. Improved simulations of crop phenology in Noah-MP-Crop led to better surface heat flux simulations, especially in the early period of growing season where current Noah-MP significantly overestimated LAI. The addition of crop yields as model outputs expand the application of Noah-MP-Crop to regional agriculture studies. There are limitations in the use of current growing degree days (GDD) criteria to predict growth stages, and it is necessary to develop a new method that combines GDD with other environmental factors, to more accurately define crop growth stages. The capability introduced in Noah-MP allows further crop-related studies and development.

  13. Sensitivity of land surface modeling to parameters: An uncertainty quantification method applied to the Community Land Model

    Science.gov (United States)

    Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.

    2015-12-01

    Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes

  14. Improved representations of coupled soil-canopy processes in the CABLE land surface model (Subversion revision 3432)

    Science.gov (United States)

    Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; Harman, Ian N.

    2016-09-01

    CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil-canopy processes by introducing an alternative hydrology model with a physically accurate representation of coupled energy and water fluxes at the soil-air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.

  15. Modeling of ground temperatures in South Shetlands (Antarctic Peninsula): Forcing a land surface model with the reanalysis ERA-Interim

    Science.gov (United States)

    João Rocha, Maria; Dutra, Emanuel; Vieira, Gonçalo; Miranda, Pedro; Ramos, Miguel

    2010-05-01

    This study focus on Livingston Island (South Shetlands Antarctic Peninsula), one of the Earth's regions where warming has been more significant in the last 50 years. Our work is integrated in a project focusing on studying the influence of climate change on permafrost temperatures, which includes systematic and long-term terrain monitoring and also modeling using land surface models. A contribution will be the evaluation of the possibilities for using land surface modeling approaches to areas of the Antarctic Peninsula with lack of data on observational meteorological forcing data, as well as on permafrost temperatures. The climate variability of the Antarctic Peninsula region was studied using the new reanalysis product from European Centre for Medium-Range Weather Forecasts (ECMWF) Era-Interim and observational data from boreholes run by our group. Monthly and annual cycles of near surface climate variables are compared. The modeling approach includes the HTESSEL (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) forced with ERA-Interim for modeling ground temperatures in the study region. The simulation results of run of HTESSEL are compared against soil temperature observations. The results show a favorable match between simulated and observed soil temperatures. The use of different forcing parameters is compared and the model vs. observation results from different results is analyzed. The main variable needing further improvement in the modeling is snow cover. The developed methodology provides a good tool for the analysis of the influence of climate variability on permafrost of the Maritime Antarctic.

  16. Attenuating the surface Urban Heat Island within the Local Thermal Zones through land surface modification.

    Science.gov (United States)

    Wang, Jiong; Ouyang, Wanlu

    2017-02-01

    Inefficient mitigation of excessive heat is attributed to the discrepancy between the scope of climate research and conventional planning practice. This study approaches this problem at both domains. Generally, the study, on one hand, claims that the climate research of the temperature phenomenon should be at local scale, where implementation of planning and design strategies can be more feasible. On the other hand, the study suggests that the land surface factors should be organized into zones or patches, which conforms to the urban planning and design manner. Thus in each zone, the land surface composition of those excessively hot places can be compared to the zonal standard. The comparison gives guidance to the modification of the land surface factors at the target places. Specifically, this study concerns the Land Surface Temperature (LST) in Wuhan, China. The land surface is classified into Local Thermal Zones (LTZ). The specifications of temperature sensitive land surface factors are relative homogeneous in each zone and so is the variation of the LST. By extending the city scale analysis of Urban Heat Island into local scale, the Local Surface Urban Heat Islands (LSUHIs) are extracted. Those places in each zone that constantly maintain as LSUHI and exceed the homogenous LST variation are considered as target places or hotspots with higher mitigation or adaptation priority. The operation is equivalent to attenuate the abnormal LST variation in each zone. The framework is practical in the form of prioritization and zoning, and mitigation strategies are essentially operated locally.

  17. Assessment of model behavior and acceptable forcing data uncertainty in the context of land surface soil moisture estimation

    Science.gov (United States)

    Dumedah, Gift; Walker, Jeffrey P.

    2017-03-01

    The sources of uncertainty in land surface models are numerous and varied, from inaccuracies in forcing data to uncertainties in model structure and parameterizations. Majority of these uncertainties are strongly tied to the overall makeup of the model, but the input forcing data set is independent with its accuracy usually defined by the monitoring or the observation system. The impact of input forcing data on model estimation accuracy has been collectively acknowledged to be significant, yet its quantification and the level of uncertainty that is acceptable in the context of the land surface model to obtain a competitive estimation remain mostly unknown. A better understanding is needed about how models respond to input forcing data and what changes in these forcing variables can be accommodated without deteriorating optimal estimation of the model. As a result, this study determines the level of forcing data uncertainty that is acceptable in the Joint UK Land Environment Simulator (JULES) to competitively estimate soil moisture in the Yanco area in south eastern Australia. The study employs hydro genomic mapping to examine the temporal evolution of model decision variables from an archive of values obtained from soil moisture data assimilation. The data assimilation (DA) was undertaken using the advanced Evolutionary Data Assimilation. Our findings show that the input forcing data have significant impact on model output, 35% in root mean square error (RMSE) for 5cm depth of soil moisture and 15% in RMSE for 15cm depth of soil moisture. This specific quantification is crucial to illustrate the significance of input forcing data spread. The acceptable uncertainty determined based on dominant pathway has been validated and shown to be reliable for all forcing variables, so as to provide optimal soil moisture. These findings are crucial for DA in order to account for uncertainties that are meaningful from the model standpoint. Moreover, our results point to a proper

  18. Modeling land-surface processes and land-atmosphere interactions in the community weather and regional climate WRF model (Invited)

    Science.gov (United States)

    Chen, F.; Barlage, M. J.

    2013-12-01

    The Weather Research and Forecasting (WRF) model has been widely used with high-resolution configuration in the weather and regional climate communities, and hence demands its land-surface models to treat not only fast-response processes, such as plant evapotranspiration that are important for numerical weather prediction but also slow-evolving processes such as snow hydrology and interactions between surface soil water and deep aquifer. Correctly representing urbanization, which has been traditionally ignored in coarse-resolution modeling, is critical for applying WRF to air quality and public health research. To meet these demands, numerous efforts have been undertaken to improve land-surface models (LSM) in WRF, including the recent implementation of the Noah-MP (Noah Multiple-Physics). Noah-MP uses multiple options for key sub-grid land-atmosphere interaction processes (Niu et al., 2011; Yang et al., 2011), and contains a separate vegetation canopy representing within- and under-canopy radiation and turbulent processes, a multilayer physically-based snow model, and a photosynthesis canopy resistance parameterization with a dynamic vegetation model. This paper will focus on the interactions between fast and slow land processes through: 1) a benchmarking of the Noah-MP performance, in comparison to five widely-used land-surface models, in simulating and diagnosing snow evolution for complex terrain forested regions, and 2) the effects of interactions between shallow and deep aquifers on regional weather and climate. Moreover, we will provide an overview of recent improvements of the integrated WRF-Urban modeling system, especially its hydrological enhancements that takes into account the effects of lawn irrigation, urban oasis, evaporation from pavements, anthropogenic moisture sources, and a green-roof parameterization.

  19. Modelling evapotranspiration during precipitation deficits: identifying critical processes in a land surface model

    Science.gov (United States)

    Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark; De Kauwe, Martin G.; Abramowitz, Gab; Kala, Jatin; Wang, Ying-Ping

    2016-06-01

    Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leaf area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.

  20. Quantification of the Scale Effect in Downscaling Remotely Sensed Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Ji Zhou

    2016-11-01

    Full Text Available Most current statistical models for downscaling the remotely sensed land surface temperature (LST are based on the assumption of the scale-invariant LST-descriptors relationship, which is being debated and requires an in-depth examination. Additionally, research on downscaling LST to high or very high resolutions (~10 m is still rare. Here, a simple analytical model was developed to quantify the scale effect in downscaling the LST from a medium resolution (~100 m to high resolutions. The model was verified in the Zhangye oasis and Beijing city. Examinations of the simulation datasets that were generated based on airborne and space station LSTs demonstrate that the developed model can predict the scale effect in LST downscaling; the scale effect exists in both of these two study areas. The model was further applied to 12 ASTER images in the Zhangye oasis during a complete crop growing season and one Landsat-8 TIRS image in Beijing city in the summer. The results demonstrate that the scale effect is intrinsically caused by the varying probability distribution of the LST and its descriptors at the native and target resolutions. The scale effect depends on the values of the descriptors, the phenology, and the ratio of the native resolution to the target resolution. Removing the scale effect would not necessarily improve the accuracy of the downscaled LST.

  1. Evaluation of BAER surface model for aerosol optical thickness retrieval over land surface

    Directory of Open Access Journals (Sweden)

    Y. S. Chiang

    2012-04-01

    Full Text Available Estimation of surface reflectance is essential for an accurate retrieval of aerosol optical thickness (AOT by satellite remote sensing approach. Due to the variability of surface reflectance over land surfaces, a surface model is required to take into account the crucial factor controlling this variability. In the present study, we attempted to simulate surface reflectance in the short-wave channels with two methods, namely the land cover type dependent method and a two-source linear model. In the two-source linear model, we assumed that the spectral property can be described by a mixture of vegetated and non-vegetated area, and both the normalized difference vegetation index (NDVI, and the vegetation continuous field (VCF was applied to summarize this surface characteristic. By comparing our estimation with surface reflectance data derived from Moderate Resolution Imaging Spectroradiometer (MODIS, it indicated that the land cover type approach did not provide a better estimation because of inhomogeneous land cover pattern and the mixing pixel properties. For the two-source linear method, the study suggested that the use of NDVI as parameterization for vegetation fraction can reflect the spectral behavior of shortwave surface reflectance, despite of some deviation due to the averaging characteristics in our linear combination process. A channel-dependent offset and scalar factor could enhance reflectance estimation and further improve AOT retrieval by the current Bremen AErosol Retrieval (BAER approach.

  2. Evaluation of Land Surface Temperature Operationally Retrieved from Korean Geostationary Satellite (COMS Data

    Directory of Open Access Journals (Sweden)

    A-Ra Cho

    2013-08-01

    Full Text Available We evaluated the precision of land surface temperature (LST operationally retrieved from the Korean multipurpose geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS. The split-window (SW-type retrieval algorithm was developed through radiative transfer model simulations under various atmospheric profiles, satellite zenith angles, surface emissivity values and surface lapse rate conditions using Moderate Resolution Atmospheric Transmission version 4 (MODTRAN4. The estimation capabilities of the COMS SW (CSW LST algorithm were evaluated for various impacting factors, and the retrieval accuracy of COMS LST data was evaluated with collocated Moderate Resolution Imaging Spectroradiometer (MODIS LST data. The surface emissivity values for two SW channels were generated using a vegetation cover method. The CSW algorithm estimated the LST distribution reasonably well (averaged bias = 0.00 K, Root Mean Square Error (RMSE = 1.41 K, correlation coefficient = 0.99; however, the estimation capabilities of the CSW algorithm were significantly impacted by large brightness temperature differences and surface lapse rates. The CSW algorithm reproduced spatiotemporal variations of LST comparing well to MODIS LST data, irrespective of what month or time of day the data were collected from. The one-year evaluation results with MODIS LST data showed that the annual mean bias, RMSE and correlation coefficient for the CSW algorithm were −1.009 K, 2.613 K and 0.988, respectively.

  3. Quantifying the influences of various ecological factors on land surface temperature of urban forests.

    Science.gov (United States)

    Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

    2016-09-01

    Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST.

  4. Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

    Science.gov (United States)

    Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Bogena, Heye; Vereecken, Harry

    2017-04-01

    Land surface models describe biogeophysical and biogeochemical processes at the land surface, and represent the lower boundary condition of atmospheric circulation models. Their key role is the quantification of mass and energy fluxes between the land surface and the atmosphere. Predictions with land surface models are affected by many unknown parameters, uncertain meteorological forcings and incomplete process understanding. Measurement data (e.g., soil moisture) can help to improve land surface model predictions. However, soil moisture products obtained from satellite remote sensing are normally available at a very coarse resolution and give information on the upper few centimetres of the soil only. Therefore, the recently developed Cosmic Ray Neutron Sensors (CRNS) are of high interest for predictions by land surface models, because they measure neutron count intensity, which is related to integral soil moisture content at the field scale (about 20 hectares). High resolution land surface models are also able to provide solutions at the same scale. In this study, we investigated whether the assimilation of soil moisture retrievals from CRNS data measured by a network of nine CRNS located in the Rur catchment in Germany (2354 km2) can improve land surface model prediction. The assimilation of soil moisture retrievals from neutron count intensity data was used to update model states and parameters of the land surface model CLM 4.5 over a two year time period, followed by a one year evaluation period without updates. This updating was done with the local ensemble transform Kalman filter. The real world experiment tested the value of CRNS using jackknifing experiments and three different initial soil maps. During the assimilation period, soil moisture predictions generally improved, for a biased soil map from an RMSE of 0.11 cm3/cm3 in the open loop run to 0.03 cm3/cm3 while during the evaluation period soil moisture predictions improved from 0.12 cm3/cm3 to 0.06 cm3

  5. Multi-site evaluation of the JULES land surface model using global and local data

    Directory of Open Access Journals (Sweden)

    D. Slevin

    2015-02-01

    Full Text Available This study evaluates the ability of the JULES land surface model (LSM to simulate photosynthesis using local and global data sets at 12 FLUXNET sites. Model parameters include site-specific (local values for each flux tower site and the default parameters used in the Hadley Centre Global Environmental Model (HadGEM climate model. Firstly, gross primary productivity (GPP estimates from driving JULES with data derived from local site measurements were compared to observations from the FLUXNET network. When using local data, the model is biased with total annual GPP underestimated by 16% across all sites compared to observations. Secondly, GPP estimates from driving JULES with data derived from global parameter and atmospheric reanalysis (on scales of 100 km or so were compared to FLUXNET observations. It was found that model performance decreases further, with total annual GPP underestimated by 30% across all sites compared to observations. When JULES was driven using local parameters and global meteorological data, it was shown that global data could be used in place of FLUXNET data with a 7% reduction in total annual simulated GPP. Thirdly, the global meteorological data sets, WFDEI and PRINCETON, were compared to local data to find that the WFDEI data set more closely matches the local meteorological measurements (FLUXNET. Finally, the JULES phenology model was tested by comparing results from simulations using the default phenology model to those forced with the remote sensing product MODIS leaf area index (LAI. Forcing the model with daily satellite LAI results in only small improvements in predicted GPP at a small number of sites, compared to using the default phenology model.

  6. The climate responses of tropical and boreal ecosystems with an improved land surface model (JULES)

    Science.gov (United States)

    Harper, Anna; Friedlingstein, Pierre; Cox, Peter; Wiltshire, Andy; Jones, Chris

    2016-04-01

    The Joint UK Land Environment Simulator (JULES) is the land surface of the next generation UK Earth System Model (UKESM1). Recently, JULES was updated with new plant functional types and physiology based on a global plant trait database. These developments improved the simulation of terrestrial gross and net primary productivity on local and global scales, and enabled a more realistic representation of the global distribution of vegetation. In this study, we explore the present-day distribution of ecosystems and their vulnerability to climate change in JULES with these improvements, focusing on tropical and boreal ecosystems. Changes to these ecosystems will have implications for biogeophysical and biogeochemical feedbacks to climate change and need to be understood. First, we examine the simulated and observed rainforest-savannah boundary, which is strongly related to annual precipitation and the maximum climatological water deficit. Second, we assess the length of growing season and biomass stored in boreal ecosystems, where 20th century warming has likely extended the growing season. In each case, we first evaluate the ability of JULES to capture observed climate-vegetation relationships and trends. Finally, we run JULES to 2100 using climate data from 3 models and 2 RCP scenarios, and examine potential 21st century changes to these ecosystems. For example, do the tropical forests shrink in response to changes in tropical rainfall seasonality? And, how does the composition of boreal ecosystems change in response to climate warming? Given the potential for climate feedbacks and the inherent value in these ecosystems, it is essential to assess their responses to a range of climate change scenarios.

  7. Improving the spatial estimation of evapotranspiration by assimilating land surface temperature data

    Science.gov (United States)

    Zink, Matthias; Samaniego, Luis; Cuntz, Matthias

    2013-04-01

    A combined investigation of the water and energy balance in hydrologic models might lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration ET and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on the integrated signal at few points within a catchment. This procedure does not take into account any spatial variability of fluxes or state variables. Satellite data are a useful source of information to incorporate spatial information into hydrologic models. The objective of this study is to improve the estimation of evapotranspiration in the spatial domain by using satellite derived land surface temperature Ts for the calibration of the distributed hydrological model mHM. The satellite products are based on data of Meteosat Second Generation (MSG) and are provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). mHM simulations of Ts are obtained by solving the energy balance wherein evapotranspiration is determined by closing the water balance. Net radiation is calculated by using incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is applied to determine the aerodynamic resistance among other parameters. The optimization is performed for the year 2009 using three objective functions that consider (1) only discharge, (2) only Ts, and (3) both discharge and Ts. For the spatial comparison of satellite derived and estimated Ts fields, a new measure accounting for local spatial variabilities is introduced. The proposed method is applied to seven major German river basins, i.e. Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The results of the Ts simulations show a bias of 4.1 K compared to the satellite data. We hypothesize that this bias is inherent to the satellite data rather than to the model simulations. This

  8. The impact of climatic and non-climatic factors on land surface temperature in southwestern Romania

    Science.gov (United States)

    Roşca, Cristina Florina; Harpa, Gabriela Victoria; Croitoru, Adina-Eliza; Herbel, Ioana; Imbroane, Alexandru Mircea; Burada, Doina Cristina

    2016-09-01

    Land surface temperature is one of the most important parameters related to global warming. It depends mainly on soil type, discontinuous vegetation cover, or lack of precipitation. The main purpose of this paper is to investigate the relationship between high LST, synoptic conditions and air masses trajectories, vegetation cover, and soil type in one of the driest region in Romania. In order to calculate the land surface temperature and normalized difference vegetation index, five satellite images of LANDSAT missions 5 and 7, covering a period of 26 years (1986-2011), were selected, all of them collected in the month of June. The areas with low vegetation density were derived from normalized difference vegetation index, while soil types have been extracted from Corine Land Cover database. HYSPLIT application was employed to identify the air masses origin based on their backward trajectories for each of the five study cases. Pearson, logarithmic, and quadratic correlations were used to detect the relationships between land surface temperature and observed ground temperatures, as well as between land surface temperature and normalized difference vegetation index. The most important findings are: strong correlation between land surface temperature derived from satellite images and maximum ground temperature recorded in a weather station located in the area, as well as between areas with land surface temperature equal to or higher than 40.0 °C and those with lack of vegetation; the sandy soils are the most prone to high land surface temperature and lack of vegetation, followed by the chernozems and brown soils; extremely severe drought events may occur in the region.

  9. Comprehensive Assessment of Land Surface, Snow, and Soil Moisture-Climate Feedbacks by Multi-model Experiments of Land Surface Models under LS3MIP

    Science.gov (United States)

    Oki, T.; Kim, H.; Hurk, B. V. D.; Krinner, G.; Derksen, C.; Seneviratne, S. I.

    2015-12-01

    The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and its predictability, including effects on the energy and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. The Land surface, snow and soil moisture model inter-comparison project (LS3MIP) experiments address together the following objectives: an evaluation of the current state of land processes including surface fluxes, snow cover and soil moisture representation in CMIP6 DECK runs (LMIP-protoDECK) a multi-model estimation of the long-term terrestrial energy/water/carbon cycles, using the surface modules of CMIP6 models under observation constrained historical (land reanalysis) and projected future (impact assessment) conditions considering land use/land cover changes. (LMIP) an assessment of the role of snow and soil moisture feedbacks in the regional response to altered climate forcings, focusing on controls of climate extremes, water availability and high-latitude climate in historical and future scenario runs (LFMIP) an assessment of the contribution of land surface processes to the current and future predictability of regional temperature/precipitation patterns. (LFMIP) These LS3MIP outcomes will contribute to the improvement of climate change projections by reducing the systematic biases from the land surface component of climate models, and a better representation of feedback mechanisms related to snow and soil moisture in climate models. Further, LS3MIP will enable the assessment of probable historical changes in energy, water, and carbon cycles over land surfaces extending more than 100 years, including spatial variability and trends in global runoff, snow cover, and soil moisture that are hard to detect purely based on observations. LS3MIP will also enable the impact assessments of climate changes on hydrological regimes and available

  10. Utilizing CLASIC observations and multiscale models to study the impact of improved Land surface representation on modeling cloud- convection

    Energy Technology Data Exchange (ETDEWEB)

    Niyogi, Devdutta S. [Purdue

    2013-06-07

    The CLASIC experiment was conducted over the US southern great plains (SGP) in June 2007 with an objective to lead an enhanced understanding of the cumulus convection particularly as it relates to land surface conditions. This project was design to help assist with understanding the overall improvement of land atmosphere convection initiation representation of which is important for global and regional models. The study helped address one of the critical documented deficiency in the models central to the ARM objectives for cumulus convection initiation and particularly under summer time conditions. This project was guided by the scientific question building on the CLASIC theme questions: What is the effect of improved land surface representation on the ability of coupled models to simulate cumulus and convection initiation? The focus was on the US Southern Great Plains region. Since the CLASIC period was anomalously wet the strategy has been to use other periods and domains to develop the comparative assessment for the CLASIC data period, and to understand the mechanisms of the anomalous wet conditions on the tropical systems and convection over land. The data periods include the IHOP 2002 field experiment that was over roughly same domain as the CLASIC in the SGP, and some of the DOE funded Ameriflux datasets.

  11. Examining the Impact of Greenspace Patterns on Land Surface Temperature by Coupling LiDAR Data with a CFD Model

    Directory of Open Access Journals (Sweden)

    Weizhong Su

    2014-09-01

    Full Text Available Understanding the link between greenspace patterns and land surface temperature is very important for mitigating the urban heat island (UHI effect and is also useful for planners and decision-makers for providing a sustainable design for urban greenspace. Although coupling remote sensing data with a computational fluid dynamics (CFD model has widely been used to examine interactions between UHI and greenspace patterns, the paper aims to examine the impact of five theoretical models of greenspace patterns on land surface temperature based on the improvement of the accuracy of CFD modeling by the combination of LiDAR data with remote sensing images to build a 3D urban model. The simulated results demonstrated that the zonal pattern always had the obvious cooling effects when there are no large buildings or terrain obstacles. For ambient environments, the building or terrain obstacles and the type of greenspace have the hugest influence on mitigating the UHI, but the greenspace area behaves as having the least cooling effect. A dotted greenspace pattern shows the best cooling effect in the central area or residential district within a city, while a radial and a wedge pattern may result in a “cold source” for the urban thermal environment.

  12. Modelling Angular Dependencies in Land Surface Temperatures From the SEVIRI Instrument onboard the Geostationary Meteosat Second Generation Satellites

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander; Pinheiro, AC; Proud, Simon Richard

    2010-01-01

    Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence on vegetat......Satellite-based estimates of land surface temperature (LST) are widely applied as an input to models. A model output is often very sensitive to error in the input data, and high-quality inputs are therefore essential. One of the main sources of errors in LST estimates is the dependence...... on vegetation structure and viewing and illumination geometry. Despite this, these effects are not considered in current operational LST products from neither polar-orbiting nor geostationary satellites. In this paper, we simulate the angular dependence that can be expected when estimating LST with the viewing...... by different land covers. The results show that the sun-target-sensor geometry plays a significant role in the estimated temperature, with variations strictly due to the angular configuration of more than ±3°C in some cases. On the continental scale, the average error is small except in hot-spot conditions...

  13. Advanced Simulation Capability for Environmental Management (ASCEM) Phase II Demonstration

    Energy Technology Data Exchange (ETDEWEB)

    Freshley, M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hubbard, S. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Flach, G. [Savannah River National Lab. (SRNL), Aiken, SC (United States); Freedman, V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Agarwal, D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Andre, B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bott, Y. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, X. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Davis, J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Faybishenko, B. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gorton, I. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Murray, C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moulton, D. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Meyer, J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rockhold, M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shoshani, A. [LBNL; Steefel, C. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wainwright, H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Waichler, S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2012-09-28

    quality assurance. The Platform and HPC capabilities are being tested and evaluated for EM applications through a suite of demonstrations being conducted by the Site Applications Thrust. In 2010, the Phase I Demonstration focused on testing initial ASCEM capabilities. The Phase II Demonstration, completed in September 2012, focused on showcasing integrated ASCEM capabilities. For Phase II, the Hanford Site Deep Vadose Zone (BC Cribs) served as an application site for an end-to-end demonstration of ASCEM capabilities on a site with relatively sparse data, with emphasis on integration and linkages between the Platform and HPC components. Other demonstrations included in this Phase II report included addressing attenuation-based remedies at the Savannah River Site F-Area, to exercise linked ASCEM components under data-dense and complex geochemical conditions, and conducting detailed simulations of a representative waste tank. This report includes descriptive examples developed by the Hanford Site Deep Vadose Zone, the SRS F-Area Attenuation-Based Remedies for the Subsurface, and the Waste Tank Performance Assessment working groups. The integrated Phase II Demonstration provides test cases to accompany distribution of the initial user release (Version 1.0) of the ASCEM software tools to a limited set of users in 2013. These test cases will be expanded with each new release, leading up to the release of a version that is qualified for regulatory applications in the 2015 time frame.

  14. An inter-comparison of soil moisture data products from satellite remote sensing and a land surface model

    Science.gov (United States)

    Fang, Li; Hain, Christopher R.; Zhan, Xiwu; Anderson, Martha C.

    2016-06-01

    Significant advances have been achieved in generating soil moisture (SM) products from satellite remote sensing and/or land surface modeling with reasonably good accuracy in recent years. However, the discrepancies among the different SM data products can be considerably large, which hampers their usage in various applications. The bias of one SM product from another is well recognized in the literature. Bias estimation and spatial correction methods have been documented for assimilating satellite SM product into land surface and hydrologic models. Nevertheless, understanding the characteristics of each of these SM data products is required for many applications where the most accurate data products are desirable. This study inter-compares five SM data products from three different sources with each other, and evaluates them against in situ SM measurements over 14-year period from 2000 to 2013. Specifically, three microwave (MW) satellite based data sets provided by ESA's Climate Change Initiative (CCI) (CCI-merged, -active and -passive products), one thermal infrared (TIR) satellite based product (ALEXI), and the Noah land surface model (LSM) simulations. The in-situ SM measurements are collected from the North American Soil Moisture Database (NASMD), which involves more than 600 ground sites from a variety of networks. They are used to evaluate the accuracies of these five SM data products. In general, each of the five SM products is capable of capturing the dry/wet patterns over the study period. However, the absolute SM values among the five products vary significantly. SM simulations from Noah LSM are more stable relative to the satellite-based products. All TIR and MW satellite based products are relatively noisier than the Noah LSM simulations. Even though MW satellite based SM retrievals have been predominantly used in the past years, SM retrievals of the ALEXI model based on TIR satellite observations demonstrate skills equivalent to all the MW satellite

  15. Development of a land surface model with coupled snow and frozen soil physics

    Science.gov (United States)

    Wang, Lei; Zhou, Jing; Qi, Jia; Sun, Litao; Yang, Kun; Tian, Lide; Lin, Yanluan; Liu, Wenbin; Shrestha, Maheswor; Xue, Yongkang; Koike, Toshio; Ma, Yaoming; Li, Xiuping; Chen, Yingying; Chen, Deliang; Piao, Shilong; Lu, Hui

    2017-06-01

    Snow and frozen soil are important factors that influence terrestrial water and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new land surface model (LSM) with coupled snow and frozen soil physics was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

  16. [A Novel Method of Soil Moisture Content Monitoring by Land Surface Temperature and LAI].

    Science.gov (United States)

    Gao, Zhong-ling; Zheng, Xiao-po; Sun, Yue-jun; Wang, Jian-hua

    2015-11-01

    Land surface temperature (Ts) is influenced by soil background and vegetation growing conditions, and the combination of Ts and vegetation indices (Vis) can indicate the status of surface soil moisture content (SMC). In this study, Advanced Temperature Vegetation Dryness Index (ATVDI) used for monitoring SMC was proposed on the basis of the simulation results with agricultural climate model CUPID. Previous studies have concluded that Normalized Difference Vegetation Index (NDVI) easily reaches the saturation point, andLeaf Area Index (LAI) was then used instead of NDVI to estimate soil moisture content in the paper. With LAI-Ts scatter diagram established by the simulation results of CUPID model; how Ts varied with LAI and SMC was found. In the case of the identical soil background, the logarithmic relations between Ts and LAI were more accurate than the linear relations included in Temperature Vegetation Dryness Index (TVDI), based on which ATVDI was then developed. LAI-Ts scatter diagram with satellite imagery were necessary for determining the expression of the upper and lower logarithmic curves while ATVDI was used for monitoring SMC. Ts derived from satellite imagery were then transformed to the Ts-value which has the same SMC and the minimum LAI in study area with look-up table. The measured SMC from the field sites in Weihe Plain, Shanxi Province, China, and the products of LAI and Ts (MOD15A2 and MOD11A2, respectively) produced by the image derived from Moderate Resolution Imaging Spectrometer (MODIS) were collected to validate the new method proposed in this study. The validation results shown that ATVDI (R² = 0.62) was accurate enough to monitor SMC, and it achieved better result than TVDI. Moreover, ATVDI-derived result were Ts values with some physical meanings, which made it comparative in different periods. Therefore, ATVDI is a promising method for monitoring SMC in different time-spatial scales in agricultural fields.

  17. Human-induced greening of the northern extratropical land surface

    Science.gov (United States)

    Mao, Jiafu; Ribes, Aurélien; Yan, Binyan; Shi, Xiaoying; Thornton, Peter E.; Séférian, Roland; Ciais, Philippe; Myneni, Ranga B.; Douville, Hervé; Piao, Shilong; Zhu, Zaichun; Dickinson, Robert E.; Dai, Yongjiu; Ricciuto, Daniel M.; Jin, Mingzhou; Hoffman, Forrest M.; Wang, Bin; Huang, Mengtian; Lian, Xu

    2016-10-01

    Significant land greening in the northern extratropical latitudes (NEL) has been documented through satellite observations during the past three decades. This enhanced vegetation growth has broad implications for surface energy, water and carbon budgets, and ecosystem services across multiple scales. Discernible human impacts on the Earth's climate system have been revealed by using statistical frameworks of detection-attribution. These impacts, however, were not previously identified on the NEL greening signal, owing to the lack of long-term observational records, possible bias of satellite data, different algorithms used to calculate vegetation greenness, and the lack of suitable simulations from coupled Earth system models (ESMs). Here we have overcome these challenges to attribute recent changes in NEL vegetation activity. We used two 30-year-long remote-sensing-based leaf area index (LAI) data sets, simulations from 19 coupled ESMs with interactive vegetation, and a formal detection and attribution algorithm. Our findings reveal that the observed greening record is consistent with an assumption of anthropogenic forcings, where greenhouse gases play a dominant role, but is not consistent with simulations that include only natural forcings and internal climate variability. These results provide the first clear evidence of a discernible human fingerprint on physiological vegetation changes other than phenology and range shifts.

  18. Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions

    Science.gov (United States)

    Xian, George

    2008-01-01

    By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects.

  19. Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data

    Directory of Open Access Journals (Sweden)

    Ugur Avdan

    2016-01-01

    Full Text Available Land surface temperature is an important factor in many areas, such as global climate change, hydrological, geo-/biophysical, and urban land use/land cover. As the latest launched satellite from the LANDSAT family, LANDSAT 8 has opened new possibilities for understanding the events on the Earth with remote sensing. This study presents an algorithm for the automatic mapping of land surface temperature from LANDSAT 8 data. The tool was developed using the LANDSAT 8 thermal infrared sensor Band 10 data. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, for the first case, the standard deviation was 2.4°C, and for the second case, it was 2.7°C. For future studies, the tool should be refined with in situ measurements of land surface temperature.

  20. Basin-scale assessment of the land surface water budget in the National Centers for Environmental Prediction operational and research NLDAS-2 systems

    Science.gov (United States)

    Xia, Youlong; Cosgrove, Brian A.; Mitchell, Kenneth E.; Peters-Lidard, Christa D.; Ek, Michael B.; Brewer, Michael; Mocko, David; Kumar, Sujay V.; Wei, Helin; Meng, Jesse; Luo, Lifeng

    2016-03-01

    The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product

  1. Inter-comparison of two land-surface models applied at different scales and their feedbacks while coupled with a regional climate model

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2012-03-01

    Full Text Available Downstream models are often used in order to study regional impacts of climate and climate change on the land surface. For this purpose, they are usually driven offline (i.e., 1-way with results from regional climate models (RCMs. However, the offline approach does not allow for feedbacks between these models. Thereby, the land surface of the downstream model is usually completely different to the land surface which is used within the RCM. Thus, this study aims at investigating the inconsistencies that arise when driving a downstream model offline instead of interactively coupled with the RCM, due to different feedbacks from the use of different land surface models (LSM. Therefore, two physically based LSMs which developed from different disciplinary backgrounds are compared in our study: while the NOAH-LSM was developed for the use within RCMs, PROMET was originally developed to answer hydrological questions on the local to regional scale. Thereby, the models use different physical formulations on different spatial scales and different parameterizations of the same land surface processes that lead to inconsistencies when driving PROMET offline with RCM output. Processes that contribute to these inconsistencies are, as described in this study, net radiation due to land use related albedo and emissivity differences, the redistribution of this net radiation over sensible and latent heat, for example, due to different assumptions about land use impermeability or soil hydraulic reasons caused by different plant and soil parameterizations. As a result, simulated evapotranspiration, e.g., shows considerable differences of max. 280 mm yr−1. For a full interactive coupling (i.e., 2-way between PROMET and the atmospheric part of the RCM, PROMET returns the land surface energy fluxes to the RCM and, thus, provides the lower boundary conditions for the RCM subsequently. Accordingly, the RCM responses to the replacement of the LSM with overall

  2. Simulations of ion beams for NDCX-II

    Energy Technology Data Exchange (ETDEWEB)

    Grote, D.P., E-mail: dpgrote@lbl.gov [LBNL MS47-112, 1 Cyclotron Rd, Bekerley, CA 94720 (United States); Lawrence Livermore National Lab, Livermore, CA 94550 (United States); Friedman, A., E-mail: afriedman@lbl.gov [Lawrence Livermore National Lab, Livermore, CA 94550 (United States); Sharp, W.M. [Lawrence Livermore National Lab, Livermore, CA 94550 (United States)

    2014-01-01

    NDCX-II, the second neutralized drift compression experiment, is a moderate energy, high current accelerator designed to drive targets for warm dense matter and IFE-relevant energy coupling studies, and to serve as a testbed for high current accelerator physics. As part of the design process, studies were carried out to assess the sensitivities of the accelerator to errors, and to further optimize the design in concert with the evolving pulsed power engineering. The Warp code was used to carry out detailed simulations in both axisymmetric and full 3-D geometry. Ensembles of simulations were carried out to characterize the effects of errors, such as timing jitter and noise on the accelerator waveforms, noise on the source waveform, and solenoid and source offsets. In some cases, the ensemble studies resulted in better designs, revealing operating points with improved performance and showing possible means for further improvement. These studies also revealed a new non-paraxial effect of the final focus solenoid on the beam, which must be taken into account in designing an optimal final focusing system.

  3. High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

    Science.gov (United States)

    Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

    2016-04-01

    The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs

  4. Land surface parameterization and modeling over desert%沙漠陆面过程参数化与模拟

    Institute of Scientific and Technical Information of China (English)

    郑辉; 刘树华

    2013-01-01

    In desert,the climate is hot and dry,the vegetation is sparse,the land surface physical processes are significantly different from those in other regions.By using the data measured in Badanjilin desert,several key land surface parameters were revised.We established a Desert Land Surface Model (DLSM).The model was compared with Noah land surface model and observation data.In this study,the Badanjilin desert surface albedo is 0.273,the emissivity is 0.950,surface roughness is 1.55×10-3 m,the soil heat capacity is 1.08×106 J · m 3 · K-1 and diffusivity is 3.34×10 7m2 ·s.Radiation transfer,sensible heat transfer and soil heat conduction are the key physical processes affecting land surface energy balance.With adequate parameterization of these three processes,the DLSM reasonably simulates the land atmosphere interaction processes over Bandanjilin desert.The root mean square errors of modeled solar radiation flux,longwave radiation flux and sensible heat flux were 7.98,6.14,33.9 W · m-2respectively,which were comparable with the results,7.98,7.72,46.6 W · m-2,from NOAH.Surface albedo is the most important land surface parameter in desert.By increasing 5% of the albedo,the reflected solar radiation increased by 5%,and the sensible heat flux decreased by 2.83%.The results are beneficial to the study on land surface parameterization,modeling and climate simulation.%沙漠地区植被稀疏、干旱少雨,其陆面物理过程具有与全球其它地区显著不同的特点.本文利用巴丹吉林沙漠观测资料,分析和计算了地表反照率、比辐射率、粗糙度和土壤热容量、热传导系数等关键陆面过程参数,建立了适合于沙漠地区的陆面过程模式DLSM (Desert Land Surface Model),并与NOAH陆面过程模式的模拟结果和观测资料进行了比较.结果表明:巴丹吉林沙漠地表反照率为0.273,比辐射率为0.950,地表粗糙度为1.55×10-3rn,土壤热容量和热扩散系数分别为1.08×106 J·m-3·K-1

  5. Detection of land surface memory by correlations between thickness of colluvial deposits and morphometric variables

    Science.gov (United States)

    Mitusov, A. V.; Dreibrodt, S.; Mitusova, O. E.; Khamnueva, S. V.; Bork, H.-R.

    2013-06-01

    Some morphometric variables store information about past land surfaces longer than others. This property of morphometric variables is recognised as land surface memory. Slope deposits, soils, and vegetation also have this memory. In this study, a memory effect was quantitatively detected by Spearman correlations between thickness of colluvium and morphometric variables of the modern land surface. During long-term sedimentation, the sign of horizontal curvature (kh) may be inverted from minus to plus, suggesting that locations with positive kh values are not accumulation zones. However, the thickness of colluvial deposits at such locations in our study area indicates sediment accumulation. The sign of minimal curvature (kmin) tends to be more stable and remains negative. This difference provides the stronger correlation of colluvial layer thickness with kmin than with kh. The strongest correlation was found for total thickness of the colluvial deposits of the Neolithic and Iron Age with kmin (- 0.84); the correlation with kh was weaker (- 0.71).

  6. An Assessment of Land Surface and Lightning Characteristics Associated with Lightning-Initiated Wildfires

    Science.gov (United States)

    Coy, James; Schultz, Christopher J.; Case, Jonathan L.

    2017-01-01

    Can we use modeled information of the land surface and characteristics of lightning beyond flash occurrence to increase the identification and prediction of wildfires? Combine observed cloud-to-ground (CG) flashes with real-time land surface model output, and Compare data with areas where lightning did not start a wildfire to determine what land surface conditions and lightning characteristics were responsible for causing wildfires. Statistical differences between suspected fire-starters and non-fire-starters were peak-current dependent 0-10 cm Volumetric and Relative Soil Moisture comparisons were statistically dependent to at least the p = 0.05 independence level for both polarity flash types Suspected fire-starters typically occurred in areas of lower soil moisture than non-fire-starters. GVF value comparisons were only found to be statistically dependent for -CG flashes. However, random sampling of the -CG non-fire starter dataset revealed that this relationship may not always hold.

  7. Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

    Science.gov (United States)

    Famiglietti, J. S.; Wood, Eric F.

    1993-01-01

    A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

  8. Letter to the EditorRetrieval of land surface temperature from combined AVHRR data

    Directory of Open Access Journals (Sweden)

    H. Fischer

    Full Text Available Accurate retrievals of land surface temperature (LST from space are of high interest for studies of land surface processes. Here, an operationally applicable method to retrieve LST from NOAA/AVHRR data is proposed, which combines a split-window technique (SWT for atmospheric correction with a Normalised Difference Vegetation Index threshold method for the retrieval of land surface emissivity. Preliminary results of LST retrievals with this "combined method" are in good agreement with ground truth measurements for bare soil and wheat crops. The results are also compared with results from the same SWT but using emissivities from laboratory measurements.Key words. Meteorology and atmospheric dynamics (radiation processes; instruments and techniques – Radio science (remote sensing

  9. Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

    Science.gov (United States)

    Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

    1997-01-01

    The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface

  10. Seasonal transition of precipitation characteristics associated with land surface conditions in and around Bangladesh

    Science.gov (United States)

    Ono, M.; Takahashi, H. G.

    2016-10-01

    This study examined the seasonal transition of precipitation characteristics and its association with land surface conditions in and around Bangladesh, where land surface conditions are predominantly wet. Hourly rain rate data from the Global Satellite Mapping of Precipitation Microwave-Infrared Combined Product and 10 day soil moisture data from the Advanced Microwave Scanning Radiometer Earth Observing System were used over the 7 years from 2003 to 2009. Area mean values of soil moisture, and precipitation amount, frequency, and intensity were calculated for each 10 day period. Results showed that higher precipitation amount and frequency were observed over the wet soil conditions, which indicates that soil moisture was influenced by previous precipitation events. However, the soil moisture could also control the precipitation characteristics. The seasonal and interannual variations in all regions suggested that precipitation amount and frequency increased in moist soil conditions, which is associated with an increase of water vapor supplied from the moist land surface. Over a flat plain (87°E-91°E, 23°N-25°N), a higher afternoon precipitation intensity was observed over drier land surfaces. This relationship was observed on seasonal and interannual variations. This suggests that the land surface conditions in this region can affect the afternoon precipitation intensity to some extent, although changes of atmospheric conditions can be a major factor particularly for the seasonal changes. However, this relationship was not observed in mountainous regions. This can be explained by other factors, such as thermally induced local circulations by the surrounding topography, being stronger than the impact of land surface conditions.

  11. Optimal Parameter and Uncertainty Estimation of a Land Surface Model: Sensitivity to Parameter Ranges and Model Complexities

    Institute of Scientific and Technical Information of China (English)

    Youlong XIA; Zong-Liang YANG; Paul L. STOFFA; Mrinal K. SEN

    2005-01-01

    Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI)to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing.The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes.Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.

  12. Modeling the Effects of Irrigation on Land Surface Fluxes and States over the Conterminous United States: Sensitivity to Input Data and Model Parameters

    Energy Technology Data Exchange (ETDEWEB)

    Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong; Sacks, William J.; Lei, Huimin; Leung, Lai-Yung R.

    2013-09-16

    Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to produce unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.

  13. Examining the Impacts of High-Resolution Land Surface Initialization on Model Predictions of Convection in the Southeastern U.S.

    Science.gov (United States)

    Case, Jonathan L.; Kumar, Sujay V.; Santos, Pablo; Medlin, Jeffrey M.; Jedlovec, Gary J.

    2009-01-01

    One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within physics parameterizations, model resolution limitations, as well as uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture and temperature, ground fluxes, and vegetation are necessary to better simulate the interactions between the land surface and atmosphere, and ultimately improve predictions of local circulations and summertime pulse convection. The NASA Short-term Prediction Research and Transition (SPORT) Center has been conducting studies to examine the impacts of high-resolution land surface initialization data generated by offline simulations of the NASA Land Informatiot System (LIS) on subsequent numerical forecasts using the Weather Research and Forecasting (WRF) model (Case et al. 2008, to appear in the Journal of Hydrometeorology). Case et al. presents improvements to simulated sea breezes and surface verification statistics over Florida by initializing WRF with land surface variables from an offline LIS spin-up run, conducted on the exact WRF domain and resolution. The current project extends the previous work over Florida, focusing on selected case studies of typical pulse convection over the southeastern U.S., with an emphasis on improving local short-term WRF

  14. AATSR Land Surface Temperature Product Validation Using Ground Measurements in China and Implications for SLSTR

    Science.gov (United States)

    Zhou, Ji; Zmuda, Andy; Desnos, Yves-Louis; Ma, Jin

    2016-08-01

    Land surface temperature (LST) is one of the most important parameters at the interface between the earth's surface and the atmosphere. It acts as a sensitive indicator of climate change and is an essential input parameter for land surface models. Because of the intense variability at different spatial and temporal scales, satellite remote sensing provides the sole opportunity to acquire LSTs over large regions. Validation of the LST products is an necessary step before their applications conducted by scientific community and it is essential for the developers to improve the LST products.

  15. Observation and modeling of land surface state and convective activity over the Qinghai - Tibet Plateau

    Science.gov (United States)

    Menenti, M.; Colin, J.; Jia, L.; Ma, Y.; Foken, T.; Sobrino, J. A.; Wang, J.; Shen, X.; Ueno, K.

    2012-04-01

    The Qinghai - Tibet Plateau is characterized by a significant intra-annual variability and spatial heterogeneity of surface conditions. Snow and vegetation cover, albedo, surface temperature and wetness change very significantly during the year and from place to place. The influence of temporal changes on convective events and the onset of the monsoon has been documented by ground based measurements of land - atmosphere exchanges of heat and water. The state of the land surface over the entire Plateau can be determined by space observation of surface albedo, temperature, snow and vegetation cover and soil moisture. This provides spatial patterns in the land surface drivers of atmospheric instability: radiative forcing, land surface temperature and soil moisture contribute to trigger convective events. Heat and vapour fluxes at the land surface have been mapped at high spatial resolution and over periods of time representative of seasonal variability using MODIS and AATSR multispectral radiometric data. The response of surface temperature to vegetation phenology has been studied by using 25 years of AVHRR observations. Snow cover has been monitored by improving and re-calibrating the MODIS snow cover product. The snow water equivalent has been monitored over a period of 28 years using SMMR and SSM/I 18 and 37 GHz data and an improved algorithm. Linkages between land surface conditions, convective events and the onset of the Asian Monsoon have been investigated using two Numerical Weather Prediction Models: GRAPES in China and WRF in Japan to analyze a set of case-studies. These first experiments were aimed at evaluating the linkages of land surface conditions with intense rainfall events in the region. Using the modeling and data assimilation system GRAPES a series of experiments was performed to assess the sensitivity to different types of Land Surface Models. Combined use of medium resolution thermal infrared sensors like AATSR or MODIS with GRAPES in a Multi

  16. Predicting Agricultural Drought using NOAH Land Surface Model, MODIS Evapotranspiration and GRACE Terrestrial Water Storage

    Science.gov (United States)

    wu, J.; Zhang, X.

    2013-12-01

    Drought is a major natural hazard in the world which costs 6-8 billion per year in the United States. Drought monitoring and prediction are difficult because it usually develops slowly and it is hard to be recognized until it becomes severe. The severity of agricultural drought was estimated by using Soil Moisture Deficit Index (SMDI) based on soil moisture simulated by Noah land surface model. Based on general water balance and delayed response of soil moisture to the forcing of climate variables, a Multiple Linear Regression (MLR) model for agricultural drought prediction was developed, the inputs of which included data at the previous one and two months of precipitation from Parameter-elevation Regressions on Independent Slopes Model (PRISM), evapotranspiration from MODIS MOD 16 product and terrestrial water storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE). The stability of the MLR model is tested using different training datasets from 2003 to 2009 with time spans of one year to six years and the results indicated that the model is stable, with very limited changes in estimated parameters between different datasets. A sensitivity analysis shows that evapotranspiration is the most significant variable affecting soil moisture change compared to precipitation and TWS. The predicted SMDI was compared with U.S. drought monitor products to evaluate its performance for the period of 2010-2012 when a severe drought occurred in the U.S. (Fig.1). The predicted SMDI successfully forecasted the severe drought in the southern U.S. in early 2012 and its expansion in the following summer. The MLR model has a high predictive skill with short-term forecast (1-2 months), while less accuracy is observed for the long-term forecast (3-6 months) (Fig.2).

  17. AATSR land surface temperature product algorithm verification over a WATERMED site

    Science.gov (United States)

    Noyes, E. J.; Sòria, G.; Sobrino, J. A.; Remedios, J. J.; Llewellyn-Jones, D. T.; Corlett, G. K.

    A new operational Land Surface Temperature (LST) product generated from data acquired by the Advanced Along-Track Scanning Radiometer (AATSR) provides the opportunity to measure LST on a global scale with a spatial resolution of 1 km2. The target accuracy of the product, which utilises nadir data from the AATSR thermal channels at 11 and 12 μm, is 2.5 K for daytime retrievals and 1.0 K at night. We present the results of an experiment where the performance of the algorithm has been assessed for one daytime and one night time overpass occurring over the WATERMED field site near Marrakech, Morocco, on 05 March 2003. Top of atmosphere (TOA) brightness temperatures (BTs) are simulated for 12 pixels from each overpass using a radiative transfer model, with the LST product and independent emissivity values and atmospheric data as inputs. We have estimated the error in the LST product over this biome for this set of conditions by applying the operational AATSR LST retrieval algorithm to the modelled BTs and comparing the results with the original AATSR LSTs input into the model. An average bias of -1.00 K (standard deviation 0.07 K) for the daytime data, and -1.74 K (standard deviation 0.02 K) for the night time data is obtained, which indicates that the algorithm is yielding an LST that is too cold under these conditions. While these results are within specification for daytime retrievals, this suggests that the target accuracy of 1.0 K at night is not being met within this biome.

  18. Characterizing the relationship between land use land cover change and land surface temperature

    Science.gov (United States)

    Tran, Duy X.; Pla, Filiberto; Latorre-Carmona, Pedro; Myint, Soe W.; Caetano, Mario; Kieu, Hoan V.

    2017-02-01

    Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

  19. Improving the representation of river-groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

    KAUST Repository

    Zampieri, Matteo

    2012-02-01

    Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land-vegetation-atmosphere interactions and the ecosystem dynamics. In regional-scale climate applications land surface models (LSMs) are commonly coupled to atmospheric models to close the surface energy, mass and carbon balance. LSMs in these applications are used to resolve the momentum, heat, water and carbon vertical fluxes, accounting for the effect of vegetation, soil type and other surface parameters, while lack of adequate resolution prevents using them to resolve horizontal sub-grid processes. Specifically, LSMs resolve the large-scale runoff production associated with infiltration excess and sub-grid groundwater convergence, but they neglect the effect from loosing streams to groundwater. Through the analysis of observed data of soil moisture obtained from the Oklahoma Mesoscale Network stations and land surface temperature derived from MODIS we provide evidence that the regional scale soil moisture and surface temperature patterns are affected by the rivers. This is demonstrated on the basis of simulations from a land surface model (i.e., Community Land Model - CLM, version 3.5). We show that the model cannot reproduce the features of the observed soil moisture and temperature spatial patterns that are related to the underlying mechanism of reinfiltration of river water to groundwater. Therefore, we implement a simple parameterization of this process in CLM showing the ability to reproduce the soil moisture and surface temperature spatial variabilities that relate to the river distribution at regional scale. The CLM with this new parameterization is used to evaluate impacts of the improved representation of river-groundwater interactions on the simulated water cycle parameters and the surface energy budget at the regional scale. © 2011 Elsevier B.V.

  20. Derivation of Land Surface Albedo at High Resolution by Combining HJ-1A/B Reflectance Observations with MODIS BRDF Products

    NARCIS (Netherlands)

    Gao, B.; Jia, L.; Wang, T.X.

    2014-01-01

    Land surface albedo is an essential parameter for monitoring global/regional climate and land surface energy balance. Although many studies have been conducted on global or regional land surface albedo using various remote sensing data over the past few decades, land surface albedo product with a hi

  1. Sensitivity of land surface and Cumulus schemes for Thunderstorm prediction

    Science.gov (United States)

    Kumar, Dinesh; Mohanty, U. C.; Kumar, Krishan

    2016-06-01

    The cloud processes play an important role in all forms of precipitation. Its proper representation is one of the challenging tasks in mesoscale numerical simulation. Studies have revealed that mesoscale feature require proper initialization which may likely to improve the convective system rainfall forecasts. Understanding the precipitation process, model initial condition accuracy and resolved/sub grid-scale precipitation processes representation, are the important areas which needed to improve in order to represent the mesoscale features properly. Various attempts have been done in order to improve the model performance through grid resolution, physical parameterizations, etc. But it is the physical parameterizations which provide a convective atmosphere for the development and intensification of convective events. Further, physical parameterizations consist of cumulus convection, surface fluxes of heat, moisture, momentum, and vertical mixing in the planetary boundary layer (PBL). How PBL and Cumulus schemes capture the evolution of thunderstorm have been analysed by taking thunderstorm cases occurred over Kolkata, India in the year 2011. PBL and cumulus schemes were customized for WSM-6 microphysics because WSM series has been widely used in operational forecast. Results have shown that KF (PBL scheme) and WSM-6 (Cumulus Scheme) have reproduced the evolution of surface variable such as CAPE, temperature and rainfall very much like observation. Further, KF and WSM-6 scheme also provided the increased moisture availability in the lower atmosphere which was taken to higher level by strong vertical velocities providing a platform to initiate a thunderstorm much better. Overestimation of rain in WSM-6 occurs primarily because of occurrence of melting and freezing process within a deeper layer in WSM-6 scheme. These Schemes have reproduced the spatial pattern and peak rainfall coverage closer to TRMM observation. It is the the combination of WSM-6, and KF schemes

  2. Sensitivity of land surface and Cumulus schemes for Thunderstorm prediction

    Directory of Open Access Journals (Sweden)

    D. Kumar

    2016-06-01

    Full Text Available The cloud processes play an important role in all forms of precipitation. Its proper representation is one of the challenging tasks in mesoscale numerical simulation. Studies have revealed that mesoscale feature require proper initialization which may likely to improve the convective system rainfall forecasts. Understanding the precipitation process, model initial condition accuracy and resolved/sub grid-scale precipitation processes representation, are the important areas which needed to improve in order to represent the mesoscale features properly. Various attempts have been done in order to improve the model performance through grid resolution, physical parameterizations, etc. But it is the physical parameterizations which provide a convective atmosphere for the development and intensification of convective events. Further, physical parameterizations consist of cumulus convection, surface fluxes of heat, moisture, momentum, and vertical mixing in the planetary boundary layer (PBL. How PBL and Cumulus schemes capture the evolution of thunderstorm have been analysed by taking thunderstorm cases occurred over Kolkata, India in the year 2011. PBL and cumulus schemes were customized for WSM-6 microphysics because WSM series has been widely used in operational forecast. Results have shown that KF (PBL scheme and WSM-6 (Cumulus Scheme have reproduced the evolution of surface variable such as CAPE, temperature and rainfall very much like observation. Further, KF and WSM-6 scheme also provided the increased moisture availability in the lower atmosphere which was taken to higher level by strong vertical velocities providing a platform to initiate a thunderstorm much better. Overestimation of rain in WSM-6 occurs primarily because of occurrence of melting and freezing process within a deeper layer in WSM-6 scheme. These Schemes have reproduced the spatial pattern and peak rainfall coverage closer to TRMM observation. It is the the combination of WSM-6

  3. Assessment of the interannual variability of agricultural yields in France using satellite data and a generic land surface model

    Science.gov (United States)

    Canal, Nicolas; Calvet, Jean-Christophe; Szczypta, Camille

    2013-04-01

    The generic ISBA-A-gs Land Surface Model (LSM) is used to simulate the interannual variability of the maximum above-ground biomass (Bagm) of cereals and grasslands in France. Agricultural statistics are used to optimize the maximal available soil water content (MaxAWC) of the model. For a number of administrative units, significant correlations between the simulated Bagm and the agricultural yield statistics are found over the 1994-2010 period. It is shown that the interannual variability of Bagm and of the simulated soil moisture correlate at given key periods. Significant correlations are found between ten-daily averaged simulated soil moisture and the simulated (observed) Bagm (yields). The corresponding plant growth stage is determined through the Leaf Area Index (LAI). Moreover, it is shown that the interannual variability of the modelled LAI and of the new satellite-derived GEOLAND2 LAI are consistent. The predictive value of both simulated and observed LAI on the agricultural yield (10 to 40 days before harvest) is investigated. The scores are used to benchmark different configurations of the model. In particular two contrasting representations of the soil moisture profile are considered: (1) one root-zone layer, (2) several soil layers with an explicit representation of diffusion processes and an exponential root density profile, with or without a deep soil layer below the root-zone.

  4. Simulation and mockup tests for developing TRR-II CNS

    Science.gov (United States)

    Lee, C. H.; Kawai, T.; Chan, Y. K.; Hong, W. T.; Lee, D. J.; Guung, T. C.; Lan, K. C.

    2002-01-01

    The Taiwan Research Reactor improvement and the utilization promotion project (TRR-II) with Cold Neutron Source (CNS) was carried out at Institute of Nuclear Energy Research. The CNS with a two-phase thermosiphon loop consists of an annular cylindrical moderator cell, a single moderator transfer tube, and a condenser. The self-regulating characteristics of a two-phase thermosiphon loop are investigated against variations of heat load. The experiments on the thermal-hydraulic characteristics have been performed using a full-scale mockup loop and a Freon-11 was used as a working fluid. Two cases were evaluated by the simulation and experiments. One case is an ORPHEE-type moderator cell in which an inner shell is open at the bottom, the other case is one with an inner cavity with no hole at the bottom but a vapor inlet opening at the uppermost part of the cavity. The flooding limitations, liquid level and void fraction in the moderator cell as a function of the initial Freon-11 inventory and the heat load are also reported.

  5. Wildfire Risk Mapping over the State of Mississippi: Land Surface Modeling Approach

    Energy Technology Data Exchange (ETDEWEB)

    Cooke, William H. [Mississippi State University (MSU); Mostovoy, Georgy [Mississippi State University (MSU); Anantharaj, Valentine G [ORNL; Jolly, W. Matt [USDA Forest Service

    2012-01-01

    Three fire risk indexes based on soil moisture estimates were applied to simulate wildfire probability over the southern part of Mississippi using the logistic regression approach. The fire indexes were retrieved from: (1) accumulated difference between daily precipitation and potential evapotranspiration (P-E); (2) top 10 cm soil moisture content simulated by the Mosaic land surface model; and (3) the Keetch-Byram drought index (KBDI). The P-E, KBDI, and soil moisture based indexes were estimated from gridded atmospheric and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). Normalized deviations of these indexes from the 31-year mean (1980-2010) were fitted into the logistic regression model describing probability of wildfires occurrence as a function of the fire index. It was assumed that such normalization provides more robust and adequate description of temporal dynamics of soil moisture anomalies than the original (not normalized) set of indexes. The logistic model parameters were evaluated for 0.25 x0.25 latitude/longitude cells and for probability representing at least one fire event occurred during 5 consecutive days. A 23-year (1986-2008) forest fires record was used. Two periods were selected and examined (January mid June and mid September December). The application of the logistic model provides an overall good agreement between empirical/observed and model-fitted fire probabilities over the study area during both seasons. The fire risk indexes based on the top 10 cm soil moisture and KBDI have the largest impact on the wildfire odds (increasing it by almost 2 times in response to each unit change of the corresponding fire risk index during January mid June period and by nearly 1.5 times during mid September-December) observed over 0.25 x0.25 cells located along the state of Mississippi Coast line. This result suggests a rather strong control of fire risk indexes on fire occurrence probability

  6. Land surface thermal characterization of Asian-pacific region with Japanese geostationary satellite

    Science.gov (United States)

    Oyoshi, K.; Tamura, M.

    2010-12-01

    Land Surface Temperature (LST) is a significant indicator of energy balance at the Earth's surface. It is required for a wide variety of climate, hydrological, ecological, and biogeochemical studies. Although LST is highly variable both temporally and spatially, it is impossible for polar-orbiting satellite to detect hourly changes in LST, because the satellite is able to only collect data of the same area at most twice a day. On the other hand, geostationary satellite is able to collect hourly data and has a possibility to monitor hourly changes in LST, therefore hourly measurements of geostationary satellite enables us to characterize detailed thermal conditions of the Earth's surface and improve our understanding of the surface energy balance. Multi-functional Transport Satellite (MTSAT) is a Japanese geostationary satellite launched in 2005 and covers Asia-Pacific region. MTSAT provides hourly data with 5 bands including two thermal infrared (TIR) bands in the 10.5-12.5 micron region. In this research, we have developed a methodology to retrieve hourly LST from thermal infrared data of MTSAT. We applied Generalized Split-window (GSW) equation to estimate LST from TIR data. First, the brightness temperatures measured at sensor on MTSAT was simulated by radiative transfer code (MODTRAN), and the numerical coefficients of GSW equation were optimized based on the simulation results with non-linear minimization algorithm. The standard deviation of derived GSW equation was less than or equal to 1.09K in the case of viewing zenith angle lower than 40 degree and 1.73K in 60 degree. Then, spatial distributions of LST have been mapped optimized GSW equation with brightness temperatures of MTSAT IR1 and IR2 and emissivity map from MODIS product. Finally, these maps were validated with MODIS LST product (MOD11A1) over four Asian-pacific regions such as Bangkok, Tokyo, UlanBator and Jakarta , It is found that RMSE of these regions were 4.57K, 2.22K, 2.71K and 3.92K

  7. PALADYN, a comprehensive land surface-vegetation-carbon cycle model of intermediate complexity

    Science.gov (United States)

    Willeit, Matteo; Ganopolski, Andrey

    2016-04-01

    PALADYN is presented, a new comprehensive and computationally efficient land surface-vegetation-carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies. The model treats in a consistent manner the interaction between atmosphere, terrestrial vegetation and soil through the fluxes of energy, water and carbon. Energy, water and carbon are conserved. The model explicitly treats permafrost, both in physical processes and as important carbon pool. The model distinguishes 9 surface types of which 5 are different vegetation types, bare soil, land ice, lake and ocean shelf. Including the ocean shelf allows to treat continuous changes in sea level and shelf area associated with glacial cycles. Over each surface type the model solves the surface energy balance and computes the fluxes of sensible, latent and ground heat and upward shortwave and longwave radiation. It includes a single snow layer. The soil model distinguishes between three different macro surface types which have their own soil column: vegetation and bare soil, ice sheet and ocean shelf. The soil is vertically discretized into 5 layers where prognostic equations for temperature, water and carbon are consistently solved. Phase changes of water in the soil are explicitly considered. A surface hydrology module computes precipitation interception by vegetation, surface runoff and soil infiltration. The soil water equation is based on Darcy's law. Given soil water content, the wetland fraction is computed based on a topographic index. Photosynthesis is computed using a light use efficiency model. Carbon assimilation by vegetation is coupled to the transpiration of water through stomatal conductance. The model includes a dynamic vegetation module with 5 plant functional types competing for the gridcell share with their respective net primary productivity. Each macro surface type has its own carbon pools represented by a litter, a fast

  8. Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

    2012-12-01

    Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

  9. Widespread land surface wind decline in the Northern Hemisphere

    Science.gov (United States)

    Vautard, R.; Cattiaux, J.; Yiou, P.; Thépaut, J.-N.; Ciais, P.

    2010-09-01

    pressure gradients, and modeled winds from weather re-analyses do not exhibit any comparable stilling trends than at surface stations. For instance, large-scale circulation changes captured in the most recent European Centre for Medium Range Weather Forecast re-analysis (ERA-interim) can only explain only up to 30% of the Eurasian wind stilling. In addition, a significant amount of the slow-down could originate from a generalized increase in surface roughness, due for instance to forest growth and expansion, and urbanization. This hypothesis is supported by theoretical calculations combined with meso-scale model simulations. For future wind power energy resource, the part of wind decline due to land cover changes is easier to cope with than that due to global atmospheric circulation slow down.

  10. The Utility of Remotely-Sensed Land Surface Temperature from Multiple Platforms For Testing Distributed Hydrologic Models over Complex Terrain

    Science.gov (United States)

    Xiang, T.; Vivoni, E. R.; Gochis, D. J.

    2011-12-01

    Land surface temperature (LST) is a key parameter in watershed energy and water budgets that is relatively unexplored as a validation metric for distributed hydrologic models. Ground-based or remotely-sensed LST datasets can provide insights into a model's ability in reproducing water and energy fluxes across a large range of terrain, vegetation, soil and meteorological conditions. As a result, spatiotemporal LST observations can serve as a strong constraint for distributed simulations and can augment other available in-situ data. LST fields are particular useful in mountainous areas where temperature varies with terrain properties and time-variable surface conditions. In this study, we collect and process remotely-sensed fields from several satellite platforms - Landsat 5/7, MODIS and ASTER - to capture spatiotemporal LST dynamics at multiple resolutions and with frequent repeat visits. We focus our analysis of these fields over the Sierra Los Locos basin (~100 km2) in Sonora, Mexico, for a period encompassing the Soil Moisture Experiment in 2004 and the North American Monsoon Experiment (SMEX04-NAME). Satellite observations are verified using a limited set of ground data from manual sampling at 30 locations and continuous measurements at 2 sites. First, we utilize the remotely-sensed fields to understand the summer seasonal evolution of LST in the basin in response to the arrival of summer storms and the vigorous ecosystem greening organized along elevation bands. Then, we utilize the ground and remote-sensing datasets to test the distributed predictions of the TIN-based Real-time Integrated Basin Simulator (tRIBS) under conditions accounting static and dynamic vegetation patterns. Basin-averaged and distributed comparisons are carried out for two different terrain products (INEGI aerial photogrammetry and ASTER stereo processing) used to derive the distributed model domain. Results from the comparisons are discussed in light of the utility of remotely-sensed LST

  11. Improving arable land heterogeneity information in available land cover products for land surface modelling using MERIS NDVI data

    Directory of Open Access Journals (Sweden)

    F. Zabel

    2010-10-01

    Full Text Available Regionalization of physical land surface models requires the supply of detailed land cover information. Numerous global and regional land cover maps already exist but generally, they do not resolve arable land into different crop types. However, arable land comprises a huge variety of different crops with characteristic phenological behaviour, demonstrated in this paper with Leaf Area Index (LAI measurements exemplarily for maize and winter wheat. This affects the mass and energy fluxes on the land surface and thus its hydrology. The objective of this study is the generation of a land cover map for central Europe based on CORINE Land Cover (CLC 2000, merged with CORINE Switzerland, but distinguishing different crop types. Accordingly, an approach was developed, subdividing the land cover class arable land into the regionally most relevant subclasses for central Europe using multiseasonal MERIS Normalized Difference Vegetation Index (NDVI data. The satellite data were used for the separation of spring and summer crops due to their different phenological behaviour. Subsequently, the generated phenological classes were subdivided following statistical data from EUROSTAT. This database was analysed concerning the acreage of different crop types. The impact of the improved land use/cover map on evapotranspiration was modelled exemplarily for the Upper Danube catchment with the hydrological model PROMET. Simulations based on the newly developed land cover approach showed a more detailed evapotranspiration pattern compared to model results using the traditional CLC map, which is ignorant of most arable subdivisions. Due to the improved temporal behaviour and spatial allocation of evapotranspiration processes in the new land cover approach, the simulated water balance more closely matches the measured gauge.

  12. Interactions of the land-surface with the atmospheric boundary layer

    NARCIS (Netherlands)

    Ek, M.B.

    2005-01-01

    We study daytime land-atmosphere interaction using a one-dimensional (column) coupled land-surface - atmospheric boundary-Iayer (ABL) model and data sets gathered at Cabauw (1978, central Netherlands) and during the Hydrological and Atmospheric Pilot Experiment - Modélisation du Bilan Hydrique (HAPE

  13. Using microwave observations to estimate land surface temperature during cloudy conditions

    Science.gov (United States)

    Land surface temperature (LST), a key ingredient for physically-based retrieval algorithms of hydrological states and fluxes, remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observations and...

  14. The Global Land Surface Satellite (GLASS Remote Sensing Data Processing System and Products

    Directory of Open Access Journals (Sweden)

    Gongqi Zhou

    2013-05-01

    Full Text Available Using remotely sensed satellite products is the most efficient way to monitor global land, water, and forest resource changes, which are believed to be the main factors for understanding global climate change and its impacts. A reliable remotely sensed product should be retrieved quantitatively through models or statistical methods. However, producing global products requires a complex computing system and massive volumes of multi-sensor and multi-temporal remotely sensed data. This manuscript describes the ground Global LAnd Surface Satellite (GLASS product generation system that can be used to generate long-sequence time series of global land surface data products based on various remotely sensed data. To ensure stabilization and efficiency in running the system, we used the methods of task management, parallelization, and multi I/O channels. An array of GLASS remote sensing products related to global land surface parameters are currently being produced and distributed by the Center for Global Change Data Processing and Analysis at Beijing Normal University in Beijing, China. These products include Leaf Area Index (LAI, land surface albedo, and broadband emissivity (BBE from the years 1981 to 2010, downward shortwave radiation (DSR and photosynthetically active radiation (PAR from the years 2008 to 2010.

  15. SGP Cloud and Land Surface Interaction Campaign (CLASIC): Science and Implementation Plan

    Energy Technology Data Exchange (ETDEWEB)

    MA Miller; R Avissar; LK Berg; SA Edgerton; ML Fischer; T Jackson; B.Kustas; PJ Lamb; GM McFarquhar; Q Min; B Schmid; MS Torn; DD Turner

    2007-06-30

    The Cloud and Land Surface Interaction Campaign is a field experiment designed to collect a comprehensive data set that can be used to quantify the interactions that occur between the atmosphere, biosphere, land surface, and subsurface. A particular focus will be on how these interactions modulate the abundance and characteristics of small and medium size cumuliform clouds that are generated by local convection. These interactions are not well understood and are responsible for large uncertainties in global climate models, which are used to forecast future climate states. The campaign will be conducted from June 8 to June 30, 2007, at the U.S. Department of Energy’s Atmospheric Radiation Measurement Climate Research Facility Southern Great Plains site. Data will be collected using eight aircraft equipped with a variety of specialized sensors, four specially instrumented surface sites, and two prototype surface radar systems. The architecture of Cloud and Land Surface Interaction Campaign includes a high-altitude surveillance aircraft and enhanced vertical thermodynamic and wind profile measurements that will characterize the synoptic scale structure of the clouds and the land surface within the Atmospheric Radiation Measurement Climate Research Facility Southern Great Plains site. Mesoscale and microscale structures will be sampled with a variety of aircraft, surface, and radar observations.

  16. Microclimatic models. Estimation of components of the energy balance over land surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Heikinheimo, M.; Venaelaeinen, A.; Tourula, T. [Finnish Meteorological Inst., Helsinki (Finland). Air Quality Dept.

    1996-12-31

    Climates at regional scale are strongly dependent on the interaction between atmosphere and its lower boundary, the oceans and the land surface mosaic. Land surfaces influence climate through their albedo, and the aerodynamic roughness, the processes of the biosphere and many soil hydrological properties; all these factors vary considerably geographically. Land surfaces receive a certain portion of the solar irradiance depending on the cloudiness, atmospheric transparency and surface albedo. Short-wave solar irradiance is the source of the heat energy exchange at the earth`s surface and also regulates many biological processes, e.g. photosynthesis. Methods for estimating solar irradiance, atmospheric transparency and surface albedo were reviewed during the course of this project. The solar energy at earth`s surface is consumed for heating the soil and the lower atmosphere. Where moisture is available, evaporation is one of the key components of the surface energy balance, because the conversion of liquid water into water vapour consumes heat. The evaporation process was studied by carrying out field experiments and testing parameterisation for a cultivated agricultural surface and for lakes. The micrometeorological study over lakes was carried out as part of the international `Northern Hemisphere Climatic Processes Experiment` (NOPEX/BAHC) in Sweden. These studies have been aimed at a better understanding of the energy exchange processes of the earth`s surface-atmosphere boundary for a more accurate and realistic parameterisation of the land surface in atmospheric models

  17. Multi-sensor remote sensing parameterization of heat fluxes over heterogeneous land surfaces

    NARCIS (Netherlands)

    Faivre, R.D.

    2014-01-01

    The parameterization of heat transfer by remote sensing, and based on SEBS scheme for turbulent heat fluxes retrieval, already proved to be very convenient for estimating evapotranspiration (ET) over homogeneous land surfaces. However, the use of such a method over heterogeneous landscapes (e.g. sem

  18. Heat waves measured with MODIS land surface temperature data predict changes in avian community structure

    Science.gov (United States)

    Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Volker C. Radeloff

    2011-01-01

    Heat waves are expected to become more frequent and severe as climate changes, with unknown consequences for biodiversity. We sought to identify ecologically-relevant broad-scale indicators of heat waves based on MODIS land surface temperature (LST) and interpolated air temperature data and assess their associations with avian community structure. Specifically, we...

  19. Calibration of a distributed hydrology and land surface model using energy flux measurements

    DEFF Research Database (Denmark)

    Larsen, Morten Andreas Dahl; Refsgaard, Jens Christian; Jensen, Karsten H.

    2016-01-01

    In this study we develop and test a calibration approach on a spatially distributed groundwater-surface water catchment model (MIKE SHE) coupled to a land surface model component with particular focus on the water and energy fluxes. The model is calibrated against time series of eddy flux measure...

  20. The Land Surface Temperature Synergistic Processor in BEAM: A Prototype towards Sentinel-3

    CERN Document Server

    Ruescas, Ana Belen; Fomferra, Norman; Brockmann, Carsten

    2016-01-01

    Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR). In this paper we explain the implementation in the Basic ENVISAT Toolbox for (A)ATSR and MERIS (BEAM) and the use of one LST algorithm developed in the framework of the Synergistic Use of The Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST) project. The LST algorithm is based on the split-window technique with an explicit dependence on the surface emissivity. Performance of the methodology is assessed by using MEdium Resolution Imaging Spectrometer/Advanced Alo...

  1. Modelling land surface fluxes of CO2 in response to climate change and nitrogen deposition

    DEFF Research Database (Denmark)

    Hansen, Kristina; Ambelas Skjøth, Carsten; Geels, Camilla

    Climate change, land use variations, and impacts of atmospheric nitrogen (N) deposition represent uncertainties for the prediction of future greenhouse gas exchange between land surfaces and the atmosphere as the mechanisms describing nutritional effects are not well developed in climate...... climate feedback mechanisms of CO2 between changes in management, land use practise, and climate change....

  2. High resolution land surface geophysical parameters estimation from ALOS PALSAR data

    Science.gov (United States)

    High resolution land surface geophysical products, such as soil moisture, surface roughness and vegetation water content, are essential for a variety of applications ranging from water management to regional climate predictions. In India high resolution geophysical products, in particular soil moist...

  3. Remote Sensing Parameterization of Land Surface Heat Fluxes over Arid and Semi-arid Areas

    Institute of Scientific and Technical Information of China (English)

    马耀明; 王介民; 黄荣辉; 卫国安; MassimoMENENTI; 苏中波; 胡泽勇; 高峰; 文军

    2003-01-01

    Dealing with the regional land surfaces heat fluxes over inhomogeneous land surfaces in arid and semi-arid areas is an important but not an easy issue. In this study, one parameterization method based on satellite remote sensing and field observations is proposed and tested for deriving the regional land surface heat fluxes over inhomogeneous landscapes. As a case study, the method is applied to the Dunhuang experimental area and the HEIFE (Heihe River Field Experiment, 1988-1994) area. The Dunhuang area is selected as a basic experimental area for the Chinese National Key Programme for Developing Basic Sciences: Research on the Formation Mecbanism and Prediction Theory of Severe Climate Disaster in China (G1998040900, 1999-2003). The four scenes of Landsat TM data used in this study are 3 June 2000,22 August 2000, and 29 January 2001 for the Dunhuang area and 9 July 1991 for the HEIFE area. The regional distributions of land surface variables, vegetation variables, and heat fluxes over inhomogeneous landscapes in arid and semi-arid areas are obtained in this study.

  4. Estimating land-surface temperature under clouds using MSG/SEVIRI observations

    NARCIS (Netherlands)

    Lu, L.; Venus, V.; Skidmore, A.K.; Wang, T.; Luo, G.

    2011-01-01

    The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the di

  5. Estimating land-surface temperature under clouds using MSG/SEVIRI observations

    NARCIS (Netherlands)

    Lu, L.; Venus, V.; Skidmore, A.K.; Wang, T.; Luo, G.

    2011-01-01

    The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the

  6. Cloud tolerance of remote sensing technologies to measure land surface temperature

    Science.gov (United States)

    Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

  7. Land-surface and boundary layer processes in a semi-arid heterogeneous landscape

    NARCIS (Netherlands)

    Jochum, A.M.

    2003-01-01

    The European Field Experiment in a Desertification-threatened Area (EFEDA) provides a comprehensive land-surface dataset for a semiarid Mediterranean environment. It is used here to study heat and moisture transport processes in the atmospheric boundary layer (ABL), to derive grid-scale surface flux

  8. Diurnal and Seasonal Variation of Clear-Sky Land Surface Temperature of Several Representative Land Surface Types in China Retrieved by GMS-5

    Institute of Scientific and Technical Information of China (English)

    WANG Minyan; Lu Daren

    2006-01-01

    The retrieved results in this paper by GMS-5/VISSR thermal infrared data with single time/dual channel Split-Window Algorithm reveal the characteristics of diurnal and seasonal variation of clear-sky land surface temperature (LST) of several representative land surface types in China, including Tarim Basin, QinghaiTibetan Plateau, Hunshandake Sands, North China Plain, and South China. The seasonal variation of clear-sky LST in above areas varies distinctly for the different surface albedo, soil water content, and the extent of influence by solar radiation. The monthly average diurnal ranges of LST have two peaks and two valleys in one year. The characteristics of LST in most land of East Asia and that of sea surface temperature (SST) in the south of Taiwan Strait and the Yellow Sea are also analyzed as comparison. Tarim Basin and Hunshandake Sands have not only considerable LST diurnal cycle but also remarkable seasonal variation.In 2000, the maximum monthly average diurnal ranges of LST in both areas are over 30 K, and the annual range in Hunshadake Sands reaches 58.50 K. Seasonal variation of LST in the Qinghai-Tibetan Plateau is less than those in East Asia, Tarim Basin, and Hunshandake Sands. However, the maximum diurnal range exists in this area. The yearly average diurnal range is 28.05 K in the Qinghai-Tibetan Plateau in 2000. The characteristics of diurnal, seasonal, and annual variation from 1998 to 2000 are also shown in this research.All the results will be valuable to the research of climate change, radiation balance, and estimation for the change of land surface types.

  9. A dynamically-coupled groundwater, land surface and regional climate model to predict seasonal watershed flow and groundwater response, FINAL LDRD REPORT.

    Energy Technology Data Exchange (ETDEWEB)

    Maxwell, R; Kollet, S; Chow, F; Granvold, P; Duan, Q

    2007-02-23

    This final report is organized in four sections. Section 1 is the project summary (below), Section 2 is a submitted manuscript that describes the offline, or spinup simulations in detail, Section 3 is also a submitted manuscript that describes the online, or fully-coupled simulations in detail and Section 3, which is report that describes work done via a subcontract with UC Berkeley. The goal of this project was to develop and apply a coupled regional climate, land-surface, groundwater flow model as a means to further understand important mass and energy couplings between regional climate, the land surface, and groundwater. The project involved coupling three distinct submodels that are traditionally used independently with abstracted and potentially oversimplified (inter-model) boundary conditions. This coupled model lead to (1) an improved understanding of the sensitivity and importance of coupled physical processes from the subsurface to the atmosphere; (2) a new tool for predicting hydrologic conditions (rainfall, temperature, snowfall, snowmelt, runoff, infiltration and groundwater flow) at the watershed scale over a range of timeframes; (3) a simulation of hydrologic response of a characteristic watershed that will provide insight into the certainty of hydrologic forecasting, dominance and sensitivity of groundwater dynamics on land-surface fluxes; and (4) a more realistic model representation of weather predictions, precipitation and temperature, at the regional scale. Regional climate models are typically used for the simulation of weather, precipitation and temperature behavior over 10-1000 km domains for weather or climate prediction purposes, and are typically driven by boundary conditions derived from global climate models (GCMs), observations or both. The land or ocean surface typically represents a bottom boundary condition of these models, where important mass (water) and energy fluxes are approximated. The viability and influence of these

  10. A dynamically-coupled groundwater, land surface and regional climate model to predict seasonal watershed flow and groundwater response, FINAL LDRD REPORT.

    Energy Technology Data Exchange (ETDEWEB)

    Maxwell, R; Kollet, S; Chow, F; Granvold, P; Duan, Q

    2007-02-23

    This final report is organized in four sections. Section 1 is the project summary (below), Section 2 is a submitted manuscript that describes the offline, or spinup simulations in detail, Section 3 is also a submitted manuscript that describes the online, or fully-coupled simulations in detail and Section 3, which is report that describes work done via a subcontract with UC Berkeley. The goal of this project was to develop and apply a coupled regional climate, land-surface, groundwater flow model as a means to further understand important mass and energy couplings between regional climate, the land surface, and groundwater. The project involved coupling three distinct submodels that are traditionally used independently with abstracted and potentially oversimplified (inter-model) boundary conditions. This coupled model lead to (1) an improved understanding of the sensitivity and importance of coupled physical processes from the subsurface to the atmosphere; (2) a new tool for predicting hydrologic conditions (rainfall, temperature, snowfall, snowmelt, runoff, infiltration and groundwater flow) at the watershed scale over a range of timeframes; (3) a simulation of hydrologic response of a characteristic watershed that will provide insight into the certainty of hydrologic forecasting, dominance and sensitivity of groundwater dynamics on land-surface fluxes; and (4) a more realistic model representation of weather predictions, precipitation and temperature, at the regional scale. Regional climate models are typically used for the simulation of weather, precipitation and temperature behavior over 10-1000 km domains for weather or climate prediction purposes, and are typically driven by boundary conditions derived from global climate models (GCMs), observations or both. The land or ocean surface typically represents a bottom boundary condition of these models, where important mass (water) and energy fluxes are approximated. The viability and influence of these

  11. Resolution and Content Improvements to MISR Aerosol and Land Surface Products

    Science.gov (United States)

    Garay, M. J.; Bull, M. A.; Diner, D. J.; Hansen, E. G.; Kalashnikova, O. V.

    2015-12-01

    Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been providing operational Level 2 (swath-based) aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution and atmospherically corrected land surface products at 1.1 km resolution. The performance of the aerosol product has been validated against ground-based Aerosol Robotic Network (AERONET) observations, model comparisons, and climatological assessments. This product has played a major role in studies of the impacts of aerosols on climate and air quality. The surface product has found a variety of uses, particularly at regional scales for assessing vegetation and land surface change. A major development effort has led to the release of an update to the operational (Version 22) MISR Level 2 aerosol and land surface retrieval products, which has been in production since December 2007. The new release is designated Version 23. The resolution of the aerosol product has been increased to 4.4 km, allowing more detailed characterization of aerosol spatial variability, especially near local sources and in urban areas. The product content has been simplified and updated to include more robust measures of retrieval uncertainty and other fields to benefit users. The land surface product has also been updated to incorporate the Version 23 aerosol product as input and to improve spatial coverage, particularly over mountainous terrain and snow/ice-covered surfaces. We will describe the major upgrades incorporated in Version 23 and present validation of the aerosol product against both the standard AERONET historical database, as well as high spatial density AERONET-DRAGON deployments. Comparisons will also be shown relative to the Version 22 aerosol and land surface products. Applications enabled by these product updates will be discussed.

  12. LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

    Science.gov (United States)

    Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

    2014-11-01

    The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product

  13. Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land-surface temperature observations

    Science.gov (United States)

    Castellví, F.; Cammalleri, C.; Ciraolo, G.; Maltese, A.; Rossi, F.

    2016-05-01

    Equations based on surface renewal (SR) analysis to estimate the sensible heat flux (H) require as input the mean ramp amplitude and period observed in the ramp-like pattern of the air temperature measured at high frequency. A SR-based method to estimate sensible heat flux (HSR-LST) requiring only low-frequency measurements of the air temperature, horizontal mean wind speed, and land-surface temperature as input was derived and tested under unstable conditions over a heterogeneous canopy (olive grove). HSR-LST assumes that the mean ramp amplitude can be inferred from the difference between land-surface temperature and mean air temperature through a linear relationship and that the ramp frequency is related to a wind shear scale characteristic of the canopy flow. The land-surface temperature was retrieved by integrating in situ sensing measures of thermal infrared energy emitted by the surface. The performance of HSR-LST was analyzed against flux tower measurements collected at two heights (close to and well above the canopy top). Crucial parameters involved in HSR-LST, which define the above mentioned linear relationship, were explained using the canopy height and the land surface temperature observed at sunrise and sunset. Although the olive grove can behave as either an isothermal or anisothermal surface, HSR-LST performed close to H measured using the eddy covariance and the Bowen ratio energy balance methods. Root mean square differences between HSR-LST and measured H were of about 55 W m-2. Thus, by using multitemporal thermal acquisitions, HSR-LST appears to bypass inconsistency between land surface temperature and the mean aerodynamic temperature. The one-source bulk transfer formulation for estimating H performed reliable after calibration against the eddy covariance method. After calibration, the latter performed similar to the proposed SR-LST method.

  14. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    indirect measurements (surface long-wave radiation observations) from the SURFace RADiation Budget (SURFRAD) Network. A simulated dataset was created to analyse the sensitivity of the proposed retrieval algorithms. In addition, the MODIS LST and GSIP LST products were adopted to cross-evaluate the accuracy of the GOES LST products. Evaluation results demonstrate that the proposed GOES LST system is capable of deriving consistent land surface temperatures with good retrieval precision. Consistent GOES LST products with high spatial/temporal coverage and reliable accuracy will better support detections and observations of meteorological over land surfaces.

  15. A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

    Science.gov (United States)

    Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.

    2011-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and

  16. Sensitivity of Land Surfaces Model to Dynamic Land Surface Parameters%陆面过程模型对下垫面参数动态变化的敏感性分析

    Institute of Scientific and Technical Information of China (English)

    蔡福; 周广胜; 李荣平; 明惠青

    2011-01-01

    Using continuous flux data, meteorological data and biological data in 2006 (from June 1 to August 9) from Jinzhou agricultural ecosystem research station, based on BATSIe model, the sensitivity of land surface model to dynamic assignment of roughness( Z0 ), leaf area index(LAI) and fractional vegetation coverage (FVEG)and albedo(α) were investigated. The results show that dynamic assignment of Z0 has effect on simulating surface soil temperature(SST) and sensible heat flux (SH) especially on the time when maize field surface covered changes from bare soil to vegetation. Dynamic LAIplays important role in improving the simulation of SST, net absorbed solar energy flux(Frs), SH and surface soil water content(SWC), at the same time affects simulation of latent heat flux (LE). Dynamic FVEG affects obviously simulations of all above-mentioned variables and shows greater sensitivity when they are smaller. Also, dynamical change of a can affect simulations of SST, LE and SH, especially for the latter. Furthermore, the interactions among different dynamic parameters are ignored by the model. The improvement of single land surface parameter might be helpful for simulating one or multivariate but not for all variables. In short, it is necessary to set up a parameterization scheme with the interactions of different land surface parameters.%利用2006年锦州玉米农田生态系统野外观测站动态连续的通量、气象及生物因子观测数据,分析了BATSl e陆面模型对动态的粗糙度(Z0)、叶面积指数(LAI)、植被履盖度(FVEG)及反照率(α)变化的敏感性.结果表明:Z0的动态变化对表层土壤温度(SST)和感热(SH)的模拟有一定影响,主要发生在玉米农田从裸土向有植被覆盖转变这一阶段.LAI的动态赋值可以改善SST、净入射短波辐射(frs)、SH和SWC的模拟效果,对潜热(LE)的模拟也有一定影响.动态FVEG对上述各变量的模拟影响最为明显,当FVEG较小时敏感性最大.α的动

  17. Impact of land surface heterogeneity on urban heat island circulation and sea-land breeze circulation in Hong Kong

    Science.gov (United States)

    Wang, Y.; Di Sabatino, S.; Martilli, A.; Li, Y.; Wong, M. S.; Gutiérrez, E.; Chan, P. W.

    2017-04-01

    Hong Kong is one of the most high-rise and highly compact cities in the world. The urban land surface is highly heterogeneous, which creates low-level convergence zones in urban areas, particularly the Kowloon Peninsula. The low-level convergence zone is due to the combined effect of urban heat island circulation (UHIC) and sea-land breeze circulation (SLBC) under weak northeasterly synoptic flow. To study the impacts of anthropogenic fluxes and built-up areas on the local circulation, the Weather Research and Forecasting (WRF) mesoscale model is combined with the multilayer urban canopy building effect parameterization/building energy model (BEP/BEM) parameterization to produce a 3 day simulation of an air pollution episode in Hong Kong in September 2012. To better represent the city land surface features, building information is assimilated in the central part of the Kowloon Peninsula. The WRF-BEP-BEM model captures the 2 m temperature distribution and local wind rotation reasonably well but overestimates the 10 m wind speed with a mean bias error of 0.70 m/s. A dome-shaped feature with a high level of moisture is captured in the convergence zones due to intensified UHIC and inflowing SLBC. The anthropogenic heat increases the air temperature by around 0.3°C up to 250 m, which in turn modifies the SLBC. A new drag coefficient based on λP, plan area per unit ground area, is tested. Besides the basic physical characteristics captured by the WRF-BEP-BEM model, the stagnation of wind in the lower level convergence zone is better captured by this approach than by the traditional constant value coefficient.

  18. Estimation and Validation of Land Surface Temperatures from Chinese Second-Generation Polar-Orbit FY-3A VIRR Data

    Directory of Open Access Journals (Sweden)

    Bo-Hui Tang

    2015-03-01

    Full Text Available This work estimated and validated the land surface temperature (LST from thermal-infrared Channels 4 (10.8 µm and 5 (12.0 µm of the Visible and Infrared Radiometer (VIRR onboard the second-generation Chinese polar-orbiting FengYun-3A (FY-3A meteorological satellite. The LST, mean emissivity and atmospheric water vapor content (WVC were divided into several tractable sub-ranges with little overlap to improve the fitting accuracy. The experimental results showed that the root mean square errors (RMSEs were proportional to the viewing zenith angles (VZAs and WVC. The RMSEs were below 1.0 K for VZA sub-ranges less than 30° or for VZA sub-ranges less than 60° and WVC less than 3.5 g/cm2, provided that the land surface emissivities were known. A preliminary validation using independently simulated data showed that the estimated LSTs were quite consistent with the actual inputs, with a maximum RMSE below 1 K for all VZAs. An inter-comparison using the Moderate Resolution Imaging Spectroradiometer (MODIS-derived LST product MOD11_L2 showed that the minimum RMSE was 1.68 K for grass, and the maximum RMSE was 3.59 K for barren or sparsely vegetated surfaces. In situ measurements at the Hailar field site in northeastern China from October, 2013, to September, 2014, were used to validate the proposed method. The result showed that the RMSE between the LSTs calculated from the ground measurements and derived from the VIRR data was 1.82 K.

  19. Quantifying the effect of lichen and bryophyte cover on permafrost soil within a global land surface model

    Science.gov (United States)

    Porada, Philipp; Ekici, Altug; Beer, Christian

    2016-04-01

    Vegetation near the surface, such as bryophytes and lichens, has an insulating effect on the soil at high latitudes and it can therefore protect permafrost conditions. Warming due to climate change, however, may change the average surface coverage of bryophytes and lichens. This can result in permafrost thawing associated with a release of soil carbon to the atmosphere, which may lead to a positive feedback on atmospheric CO2. Thus, it is important to predict how the bryophyte and lichen cover at high latitudes will react to environmental change. However, current global land surface models so far contain mostly empirical approaches to represent bryophytes and lichens, which makes it impractical to predict their future state and function. For this reason, we integrate a process-based model of bryophyte and lichen growth into the global land surface model JSBACH. We explicitly represent dynamic thermal properties of the bryophyte and lichen cover and their relation to climate. Subsequently, we compare simulations with and without bryophyte and lichen cover to quantify the insulating effect. We estimate an annual average cooling effect of the bryophyte and lichen cover of 2.7 K on topsoil temperature for the northern high latitudes under current climate. Locally, the cooling may reach up to 5.7 K. Moreover, we show that neglecting dynamic properties of the bryophyte and lichen cover by using a simple, empirical scheme only results in an average cooling of around 0.5 K. This suggests that bryophytes and lichens have a significant impact on soil temperature in high-latitude ecosystems and also that a process-based description of their thermal properties is necessary for a realistic representation of the cooling effect.

  20. Seasonal evaluation of the land surface sheme HTESSEL against remote sensing derived energy fluxes of the Transdanubian regions in Hungary

    NARCIS (Netherlands)

    Wipfler, E.L.; Metselaar, K.; Dam, van J.C.; Feddes, R.A.; Meijgaard, van E.; Ulft, van L.H.; Hurk, van den B.; Zwart, S.J.; Bastiaanssen, W.G.M.

    2011-01-01

    The skill of the land surface model HTESSEL is assessed to reproduce evaporation in response to land surface characteristics and atmospheric forcing, both being spatially variable. Evaporation estimates for the 2005 growing season are inferred from satellite observations of the Western part of

  1. Relation between seasonally detrended shortwave infrared reflectance data and land surface moisture in semi-arid Sahel

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard; Ceccato, Pietro; Proud, Simon Richard;

    2013-01-01

    In the Sudano-Sahelian areas of Africa droughts can have serious impacts on natural resources, and therefore land surface moisture is an important factor. Insufficient conventional sites for monitoring land surface moisture make the use of Earth Observation data for this purpose a key issue...

  2. Research on the Contribution of Urban Land Surface Moisture to the Alleviation Effect of Urban Land Surface Heat Based on Landsat 8 Data

    Directory of Open Access Journals (Sweden)

    Yu Zhang

    2015-08-01

    Full Text Available This paper presents a new assessment method for alleviating urban heat island (UHI effects by using an urban land surface moisture (ULSM index. With the aid of Landsat 8 OLI/TIRS data, the land surface temperature (LST was retrieved by a mono-window algorithm, and ULSM was extracted by tasselled cap transformation. Polynomial regression and buffer analysis were used to analyze the effects of ULSM on the LST, and the alleviation effect of ULSM was compared with three vegetation indices, GVI, SAVI, and FVC, by using the methods of grey relational analysis and Taylor skill calculation. The results indicate that when the ULSM value is greater than the value of an extreme point, the LST declines with the increasing ULSM value. Areas with a high ULSM value have an obvious reducing effect on the temperature of their surrounding areas within 150 m. Grey relational degrees and Taylor skill scores between ULSM and the LST are 0.8765 and 0.9378, respectively, which are higher than the results for the three vegetation indices GVI, SAVI, and FVC. The reducing effect of the ULSM index on environmental temperatures is significant, and ULSM can be considered to be a new and more effective index to estimate UHI alleviation effects for urban areas.

  3. Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France

    Directory of Open Access Journals (Sweden)

    N. Canal

    2014-05-01

    Full Text Available The interannual variability of cereal grain yield and permanent grassland dry matter yield is simulated over French sites by the Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs generic Land Surface Model (LSM. The two soil profile schemes available in the model are used to simulate the above-ground biomass (Bag of cereals and grasslands: a 2-layer force-restore (FR-2L bulk reservoir model and a multi-layer diffusion (DIF model. The DIF model is implemented with or without deep soil layers below the root-zone. The evaluation of the various root water uptake models is achieved by using the French agricultural statistics of Agreste over the 1994–2010 period at 45 cropland and 48 grassland sites, for a range of rooting depths. The number of sites where the simulated annual maximum Bag presents a significant correlation with the yield observations is used as a metric to benchmark the root water uptake models. Significant correlations (p value < 0.01 are found for up to 29% of the cereal sites and 77% of the grassland sites. It is found that modelling additional subroot zone base flow soil layers does not improve (and may even degrade the representation of the interannual variability of the vegetation above-ground biomass. These results are particularly robust for grasslands as calibrated simulations are able to represent the extreme 2003 and 2007 years corresponding to unfavourable and favourable fodder production, respectively.

  4. Linkages between Land Surface Phenology Metrics and Natural and Anthropogenic Events in Drylands (Invited)

    Science.gov (United States)

    de Beurs, K.; Brown, M. E.; Ahram, A.; Walker, J.; Henebry, G. M.

    2013-12-01

    Tracking vegetation dynamics across landscapes using remote sensing, or 'land surface phenology,' is a key mechanism that allows us to understand ecosystem changes. Land surface phenology models rely on vegetation information from remote sensing, such as the datasets derived from the Advanced Very High Resolution Radiometer (AVHRR), the newer MODIS sensors on Aqua and Terra, and sometimes the higher spatial resolution Landsat data. Vegetation index data can aid in the assessment of variables such as the start of season, growing season length and overall growing season productivity. In this talk we use Landsat, MODIS and AVHRR data and derive growing season metrics based on land surface phenology models that couple vegetation indices with satellite derived accumulated growing degreeday and evapotranspiration estimates. We calculate the timing and the height of the peak of the growing season and discuss the linkage of these land surface phenology metrics with natural and anthropogenic changes on the ground in dryland ecosystems. First we will discuss how the land surface phenology metrics link with annual and interannual price fluctuations in 229 markets distributed over Africa. Our results show that there is a significant correlation between the peak height of the growing season and price increases for markets in countries such as Nigeria, Somalia and Niger. We then demonstrate how land surface phenology metrics can improve models of post-conflict resolution in global drylands. We link the Uppsala Conflict Data Program's dataset of political, economic and social factors involved in civil war termination with an NDVI derived phenology metric and the Palmer Drought Severity Index (PDSI). An analysis of 89 individual conflicts in 42 dryland countries (totaling 892 individual country-years of data between 1982 and 2005) revealed that, even accounting for economic and political factors, countries that have higher NDVI growth following conflict have a lower risk of

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

    Science.gov (United States)

    Naha, Shaini; Thakur, Praveen K.; Aggarwal, S. P.

    2016-06-01

    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 using observed

  6. 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

  7. On the Comparison of the Global Surface Soil Moisture product and Land Surface Modeling

    Science.gov (United States)

    Delorme, B., Jr.; Ottlé, C.; Peylin, P.; Polcher, J.

    2016-12-01

    Thanks to its large spatio-temporal coverage, the new ESA CCI multi-instruments dataset offers a good opportunity to assess and improve land surface models parametrization. In this study, the ESA CCI surface soil moisture (SSM) combined product (v2.2) has been compared to the simulated top first layers of the ORCHIDEE LSM (the continental part of the IPSL earth system model), in order to evaluate its potential of improvements with data assimilation techniques. The ambition of the work was to develop a comprehensive comparison methodology by analyzing simultaneously the temporal and spatial structures of both datasets. We analyzed the SSM synoptic, seasonal, and inter-annual variations by decomposing the signals into fast and slow components. ORCHIDEE was shown to adequately reproduce the observed SSM dynamics in terms of temporal correlation. However, these correlation scores are supposed to be strongly influenced by SSM seasonal variability and the quality of the model input forcing. Autocorrelation and spectral analyses brought out disagreements in the temporal inertia of the upper soil moisture reservoirs. By linking our results to land cover maps, we found that ORCHIDEE is more dependent on rainfall events compared to the observations in regions with sparse vegetation cover. These diflerences might be due to a wrong partition of rainfall between soil evaporation, transpiration, runofl and drainage in ORCHIDEE. To refine this analysis, a single value decomposition (SVD) of the co-variability between rainfall provided by WFDEI and soil moisture was pursued over Central Europe and South Africa. It showed that spatio-temporal co-varying patterns between ORCHIDEE and rainfall and the ESA-CCI product and rainfall are in relatively good agreement. However, the leading SVD pattern, which exhibits a strong annual cycle and explains the same portion of covariance for both datasets, explains a much larger fraction of variance for ORCHIDEE than for the ESA-CCI product

  8. AWRA-G: A continental scale groundwater component linked to a land surface water balance model

    Science.gov (United States)

    Joehnk, Klaus; Crosbie, Russell; Peeters, Luk; Doble, Rebecca

    2013-04-01

    The Australian Water Resources Assessment (AWRA) system is a combination of models, data sources and analysis techniques that together will describe the water balance of Australia's landscapes, rivers and groundwater systems. It is a grid based water balance model that has lumped representation of the water balance of the soil, groundwater and surface water stores for each cell. The purpose of AWRA is to operationally provide up to date, credible, comprehensive, and accurate information about the history, present state and future trajectory of the water balance across Australia with sufficient spatial and temporal detail and enable water resources management for undertaking annual water resource assessments and national water accounts. AWRA is developed to link three major components: a landscape water balance model (AWRA-L), a river routing model (AWRA-R), and a groundwater component model (AWRA-G). These three component models combined are expected to be able to model the fluxes and stores of water throughout the landscape. The groundwater component (AWRA-G) addresses an improved representation of groundwater in the AWRA system to describe basic aquifer dynamics and groundwater-surface water processes. While most continental scale land surface models do not have the capacity to allow water to flow between cells and thus ignore this element of the water balance, AWRA-G does account for lateral flows. In general, AWRA-G provides estimates of groundwater fluxes that are not incorporated into either AWRA-L and its modifications to in-cell soil and groundwater processes, or AWRA-R. The processes integrated into AWRA-G thus are lateral groundwater flow between cells in regional and intermediate groundwater flow systems, groundwater discharge to the ocean, groundwater extraction and infiltration, river losses to groundwater, recharge from overbank flooding, and interactions between deep confined systems and surficial groundwater systems. Basis of AWRA-G is a good

  9. Performance of the JULES land surface model for UK Biogenic VOC emissions

    Science.gov (United States)

    Hayman, Garry; Comyn-Platt, Edward; Vieno, Massimo; Langford, Ben

    2017-04-01

    Emissions of biogenic non-methane volatile organic compounds (NMVOCs) are important for air quality and tropospheric composition. Through their contribution to the production of tropospheric ozone and secondary organic aerosol (SOA), biogenic VOCs indirectly contribute to climate forcing and climate feedbacks [1]. Biogenic VOCs encompass a wide range of compounds and are produced by plants for growth, development, reproduction, defence and communication [2]. There are both biological and physico-chemical controls on emissions [3]. Only a few of the many biogenic VOCs are of wider interest and only two or three (isoprene and the monoterpenes, α- and β-pinene) are represented in chemical transport models. We use the Joint UK Land Environment Simulator (JULES), the UK community land surface model, to estimate biogenic VOC emission fluxes. JULES is a process-based model that describes the water, energy and carbon balances and includes temperature, moisture and carbon stores [4, 5]. JULES currently provides emission fluxes of the 4 largest groups of biogenic VOCs: isoprene, terpenes, methanol and acetone. The JULES isoprene scheme uses gross primary productivity (GPP), leaf internal carbon and the leaf temperature as a proxy for the electron requirement for isoprene synthesis [6]. In this study, we compare JULES biogenic VOC emission estimates of isoprene and terepenes with (a) flux measurements made at selected sites in the UK and Europe and (b) gridded estimates for the UK from the EMEP/EMEP4UK atmospheric chemical transport model [7, 8], using site-specific or EMEP4UK driving meteorological data, respectively. We compare the UK-scale emission estimates with literature estimates. We generally find good agreement in the comparisons but the estimates are sensitive to the choice of the base or reference emission potentials. References (1) Unger, 2014: Geophys. Res. Lett., 41, 8563, doi:10.1002/2014GL061616; (2) Laothawornkitkul et al., 2009: New Phytol., 183, 27, doi

  10. Assimilation of gridded terrestrial water storage observations from GRACE into a land surface model

    Science.gov (United States)

    Girotto, Manuela; De Lannoy, Gabriëlle J. M.; Reichle, Rolf H.; Rodell, Matthew

    2016-05-01

    (SMAP). Finally, we demonstrate that the scaling parameters that are applied to the GRACE observations prior to assimilation should be consistent with the land surface model that is used within the assimilation system.

  11. Simulation of advanced ultrasound systems using Field II

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2004-01-01

    impulse responses is explained. A simulation example for a synthetic aperture spread spectrum flow systems is described. It is shown how the advanced coded excitation can be set up, and how the simulation can be parallelized to reduce the simulation time from 17 months to 391 hours using a 32 CPU Linux...

  12. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed......; shaded and sunlit canopy and background, respectively. Given data on vegetation structure and density, the model estimates the fractions of the four components as well as the directional composite temperature in the view of a sensor, given the illumination and viewing geometry. The modeling results show...

  13. Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

    Science.gov (United States)

    Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

    2017-04-01

    The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description o