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Sample records for correct non-precipitating weather

  1. The impact of reflectivity correction and conversion methods to improve precipitation estimation by weather radar for an extreme low-land Mesoscale Convective System

    Science.gov (United States)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2014-05-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands. For most of the country this led to over 15 hours of near-continuous precipitation, which resulted in total event accumulations exceeding 150 mm in the eastern part of the Netherlands. Such accumulations belong to the largest sums ever recorded in this country and gave rise to local flooding. Measuring precipitation by weather radar within such mesoscale convective systems is known to be a challenge, since measurements are affected by multiple sources of error. For the current event the operational weather radar rainfall product only estimated about 30% of the actual amount of precipitation as measured by rain gauges. In the current presentation we will try to identify what gave rise to such large underestimations. In general weather radar measurement errors can be subdivided into two different groups: 1) errors affecting the volumetric reflectivity measurements taken, and 2) errors related to the conversion of reflectivity values in rainfall intensity and attenuation estimates. To correct for the first group of errors, the quality of the weather radar reflectivity data was improved by successively correcting for 1) clutter and anomalous propagation, 2) radar calibration, 3) wet radome attenuation, 4) signal attenuation and 5) the vertical profile of reflectivity. Such consistent corrections are generally not performed by operational meteorological services. Results show a large improvement in the quality of the precipitation data, however still only ~65% of the actual observed accumulations was estimated. To further improve the quality of the precipitation estimates, the second group of errors are corrected for by making use of disdrometer measurements taken in close vicinity of the radar. Based on these data the parameters of a normalized drop size distribution are estimated for the total event as well as for each precipitation type separately (convective

  2. The impact of reflectivity correction and accounting for raindrop size distribution variability to improve precipitation estimation by weather radar for an extreme low-land mesoscale convective system

    Science.gov (United States)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2014-11-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z - R) and radar reflectivity-specific attenuation (Z - k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the

  3. A new precipitation and drought climatology based on weather patterns.

    Science.gov (United States)

    Richardson, Douglas; Fowler, Hayley J; Kilsby, Christopher G; Neal, Robert

    2018-02-01

    Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterize the broad-scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI-based drought months. The new weather-pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation-based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification-based analyses in the UK.

  4. Improved estimation of heavy rainfall by weather radar after reflectivity correction and accounting for raindrop size distribution variability

    Science.gov (United States)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z-R) and radar reflectivity-specific attenuation (Z-k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the

  5. Errors and Correction of Precipitation Measurements in China

    Institute of Scientific and Technical Information of China (English)

    REN Zhihua; LI Mingqin

    2007-01-01

    In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the "horizontal precipitation gauge" was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper.A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.

  6. Bias correction of satellite precipitation products for flood forecasting application at the Upper Mahanadi River Basin in Eastern India

    Science.gov (United States)

    Beria, H.; Nanda, T., Sr.; Chatterjee, C.

    2015-12-01

    High resolution satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM), Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF), etc., offer a promising alternative to flood forecasting in data scarce regions. At the current state-of-art, these products cannot be used in the raw form for flood forecasting, even at smaller lead times. In the current study, these precipitation products are bias corrected using statistical techniques, such as additive and multiplicative bias corrections, and wavelet multi-resolution analysis (MRA) with India Meteorological Department (IMD) gridded precipitation product,obtained from gauge-based rainfall estimates. Neural network based rainfall-runoff modeling using these bias corrected products provide encouraging results for flood forecasting upto 48 hours lead time. We will present various statistical and graphical interpretations of catchment response to high rainfall events using both the raw and bias corrected precipitation products at different lead times.

  7. Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data

    Science.gov (United States)

    Moore, Angelyn W.; Webb, Frank H.; Fishbein, Evan F.; Fielding, Eric J.; Owen, Susan E.; Granger, Stephanie L.; Bjoerndahl, Fredrik; Loefgren, Johan; Fang, Peng; Means, James D.; hide

    2013-01-01

    Atmospheric errors due to the troposphere are a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging. This software generates tropospheric delay maps that can be used to correct atmospheric artifacts in InSAR data. The software automatically acquires all needed GPS (Global Positioning System), weather, and Digital Elevation Map data, and generates a tropospheric correction map using a novel algorithm for combining GPS and weather information while accounting for terrain. Existing JPL software was prototypical in nature, required a MATLAB license, required additional steps to acquire and ingest needed GPS and weather data, and did not account for topography in interpolation. Previous software did not achieve a level of automation suitable for integration in a Web portal. This software overcomes these issues. GPS estimates of tropospheric delay are a source of corrections that can be used to form correction maps to be applied to InSAR data, but the spacing of GPS stations is insufficient to remove short-wavelength tropospheric artifacts. This software combines interpolated GPS delay with weather model precipitable water vapor (PWV) and a digital elevation model to account for terrain, increasing the spatial resolution of the tropospheric correction maps and thus removing short wavelength tropospheric artifacts to a greater extent. It will be integrated into a Web portal request system, allowing use in a future L-band SAR Earth radar mission data system. This will be a significant contribution to its technology readiness, building on existing investments in in situ space geodetic networks, and improving timeliness, quality, and science value of the collected data

  8. It Started in a GE Freezer: Basic Precipitation Research Triggers the Business of Weather Modification

    Science.gov (United States)

    Harper, K.

    2015-12-01

    At the end of World War II, Nobel Prize-winning chemist Irving Langmuir and his team at the General Electric Research Laboratory in Schenectady, New York, were doing advanced research on cloaking smokes and aircraft icing for the US military. Trying to determine why some clouds precipitated while others did not, Langmuir concluded that non-precipitating clouds were lacking "ice nuclei" that would gather up cloud droplets until they became large enough to fall out of the cloud. If they could find an artificial substitute, it would be possible to modify clouds and the weather. Dry ice particles did the trick, military funding followed, and cloud busting commenced. But a handful of entrepreneurial meteorologists saw a different purpose: enhancing precipitation and preventing hail damage. The commercialization of weather modification was underway, with cloud seeding enhancing rainfall east of the Cascades, in the Desert Southwest, and even in the watersheds serving New York City. Hail busting took off in the Dakotas, and snowpack enhancement got a boost in Montana. Basic cloud physics research very quickly became commercial weather modification, fulfilling a postwar desire to use science and technology to control nature and creating an opening for meteorologists to provide a variety of specialized services to businesses whose profits depend on the weather.

  9. GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters

    Science.gov (United States)

    Moore, Angelyn W.; Gutman, Seth I.; Holub, Kirk; Bock, Yehuda; Danielson, David; Laber, Jayme; Small, Ivory

    2013-01-01

    Global Positioning System (GPS) meteorology provides enhanced density, low-latency (30-min resolution), integrated precipitable water (IPW) estimates to NOAA NWS (National Oceanic and Atmospheric Adminis tration Nat ional Weather Service) Weather Forecast Offices (WFOs) to provide improved model and satellite data verification capability and more accurate forecasts of extreme weather such as flooding. An early activity of this project was to increase the number of stations contributing to the NOAA Earth System Research Laboratory (ESRL) GPS meteorology observing network in Southern California by about 27 stations. Following this, the Los Angeles/Oxnard and San Diego WFOs began using the enhanced GPS-based IPW measurements provided by ESRL in the 2012 and 2013 monsoon seasons. Forecasters found GPS IPW to be an effective tool in evaluating model performance, and in monitoring monsoon development between weather model runs for improved flood forecasting. GPS stations are multi-purpose, and routine processing for position solutions also yields estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV (precipitable water vapor) using in situ pressure and temperature measurements, the basis for GPS meteorology. NOAA ESRL has implemented this concept with a nationwide distribution of more than 300 "GPSMet" stations providing IPW estimates at sub-hourly resolution currently used in operational weather models in the U.S.

  10. Evaluation of NWP-based Satellite Precipitation Error Correction with Near-Real-Time Model Products and Flood-inducing Storms

    Science.gov (United States)

    Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.

    2017-12-01

    Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.

  11. Rain cell-based identification of the vertical profile of reflectivity as observed by weather radar and its use for precipitation uncertainty estimation

    Science.gov (United States)

    Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Uijlenhoet, R.

    2012-04-01

    The wide scale implementation of weather radar systems over the last couple of decades has increased our understanding concerning spatio-temporal precipitation dynamics. However, the quantitative estimation of precipitation by these devices is affected by many sources of error. A very dominant source of error results from vertical variations in the hydrometeor size distribution known as the vertical profile of reflectivity (VPR). Since the height of the measurement as well as the beam volume increases with distance from the radar, for stratiform precipitation this results in a serious underestimation (overestimation) of the surface reflectivity while sampling within the snow (bright band) region. This research presents a precipitation cell-based implementation to correct volumetric weather radar measurements for VPR effects. Using the properties of a flipping carpenter square, a contour-based identification technique was developed, which is able to identify and track precipitation cells in real time, distinguishing between convective, stratiform and undefined precipitation. For the latter two types of systems, for each individual cell, a physically plausible vertical profile of reflectivity is estimated using a Monte Carlo optimization method. Since it can be expected that the VPR will vary within a given precipitation cell, a method was developed to take the uncertainty of the VPR estimate into account. As a result, we are able to estimate the amount of precipitation uncertainty as observed by weather radar due to VPR for a given precipitation type and storm cell. We demonstrate the possibilities of this technique for a number of winter precipitation systems observed within the Belgian Ardennes. For these systems, in general, the precipitation uncertainty estimate due to vertical reflectivity profile variations varies between 10-40%.

  12. Quantitative analysis of X-band weather radar attenuation correction accuracy

    NARCIS (Netherlands)

    Berne, A.D.; Uijlenhoet, R.

    2006-01-01

    At short wavelengths, especially C-, X-, and K-band, weather radar signals arc attenuated by the precipitation along their paths. This constitutes a major source of error for radar rainfall estimation, in particular for intense precipitation. A recently developed stochastic simulator of range

  13. Recent advances in precipitation-bias correction and application

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Significant progresses have been made in recent years in precipitation data analyses at regional to global scales. This paper re-views and synthesizes recent advances in precipitation-bias corrections and applications in many countries and over the cold re-gions. The main objective of this review is to identify and examine gaps in regional and national precipitation-error analyses. This paper also discusses and recommends future research needs and directions. More effort and coordination are necessary in the determinations of precipitation biases on large regions across national borders. It is important to emphasize that bias cor-rections of precipitation measurements affect both water budget and energy balance calculations, particularly over the cold regions.

  14. Synthetic weather generator SYNTOR: Implementing improvements in precipitation generation

    Science.gov (United States)

    Infrequent high precipitation events produce a disproportionally large amount of the annual surface runoff, soil erosion, nutrient movement, and watershed sediment yield. Numerical simulation of these watershed processes often lack sufficiently long weather data records to adequately capture the sto...

  15. Future weather types and their influence on mean and extreme climate indices for precipitation and temperature in Central Europe

    Directory of Open Access Journals (Sweden)

    Ulf Riediger

    2014-09-01

    occurrence of warm south-westerlies and a decrease in cold easterlies. Thereby, an increase of extensive areal rainfall events is simulated for specific weather types. Otherwise, warmer and drier summers are projected by the RCM ensemble. Here, a few weather patterns are relevant for very hot conditions with the total number of very hot days where the mean daily temperature greater than 25 °C increases. Thereby, anticyclonic weather patterns are most relevant for non precipitation events and particulary, the number of days with anticyclonic westerlies is expected to double in the future.

  16. Identification and uncertainty estimation of vertical reflectivity profiles using a Lagrangian approach to support quantitative precipitation measurements by weather radar

    Science.gov (United States)

    Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Delrieu, G.; Uijlenhoet, R.

    2013-09-01

    This paper presents a novel approach to estimate the vertical profile of reflectivity (VPR) from volumetric weather radar data using both a traditional Eulerian as well as a newly proposed Lagrangian implementation. For this latter implementation, the recently developed Rotational Carpenter Square Cluster Algorithm (RoCaSCA) is used to delineate precipitation regions at different reflectivity levels. A piecewise linear VPR is estimated for either stratiform or neither stratiform/convective precipitation. As a second aspect of this paper, a novel approach is presented which is able to account for the impact of VPR uncertainty on the estimated radar rainfall variability. Results show that implementation of the VPR identification and correction procedure has a positive impact on quantitative precipitation estimates from radar. Unfortunately, visibility problems severely limit the impact of the Lagrangian implementation beyond distances of 100 km. However, by combining this procedure with the global Eulerian VPR estimation procedure for a given rainfall type (stratiform and neither stratiform/convective), the quality of the quantitative precipitation estimates increases up to a distance of 150 km. Analyses of the impact of VPR uncertainty shows that this aspect accounts for a large fraction of the differences between weather radar rainfall estimates and rain gauge measurements.

  17. Weather Type classification over Chile; patterns, trends, and impact in precipitation and temperature

    Science.gov (United States)

    Frias, T.; Trigo, R. M.; Garreaud, R.

    2009-04-01

    The Andes Cordillera induces considerable disturbances on the structure and evolution of the pressure systems that influences South America. Different weather types for southern South America are derived from the daily maps of geopotential height at 850hPa corresponding to a 42 year period, spanning from 1958 to 2000. Here we have used the ECWMF ERA-40 reanalysis dataset to construct an automated version of the Lamb Weather type (WTs) classification scheme (Jones et al., 1993) developed for the UK. We have identified 8 basic WTs (Cyclonic, Anticyclonic and 6 main directional types) following a similar methodology to that previously adopted by Trigo and DaCamara, 2000 (for Iberia). This classification was applied to two regions of study (CLnorth and CLsouth) which differ 20° in latitude, so that the vast Chile territory could be covered. Then were assessed the impact of the occurrence of this weather types in precipitation in Chile, as well as in the distribution of precipitation and temperature fields (reanalysis data) in southern half of South America. The results allow to conclude that the precipitation in central region of Chile is largely linked with the class occurrence (concerning CLnorth) of cyclonic circulation and of West quadrant (SW, W and NW), despite of it's relatively low frequency. In CLsouth, for its part, it is verified that the most frequent circulation is from the west quadrant, although the associated amount of rainfall is lower than in CLnorth. There was also a general decrease of precipitation at local weather stations chosen in the considered period of study, particularly in austral winter.

  18. Bias Correction of Satellite Precipitation Products (SPPs) using a User-friendly Tool: A Step in Enhancing Technical Capacity

    Science.gov (United States)

    Rushi, B. R.; Ellenburg, W. L.; Adams, E. C.; Flores, A.; Limaye, A. S.; Valdés-Pineda, R.; Roy, T.; Valdés, J. B.; Mithieu, F.; Omondi, S.

    2017-12-01

    SERVIR, a joint NASA-USAID initiative, works to build capacity in Earth observation technologies in developing countries for improved environmental decision making in the arena of: weather and climate, water and disasters, food security and land use/land cover. SERVIR partners with leading regional organizations in Eastern and Southern Africa, Hindu Kush-Himalaya, Mekong region, and West Africa to achieve its objectives. SERVIR develops hydrological applications to address specific needs articulated by key stakeholders and daily rainfall estimates are a vital input for these applications. Satellite-derived rainfall is subjected to systemic biases which need to be corrected before it can be used for any hydrologic application such as real-time or seasonal forecasting. SERVIR and the SWAAT team at the University of Arizona, have co-developed an open-source and user friendly tool of rainfall bias correction approaches for SPPs. Bias correction tools were developed based on Linear Scaling and Quantile Mapping techniques. A set of SPPs, such as PERSIANN-CCS, TMPA-RT, and CMORPH, are bias corrected using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data which incorporates ground based precipitation observations. This bias correction tools also contains a component, which is included to improve monthly mean of CHIRPS using precipitation products of the Global Surface Summary of the Day (GSOD) database developed by the National Climatic Data Center (NCDC). This tool takes input from command-line which makes it user-friendly and applicable in any operating platform without prior programming skills. This presentation will focus on this bias-correction tool for SPPs, including application scenarios.

  19. Detection of Weather Radar Clutter

    DEFF Research Database (Denmark)

    Bøvith, Thomas

    2008-01-01

    classification and use a range of different techniques and input data. The first method uses external information from multispectral satellite images to detect clutter. The information in the visual, near-infrared, and infrared parts of the spectrum can be used to distinguish between cloud and cloud-free areas......Weather radars provide valuable information on precipitation in the atmosphere but due to the way radars work, not only precipitation is observed by the weather radar. Weather radar clutter, echoes from non-precipitating targets, occur frequently in the data, resulting in lowered data quality....... Especially in the application of weather radar data in quantitative precipitation estimation and forecasting a high data quality is important. Clutter detection is one of the key components in achieving this goal. This thesis presents three methods for detection of clutter. The methods use supervised...

  20. Quantifying chemical weathering rates along a precipitation gradient on Basse-Terre Island, French Guadeloupe: new insight from U-series isotopes in weathering rinds

    Science.gov (United States)

    Engel, Jacqueline M.; May, Linda; Sak, Peter B.; Gaillardet, Jerome; Ren, Minghua; Engle, Mark A.; Brantley, Susan L.

    2016-01-01

    Inside soil and saprolite, rock fragments can form weathering clasts (alteration rinds surrounding an unweathered core) and these weathering rinds provide an excellent field system for investigating the initiation of weathering and long term weathering rates. Recently, uranium-series (U-series) disequilibria have shown great potential for determining rind formation rates and quantifying factors controlling weathering advance rates in weathering rinds. To further investigate whether the U-series isotope technique can document differences in long term weathering rates as a function of precipitation, we conducted a new weathering rind study on tropical volcanic Basse-Terre Island in the Lesser Antilles Archipelago. In this study, for the first time we characterized weathering reactions and quantified weathering advance rates in multiple weathering rinds across a steep precipitation gradient. Electron microprobe (EMP) point measurements, bulk major element contents, and U-series isotope compositions were determined in two weathering clasts from the Deshaies watershed with mean annual precipitation (MAP) = 1800 mm and temperature (MAT) = 23 °C. On these clasts, five core-rind transects were measured for locations with different curvature (high, medium, and low) of the rind-core boundary. Results reveal that during rind formation the fraction of elemental loss decreases in the order: Ca ≈ Na > K ≈ Mg > Si ≈ Al > Zr ≈ Ti ≈ Fe. Such observations are consistent with the sequence of reactions after the initiation of weathering: specifically, glass matrix and primary minerals (plagioclase, pyroxene) weather to produce Fe oxyhydroxides, gibbsite and minor kaolinite.Uranium shows addition profiles in the rind due to the infiltration of U-containing soil pore water into the rind as dissolved U phases. U is then incorporated into the rind as Fe-Al oxides precipitate. Such processes lead to significant U-series isotope disequilibria in the rinds

  1. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  2. Combining weather radar nowcasts and numerical weather prediction models to estimate short-term quantitative precipitation and uncertainty

    DEFF Research Database (Denmark)

    Jensen, David Getreuer

    The topic of this Ph.D. thesis is short term forecasting of precipitation for up to 6 hours called nowcasts. The focus is on improving the precision of deterministic nowcasts, assimilation of radar extrapolation model (REM) data into Danish Meteorological Institutes (DMI) HIRLAM numerical weather...

  3. Model Consistent Pseudo-Observations of Precipitation and Their Use for Bias Correcting Regional Climate Models

    Directory of Open Access Journals (Sweden)

    Peter Berg

    2015-01-01

    Full Text Available Lack of suitable observational data makes bias correction of high space and time resolution regional climate models (RCM problematic. We present a method to construct pseudo-observational precipitation data bymerging a large scale constrained RCMreanalysis downscaling simulation with coarse time and space resolution observations. The large scale constraint synchronizes the inner domain solution to the driving reanalysis model, such that the simulated weather is similar to observations on a monthly time scale. Monthly biases for each single month are corrected to the corresponding month of the observational data, and applied to the finer temporal resolution of the RCM. A low-pass filter is applied to the correction factors to retain the small spatial scale information of the RCM. The method is applied to a 12.5 km RCM simulation and proven successful in producing a reliable pseudo-observational data set. Furthermore, the constructed data set is applied as reference in a quantile mapping bias correction, and is proven skillful in retaining small scale information of the RCM, while still correcting the large scale spatial bias. The proposed method allows bias correction of high resolution model simulations without changing the fine scale spatial features, i.e., retaining the very information required by many impact models.

  4. Effect of precipitation bias correction on water budget calculation in Upper Yellow River, China

    International Nuclear Information System (INIS)

    Ye Baisheng; Yang Daqing; Ma Lijuan

    2012-01-01

    This study quantifies the effect of precipitation bias corrections on basin water balance calculations for the Yellow River Source region (YRS). We analyse long-term (1959–2001) monthly and yearly data of precipitation, runoff, and ERA-40 water budget variables and define a water balance regime. Basin precipitation, evapotranspiration and runoff are high in summer and low in winter. The basin water storage change is positive in summer and negative in winter. Monthly precipitation bias corrections, ranging from 2 to 16 mm, do not significantly alter the pattern of the seasonal water budget. The annual bias correction of precipitation is about 98 mm (19%); this increase leads to the same amount of evapotranspiration increase, since yearly runoff remains unchanged and the long-term storage change is assumed to be zero. Annual runoff and evapotranspiration coefficients change, due to precipitation bias corrections, from 0.33 and 0.67 to 0.28 and 0.72, respectively. These changes will impact the parameterization and calibration of land surface and hydrological models. The bias corrections of precipitation data also improve the relationship between annual precipitation and runoff. (letter)

  5. Aerosols and their Impact on Radiation, Clouds, Precipitation & Severe Weather Events

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zhanqing; Rosenfeld, Daniel; Fan, Jiwen

    2017-09-22

    Aerosols, the tiny particles suspended in the atmosphere, have been in the forefront of environmental and climate change sciences as the primary atmospheric pollutant and external force affecting Earth’s weather and climate. There are two dominant mechanisms by which aerosols affect weather and climate: aerosol-radiation interactions (ARI) and aerosol-cloud interactions (ACI). ARI arises from aerosol scattering and absorption, which alters the radiation budgets of the atmosphere and surface, while ACI is rooted to the fact that aerosols serve as cloud condensation nuclei and ice nuclei. Both ARI and ACI are coupled with atmospheric dynamics to produce a chain of complex interactions with a large range of meteorological variables that influence both weather and climate. Elaborated here are the impacts of aerosols on the radiation budget, clouds (microphysics, structure, and lifetime), precipitation, and severe weather events (lightning, thunderstorms, hail, and tornados). Depending on environmental variables and aerosol properties, the effects can be both positive and negative, posing the largest uncertainties in the external forcing of the climate system. This has considerably hindered our ability in projecting future climate changes and in doing accurate numerical weather predictions.

  6. The Contribution of Extreme Precipitation to the Total Precipitation in China

    Institute of Scientific and Technical Information of China (English)

    SUN Jian-Qi

    2012-01-01

    Using daily precipitation data from weather stations in China, the variations in the contribution of extreme precipitation to the total precipitation are analyzed. It is found that extreme precipitation accounts for approximately one third of the total precipitation based on the overall mean for China. Over the past half century, extreme precipitation has played a dominant role in the year-to-year variability of the total precipitation. On the decadal time scale, the extreme precipitation makes different contributions to the wetting and drying regions of China. The wetting trends of particular regions are mainly attributed to increases in extreme precipitation; in contrast, the drying trends of other regions are mainly due to decreases in non-extreme precipitation.

  7. GLUE Based Uncertainty Estimation of Urban Drainage Modeling Using Weather Radar Precipitation Estimates

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2011-01-01

    Distributed weather radar precipitation measurements are used as rainfall input for an urban drainage model, to simulate the runoff from a small catchment of Denmark. It is demonstrated how the Generalized Likelihood Uncertainty Estimation (GLUE) methodology can be implemented and used to estimate...

  8. The influence of weather conditions on road safety : an assessment of the effect of precipitation and temperature.

    NARCIS (Netherlands)

    Bijleveld, F.D. & Churchill, T.

    2009-01-01

    The influence of changes in extreme weather conditions is often identified as a cause of fluctuations in road safety and the resulting numbers of crashes and casualties. This report focuses on an analysis of the aggregate, accumulated effect of weather conditions (precipitation and temperature) on

  9. Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system

    Science.gov (United States)

    Bera, Maitreyee; Ortel, Terry W.

    2018-01-12

    The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.

  10. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Science.gov (United States)

    Zhou, C.; Zhang, X.; Gong, S.; Wang, Y.; Xue, M.

    2016-01-01

    A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under a China Meteorological Administration (CMA) chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme - WDM6) and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  11. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Directory of Open Access Journals (Sweden)

    C. Zhou

    2016-01-01

    Full Text Available A comprehensive aerosol–cloud–precipitation interaction (ACI scheme has been developed under a China Meteorological Administration (CMA chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme – WDM6 and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  12. Bias correction of daily satellite precipitation data using genetic algorithm

    Science.gov (United States)

    Pratama, A. W.; Buono, A.; Hidayat, R.; Harsa, H.

    2018-05-01

    Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) was producted by blending Satellite-only Climate Hazards Group InfraRed Precipitation (CHIRP) with Stasion observations data. The blending process was aimed to reduce bias of CHIRP. However, Biases of CHIRPS on statistical moment and quantil values were high during wet season over Java Island. This paper presented a bias correction scheme to adjust statistical moment of CHIRP using observation precipitation data. The scheme combined Genetic Algorithm and Nonlinear Power Transformation, the results was evaluated based on different season and different elevation level. The experiment results revealed that the scheme robustly reduced bias on variance around 100% reduction and leaded to reduction of first, and second quantile biases. However, bias on third quantile only reduced during dry months. Based on different level of elevation, the performance of bias correction process is only significantly different on skewness indicators.

  13. Combining C- and X-band Weather Radars for Improving Precipitation Estimates over Urban Areas

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk

    of future system state. Accurate and reliable weather radar measurements are, therefore, important for future developments and achievements within urban drainage. This PhD study investigates two types of weather radars. Both systems are in operational use in Denmark today. A network of meteorological C...... individually and owned by local water utility companies. Although the two radar systems use similar working principles, the systems have significant differences regarding technology, temporal resolution, spatial resolution, range and scanning strategy. The focus of the research was to combine the precipitation...

  14. New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

    Science.gov (United States)

    Cane, D.; Milelli, M.

    2009-09-01

    The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

  15. On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes

    Science.gov (United States)

    Stisen, S.; Højberg, A. L.; Troldborg, L.; Refsgaard, J. C.; Christensen, B. S. B.; Olsen, M.; Henriksen, H. J.

    2012-11-01

    Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM) and the time-space variable (TSV) correction, resulted in different winter precipitation rates for the period 1990-2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model), revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests). We conclude that TSV

  16. On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes

    Directory of Open Access Journals (Sweden)

    S. Stisen

    2012-11-01

    Full Text Available Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM and the time–space variable (TSV correction, resulted in different winter precipitation rates for the period 1990–2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model, revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests

  17. Effects of Atmospheric Refraction on an Airborne Weather Radar Detection and Correction Method

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2015-01-01

    Full Text Available This study investigates the effect of atmospheric refraction, affected by temperature, atmospheric pressure, and humidity, on airborne weather radar beam paths. Using three types of typical atmospheric background sounding data, we established a simulation model for an actual transmission path and a fitted correction path of an airborne weather radar beam during airplane take-offs and landings based on initial flight parameters and X-band airborne phased-array weather radar parameters. Errors in an ideal electromagnetic beam propagation path are much greater than those of a fitted path when atmospheric refraction is not considered. The rates of change in the atmospheric refraction index differ with weather conditions and the radar detection angles differ during airplane take-off and landing. Therefore, the airborne radar detection path must be revised in real time according to the specific sounding data and flight parameters. However, an error analysis indicates that a direct linear-fitting method produces significant errors in a negatively refractive atmosphere; a piecewise-fitting method can be adopted to revise the paths according to the actual atmospheric structure. This study provides researchers and practitioners in the aeronautics and astronautics field with updated information regarding the effect of atmospheric refraction on airborne weather radar detection and correction methods.

  18. Evaluation of radar-derived precipitation estimates using runoff simulation : report for the NFR Energy Norway funded project 'Utilisation of weather radar data in atmospheric and hydrological models'

    Energy Technology Data Exchange (ETDEWEB)

    Abdella, Yisak; Engeland, Kolbjoern; Lepioufle, Jean-Marie

    2012-11-01

    This report presents the results from the project called 'Utilisation of weather radar data in atmospheric and hydrological models' funded by NFR and Energy Norway. Three precipitation products (radar-derived, interpolated and combination of the two) were generated as input for hydrological models. All the three products were evaluated by comparing the simulated and observed runoff at catchments. In order to expose any bias in the precipitation inputs, no precipitation correction factors were applied. Three criteria were used to measure the performance: Nash, correlation coefficient, and bias. The results shows that the simulations with the combined precipitation input give the best performance. We also see that the radar-derived precipitation estimates give reasonable runoff simulation even without a region specific parameters for the Z-R relationship. All the three products resulted in an underestimation of the estimated runoff, revealing a systematic bias in measurements (e.g. catch deficit, orographic effects, Z-R relationships) that can be improved. There is an important potential of using radar-derived precipitation for simulation of runoff, especially in catchments without precipitation gauges inside.(Author)

  19. Can the variability in precipitation simulations across GCMs be reduced through sensible bias correction?

    Science.gov (United States)

    Nguyen, Ha; Mehrotra, Rajeshwar; Sharma, Ashish

    2017-11-01

    This work investigates the performance of four bias correction alternatives for representing persistence characteristics of precipitation across 37 General Circulation Models (GCMs) from the CMIP5 data archive. The first three correction approaches are the Simple Monthly Bias Correction (SMBC), Equidistance Quantile Mapping (EQM), and Nested Bias Correction (NBC), all of which operate in the time domain, with a focus on representing distributional and moment attributes in the observed precipitation record. The fourth approach corrects for the biases in high- and low-frequency variability or persistence of the GCM time series in the frequency domain and is named as Frequency-based Bias Correction (FBC). The Climatic Research Unit (CRU) gridded precipitation data covering the global land surface is used as a reference dataset. The assessment focusses on current and future means, variability, and drought-related characteristics at different temporal and spatial scales. For the current climate, all bias correction approaches perform reasonably well at the global scale by reproducing the observed precipitation statistics. For the future climate, focus is drawn on the agreement of the attributes across the GCMs considered. The inter-model difference/spread of each attribute across the GCMs is used as a measure of this agreement. Our results indicate that out of the four bias correction approaches used, FBC provides the lowest inter-model spreads, specifically for persistence attributes, over most regions/ parts over the global land surface. This has significant implications for most hydrological studies where the effect of low-frequency variability is of considerable importance.

  20. Multisite bias correction of precipitation data from regional climate models

    Czech Academy of Sciences Publication Activity Database

    Hnilica, Jan; Hanel, M.; Puš, V.

    2017-01-01

    Roč. 37, č. 6 (2017), s. 2934-2946 ISSN 0899-8418 R&D Projects: GA ČR GA16-05665S Grant - others:Grantová agentura ČR - GA ČR(CZ) 16-16549S Institutional support: RVO:67985874 Keywords : bias correction * regional climate model * correlation * covariance * multivariate data * multisite correction * principal components * precipitation Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Climatic research Impact factor: 3.760, year: 2016

  1. Neural network based daily precipitation generator (NNGEN-P)

    Energy Technology Data Exchange (ETDEWEB)

    Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Paris (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Penalba, Olga [University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)

    2007-02-15

    Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation. (orig.)

  2. ASSESSMENT OF SATELLITE PRECIPITATION PRODUCTS IN THE PHILIPPINE ARCHIPELAGO

    Directory of Open Access Journals (Sweden)

    M. D. Ramos

    2016-06-01

    Full Text Available Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1 the Tropical Rainfall Measuring Mission (TRMM, (2 the CPC Morphing technique (CMORPH of NOAA and (3 the Global Satellite Mapping of Precipitation (GSMAP and (4 Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN. Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE and Root Mean Square Error (RMSE. In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

  3. Assessment of Satellite Precipitation Products in the Philippine Archipelago

    Science.gov (United States)

    Ramos, M. D.; Tendencia, E.; Espana, K.; Sabido, J.; Bagtasa, G.

    2016-06-01

    Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1) the Tropical Rainfall Measuring Mission (TRMM), (2) the CPC Morphing technique (CMORPH) of NOAA and (3) the Global Satellite Mapping of Precipitation (GSMAP) and (4) Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN). Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC) for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN) values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

  4. Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction

    Directory of Open Access Journals (Sweden)

    Nam Do Hoai

    2011-01-01

    Full Text Available Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron (MLP neural network. The MLP architecture was optimized by considering physical bases that determine the circulation of atmospheric variables. Downscaled precipitation was then used as inputs to the super tank model (runoff model for flood prediction. The case study was conducted for the Thu Bon River Basin, located in Central Vietnam. Study results showed that the precipitation predicted by MLP outperformed that directly obtained from model outputs or downscaled using multiple linear regression. Consequently, flood forecast based on the downscaled precipitation was very encouraging. It has demonstrated as a robust technology, simple to implement, reliable, and universal application for flood prediction through the combination of downscaling model and super tank model.

  5. A Numerical Method to Generate High Temporal Resolution Precipitation Time Series by Combining Weather Radar Measurements with a Nowcast Model

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2014-01-01

    The topic of this paper is temporal interpolation of precipitation observed by weather radars. Precipitation measurements with high spatial and temporal resolution are, in general, desired for urban drainage applications. An advection-based interpolation method is developed which uses methods...

  6. Applying volumetric weather radar data for rainfall runoff modeling: The importance of error correction.

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.; Delobbe, L.; Weerts, A.; Reggiani, P.

    2009-04-01

    In the current study half a year of volumetric radar data for the period October 1, 2002 until March 31, 2003 is being analyzed which was sampled at 5 minutes intervals by C-band Doppler radar situated at an elevation of 600 m in the southern Ardennes region, Belgium. During this winter half year most of the rainfall has a stratiform character. Though radar and raingauge will never sample the same amount of rainfall due to differences in sampling strategies, for these stratiform situations differences between both measuring devices become even larger due to the occurrence of a bright band (the point where ice particles start to melt intensifying the radar reflectivity measurement). For these circumstances the radar overestimates the amount of precipitation and because in the Ardennes bright bands occur within 1000 meter from the surface, it's detrimental effects on the performance of the radar can already be observed at relatively close range (e.g. within 50 km). Although the radar is situated at one of the highest points in the region, very close to the radar clutter is a serious problem. As a result both nearby and farther away, using uncorrected radar results in serious errors when estimating the amount of precipitation. This study shows the effect of carefully correcting for these radar errors using volumetric radar data, taking into account the vertical reflectivity profile of the atmosphere, the effects of attenuation and trying to limit the amount of clutter. After applying these correction algorithms, the overall differences between radar and raingauge are much smaller which emphasizes the importance of carefully correcting radar rainfall measurements. The next step is to assess the effect of using uncorrected and corrected radar measurements on rainfall-runoff modeling. The 1597 km2 Ourthe catchment lies within 60 km of the radar. Using a lumped hydrological model serious improvement in simulating observed discharges is found when using corrected radar

  7. A study of the relationship between cloud-to-ground lightning and precipitation in the convective weather system in China

    Directory of Open Access Journals (Sweden)

    Y. Zhou

    Full Text Available In this paper, the correlation between cloud-to-ground (CG lightning and precipitation has been studied by making use of the data from weather radar, meteorological soundings, and a lightning location system that includes three direction finders about 40 km apart from each other in the Pingliang area of east Gansu province in P. R. China. We have studied the convective systems that developed during two cold front processes passing over the observation area, and found that the CG lightning can be an important factor in the precipitation estimation. The regression equation between the average precipitation intensity (R and the number of CG lightning flashes (L in the main precipitation period is R = 1.69 ln (L - 0.27, and the correlation coefficient r is 0.86. The CG lightning flash rate can be used as an indicator of the formation and development of the convective weather system. Another more exhaustive precipitation estimation method has been developed by analyzing the temporal and spatial distributions of the precipitation relative to the location of the CG lightning flashes. Precipitation calculated from the CG lightning flashes is very useful, especially in regions with inadequate radar cover.

    Key words. Meteorology and atmospheric dynamics (atmospheric electricity; lightning; precipitation

  8. Copula-based assimilation of radar and gauge information to derive bias-corrected precipitation fields

    Directory of Open Access Journals (Sweden)

    S. Vogl

    2012-07-01

    Full Text Available This study addresses the problem of combining radar information and gauge measurements. Gauge measurements are the best available source of absolute rainfall intensity albeit their spatial availability is limited. Precipitation information obtained by radar mimics well the spatial patterns but is biased for their absolute values.

    In this study copula models are used to describe the dependence structure between gauge observations and rainfall derived from radar reflectivity at the corresponding grid cells. After appropriate time series transformation to generate "iid" variates, only the positive pairs (radar >0, gauge >0 of the residuals are considered. As not each grid cell can be assigned to one gauge, the integration of point information, i.e. gauge rainfall intensities, is achieved by considering the structure and the strength of dependence between the radar pixels and all the gauges within the radar image. Two different approaches, namely Maximum Theta and Multiple Theta, are presented. They finally allow for generating precipitation fields that mimic the spatial patterns of the radar fields and correct them for biases in their absolute rainfall intensities. The performance of the approach, which can be seen as a bias-correction for radar fields, is demonstrated for the Bavarian Alps. The bias-corrected rainfall fields are compared to a field of interpolated gauge values (ordinary kriging and are validated with available gauge measurements. The simulated precipitation fields are compared to an operationally corrected radar precipitation field (RADOLAN. The copula-based approach performs similarly well as indicated by different validation measures and successfully corrects for errors in the radar precipitation.

  9. High resolution reconstruction of monthly precipitation of Iberian Peninsula using circulation weather types

    Science.gov (United States)

    Cortesi, N.; Trigo, R.; Gonzalez-Hidalgo, J. C.; Ramos, A. M.

    2012-06-01

    Precipitation over the Iberian Peninsula (IP) is highly variable and shows large spatial contrasts between wet mountainous regions, to the north, and dry regions in the inland plains and southern areas. In this work, a high-density monthly precipitation dataset for the IP was coupled with a set of 26 atmospheric circulation weather types (Trigo and DaCamara, 2000) to reconstruct Iberian monthly precipitation from October to May with a very high resolution of 3030 precipitation series (overall mean density one station each 200 km2). A stepwise linear regression model with forward selection was used to develop monthly reconstructed precipitation series calibrated and validated over 1948-2003 period. Validation was conducted by means of a leave-one-out cross-validation over the calibration period. The results show a good model performance for selected months, with a mean coefficient of variation (CV) around 0.6 for validation period, being particularly robust over the western and central sectors of IP, while the predicted values in the Mediterranean and northern coastal areas are less acute. We show for three long stations (Lisbon, Madrid and Valencia) the comparison between model and original data as an example to how these models can be used in order to obtain monthly precipitation fields since the 1850s over most of IP for this very high density network.

  10. Analysis of legal and economic aspects of precipitation weather derivatives for Serbian agricultural sector

    Directory of Open Access Journals (Sweden)

    Veselinović Janko

    2014-01-01

    Full Text Available Weather derivatives are not present in Serbia nor in the neighbouring countries and have no significant application in the European Union, either. Weather derivatives originated in the USA, where the market for these instruments is most developed, in terms of both economy and law. However, positive effects of their application, through the decrease of influence of unfavourable weather conditions on agricultural crops, are a good basis for their further study. The most common reasons for their absence from our financial market are their complexity and the inexistence of prerequisites for their introduction. This paper analyses legal and economic aspects of weather derivatives, as forms of financial derivatives, as well as weather derivative contracts concluded with the aim of hedging against precipitation exposure. The goal of the analysis is to find an optimal contract structure, but also the conditions that have to be met in order for its signing to be economically justified for both contractual parties, as well as the creation of preconditions for this weather derivative contract to be the instrument of trade on the financial market. The paper also analyses normative frameworks for the conclusion of these derivative contracts, as well as the necessity to educate market participants, which refers both to agricultural producers and financial institutions. Furthermore, it emphasizes the difference in relation to the classical contract of insurance against drought risk.

  11. Comparison between weather station data in south-eastern Italy and CRU precipitation datasets

    Science.gov (United States)

    Miglietta, D.

    2009-04-01

    Monthly precipitation data in south-eastern Italy from 1920 to 2005 have been extensively analyzed. Data were collected in almost 200 weather stations located 10-20km apart from each other and almost uniformly distributed in Puglia and Basilicata regions. Apart from few years around world war II, time series are mostly complete and allow a reliable reconstruction of climate variability in the considered region. Statistically significant trends have been studied by applying the Mann-Kendall test to annual, seasonal and monthly values. A comparison has been made between observations and precipitation data given by the Climate Research Unit (CRU), University of East Anglia, with both low (30') and high (10') space resolution grid. In particular, rainfall records, time series behaviors and annual cycles at each station have been compared to the corresponding CRU data. CRU time series show a large negative trend for winter since 1970. Trend is not significant if the whole 20th century is considered (both for the whole year and for winter only). This might be considered as an evidence of recent acceleration towards increasingly dry conditions. However correlation between CRU data and observations is not very high and large percent errors are present mainly in the mountains regions, where observations show a large annual cycle, with intense precipitation in winter, which is not present in CRU data. To identify trends, therefore observed data are needed, even at monthly scale. In particular observations confirm the overall trend, but also indicate large spatial variability, with locations where precipitation has even increased since 1970. Daily precipitation data coming from a subset of weather stations have also been studied for the same time period. The distributions of maximum annual rainfalls, wet spells and dry spells were analyzed for each station, together with their time series. The tools of statistical analysis of extremes have been used in order to evaluate

  12. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

    The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

  13. Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN) over Peninsular Malaysia

    Science.gov (United States)

    Syafrina, A. H.; Zalina, M. D.; Juneng, L.

    2014-09-01

    A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM) outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF). New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081-2100). The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10-40 years.

  14. Advanced Corrections for InSAR Using GPS and Numerical Weather Models

    Science.gov (United States)

    Cossu, F.; Foster, J. H.; Amelung, F.; Varugu, B. K.; Businger, S.; Cherubini, T.

    2017-12-01

    We present results from an investigation into the application of numerical weather models for generating tropospheric correction fields for Interferometric Synthetic Aperture Radar (InSAR). We apply the technique to data acquired from a UAVSAR campaign as well as from the CosmoSkyMed satellites. The complex spatial and temporal changes in the atmospheric propagation delay of the radar signal remain the single biggest factor limiting InSAR's potential for hazard monitoring and mitigation. A new generation of InSAR systems is being built and launched, and optimizing the science and hazard applications of these systems requires advanced methodologies to mitigate tropospheric noise. We use the Weather Research and Forecasting (WRF) model to generate a 900 m spatial resolution atmospheric models covering the Big Island of Hawaii and an even higher, 300 m resolution grid over the Mauna Loa and Kilauea volcanoes. By comparing a range of approaches, from the simplest, using reanalyses based on typically available meteorological observations, through to the "kitchen-sink" approach of assimilating all relevant data sets into our custom analyses, we examine the impact of the additional data sets on the atmospheric models and their effectiveness in correcting InSAR data. We focus particularly on the assimilation of information from the more than 60 GPS sites in the island. We ingest zenith tropospheric delay estimates from these sites directly into the WRF analyses, and also perform double-difference tomography using the phase residuals from the GPS processing to robustly incorporate heterogeneous information from the GPS data into the atmospheric models. We assess our performance through comparisons of our atmospheric models with external observations not ingested into the model, and through the effectiveness of the derived phase screens in reducing InSAR variance. Comparison of the InSAR data, our atmospheric analyses, and assessments of the active local and mesoscale

  15. Radar rainfall estimation of stratiform winter precipitation in the Belgian Ardennes

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.

    2011-02-01

    Radars are known for their ability to obtain a wealth of information about spatial storm field characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar rainfall estimates starts to decrease at relatively close ranges. In the current study, the hydrological potential of weather radar is analyzed during a winter half-year for the hilly region of the Belgian Ardennes. A correction algorithm is proposed which corrects the radar data for errors related to attenuation, ground clutter, anomalous propagation, the vertical profile of reflectivity (VPR), and advection. No final bias correction with respect to rain gauge data was implemented because such an adjustment would not add to a better understanding of the quality of the radar data. The impact of the different corrections is assessed using rainfall information sampled by 42 hourly rain gauges. The largest improvement in the quality of the radar data is obtained by correcting for ground clutter. The impact of VPR correction and advection depends on the spatial variability and velocity of the precipitation system. Overall during the winter period, the radar underestimates the amount of precipitation as compared to the rain gauges. Remaining differences between both instruments can be attributed to spatial and temporal variability in the type of precipitation, which has not been taken into account.

  16. Future projections of extreme precipitation using Advanced Weather Generator (AWE-GEN over Peninsular Malaysia

    Directory of Open Access Journals (Sweden)

    A. H. Syafrina

    2014-09-01

    Full Text Available A stochastic downscaling methodology known as the Advanced Weather Generator, AWE-GEN, has been tested at four stations in Peninsular Malaysia using observations available from 1975 to 2005. The methodology involves a stochastic downscaling procedure based on a Bayesian approach. Climate statistics from a multi-model ensemble of General Circulation Model (GCM outputs were calculated and factors of change were derived to produce the probability distribution functions (PDF. New parameters were obtained to project future climate time series. A multi-model ensemble was used in this study. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081–2100. The model was able to simulate both hourly and 24-h extreme precipitation, as well as wet spell durations quite well for almost all regions. However, the performance of GCM models varies significantly in all regions showing high variability of monthly precipitation for both observed and future periods. The extreme precipitation for both hourly and 24-h seems to increase in future, while extreme of wet spells remain unchanged, up to the return periods of 10–40 years.

  17. Predictability of heavy sub-hourly precipitation amounts for a weather radar based nowcasting system

    Science.gov (United States)

    Bech, Joan; Berenguer, Marc

    2015-04-01

    Heavy precipitation events and subsequent flash floods are one of the most dramatic hazards in many regions such as the Mediterranean basin as recently stressed in the HyMeX (HYdrological cycle in the Mediterranean EXperiment) international programme. The focus of this study is to assess the quality of very short range (below 3 hour lead times) precipitation forecasts based on weather radar nowcasting system. Specific nowcasting amounts of 10 and 30 minutes generated with a nowcasting technique (Berenguer et al 2005, 2011) are compared against raingauge observations and also weather radar precipitation estimates observed over Catalonia (NE Spain) using data from the Meteorological Service of Catalonia and the Water Catalan Agency. Results allow to discuss the feasibility of issuing warnings for different precipitation amounts and lead times for a number of case studies, including very intense convective events with 30minute precipitation amounts exceeding 40 mm (Bech et al 2005, 2011). As indicated by a number of verification scores single based radar precipitation nowcasts decrease their skill quickly with increasing lead times and rainfall thresholds. This work has been done in the framework of the Hymex research programme and has been partly funded by the ProFEWS project (CGL2010-15892). References Bech J, N Pineda, T Rigo, M Aran, J Amaro, M Gayà, J Arús, J Montanyà, O van der Velde, 2011: A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis. Atmospheric Research 100:621-637 http://dx.doi.org/10.1016/j.atmosres.2010.12.024 Bech J, R Pascual, T Rigo, N Pineda, JM López, J Arús, and M Gayà, 2007: An observational study of the 7 September 2005 Barcelona tornado outbreak. Natural Hazards and Earth System Science 7:129-139 http://dx.doi.org/10.5194/nhess-7-129-2007 Berenguer M, C Corral, R Sa0nchez-Diezma, D Sempere-Torres, 2005: Hydrological validation of a radar based nowcasting technique. Journal of

  18. Downscaling atmospheric patterns to multi-site precipitation amounts in southern Scandinavia

    DEFF Research Database (Denmark)

    Gelati, Emiliano; Christensen, O.B.; Rasmussen, P.F.

    2010-01-01

    A non-homogeneous hidden Markov model (NHMM) is applied for downscaling atmospheric synoptic patterns to winter multi-site daily precipitation amounts. The implemented NHMM assumes precipitation to be conditional on a hidden weather state that follows a Markov chain, whose transition probabilities...... depend on current atmospheric information. The gridded atmospheric fields are summarized through the singular value decomposition (SVD) technique. SVD is applied to geopotential height and relative humidity at several pressure levels, to identify their principal spatial patterns co...... products of bivariate distributions. Conditional on the weather state, precipitation amounts are modelled separately at each gauge as independent gamma-distributed random variables. This modelling approach is applied to 51 precipitation gauges in Denmark and southern Sweden for the period 1981...

  19. Fluoride pollution of atmospheric precipitation and its relationship with air circulation and weather patterns (Wielkopolski National Park, Poland).

    Science.gov (United States)

    Walna, Barbara; Kurzyca, Iwona; Bednorz, Ewa; Kolendowicz, Leszek

    2013-07-01

    A 2-year study (2010-2011) of fluorides in atmospheric precipitation in the open area and in throughfall in Wielkopolski National Park (west-central Poland) showed their high concentrations, reaching a maximum value of 2 mg/l under the tree crowns. These high values indicate substantial deposition of up to 52 mg/m(2)/year. In 2011, over 51% of open area precipitation was characterized by fluoride concentration higher than 0.10 mg/l, and in throughfall such concentrations were found in more than 86% of events. In 2010, a strong connection was evident between fluoride and acid-forming ions, and in 2011, a correlation between phosphate and nitrite ions was seen. Analysis of available data on F(-) concentrations in the air did not show an unequivocal effect on F(-) concentrations in precipitation. To find reasons for and source areas of high fluoride pollution, the cases of extreme fluoride concentration in rainwater were related to atmospheric circulation and weather patterns. Weather conditions on days of extreme pollution were determined by movement of weather fronts over western Poland, or by small cyclonic centers with meteorological fronts. Macroscale air advection over the sampling site originated in the western quadrant (NW, W, and SW), particularly in the middle layers of the troposphere (2,500-5,000 m a.s.l.). Such directions indicate western Poland and Germany as possible sources of the pollution. At the same time in the lower troposphere, air inflow was frequently from the north, showing short distance transport from local emitters, and from the agglomeration of Poznań.

  20. Generating daily weather data for ecosystem modelling in the Congo River Basin

    Science.gov (United States)

    Petritsch, Richard; Pietsch, Stephan A.

    2010-05-01

    Daily weather data are an important constraint for diverse applications in ecosystem research. In particular, temperature and precipitation are the main drivers for forest ecosystem productivity. Mechanistic modelling theory heavily relies on daily values for minimum and maximum temperatures, precipitation, incident solar radiation and vapour pressure deficit. Although the number of climate measurement stations increased during the last centuries, there are still regions with limited climate data. For example, in the WMO database there are only 16 stations located in Gabon with daily weather measurements. Additionally, the available time series are heavily affected by measurement errors or missing values. In the WMO record for Gabon, on average every second day is missing. Monthly means are more robust and may be estimated over larger areas. Therefore, a good alternative is to interpolate monthly mean values using a sparse network of measurement stations, and based on these monthly data generate daily weather data with defined characteristics. The weather generator MarkSim was developed to produce climatological time series for crop modelling in the tropics. It provides daily values for maximum and minimum temperature, precipitation and solar radiation. The monthly means can either be derived from the internal climate surfaces or prescribed as additional inputs. We compared the generated outputs observations from three climate stations in Gabon (Lastourville, Moanda and Mouilla) and found that maximum temperature and solar radiation were heavily overestimated during the long dry season. This is due to the internal dependency of the solar radiation estimates to precipitation. With no precipitation a cloudless sky is assumed and thus high incident solar radiation and a large diurnal temperature range. However, in reality it is cloudy in the Congo River Basin during the long dry season. Therefore, we applied a correction factor to solar radiation and temperature range

  1. Laboratory weathering of combusted oil shale

    International Nuclear Information System (INIS)

    Essington, M.E.

    1991-01-01

    The objective of this study was to examine the mineralogy and leachate chemistry of three combusted oil shales (two Green River Formation and one New Albany) in a laboratory weathering environment using the humidity cell technique. The mineralogy of the combusted western oil shales (Green River Formation) is process dependent. In general, processing resulted in the formation of anhydrite, lime, periclase, and hematite. During the initial stages of weathering, lime, periclase, and hematite. During the initial stages of weathering, lime, periclase, and anhydrite dissolve and ettringite precipitates. The initial leachates are highly alkaline, saline, and dominated by Na, hydroxide, and SO 4 . As weathering continues, ettringite precipitates. The initial leachates are highly alkaline, saline, and dominated by Na, hydroxide, and SO 4 . As weathering continues, ettringite dissolves, gypsum and calcite precipitate, and the leachates are dominated by Mg, SO 4 , and CO 3 . Leachate pH is rapidly reduced to between 8.5 and 9 with leaching. The combusted eastern oil shale (New Albany) is composed of quartz, illite, hematite, and orthoclase. Weathering results in the precipitation of gypsum. The combusted eastern oil shale did not display a potential to produce acid drainage. Leachate chemistry was dominated by Ca and SO 4 . Element concentrations continually decreased with weathering. IN a western disposal environment receiving minimal atmospheric precipitation, spent oil shale will remain in the initial stages of weathering, and highly alkaline and saline conditions will dominate leachate chemistry. In an eastern disposal environment, soluble salts will be rapidly removed from the spent oil shale to potentially affect the surrounding environment

  2. SPAGETTA: a Multi-Purpose Gridded Stochastic Weather Generator

    Science.gov (United States)

    Dubrovsky, M.; Huth, R.; Rotach, M. W.; Dabhi, H.

    2017-12-01

    SPAGETTA is a new multisite/gridded multivariate parametric stochastic weather generator (WG). Site-specific precipitation occurrence and amount are modelled by Markov chain and Gamma distribution, the non-precipitation variables are modelled by an autoregressive (AR) model conditioned on precipitation occurrence, and the spatial coherence of all variables is modelled following the Wilks' (2009) approach. SPAGETTA may be run in two modes. Mode 1: it is run as a classical WG, which is calibrated using weather series from multiple sites, and only then it may produce arbitrarily long synthetic series mimicking the spatial and temporal structure of the calibration data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. Mode 2: the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying AR model, which produces the multi-site weather series. Optionally, the user may add the spatially varying trend, which is superimposed to the synthetic series. The contribution consists of following parts: (a) Model of the WG. (b) Validation of WG in terms of the spatial temperature and precipitation characteristics, including characteristics of spatial hot/cold/dry/wet spells. (c) Results of the climate change impact experiment, in which the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and the effect on the above spatial validation indices is analysed. In this experiment, the WG is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulations (CORDEX database). (d) The second mode of operation will be

  3. SHORT-TERM PRECIPITATION OCCURRENCE PREDICTION FOR STRONG CONVECTIVE WEATHER USING FY2-G SATELLITE DATA: A CASE STUDY OF SHENZHEN,SOUTH CHINA

    Directory of Open Access Journals (Sweden)

    K. Chen

    2016-06-01

    Full Text Available Short-term precipitation commonly occurs in south part of China, which brings intensive precipitation in local region for very short time. Massive water would cause the intensive flood inside of city when precipitation amount beyond the capacity of city drainage system. Thousands people’s life could be influenced by those short-term disasters and the higher city managements are required to facing these challenges. How to predict the occurrence of heavy precipitation accurately is one of the worthwhile scientific questions in meteorology. According to recent studies, the accuracy of short-term precipitation prediction based on numerical simulation model still remains low reliability, in some area where lack of local observations, the accuracy may be as low as 10%. The methodology for short term precipitation occurrence prediction still remains a challenge. In this paper, a machine learning method based on SVM was presented to predict short-term precipitation occurrence by using FY2-G satellite imagery and ground in situ observation data. The results were validated by traditional TS score which commonly used in evaluation of weather prediction. The results indicate that the proposed algorithm can present overall accuracy up to 90% for one-hour to six-hour forecast. The result implies the prediction accuracy could be improved by using machine learning method combining with satellite image. This prediction model can be further used to evaluated to predicted other characteristics of weather in Shenzhen in future.

  4. Contribution of long-term accounting for raindrop size distribution variations on quantitative precipitation estimation by weather radar: Disdrometers vs parameter optimization

    Science.gov (United States)

    Hazenberg, P.; Uijlenhoet, R.; Leijnse, H.

    2015-12-01

    Volumetric weather radars provide information on the characteristics of precipitation at high spatial and temporal resolution. Unfortunately, rainfall measurements by radar are affected by multiple error sources, which can be subdivided into two main groups: 1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, vertical profile of reflectivity, attenuation, etc.), and 2) errors related to the conversion of the observed reflectivity (Z) values into rainfall intensity (R) and specific attenuation (k). Until the recent wide-scale implementation of dual-polarimetric radar, this second group of errors received relatively little attention, focusing predominantly on precipitation type-dependent Z-R and Z-k relations. The current work accounts for the impact of variations of the drop size distribution (DSD) on the radar QPE performance. We propose to link the parameters of the Z-R and Z-k relations directly to those of the normalized gamma DSD. The benefit of this procedure is that it reduces the number of unknown parameters. In this work, the DSD parameters are obtained using 1) surface observations from a Parsivel and Thies LPM disdrometer, and 2) a Monte Carlo optimization procedure using surface rain gauge observations. The impact of both approaches for a given precipitation type is assessed for 45 days of summertime precipitation observed within The Netherlands. Accounting for DSD variations using disdrometer observations leads to an improved radar QPE product as compared to applying climatological Z-R and Z-k relations. However, overall precipitation intensities are still underestimated. This underestimation is expected to result from unaccounted errors (e.g. transmitter calibration, erroneous identification of precipitation as clutter, overshooting and small-scale variability). In case the DSD parameters are optimized, the performance of the radar is further improved, resulting in the best performance of the radar QPE product. However

  5. Weather extremes and the Romans - A marine palynological perspective on Italian temperature and precipitation between 200 BC and 500 AD

    Science.gov (United States)

    Zonneveld, Karin; Clotten, Caroline; Chen, Liang

    2015-04-01

    Sediments of a tephra-dated marine sediment core located at the distal part of the Po-river discharge plume (southern Italy) have been studied with a three annual resolution. Based on the variability in the dinoflagellate cyst content detailed reconstructions have been established of variability in precipitation related river discharge rates and local air temperature. Furthermore about the variability in distort water quality has been reconstructed. We show that both precipitation and temperature signals vary in tune with cyclic changes in solar insolation. On top of these cyclic changes, short term extremes in temperature and precipitation can be observed that can be interpreted to reflect periods of local weather extremes. Comparison of our reconstructions with historical information suggest that times of high temperatures and maximal precipitation corresponds to the period of maximal expansion of the Roman Empire. We have strong indications that at this time discharge waters might have contained higher nutrient concentrations compared to previous and later time intervals suggesting anthropogenic influence of the water quality. First pilot-results suggest that the decrease in temperature reconstructed just after the "Roman Optimum" corresponds to an increase in numbers of armored conflicts between the Roman and German cultures. Furthermore we observe a resemblance in timing of short-term intervals with cold weather spells during the early so called "Dark-Age-Period" to correspond to epidemic/pandemic events in Europe.

  6. Reproducibility of Carbon and Water Cycle by an Ecosystem Process Based Model Using a Weather Generator and Effect of Temporal Concentration of Precipitation on Model Outputs

    Science.gov (United States)

    Miyauchi, T.; Machimura, T.

    2014-12-01

    GCM is generally used to produce input weather data for the simulation of carbon and water cycle by ecosystem process based models under climate change however its temporal resolution is sometimes incompatible to requirement. A weather generator (WG) is used for temporal downscaling of input weather data for models, where the effect of WG algorithms on reproducibility of ecosystem model outputs must be assessed. In this study simulated carbon and water cycle by Biome-BGC model using weather data measured and generated by CLIMGEN weather generator were compared. The measured weather data (daily precipitation, maximum, minimum air temperature) at a few sites for 30 years was collected from NNDC Online weather data. The generated weather data was produced by CLIMGEN parameterized using the measured weather data. NPP, heterotrophic respiration (HR), NEE and water outflow were simulated by Biome-BGC using measured and generated weather data. In the case of deciduous broad leaf forest in Lushi, Henan Province, China, 30 years average monthly NPP by WG was 10% larger than that by measured weather in the growing season. HR by WG was larger than that by measured weather in all months by 15% in average. NEE by WG was more negative in winter and was close to that by measured weather in summer. These differences in carbon cycle were because the soil water content by WG was larger than that by measured weather. The difference between monthly water outflow by WG and by measured weather was large and variable, and annual outflow by WG was 50% of that by measured weather. The inconsistency in carbon and water cycle by WG and measured weather was suggested be affected by the difference in temporal concentration of precipitation, which was assessed.

  7. An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

    Science.gov (United States)

    Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

    2018-01-01

    Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

  8. Simulating the convective precipitation diurnal cycle in a North American scale convection-permitting model

    Science.gov (United States)

    Scaff, L.; Li, Y.; Prein, A. F.; Liu, C.; Rasmussen, R.; Ikeda, K.

    2017-12-01

    A better representation of the diurnal cycle of convective precipitation is essential for the analysis of the energy balance and the water budget components such as runoff, evaporation and infiltration. Convection-permitting regional climate modeling (CPM) has been shown to improve the models' performance of summer precipitation, allowing to: (1) simulate the mesoscale processes in more detail and (2) to provide more insights in future changes in convective precipitation under climate change. In this work we investigate the skill of the Weather Research and Forecast model (WRF) in simulating the summer precipitation diurnal cycle over most of North America. We use 4 km horizontal grid spacing in a 13-years long current and future period. The future scenario is assuming no significant changes in large-scale weather patterns and aims to answer how the weather of the current climate would change if it would reoccur at the end of the century under a high-end emission scenario (Pseudo Global Warming). We emphasize on a region centered on the lee side of the Canadian Rocky Mountains, where the summer precipitation amount shows a regional maximum. The historical simulations are capable to correctly represent the diurnal cycle. At the lee-side of the Canadian Rockies the increase in the convective available potential energy as well as pronounced low-level moisture flux from the southeast Prairies explains the local maximum in summer precipitation. The PGW scenario shows an increase in summer precipitation amount and intensity in this region, consistently with a stronger source of moisture and convective energy.

  9. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  10. Fabulous Weather Day

    Science.gov (United States)

    Marshall, Candice; Mogil, H. Michael

    2007-01-01

    Each year, first graders at Kensington Parkwood Elementary School in Kensington, Maryland, look forward to Fabulous Weather Day. Students learn how meteorologists collect data about the weather, how they study wind, temperature, precipitation, basic types/characteristics of clouds, and how they forecast. The project helps the students grow in…

  11. Weather types in Sosnowiec (Poland during the period 1999-2013

    Directory of Open Access Journals (Sweden)

    Dobrowolska Ksenia

    2014-09-01

    Full Text Available The study presents the structure of weather types for the city of Sosnowiec during the period 1999-2013. The analysis was carried out on the basis of daily thermal data (the average daily air temperature, the minimum and maximum daily air temperature, cloudiness and precipitation. The data was obtained from a meteorological station belonging to the Department of Climatology at the Faculty of Earth Sciences at the University of Silesia. Weather types were established according to weather type classification after Woś (2010. 48 weather types were specified on the basis of a combination of 3 selected meteorological elements (temperature, cloudiness, precipitation. The number of days in the year and the frequency of particular thermal weather types, weather subtype, weather classes and weather types were characterized, and the changeability of weather types was analyzed. Furthermore, sequences of days with specific weather types were described. The analysis conducted has lead to the conclusion that, during the research period, the weather structure for the city of Sosnowiec was characterized by a great number of weather types observed, with relatively low frequency of occurrence. Weather throughout the year was dominated by warm weather types (3--, 2--, 2--, with weather marked as 310 – very warm, moderately cloudy, without precipitation (12.9% recorded as the most frequent, followed by 221 – moderately warm, very cloudy, with precipitation (11.6%, and 210 – moderately warm, moderately cloudy, without precipitation (11.4%as the least frequent one. A diversification in the number of particular classification units in consecutive years of the examined 15-year period does not display significant variability. Short sequences of 2 and 3 days dominated the selected sequences of specific weather types.

  12. An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

    Directory of Open Access Journals (Sweden)

    J. Chardon

    2018-01-01

    Full Text Available Statistical downscaling models (SDMs are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

  13. Assessment and correction of BCC_CSM's performance in capturing leading modes of summer precipitation over North Asia

    KAUST Repository

    Gong, Zhiqiang

    2017-11-07

    This article examines the ability of Beijing Climate Center Climate System Model (BCC_CSM) in demonstrating the prediction accuracy and the leading modes of the summer precipitation over North Asia (NA). A dynamic-statistic combined approach for improving the prediction accuracy and the prediction of the leading modes of the summer precipitation over NA is proposed. Our results show that the BCC_CSM can capture part of the spatial anomaly features of the first two leading modes of NA summer precipitation. Moreover, BCC_CSM regains relationships such that the first and second mode of the empirical orthogonal function (EOF1 and EOF2) of NA summer precipitation, respectively, corresponds to the development of the El Niño and La Niña conditions in the tropical East Pacific. Nevertheless, BCC_CSM exhibits limited prediction skill over most part of NA and presents a deficiency in reproducing the EOF1\\'s and EOF2\\'s spatial pattern over central NA and EOF2\\'s interannual variability. This can be attributed as the possible reasons why the model is unable to capture the correct relationships among the basic climate elements over the central NA, lacks in its ability to reproduce a consistent zonal atmospheric pattern over NA, and has bias in predicting the relevant Sea Surface Temperature (SST) modes over the tropical Pacific and Indian Ocean regions. Based on the proposed dynamic-statistic combined correction approach, compared with the leading modes of BCC_CSM\\'s original prediction, anomaly correlation coefficients of corrected EOF1/EOF2 with the tropical Indian Ocean SST are improved from 0.18/0.36 to 0.51/0.62. Hence, the proposed correction approach suggests that the BCC_CSM\\'s prediction skill for the summer precipitation prediction over NA and its ability to capture the dominant modes could be certainly improved by choosing proper historical analogue information.

  14. An objective daily Weather Type classification for Iberia since 1850; patterns, trends, variability and impact in precipitation

    Science.gov (United States)

    Ramos, A. M.; Trigo, R. M.; Lorenzo, M. N.; Vaquero, J. M.; Gallego, M. C.; Valente, M. A.; Gimeno, L.

    2009-04-01

    In recent years a large number of automated classifications of atmospheric circulation patterns have been published covering the entire European continent or specific sub-regions (Huth et al., 2008). This generalized use of objective classifications results from their relatively straightforward computation but crucially from their capacity to provide simple description of typical synoptic conditions as well as their climatic and environmental impact. For this purpose, the vast majority of authors has employed the Reanalyses datasets, namely from either NCEP/NCAR or ECMWF projects. However, both these widely used datasets suffer from important caveats, namely their restricted temporal coverage, that is limited to the last six decades (NCEP/NCAR since 1948 and ECMWF since 1958). This limitation has been partially mitigated by the recent availability of continuous daily mean sea level pressure obtained within the European project EMULATE, that extended the historic records over the extra-tropical Atlantic and Europe (70°-25° N by 70° W-50° E), for the period 1850 to the present (Ansell, T. J. et al. 2006). Here we have used the extended EMULATE dataset to construct an automated version of the Lamb Weather type (WTs) classification scheme (Jones et al 1993) adapted for the center of the Iberian Peninsula. We have identified 10 basic WTs (Cyclonic, Anticyclonic and 8 directional types) following a similar methodology to that previously adopted by Trigo and DaCamara, 2000 (for Portugal) and Lorenzo et al. 2008 (for Galicia, northwestern Iberia). We have evaluated trends of monthly/seasonal frequency of each WT for the entire period and several shorter periods. Finally, we use the long-term precipitation time series from Lisbon (recently digitized) and Cadiz (southern Spain) to evaluate, the impact of each WT on the precipitation regime. It is shown that the Anticyclonic (A) type, although being the most frequent class in winter, gives a rather small contribution to

  15. Use of bias correction techniques to improve seasonal forecasts for reservoirs - A case-study in northwestern Mediterranean.

    Science.gov (United States)

    Marcos, Raül; Llasat, Ma Carmen; Quintana-Seguí, Pere; Turco, Marco

    2018-01-01

    In this paper, we have compared different bias correction methodologies to assess whether they could be advantageous for improving the performance of a seasonal prediction model for volume anomalies in the Boadella reservoir (northwestern Mediterranean). The bias correction adjustments have been applied on precipitation and temperature from the European Centre for Middle-range Weather Forecasting System 4 (S4). We have used three bias correction strategies: two linear (mean bias correction, BC, and linear regression, LR) and one non-linear (Model Output Statistics analogs, MOS-analog). The results have been compared with climatology and persistence. The volume-anomaly model is a previously computed Multiple Linear Regression that ingests precipitation, temperature and in-flow anomaly data to simulate monthly volume anomalies. The potential utility for end-users has been assessed using economic value curve areas. We have studied the S4 hindcast period 1981-2010 for each month of the year and up to seven months ahead considering an ensemble of 15 members. We have shown that the MOS-analog and LR bias corrections can improve the original S4. The application to volume anomalies points towards the possibility to introduce bias correction methods as a tool to improve water resource seasonal forecasts in an end-user context of climate services. Particularly, the MOS-analog approach gives generally better results than the other approaches in late autumn and early winter. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Optimal Physics Parameterization Scheme Combination of the Weather Research and Forecasting Model for Seasonal Precipitation Simulation over Ghana

    Directory of Open Access Journals (Sweden)

    Richard Yao Kuma Agyeman

    2017-01-01

    Full Text Available Seasonal predictions of precipitation, among others, are important to help mitigate the effects of drought and floods on agriculture, hydropower generation, disasters, and many more. This work seeks to obtain a suitable combination of physics schemes of the Weather Research and Forecasting (WRF model for seasonal precipitation simulation over Ghana. Using the ERA-Interim reanalysis as forcing data, simulation experiments spanning eight months (from April to November were performed for two different years: a dry year (2001 and a wet year (2008. A double nested approach was used with the outer domain at 50 km resolution covering West Africa and the inner domain covering Ghana at 10 km resolution. The results suggest that the WRF model generally overestimated the observed precipitation by a mean value between 3% and 64% for both years. Most of the scheme combinations overestimated (underestimated precipitation over coastal (northern zones of Ghana for both years but estimated precipitation reasonably well over forest and transitional zones. On the whole, the combination of WRF Single-Moment 6-Class Microphysics Scheme, Grell-Devenyi Ensemble Cumulus Scheme, and Asymmetric Convective Model Planetary Boundary Layer Scheme simulated the best temporal pattern and temporal variability with the least relative bias for both years and therefore is recommended for Ghana.

  17. Weather and road capacity

    DEFF Research Database (Denmark)

    Jensen, Thomas Christian

    2014-01-01

    The paper presents estimations of the effect of bad weather on the observed speed on a Danish highway section; Køge Bugt Motorvejen. The paper concludes that weather, primarily precipitation and snow, has a clear negative effect on speed when the road is not in hypercongestion mode. Furthermore...

  18. Reconstruction of Historical Weather by Assimilating Old Weather Diary Data

    Science.gov (United States)

    Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.

    2017-12-01

    Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any

  19. Simulation and Prediction of Weather Radar Clutter Using a Wave Propagator on High Resolution NWP Data

    DEFF Research Database (Denmark)

    Benzon, Hans-Henrik; Bovith, Thomas

    2008-01-01

    for prediction of this type of weather radar clutter is presented. The method uses a wave propagator to identify areas of potential non-standard propagation. The wave propagator uses a three dimensional refractivity field derived from the geophysical parameters: temperature, humidity, and pressure obtained from......Weather radars are essential sensors for observation of precipitation in the troposphere and play a major part in weather forecasting and hydrological modelling. Clutter caused by non-standard wave propagation is a common problem in weather radar applications, and in this paper a method...... a high-resolution Numerical Weather Prediction (NWP) model. The wave propagator is based on the parabolic equation approximation to the electromagnetic wave equation. The parabolic equation is solved using the well-known Fourier split-step method. Finally, the radar clutter prediction technique is used...

  20. Automatic Classification of Offshore Wind Regimes With Weather Radar Observations

    DEFF Research Database (Denmark)

    Trombe, Pierre-Julien; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    Weather radar observations are called to play an important role in offshore wind energy. In particular, they can enable the monitoring of weather conditions in the vicinity of large-scale offshore wind farms and thereby notify the arrival of precipitation systems associated with severe wind...... and amplitude) using reflectivity observations from a single weather radar system. A categorical sequence of most likely wind regimes is estimated from a wind speed time series by combining a Markov-Switching model and a global decoding technique, the Viterbi algorithm. In parallel, attributes of precipitation...... systems are extracted from weather radar images. These attributes describe the global intensity, spatial continuity and motion of precipitation echoes on the images. Finally, a CART classification tree is used to find the broad relationships between precipitation attributes and wind regimes...

  1. Statistical Correction of Air Temperature Forecasts for City and Road Weather Applications

    Science.gov (United States)

    Mahura, Alexander; Petersen, Claus; Sass, Bent; Gilet, Nicolas

    2014-05-01

    The method for statistical correction of air /road surface temperatures forecasts was developed based on analysis of long-term time-series of meteorological observations and forecasts (from HIgh Resolution Limited Area Model & Road Conditions Model; 3 km horizontal resolution). It has been tested for May-Aug 2012 & Oct 2012 - Mar 2013, respectively. The developed method is based mostly on forecasted meteorological parameters with a minimal inclusion of observations (covering only a pre-history period). Although the st iteration correction is based taking into account relevant temperature observations, but the further adjustment of air and road temperature forecasts is based purely on forecasted meteorological parameters. The method is model independent, e.g. it can be applied for temperature correction with other types of models having different horizontal resolutions. It is relatively fast due to application of the singular value decomposition method for matrix solution to find coefficients. Moreover, there is always a possibility for additional improvement due to extra tuning of the temperature forecasts for some locations (stations), and in particular, where for example, the MAEs are generally higher compared with others (see Gilet et al., 2014). For the city weather applications, new operationalized procedure for statistical correction of the air temperature forecasts has been elaborated and implemented for the HIRLAM-SKA model runs at 00, 06, 12, and 18 UTCs covering forecast lengths up to 48 hours. The procedure includes segments for extraction of observations and forecast data, assigning these to forecast lengths, statistical correction of temperature, one-&multi-days statistical evaluation of model performance, decision-making on using corrections by stations, interpolation, visualisation and storage/backup. Pre-operational air temperature correction runs were performed for the mainland Denmark since mid-April 2013 and shown good results. Tests also showed

  2. Statistical simulation of ensembles of precipitation fields for data assimilation applications

    Science.gov (United States)

    Haese, Barbara; Hörning, Sebastian; Chwala, Christian; Bárdossy, András; Schalge, Bernd; Kunstmann, Harald

    2017-04-01

    The simulation of the hydrological cycle by models is an indispensable tool for a variety of environmental challenges such as climate prediction, water resources management, or flood forecasting. One of the crucial variables within the hydrological system, and accordingly one of the main drivers for terrestrial hydrological processes, is precipitation. A correct reproduction of the spatio-temporal distribution of precipitation is crucial for the quality and performance of hydrological applications. In our approach we stochastically generate precipitation fields conditioned on various precipitation observations. Rain gauges provide high-quality information for a specific measurement point, but their spatial representativeness is often rare. Microwave links, e. g. from commercial cellular operators, on the other hand can be used to estimate line integrals of near-surface rainfall information. They provide a very dense observational system compared to rain gauges. A further prevalent source of precipitation information are weather radars, which provide rainfall pattern informations. In our approach we derive precipitation fields, which are conditioned on combinations of these different observation types. As method to generate precipitation fields we use the random mixing method. Following this method a precipitation field is received as a linear combination of unconditional spatial random fields, where the spatial dependence structure is described by copulas. The weights of the linear combination are chosen in the way that the observations and the spatial structure of precipitation are reproduced. One main advantage of the random mixing method is the opportunity to consider linear and non-linear constraints. For a demonstration of the method we use virtual observations generated from a virtual reality of the Neckar catchment. These virtual observations mimic advantages and disadvantages of real observations. This virtual data set allows us to evaluate simulated

  3. The More Extreme Nature of North American Monsoon Precipitation in the Southwestern United States as Revealed by a Historical Climatology of Simulated Severe Weather Events

    KAUST Repository

    Luong, Thang M.; Castro, Christopher L.; Chang, Hsin-I; Lahmers, Timothy; Adams, David K.; Ochoa-Moya, Carlos A.

    2017-01-01

    Long-term changes in North American monsoon (NAM) precipitation intensity in the southwestern United States are evaluated through the use of convective-permitting model simulations of objectively identified severe weather events during

  4. The More Extreme Nature of North American Monsoon Precipitation in the Southwestern United States as Revealed by a Historical Climatology of Simulated Severe Weather Events

    KAUST Repository

    Luong, Thang M.

    2017-07-03

    Long-term changes in North American monsoon (NAM) precipitation intensity in the southwestern United States are evaluated through the use of convective-permitting model simulations of objectively identified severe weather events during

  5. Evaluation of stochastic weather generators for capturing the statistics of extreme precipitation events in the Catskill Mountain watersheds, New York State

    Science.gov (United States)

    Acharya, N.; Frei, A.; Owens, E. M.; Chen, J.

    2015-12-01

    Watersheds located in the Catskill Mountains area, part of the eastern plateau climate region of New York, contributes about 90% of New York City's municipal water supply, serving 9 million New Yorkers with about 1.2 billion gallons of clean drinking water each day. The New York City Department of Environmental Protection has an ongoing series of studies to assess the potential impacts of climate change on the availability of high quality water in this water supply system. Recent studies identify increasing trends in total precipitation and in the frequency of extreme precipitation events in this region. The objectives of the present study are: to analyze the proba­bilistic structure of extreme precipitation based on historical observations: and to evaluate the abilities of stochastic weather generators (WG), statistical models that produce synthetic weather time series based on observed statistical properties at a particular location, to simulate the statistical properties of extreme precipitation events over this region. The generalized extreme value distribution (GEV) has been applied to the annual block maxima of precipitation for 60 years (1950 to 2009) observed data in order to estimate the events with return periods of 50, 75, and 100 years. These results were then used to evaluate a total of 13 WGs were : 12 parametric WGs including all combinations of three different orders of Markov chain (MC) models (1st , 2nd and 3rd) and four different probability distributions (exponential, gamma, skewed normal and mixed exponential); and one semi parametric WG based on k-nearest neighbor bootstrapping. Preliminary results suggest that three-parameter (skewed normal and mixed exponential distribution) and semi-parametric (k-nearest neighbor bootstrapping) WGs are more consistent with observations. It is also found that first order MC models perform as well as second or third order MC models.

  6. Re-examining the Non-Linear Moisture-Precipitation Relationship over the Tropical Oceans.

    Science.gov (United States)

    Rushley, S S; Kim, D; Bretherton, C S; Ahn, M-S

    2018-01-28

    Bretherton et al. (2004) used the Special Sensor Microwave Imager (SSM/I) version 5 product to derive an exponential curve that describes the relationship between precipitation and column relative humidity (CRH) over the tropical oceans. The curve, which features a precipitation pickup at a CRH of about 0.75 and a rapid increase of precipitation with CRH after the pickup, has been widely used in the studies of the tropical atmosphere. This study re-examines the moisture-precipitation relationship by using the version 7 SSM/I data, in which several biases in the previous version are corrected, and evaluates the relationship in the Coupled Model Intercomparison Project phase 5 (CMIP5) models. In the revised exponential curve derived using the updated satellite data, the precipitation pick-up occurs at a higher CRH (~0.8), and precipitation increases more slowly with CRH than in the previous curve. In most CMIP5 models, the precipitation pickup is too early due to the common model bias of overestimated (underestimated) precipitation in the dry (wet) regime.

  7. Incorporating Satellite Precipitation Estimates into a Radar-Gauge Multi-Sensor Precipitation Estimation Algorithm

    Directory of Open Access Journals (Sweden)

    Yuxiang He

    2018-01-01

    Full Text Available This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE that would objectively blend real-time satellite quantitative precipitation estimates (SQPE with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a five-year period between 2003–2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS (National Weather Service operations over two regions: (I Inside radar effective coverage and (II immediately outside radar coverage. The outcomes of the evaluation indicate (a ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and (b blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

  8. High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

    Science.gov (United States)

    Porada, Philipp; Lenton, Tim; Pohl, Alexandre; Weber, Bettina; Mander, Luke; Donnadieu, Yannick; Beer, Christian; Pöschl, Ulrich; Kleidon, Axel

    2017-04-01

    Early non-vascular vegetation in the Late Ordovician may have strongly increased chemical weathering rates of surface rocks at the global scale. This could have led to a drawdown of atmospheric CO2 and, consequently, a decrease in global temperature and an interval of glaciations. Under current climatic conditions, usually field or laboratory experiments are used to quantify enhancement of chemical weathering rates by non-vascular vegetation. However, these experiments are constrained to a small spatial scale and a limited number of species. This complicates the extrapolation to the global scale, even more so for the geological past, where physiological properties of non-vascular vegetation may have differed from current species. Here we present a spatially explicit modelling approach to simulate large-scale chemical weathering by non-vascular vegetation in the Late Ordovician. For this purpose, we use a process-based model of lichens and bryophytes, since these organisms are probably the closest living analogue to Late Ordovician vegetation. The model explicitly represents multiple physiological strategies, which enables the simulated vegetation to adapt to Ordovician climatic conditions. We estimate productivity of Ordovician vegetation with the model, and relate it to chemical weathering by assuming that the organisms dissolve rocks to extract phosphorus for the production of new biomass. Thereby we account for limits on weathering due to reduced supply of unweathered rock material in shallow regions, as well as decreased transport capacity of runoff for dissolved weathered material in dry areas. We simulate a potential global weathering flux of 2.8 km3 (rock) per year, which we define as volume of primary minerals affected by chemical transformation. Our estimate is around 3 times larger than today's global chemical weathering flux. Furthermore, chemical weathering rates simulated by our model are highly sensitive to atmospheric CO2 concentration, which implies

  9. Loop corrections to primordial non-Gaussianity

    Science.gov (United States)

    Boran, Sibel; Kahya, E. O.

    2018-02-01

    We discuss quantum gravitational loop effects to observable quantities such as curvature power spectrum and primordial non-Gaussianity of cosmic microwave background (CMB) radiation. We first review the previously shown case where one gets a time dependence for zeta-zeta correlator due to loop corrections. Then we investigate the effect of loop corrections to primordial non-Gaussianity of CMB. We conclude that, even with a single scalar inflaton, one might get a huge value for non-Gaussianity which would exceed the observed value by at least 30 orders of magnitude. Finally we discuss the consequences of this result for scalar driven inflationary models.

  10. User's Guide, software for reduction and analysis of daily weather and surface-water data: Tools for time series analysis of precipitation, temperature, and streamflow data

    Science.gov (United States)

    Hereford, Richard

    2006-01-01

    The software described here is used to process and analyze daily weather and surface-water data. The programs are refinements of earlier versions that include minor corrections and routines to calculate frequencies above a threshold on an annual or seasonal basis. Earlier versions of this software were used successfully to analyze historical precipitation patterns of the Mojave Desert and the southern Colorado Plateau regions, ecosystem response to climate variation, and variation of sediment-runoff frequency related to climate (Hereford and others, 2003; 2004; in press; Griffiths and others, 2006). The main program described here (Day_Cli_Ann_v5.3) uses daily data to develop a time series of various statistics for a user specified accounting period such as a year or season. The statistics include averages and totals, but the emphasis is on the frequency of occurrence in days of relatively rare weather or runoff events. These statistics are indices of climate variation; for a discussion of climate indices, see the Climate Research Unit website of the University of East Anglia (http://www.cru.uea.ac.uk/projects/stardex/) and the Climate Change Indices web site (http://cccma.seos.uvic.ca/ETCCDMI/indices.html). Specifically, the indices computed with this software are the frequency of high intensity 24-hour rainfall, unusually warm temperature, and unusually high runoff. These rare, or extreme events, are those greater than the 90th percentile of precipitation, streamflow, or temperature computed for the period of record of weather or gaging stations. If they cluster in time over several decades, extreme events may produce detectable change in the physical landscape and ecosystem of a given region. Although the software has been tested on a variety of data, as with any software, the user should carefully evaluate the results with their data. The programs were designed for the range of precipitation, temperature, and streamflow measurements expected in the semiarid

  11. wradlib - an Open Source Library for Weather Radar Data Processing

    Science.gov (United States)

    Pfaff, Thomas; Heistermann, Maik; Jacobi, Stephan

    2014-05-01

    Even though weather radar holds great promise for the hydrological sciences, offering precipitation estimates with unrivaled spatial and temporal resolution, there are still problems impeding its widespread use, among which are: almost every radar data set comes with a different data format with public reading software being available only rarely. standard products as issued by the meteorological services often do not serve the needs of original research, having either too many or too few corrections applied. Especially when new correction methods are to be developed, researchers are often forced to start from scratch having to implement many corrections in addition to those they are actually interested in. many algorithms published in the literature cannot be recreated using the corresponding article only. Public codes, providing insight into the actual implementation and how an approach deals with possible exceptions are rare. the radial scanning setup of weather radar measurements produces additional challenges, when it comes to visualization or georeferencing of this type of data. Based on these experiences, and in the hope to spare others at least some of these tedious tasks, wradlib offers the results of the author's own efforts and a growing number of community-supplied methods. wradlib is designed as a Python library of functions and classes to assist users in their analysis of weather radar data. It provides solutions for all tasks along a typical processing chain leading from raw reflectivity data to corrected, georeferenced and possibly gauge adjusted quantitative precipitation estimates. There are modules for data input/output, data transformation including Z/R transformation, clutter identification, attenuation correction, dual polarization and differential phase processing, interpolation, georeferencing, compositing, gauge adjustment, verification and visualization. The interpreted nature of the Python programming language makes wradlib an ideal tool

  12. Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction

    Science.gov (United States)

    Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping

    2017-10-01

    A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3

  13. Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

    Science.gov (United States)

    Isaac, G. A.; Joe, P. I.; Mailhot, J.; Bailey, M.; Bélair, S.; Boudala, F. S.; Brugman, M.; Campos, E.; Carpenter, R. L.; Crawford, R. W.; Cober, S. G.; Denis, B.; Doyle, C.; Reeves, H. D.; Gultepe, I.; Haiden, T.; Heckman, I.; Huang, L. X.; Milbrandt, J. A.; Mo, R.; Rasmussen, R. M.; Smith, T.; Stewart, R. E.; Wang, D.; Wilson, L. J.

    2014-01-01

    A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0-6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.

  14. Application of Volumetric Weather Radar Data and the Distributed Rainfall Runoff Model REW in the Ourthe Catchment

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Torfs, P.; Uijlenhoet, R.; Weerts, A.; Reggiani, P.; Delobbe, L.

    2008-12-01

    In the southern Ardennes region of Belgium near the border with Luxembourg, the Royal Meteorological Institute of Belgium (RMI) installed a C-band Doppler weather radar at an elevation of 600 m in the year 2001. This volumetric weather radar scans over multiple elevations at a temporal resolution of 5 minutes. The current study explores the possibility of using the volumetric information of the precipitation field to correct for the effects of the Vertical Profile of Reflectivity (VPR) over the period October 1, 2002 until March 31, 2003. During this winter half year storm events are mainly stratiform, giving rise to bright band effects which can decrease the performance of the radar. Previous studies have shown multiple drawbacks in applying a single estimated VPR profile to correct such reflectivity data. Therefore, the focus here is on the temporal variability of the VPR as measured by the radar and its variability over different spatial scales. This information is applied to generate a number of possible rainfall fields. These realizations are employed to try to quantify some of the discrepancies in precipitation intensities as estimated by the weather radar and those measured by a raingauge network. The final step then is to assess their potential within a distributed rainfall runoff model. The 1597 km2 Ourthe catchment lies within 60 km of the radar. Over this medium sized watershed ten raingauges measuring at an hourly interval are more or less equally distributed. Near the outlet discharge data are collected at the same time step. The distributed hydrological Representative Elementary Watershed (REW) model is applied to model the hydrological behavior of the Ourthe over the six month period. The benefits of the high spatial and temporal resolution of weather radar data compared to a conventional raingauge network plus the possibility of generating multiple realizations of the precipitation field are expected to yield more information about the hydrological

  15. NWS Corrections to Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Form B-14 is the National Weather Service form entitled 'Notice of Corrections to Weather Records.' The forms are used to make corrections to observations on forms...

  16. Improving precipitation estimates over the western United States using GOES-R precipitation data

    Science.gov (United States)

    Karbalaee, N.; Kirstetter, P. E.; Gourley, J. J.

    2017-12-01

    Satellite remote sensing data with fine spatial and temporal resolution are widely used for precipitation estimation for different applications such as hydrological modeling, storm prediction, and flash flood monitoring. The Geostationary Operational Environmental Satellites-R series (GOES-R) is the next generation of environmental satellites that provides hydrologic, atmospheric, and climatic information every 30 seconds over the western hemisphere. The high-resolution and low-latency of GOES-R observations is essential for the monitoring and prediction of floods, specifically in the Western United States where the vantage point of space can complement the degraded weather radar coverage of the NEXRAD network. The GOES-R rainfall rate algorithm will yield deterministic quantitative precipitation estimates (QPE). Accounting for inherent uncertainties will further advance the GOES-R QPEs since with quantifiable error bars, the rainfall estimates can be more readily fused with ground radar products. On the ground, the high-resolution NEXRAD-based precipitation estimation from the Multi-Radar/Multi-Sensor (MRMS) system, which is now operational in the National Weather Service (NWS), is challenged due to a lack of suitable coverage of operational weather radars over complex terrain. Distribution of QPE uncertainties associated with the GOES-R deterministic retrievals are derived and analyzed using MRMS over regions with good radar coverage. They will be merged with MRMS-based probabilistic QPEs developed to advance multisensor QPE integration. This research aims at improving precipitation estimation over the CONUS by combining the observations from GOES-R and MRMS to provide consistent, accurate and fine resolution precipitation rates with uncertainties over the CONUS.

  17. An Ultra-high Resolution Synthetic Precipitation Data for Ungauged Sites

    Science.gov (United States)

    Kim, Hong-Joong; Choi, Kyung-Min; Oh, Jai-Ho

    2018-05-01

    Despite the enormous damage caused by record heavy rainfall, the amount of precipitation in areas without observation points cannot be known precisely. One way to overcome these difficulties is to estimate meteorological data at ungauged sites. In this study, we have used observation data over Seoul city to calculate high-resolution (250-meter resolution) synthetic precipitation over a 10-year (2005-2014) period. Furthermore, three cases are analyzed by evaluating the rainfall intensity and performing statistical analysis over the 10-year period. In the case where the typhoon "Meari" passed to the west coast during 28-30 June 2011, the Pearson correlation coefficient was 0.93 for seven validation points, which implies that the temporal correlation between the observed precipitation and synthetic precipitation was very good. It can be confirmed that the time series of observation and synthetic precipitation in the period almost completely matches the observed rainfall. On June 28-29, 2011, the estimation of 10 to 30 mm h-1 of continuous strong precipitation was correct. In addition, it is shown that the synthetic precipitation closely follows the observed precipitation for all three cases. Statistical analysis of 10 years of data reveals a very high correlation coefficient between synthetic precipitation and observed rainfall (0.86). Thus, synthetic precipitation data show good agreement with the observations. Therefore, the 250-m resolution synthetic precipitation amount calculated in this study is useful as basic data in weather applications, such as urban flood detection.

  18. Introducing GFWED: The Global Fire Weather Database

    Science.gov (United States)

    Field, R. D.; Spessa, A. C.; Aziz, N. A.; Camia, A.; Cantin, A.; Carr, R.; de Groot, W. J.; Dowdy, A. J.; Flannigan, M. D.; Manomaiphiboon, K.; hide

    2015-01-01

    The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5 latitude by 2-3 longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded data sets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia,Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DCD1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously identified in MERRAs precipitation, and they reinforce the need to consider alternative sources of precipitation data. GFWED can be used for analyzing historical relationships between fire weather and fire activity at continental and global scales, in identifying large-scale atmosphereocean controls on fire weather, and calibration of FWI-based fire prediction models.

  19. Soils and climate: redness and weathering as indicators of mean annual precipitation

    Science.gov (United States)

    Lucke, Bernhard

    2016-04-01

    Paleosols can be used as archives of past changes of climate and landscapes, but their interpretation has to be based on modern analogies such as Budyko's law of soil zonality. These can be very useful if the respective processes of soil formation are sufficiently well understood. However, some soils such as the Terra Rossa or Red Mediterranean Soils, that are widespread at the fringes of the steppes and deserts, are still disputed with regard to their genesis and environmental significance. In particular, there is no agreement whether they resemble current environmental conditions, or are inherited from climates or sediments of the past. In this context, a remarkable change of the color of surface soils can be observed when driving from the city of Irbid in Jordan towards the east. Soil color apparently changes slowly, but steadily from dark red to yellow colors. However, attempting to express these color changes in numerical form is challenging, and it seemed questionable whether color is indeed connected with soil weathering intensity, or an optical illusion. However, a systematic comparison of different approaches of calculating soil redness found that the CIELAB-color system is suited for numerical expressions of soil redness and performs better than the Munsell charts. Along the investigated transect in Jordan, soil color seems strongly connected with weathering intensity, since various weathering indicators point to a steady increase of soil development with moisture. This suggests that such indices can well be used in semi-arid areas of 250-600 mm of mean annual precipitation. A very strong correlation of magnetic enhancement and rainfall indicates that the investigated soils are forming in equilibrium with current climatic conditions, and regressions based on this gradient might be suited for estimating paleorainfalls recorded by buried paelosols. It seems therefore that surface Terra Rossa soils in Jordan can be in equilibrium with current climate

  20. Applications of Kalman filters based on non-linear functions to numerical weather predictions

    Directory of Open Access Journals (Sweden)

    G. Galanis

    2006-10-01

    Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.

  1. Applications of Kalman filters based on non-linear functions to numerical weather predictions

    Directory of Open Access Journals (Sweden)

    G. Galanis

    2006-10-01

    Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.

  2. Analysis of Roanoke Region Weather Patterns Under Global Teleconnections

    OpenAIRE

    LaRocque, Eric John

    2006-01-01

    This work attempts to relate global teleconnections, through physical phenomena such as the El Nino-Southern Oscillation (ENSO), Artic Oscillation (AO), North Atlantic Oscillation (NAO), and the Pacific North American (PNA) pattern to synoptic-scale weather patterns and precipitation in the Roanoke, Virginia region. The first chapter describes the behavior of the El Nino-Southern Oscillation (ENSO) by implementing non-homogeneous and homogeneous Markov Chain models on a monthly time series o...

  3. Impact of precipitation and land biophysical variables on the simulated discharge of European and Mediterranean rivers

    Science.gov (United States)

    Szczypta, C.; Decharme, B.; Carrer, D.; Calvet, J.-C.; Lafont, S.; Somot, S.; Faroux, S.; Martin, E.

    2012-09-01

    This study investigates the impact on river discharge simulations of errors in the precipitation forcing, together with changes in the representation of vegetation variables and of plant transpiration. The most recent European Centre for Medium-Range Weather Forecasts reanalysis (ERA-Interim) is used to drive the Interactions between Soil, Biosphere, and Atmosphere-Total Runoff Integrating Pathways (ISBA-TRIP) continental hydrological system over Europe and the Mediterranean basin over the 1991-2008 period. As ERA-Interim tends to underestimate precipitation, a number of precipitation corrections are proposed. In particular, the monthly Global Precipitation Climatology Centre (GPCC) precipitation product is used to bias-correct the 3-hourly ERA-Interim estimates. This correction markedly improves the match between the ISBA-TRIP simulations and the river discharge observations from the Global Runoff Data Centre (GRDC), at 150 gauging stations. The impact on TRIP river discharge simulations of various representations of the evapotranspiration in the ISBA land surface model is investigated as well: ISBA is used together with its upgraded carbon flux version (ISBA-A-gs). The latter is either driven by the satellite-derived climatology of the Leaf Area Index (LAI) used by ISBA, or performs prognostic LAI simulations. The ISBA-A-gs model, with or without dynamically simulated LAI, allows a better representation of river discharge at low water levels. On the other hand, ISBA-A-gs does not perform as well as the original ISBA model at springtime.

  4. A Precipitation Climatology of the Snowy Mountains, Australia

    Science.gov (United States)

    Theobald, Alison; McGowan, Hamish; Speirs, Johanna

    2014-05-01

    The precipitation that falls in the Snowy Mountains region of southeastern Australia provides critical water resources for hydroelectric power generation. Water storages in this region are also a major source of agricultural irrigation, environmental flows, and offer a degree of flood protection for some of the major river systems in Australia. Despite this importance, there remains a knowledge gap regarding the long-term, historic variability of the synoptic weather systems that deliver precipitation to the region. This research aims to increase the understanding of long-term variations in precipitation-bearing weather systems resulting in runoff into the Snowy Mountains catchments and reservoirs, and the way in which these are influenced by large-scale climate drivers. Here we present initial results on the development of a climatology of precipitation-bearing synoptic weather systems (synoptic typology), spanning a period of over 100 years. The synoptic typology is developed from the numerical weather model re-analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), in conjunction with regional precipitation and temperature data from a network of private gauges. Given the importance of surface, mid- and upper-air patterns on seasonal precipitation, the synoptic typing will be based on a range of meteorological variables throughout the depth of the troposphere, highlighting the importance of different atmospheric levels on the development and steering of synoptic precipitation bearing systems. The temporal and spatial variability of these synoptic systems, their response to teleconnection forcings and their contribution to inflow generation in the headwater catchments of the Snowy Mountains will be investigated. The resulting climatology will provide new understanding of the drivers of regional-scale precipitation variability at inter- and intra-annual timescales. It will enable greater understanding of how variability in synoptic scale

  5. Investigation of Weather Radar Quantitative Precipitation Estimation Methodologies in Complex Orography

    Directory of Open Access Journals (Sweden)

    Mario Montopoli

    2017-02-01

    Full Text Available Near surface quantitative precipitation estimation (QPE from weather radar measurements is an important task for feeding hydrological models, limiting the impact of severe rain events at the ground as well as aiding validation studies of satellite-based rain products. To date, several works have analyzed the performance of various QPE algorithms using actual and synthetic experiments, possibly trained by measurement of particle size distributions and electromagnetic models. Most of these studies support the use of dual polarization radar variables not only to ensure a good level of data quality but also as a direct input to rain estimation equations. One of the most important limiting factors in radar QPE accuracy is the vertical variability of particle size distribution, which affects all the acquired radar variables as well as estimated rain rates at different levels. This is particularly impactful in mountainous areas, where the sampled altitudes are likely several hundred meters above the surface. In this work, we analyze the impact of the vertical profile variations of rain precipitation on several dual polarization radar QPE algorithms when they are tested in a complex orography scenario. So far, in weather radar studies, more emphasis has been given to the extrapolation strategies that use the signature of the vertical profiles in terms of radar co-polar reflectivity. This may limit the use of the radar vertical profiles when dual polarization QPE algorithms are considered. In that case, all the radar variables used in the rain estimation process should be consistently extrapolated at the surface to try and maintain the correlations among them. To avoid facing such a complexity, especially with a view to operational implementation, we propose looking at the features of the vertical profile of rain (VPR, i.e., after performing the rain estimation. This procedure allows characterization of a single variable (i.e., rain when dealing with

  6. A hybrid convection scheme for use in non-hydrostatic numerical weather prediction models

    Directory of Open Access Journals (Sweden)

    Volker Kuell

    2008-12-01

    Full Text Available The correct representation of convection in numerical weather prediction (NWP models is essential for quantitative precipitation forecasts. Due to its small horizontal scale convection usually has to be parameterized, e.g. by mass flux convection schemes. Classical schemes originally developed for use in coarse grid NWP models assume zero net convective mass flux, because the whole circulation of a convective cell is confined to the local grid column and all convective mass fluxes cancel out. However, in contemporary NWP models with grid sizes of a few kilometers this assumption becomes questionable, because here convection is partially resolved on the grid. To overcome this conceptual problem we propose a hybrid mass flux convection scheme (HYMACS in which only the convective updrafts and downdrafts are parameterized. The generation of the larger scale environmental subsidence, which may cover several grid columns, is transferred to the grid scale equations. This means that the convection scheme now has to generate a net convective mass flux exerting a direct dynamical forcing to the grid scale model via pressure gradient forces. The hybrid convection scheme implemented into the COSMO model of Deutscher Wetterdienst (DWD is tested in an idealized simulation of a sea breeze circulation initiating convection in a realistic manner. The results are compared with analogous simulations with the classical Tiedtke and Kain-Fritsch convection schemes.

  7. Vertical Pointing Weather Radar for Built-up Urban Areas

    DEFF Research Database (Denmark)

    Rasmussen, Michael R.; Thorndahl, Søren; Schaarup-Jensen, Kjeld

    2008-01-01

      A cost effective vertical pointing X-band weather radar (VPR) has been tested for measurement of precipitation in urban areas. Stationary tests indicate that the VPR performs well compared to horizontal weather radars, such as the local area weather radars (LAWR). The test illustrated...

  8. Generation of future potential scenarios in an Alpine Catchment by applying bias-correction techniques, delta-change approaches and stochastic Weather Generators at different spatial scale. Analysis of their influence on basic and drought statistics.

    Science.gov (United States)

    Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Iguzquiza, Eulogio

    2017-04-01

    Assessing impacts of potential future climate change scenarios in precipitation and temperature is essential to design adaptive strategies in water resources systems. The objective of this work is to analyze the possibilities of different statistical downscaling methods to generate future potential scenarios in an Alpine Catchment from historical data and the available climate models simulations performed in the frame of the CORDEX EU project. The initial information employed to define these downscaling approaches are the historical climatic data (taken from the Spain02 project for the period 1971-2000 with a spatial resolution of 12.5 Km) and the future series provided by climatic models in the horizon period 2071-2100 . We have used information coming from nine climate model simulations (obtained from five different Regional climate models (RCM) nested to four different Global Climate Models (GCM)) from the European CORDEX project. In our application we have focused on the Representative Concentration Pathways (RCP) 8.5 emissions scenario, which is the most unfavorable scenario considered in the fifth Assessment Report (AR5) by the Intergovernmental Panel on Climate Change (IPCC). For each RCM we have generated future climate series for the period 2071-2100 by applying two different approaches, bias correction and delta change, and five different transformation techniques (first moment correction, first and second moment correction, regression functions, quantile mapping using distribution derived transformation and quantile mapping using empirical quantiles) for both of them. Ensembles of the obtained series were proposed to obtain more representative potential future climate scenarios to be employed to study potential impacts. In this work we propose a non-equifeaseble combination of the future series giving more weight to those coming from models (delta change approaches) or combination of models and techniques that provides better approximation to the basic

  9. Introducing the Global Fire WEather Database (GFWED)

    Science.gov (United States)

    Field, R. D.

    2015-12-01

    The Canadian Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations beginning in 1980 called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5° latitude by 2/3° longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded datasets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia, Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA-based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DC=1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously-identified in MERRA's precipitation and reinforce the need to consider alternative sources of precipitation data. GFWED is being used by researchers around the world for analyzing historical relationships between fire weather and fire activity at large scales, in identifying large-scale atmosphere-ocean controls on fire weather, and calibration of FWI-based fire prediction models. These applications will be discussed. More information on GFWED can be found at http://data.giss.nasa.gov/impacts/gfwed/

  10. Identification of large-scale meteorological patterns associated with extreme precipitation in the US northeast

    Science.gov (United States)

    Agel, Laurie; Barlow, Mathew; Feldstein, Steven B.; Gutowski, William J.

    2018-03-01

    Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979-2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.

  11. Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model

    Science.gov (United States)

    Sahyoun, Maher; Korsholm, Ulrik S.; Sørensen, Jens H.; Šantl-Temkiv, Tina; Finster, Kai; Gosewinkel, Ulrich; Nielsen, Niels W.

    2017-12-01

    Bacterial ice-nucleating particles (INP) have the ability to facilitate ice nucleation from super-cooled cloud droplets at temperatures just below the melting point. Bacterial INP have been detected in cloud water, precipitation, and dry air, hence they may have an impact on weather and climate. In modeling studies, the potential impact of bacteria on ice nucleation and precipitation formation on global scale is still uncertain due to their small concentration compared to other types of INP, i.e. dust. Those earlier studies did not account for the yet undetected high concentration of nanoscale fragments of bacterial INP, which may be found free or attached to soil dust in the atmosphere. In this study, we investigate the sensitivity of modeled cloud ice, precipitation and global solar radiation in different weather scenarios to changes in the fraction of cloud droplets containing bacterial INP, regardless of their size. For this purpose, a module that calculates the probability of ice nucleation as a function of ice nucleation rate and bacterial INP fraction was developed and implemented in a numerical weather prediction model. The threshold value for the fraction of cloud droplets containing bacterial INP needed to produce a 1% increase in cloud ice was determined at 10-5 to 10-4. We also found that increasing this fraction causes a perturbation in the forecast, leading to significant differences in cloud ice and smaller differences in convective and total precipitation and in net solar radiation reaching the surface. These effects were most pronounced in local convective events. Our results show that bacterial INP can be considered as a trigger factor for precipitation, but not an enhancement factor.

  12. Non-Uniformity Correction Using Nonlinear Characteristic Performance Curves for Calibration

    Science.gov (United States)

    Lovejoy, McKenna Roberts

    Infrared imaging is an expansive field with many applications. Advances in infrared technology have lead to a greater demand from both commercial and military sectors. However, a known problem with infrared imaging is its non-uniformity. This non-uniformity stems from the fact that each pixel in an infrared focal plane array has its own photoresponse. Many factors such as exposure time, temperature, and amplifier choice affect how the pixels respond to incoming illumination and thus impact image uniformity. To improve performance non-uniformity correction (NUC) techniques are applied. Standard calibration based techniques commonly use a linear model to approximate the nonlinear response. This often leaves unacceptable levels of residual non-uniformity. Calibration techniques often have to be repeated during use to continually correct the image. In this dissertation alternates to linear NUC algorithms are investigated. The goal of this dissertation is to determine and compare nonlinear non-uniformity correction algorithms. Ideally the results will provide better NUC performance resulting in less residual non-uniformity as well as reduce the need for recalibration. This dissertation will consider new approaches to nonlinear NUC such as higher order polynomials and exponentials. More specifically, a new gain equalization algorithm has been developed. The various nonlinear non-uniformity correction algorithms will be compared with common linear non-uniformity correction algorithms. Performance will be compared based on RMS errors, residual non-uniformity, and the impact quantization has on correction. Performance will be improved by identifying and replacing bad pixels prior to correction. Two bad pixel identification and replacement techniques will be investigated and compared. Performance will be presented in the form of simulation results as well as before and after images taken with short wave infrared cameras. The initial results show, using a third order

  13. Corrective Action Investigation Plan for Corrective Action Unit 321: Area 22 Weather Station Fuel Storage, Nevada Test Site, Nevada; TOPICAL

    International Nuclear Information System (INIS)

    1999-01-01

    This Corrective Action Investigation Plan (CAIP) has been developed in accordance with the Federal Facility Agreement and Consent Order (FFACO) that was agreed to by the US Department of Energy, Nevada Operations Office (DOE/NV); the State of Nevada Division of Environmental Protection (NDEP); and the US Department of Defense (FFACO, 1996). The CAIP is a document that provides or references all of the specific information for investigation activities associated with Corrective Action Units (CAUs) or Corrective Action Sites (CASs). According to the FFACO (1996), CASs are sites potentially requiring corrective action(s) and may include solid waste management units or individual disposal or release sites. A CAU consists of one or more CASs grouped together based on geography, technical similarity, or agency responsibility for the purpose of determining corrective actions. This CAIP contains the environmental sample collection objectives and the criteria for conducting site investigation activities at the CAU 321 Area 22 Weather Station Fuel Storage, CAS 22-99-05 Fuel Storage Area. For purposes of this discussion, this site will be referred to as either CAU 321 or the Fuel Storage Area. The Fuel Storage Area is located in Area 22 of the Nevada Test Site (NTS). The NTS is approximately 105 kilometers (km) (65 miles[mi]) northwest of Las Vegas, Nevada (Figure 1-1) (DOE/NV, 1996a). The Fuel Storage Area (Figure 1-2) was used to store fuel and other petroleum products necessary for motorized operations at the historic Camp Desert Rock facility which was operational from 1951 to 1958 at the Nevada Test Site, Nevada. The site was dismantled after 1958 (DOE/NV, 1996a)

  14. Chronic repeated exposure to weather-related stimuli elicits few symptoms of chronic stress in captive molting and non-molting European starlings (Sturnus vulgaris).

    Science.gov (United States)

    de Bruijn, Robert; Reed, J Michael; Romero, L Michael

    2017-10-01

    Repeated exposure to acute stressors causes dramatic changes in an animal's stress physiology and the cumulative effects are often called chronic stress. Recently we showed that short-term exposure to weather-related stimuli, such as temperature change, artificial precipitation, and food restriction, cause acute responses in captive European starlings (Sturnus vulgaris). Here, we examined the effect of repeated exposure to weather-related stressors on heart rate and corticosterone (CORT) of captive non-molting and molting European starlings. Four times every day for 3 weeks, birds were exposed to either 30 min of a subtle (3°C) decrease in temperature, a short bout of simulated rain, or 2 hr of food removal. The order and time of presentation were randomly assigned on each day. We found no differences in heart rate or heart rate variability. Furthermore, there were no changes in baseline CORT levels, CORT negative feedback efficacy, or maximal adrenal capacity. Mass increased across the experimental period only in molting birds. CORT responses to restraint were decreased in both groups following treatment, suggesting the birds had downregulated their responses to acute stress. Molting birds showed evidence of suppression of the HPA axis compared with non-molting birds, which is consistent with previous research. Overall, our data show that repeated exposure to weather-related stressors does not elicit most of the symptoms normally associated with chronic stress. © 2018 Wiley Periodicals, Inc.

  15. The Potential of Tropospheric Gradients for Regional Precipitation Prediction

    Science.gov (United States)

    Boisits, Janina; Möller, Gregor; Wittmann, Christoph; Weber, Robert

    2017-04-01

    Changes of temperature and humidity in the neutral atmosphere cause variations in tropospheric path delays and tropospheric gradients. By estimating zenith wet delays (ZWD) and gradients using a GNSS reference station network the obtained time series provide information about spatial and temporal variations of water vapour in the atmosphere. Thus, GNSS-based tropospheric parameters can contribute to the forecast of regional precipitation events. In a recently finalized master thesis at TU Wien the potential of tropospheric gradients for weather prediction was investigated. Therefore, ZWD and gradient time series at selected GNSS reference stations were compared to precipitation data over a period of six months (April to September 2014). The selected GNSS stations form two test areas within Austria. All required meteorological data was provided by the Central Institution for Meteorology and Geodynamics (ZAMG). Two characteristics in ZWD and gradient time series can be anticipated in case of an approaching weather front. First, an induced asymmetry in tropospheric delays results in both, an increased magnitude of the gradient and in gradients pointing towards the weather front. Second, an increase in ZWD reflects the increased water vapour concentration right before a precipitation event. To investigate these characteristics exemplary test events were processed. On the one hand, the sequence of the anticipated increase in ZWD at each GNSS station obtained by cross correlation of the time series indicates the direction of the approaching weather front. On the other hand, the corresponding peak in gradient time series allows the deduction of the direction of movement as well. To verify the results precipitation data from ZAMG was used. It can be deduced, that tropospheric gradients show high potential for predicting precipitation events. While ZWD time series rather indicate the orientation of the air mass boundary, gradients rather indicate the direction of movement

  16. 21st Century Changes in Precipitation Extremes Based on Resolved Atmospheric Patterns

    Science.gov (United States)

    Gao, X.; Schlosser, C. A.; O'Gorman, P. A.; Monier, E.

    2014-12-01

    Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency distribution of precipitation, especially at the regional scale. In this study, a validated analogue method is employed to diagnose the potential future shifts in the probability of extreme precipitation over the United States under global warming. The method is based on the use of the resolved large-scale meteorological conditions (i.e. flow features, moisture supply) to detect the occurrence of extreme precipitation. The CMIP5 multi-model projections have been compiled for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The application of such analogue method to detect other types of hazard events, i.e. landslides is also explored. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.

  17. Precipitation Matters

    Science.gov (United States)

    McDuffie, Thomas

    2007-01-01

    Although weather, including its role in the water cycle, is included in most elementary science programs, any further examination of raindrops and snowflakes is rare. Together rain and snow make up most of the precipitation that replenishes Earth's life-sustaining fresh water supply. When viewed individually, raindrops and snowflakes are quite…

  18. Relation between the St. Louis urban precipitation anomaly and synoptic weather factors

    International Nuclear Information System (INIS)

    Vogel, J.L.; Huff, F.A.

    1978-01-01

    The summer (June--August) rainfall distribution on the METROMEX network was analyzed to determine the synoptic conditions during which the urban-industrial regions of St. Louis affect the precipitation process. The rainfall patterns were stratified by direction of movement of convective entities in storm systems, surface wind direction, and basic synoptic weather types. The results provide support for enhancement of rainfall downstorm from the urban-industrial region. Although only 23% of the 330 storms moved from the west-southwest, the storms produced 42% of the network rainfall and were strong contributors to the rainfall anomaly that maximizes 25--30 km northeast of St. Louis. Cold front conditions with the major convective entities moving from the southwest, and squall lines with any storm motion were associated with the most intense rainstorms over the raingage network, and these storms were also largely responsible for the rainfall anomaly. The rainfall pattern based on air mass storms did not indicate any The rainfall pattern based on air mass storms did not indicate any significant urban enhancement of rainfall and study of squall zone storms suggested possible reduction of rainfall in the urban region

  19. Precipitation in as-solidified undercooled Ni-Si hypoeutectic alloy: Effect of non-equilibrium solidification

    Energy Technology Data Exchange (ETDEWEB)

    Fan Kai [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an, Shaanxi 710072 (China); Liu Feng, E-mail: liufeng@nwpu.edu.cn [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an, Shaanxi 710072 (China); Yang Gencang; Zhou Yaohe [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi' an, Shaanxi 710072 (China)

    2011-08-25

    Highlights: {yields} The solid solubility of Si atom in {alpha}-Ni matrix increased with undercooling in the as-solidified sample. {yields} The effect of non-equilibrium solidification on precipitation has been theoretically described. {yields} The nucleation density, the real-time particle size and the precipitation rate are all increased upon annealing. {yields} The precipitate process can be artificially controlled by modifying the initial melt undercooling and the annealing time. - Abstract: Applying glass fluxing and cyclic superheating, high undercooling up to {approx}350 K was achieved for Ni-Si hypoeutectic alloy melt. By isothermally annealing the as-solidified alloy subjected to different undercoolings, precipitation behavior of Ni{sub 3}Si particle, at 973 K, was systematically studied. It was found that, the nucleation density and the real-time particle size, as well as the precipitation rate, were all increased, provided the sample was solidified subjected to higher undercooling. This was ascribed mainly to the increased solid solubility of Si atom in {alpha}-Ni matrix upon non-equilibrium solidification. On this basis, the non-equilibrium dendrite growth upon solidification and the soft impingement prevailing upon solid-state precipitation have been quantitatively connected. As such, the effect of liquid/solid transformation on subsequent precipitation was described.

  20. Precipitation in as-solidified undercooled Ni-Si hypoeutectic alloy: Effect of non-equilibrium solidification

    International Nuclear Information System (INIS)

    Fan Kai; Liu Feng; Yang Gencang; Zhou Yaohe

    2011-01-01

    Highlights: → The solid solubility of Si atom in α-Ni matrix increased with undercooling in the as-solidified sample. → The effect of non-equilibrium solidification on precipitation has been theoretically described. → The nucleation density, the real-time particle size and the precipitation rate are all increased upon annealing. → The precipitate process can be artificially controlled by modifying the initial melt undercooling and the annealing time. - Abstract: Applying glass fluxing and cyclic superheating, high undercooling up to ∼350 K was achieved for Ni-Si hypoeutectic alloy melt. By isothermally annealing the as-solidified alloy subjected to different undercoolings, precipitation behavior of Ni 3 Si particle, at 973 K, was systematically studied. It was found that, the nucleation density and the real-time particle size, as well as the precipitation rate, were all increased, provided the sample was solidified subjected to higher undercooling. This was ascribed mainly to the increased solid solubility of Si atom in α-Ni matrix upon non-equilibrium solidification. On this basis, the non-equilibrium dendrite growth upon solidification and the soft impingement prevailing upon solid-state precipitation have been quantitatively connected. As such, the effect of liquid/solid transformation on subsequent precipitation was described.

  1. Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes

    Science.gov (United States)

    Johnson, Christopher M.; Fan, Xingang; Mahmood, Rezaul; Groves, Chris; Polk, Jason S.; Yan, Jun

    2018-03-01

    Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land-atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant

  2. Effect of non-metallic precipitates and grain size on core loss of non-oriented electrical silicon steels

    Science.gov (United States)

    Wang, Jiayi; Ren, Qiang; Luo, Yan; Zhang, Lifeng

    2018-04-01

    In the current study, the number density and size of non-metallic precipitates and the size of grains on the core loss of the 50W800 non-oriented electrical silicon steel sheets were investigated. The number density and size of precipitates and grains were statistically analyzed using an automatic scanning electron microscope (ASPEX) and an optical microscope. Hypothesis models were established to reveal the physical feature for the function of grain size and precipitates on the core loss of the steel. Most precipitates in the steel were AlN particles smaller than 1 μm so that were detrimental to the core loss of the steel. These finer AlN particles distributed on the surface of the steel sheet. The relationship between the number density of precipitates (x in number/mm2 steel area) and the core loss (P1.5/50 in W/kg) was regressed as P1.5/50 = 4.150 + 0.002 x. The average grain size was approximately 25-35 μm. The relationship between the core loss and grain size (d in μm) was P1.5/50 = 3.851 + 20.001 d-1 + 60.000 d-2.

  3. On the Precipitation and Precipitation Change in Alaska

    Directory of Open Access Journals (Sweden)

    Gerd Wendler

    2017-12-01

    Full Text Available Alaska observes very large differences in precipitation throughout the state; southeast Alaska experiences consistently wet conditions, while northern Arctic Alaska observes very dry conditions. The maximum mean annual precipitation of 5727 mm is observed in the southeastern panhandle at Little Port Arthur, while the minimum of 92 mm occurs on the North Slope at Kuparuk. Besides explaining these large differences due to geographic and orographic location, we discuss the changes in precipitation with time. Analyzing the 18 first-order National Weather Service stations, we found that the total average precipitation in the state increased by 17% over the last 67 years. The observed changes in precipitation are furthermore discussed as a function of the observed temperature increase of 2.1 °C, the mean temperature change of the 18 stations over the same period. This observed warming of Alaska is about three times the magnitude of the mean global warming and allows the air to hold more water vapor. Furthermore, we discuss the effect of the Pacific Decadal Oscillation (PDO, which has a strong influence on both the temperature and precipitation in Alaska.

  4. Hydrologic applications of weather radar

    Science.gov (United States)

    Seo, Dong-Jun; Habib, Emad; Andrieu, Hervé; Morin, Efrat

    2015-12-01

    By providing high-resolution quantitative precipitation information (QPI), weather radars have revolutionized hydrology in the last two decades. With the aid of GIS technology, radar-based quantitative precipitation estimates (QPE) have enabled routine high-resolution hydrologic modeling in many parts of the world. Given the ever-increasing need for higher-resolution hydrologic and water resources information for a wide range of applications, one may expect that the use of weather radar will only grow. Despite the tremendous progress, a number of significant scientific, technological and engineering challenges remain to realize its potential. New challenges are also emerging as new areas of applications are discovered, explored and pursued. The purpose of this special issue is to provide the readership with some of the latest advances, lessons learned, experiences gained, and science issues and challenges related to hydrologic applications of weather radar. The special issue features 20 contributions on various topics which reflect the increasing diversity as well as the areas of focus in radar hydrology today. The contributions may be grouped as follows:

  5. A test for Improvement of high resolution Quantitative Precipitation Estimation for localized heavy precipitation events

    Science.gov (United States)

    Lee, Jung-Hoon; Roh, Joon-Woo; Park, Jeong-Gyun

    2017-04-01

    Accurate estimation of precipitation is one of the most difficult and significant tasks in the area of weather diagnostic and forecasting. In the Korean Peninsula, heavy precipitations are caused by various physical mechanisms, which are affected by shortwave trough, quasi-stationary moisture convergence zone among varying air masses, and a direct/indirect effect of tropical cyclone. In addition to, various geographical and topographical elements make production of temporal and spatial distribution of precipitation is very complicated. Especially, localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances. In weather radar data with high temporal and spatial resolution, accurate estimation of rain rate from radar reflectivity data is too difficult. Z-R relationship (Marshal and Palmer 1948) have adapted representatively. In addition to, several methods such as support vector machine (SVM), neural network, Fuzzy logic, Kriging were utilized in order to improve the accuracy of rain rate. These methods show the different quantitative precipitation estimation (QPE) and the performances of accuracy are different for heavy precipitation cases. In this study, in order to improve the accuracy of QPE for localized heavy precipitation, ensemble method for Z-R relationship and various techniques was tested. This QPE ensemble method was developed by a concept based on utilizing each advantage of precipitation calibration methods. The ensemble members were produced for a combination of different Z-R coefficient and calibration method.

  6. Rainfall estimation for hydrology using volumetric weather radar

    NARCIS (Netherlands)

    Hazenberg, P.

    2013-01-01

    This thesis focuses specifically on weather radar rainfall measurements in strati form precipitation. In North-Western Europe this type of precipitation is most dominant in winter and leads to the largest hydro logical response of catchments. Unfortunately, the quality of uncorrected radar rainfall

  7. US Weather Bureau Storm Reports

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather Bureau and US Army Corps and other reports of storms from 1886-1955. Hourly precipitation from recording rain gauges captured during heavy rain, snow,...

  8. How Cities Make Their Own Weather

    Science.gov (United States)

    Shepherd, J. Marshall

    2004-01-01

    Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in d e near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. We will also present results from experiments using a regional atmospheric-land surface modeling system. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

  9. Hydrological Applications of a High-Resolution Radar Precipitation Data Base for Sweden

    Science.gov (United States)

    Olsson, Jonas; Berg, Peter; Norin, Lars; Simonsson, Lennart

    2017-04-01

    There is an increasing need for high-resolution observations of precipitation on local, regional, national and even continental level. Urbanization and other environmental changes often make societies more vulnerable to intense short-duration rainfalls (cloudbursts) and their consequences in terms of e.g. flooding and landslides. Impact and forecasting models of these hazards put very high demands on the rainfall input in terms of both resolution and accuracy. Weather radar systems obviously have a great potential in this context, but also limitations with respect to e.g. conversion algorithms and various error sources that may have a significant impact on the subsequent hydrological modelling. In Sweden, the national weather radar network has been in operation for nearly three decades, but until recently the hydrological applications have been very limited. This is mainly because of difficulties in managing the different errors and biases in the radar precipitation product, which made it hard to demonstrate any distinct added value as compared with gauge-based precipitation products. In the last years, however, in light of distinct progress in developing error correction procedures, substantial efforts have been made to develop a national gauge-adjusted radar precipitation product - HIPRAD (High-Resolution Precipitation from Gauge-Adjusted Weather Radar). In HIPRAD, the original radar precipitation data are scaled to match the monthly accumulations in a national grid (termed PTHBV) created by optimal interpolation of corrected daily gauge observations, with the intention to attain both a high spatio-temporal resolution and accurate long-term accumulations. At present, HIPRAD covers the period 2000-present with resolutions 15 min and 2×2 km2. A key motivation behind the development of HIPRAD is the intention to increase the temporal resolution in the national flood forecasting system from 1 day to 1 hour. Whereas a daily time step is sufficient to describe the

  10. Impacts of weather on long-term patterns of plant richness and diversity vary with location and management.

    Science.gov (United States)

    Jonas, Jayne L; Buhl, Deborah A; Symstad, Amy J

    2015-09-01

    Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity

  11. Bias correction of daily precipitation projected by the CORDEX-Africa ensemble for a sparsely gauged region in West Africa with regionalized distribution parameters

    Science.gov (United States)

    Lorenz, Manuel; Bliefernicht, Jan; Laux, Patrick; Kunstmann, Harald

    2017-04-01

    Reliable estimates of future climatic conditions are indispensable for the sustainable planning of agricultural activities in West Africa. Precipitation time series of regional climate models (RCMs) typically exhibit a bias in the distribution of both rainfall intensities and wet day frequencies. Furthermore, the annual and monthly sums of precipitation may remarkably vary from the observations in this region. As West Africa experiences a distinct rainy season, sowing dates are oftentimes planned based on the beginning of this rainfall period. A biased representation of the annual cycle of precipitation in the uncorrected RCMs can therefore lead to crop failure. The precipitation ensemble, obtained from the Coordinated Downscaling Experiment CORDEX-Africa, was bias-corrected for the study region in West Africa (extending approximately 343,358 km2) which covers large parts of Burkina Faso, Ghana and Benin. In oder to debias the RCM precipitation simulations, a Quantile-Mapping method was applied to the historical period 1950-2005. For the RCM future projections (2006-2100), the Double-Quantile-Mapping procedure was chosen. This method makes use of the shift in the distribution function of the future precipitation values which allows to incorporate the climate change signal of the RCM projections into the bias correction. As large areas of the study region are ungauged, the assignment of the information from the nearest station to the ungauged location would lead to sharp changes in the estimated statistics from one location to another. Thus, the distribution parameters needed for the Quantile-Mapping were estimated by Kriging the distribution parameters of the available measurement stations. This way it is possible to obtain reasonable estimates of the expected distribution of precipitation at ungauged locations. The presentation will illustrate some aspects and trade-offs in the distribution parameter interpolation as well as an analysis of the uncertainties of the

  12. Weather Station: Hawaii: Oahu: Coconut Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Hawaii Institute of Marine Biology (HIMB) automatic weather station (AWS) records hourly measurements of precipitation, air temperature, wind speed and...

  13. Height drift correction in non-raster atomic force microscopy

    Energy Technology Data Exchange (ETDEWEB)

    Meyer, Travis R. [Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095 (United States); Ziegler, Dominik [Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Brune, Christoph [Institute for Computational and Applied Mathematics, University of Münster (Germany); Chen, Alex [Statistical and Applied Mathematical Sciences Institute, Research Triangle Park, NC 27709 (United States); Farnham, Rodrigo; Huynh, Nen; Chang, Jen-Mei [Department of Mathematics and Statistics, California State University Long Beach, Long Beach, CA 90840 (United States); Bertozzi, Andrea L., E-mail: bertozzi@math.ucla.edu [Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095 (United States); Ashby, Paul D., E-mail: pdashby@lbl.gov [Molecular Foundry, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)

    2014-02-01

    We propose a novel method to detect and correct drift in non-raster scanning probe microscopy. In conventional raster scanning drift is usually corrected by subtracting a fitted polynomial from each scan line, but sample tilt or large topographic features can result in severe artifacts. Our method uses self-intersecting scan paths to distinguish drift from topographic features. Observing the height differences when passing the same position at different times enables the reconstruction of a continuous function of drift. We show that a small number of self-intersections is adequate for automatic and reliable drift correction. Additionally, we introduce a fitness function which provides a quantitative measure of drift correctability for any arbitrary scan shape. - Highlights: • We propose a novel height drift correction method for non-raster SPM. • Self-intersecting scans enable the distinction of drift from topographic features. • Unlike conventional techniques our method is unsupervised and tilt-invariant. • We introduce a fitness measure to quantify correctability for general scan paths.

  14. Seafloor weathering buffering climate: numerical experiments

    Science.gov (United States)

    Farahat, N. X.; Archer, D. E.; Abbot, D. S.

    2013-12-01

    Continental silicate weathering is widely held to consume atmospheric CO2 at a rate controlled in part by temperature, resulting in a climate-weathering feedback [Walker et al., 1981]. It has been suggested that weathering of oceanic crust of warm mid-ocean ridge flanks also has a CO2 uptake rate that is controlled by climate [Sleep and Zahnle, 2001; Brady and Gislason, 1997]. Although this effect might not be significant on present-day Earth [Caldeira, 1995], seafloor weathering may be more pronounced during snowball states [Le Hir et al., 2008], during the Archean when seafloor spreading rates were faster [Sleep and Zahnle, 2001], and on waterworld planets [Abbot et al., 2012]. Previous studies of seafloor weathering have made significant contributions using qualitative, generally one-box, models, and the logical next step is to extend this work using a spatially resolved model. For example, experiments demonstrate that seafloor weathering reactions are temperature dependent, but it is not clear whether the deep ocean temperature affects the temperature at which the reactions occur, or if instead this temperature is set only by geothermal processes. Our goal is to develop a 2-D numerical model that can simulate hydrothermal circulation and resulting alteration of oceanic basalts, and can therefore address such questions. A model of diffusive and convective heat transfer in fluid-saturated porous media simulates hydrothermal circulation through porous oceanic basalt. Unsteady natural convection is solved for using a Darcy model of porous media flow that has been extensively benchmarked. Background hydrothermal circulation is coupled to mineral reaction kinetics of basaltic alteration and hydrothermal mineral precipitation. In order to quantify seafloor weathering as a climate-weathering feedback process, this model focuses on hydrothermal reactions that influence carbon uptake as well as ocean alkalinity: silicate rock dissolution, calcium and magnesium leaching

  15. Precipitation formation in recrystallized nickel-plated non-sag tungsten wire

    International Nuclear Information System (INIS)

    Lai, Z.H.

    1994-01-01

    It is well established that some metals, such as palladium and nickel, can easily penetrate into tungsten by fast diffusion via crystal defects such as grain boundaries and dislocations. As a result of the fast penetration of these so called activators the recrystallization temperature of heavily drawn non-sag tungsten wire can be lower from about 2,000 C to about 1,000 C, thus the application of the tungsten wire, serving as reinforcement material in metal matrix composites used at high temperatures, is limited. An interesting question is in which form these activators exist in the recrystallized tungsten wire. It is generally believed that W-Ni intermediate compounds could form in the recrystallized material, presumably at grain boundaries. The free energy difference between the pure tungsten fibbers and the precipitating W(Ni) solid solution was suggested as the chemical driving force which governed the recrystallization process. The presence of nickel in small particles had also been observed in recrystallized grains of nickel plated tungsten wires using scanning electron microscopy (SEM) and secondary ion mass spectroscopy. These particles were considered to be nickel rich precipitates. However, a detailed investigation of the precipitation process has not been reported. In the present work an investigation of the structure, composition and distribution of nickel rich particles precipitated in recrystallized grains of nickel plated heavily drawn non-sage tungsten wires was carried out using analytical electron microscopy (AEM)

  16. A conditional stochastic weather generator for seasonal to multi-decadal simulations

    Science.gov (United States)

    Verdin, Andrew; Rajagopalan, Balaji; Kleiber, William; Podestá, Guillermo; Bert, Federico

    2018-01-01

    We present the application of a parametric stochastic weather generator within a nonstationary context, enabling simulations of weather sequences conditioned on interannual and multi-decadal trends. The generalized linear model framework of the weather generator allows any number of covariates to be included, such as large-scale climate indices, local climate information, seasonal precipitation and temperature, among others. Here we focus on the Salado A basin of the Argentine Pampas as a case study, but the methodology is portable to any region. We include domain-averaged (e.g., areal) seasonal total precipitation and mean maximum and minimum temperatures as covariates for conditional simulation. Areal covariates are motivated by a principal component analysis that indicates the seasonal spatial average is the dominant mode of variability across the domain. We find this modification to be effective in capturing the nonstationarity prevalent in interseasonal precipitation and temperature data. We further illustrate the ability of this weather generator to act as a spatiotemporal downscaler of seasonal forecasts and multidecadal projections, both of which are generally of coarse resolution.

  17. Quantitative precipitation estimation based on high-resolution numerical weather prediction and data assimilation with WRF – a performance test

    Directory of Open Access Journals (Sweden)

    Hans-Stefan Bauer

    2015-04-01

    Full Text Available Quantitative precipitation estimation and forecasting (QPE and QPF are among the most challenging tasks in atmospheric sciences. In this work, QPE based on numerical modelling and data assimilation is investigated. Key components are the Weather Research and Forecasting (WRF model in combination with its 3D variational assimilation scheme, applied on the convection-permitting scale with sophisticated model physics over central Europe. The system is operated in a 1-hour rapid update cycle and processes a large set of in situ observations, data from French radar systems, the European GPS network and satellite sensors. Additionally, a free forecast driven by the ECMWF operational analysis is included as a reference run representing current operational precipitation forecasting. The verification is done both qualitatively and quantitatively by comparisons of reflectivity, accumulated precipitation fields and derived verification scores for a complex synoptic situation that developed on 26 and 27 September 2012. The investigation shows that even the downscaling from ECMWF represents the synoptic situation reasonably well. However, significant improvements are seen in the results of the WRF QPE setup, especially when the French radar data are assimilated. The frontal structure is more defined and the timing of the frontal movement is improved compared with observations. Even mesoscale band-like precipitation structures on the rear side of the cold front are reproduced, as seen by radar. The improvement in performance is also confirmed by a quantitative comparison of the 24-hourly accumulated precipitation over Germany. The mean correlation of the model simulations with observations improved from 0.2 in the downscaling experiment and 0.29 in the assimilation experiment without radar data to 0.56 in the WRF QPE experiment including the assimilation of French radar data.

  18. Integrating K-means Clustering with Kernel Density Estimation for the Development of a Conditional Weather Generation Downscaling Model

    Science.gov (United States)

    Chen, Y.; Ho, C.; Chang, L.

    2011-12-01

    In previous decades, the climate change caused by global warming increases the occurrence frequency of extreme hydrological events. Water supply shortages caused by extreme events create great challenges for water resource management. To evaluate future climate variations, general circulation models (GCMs) are the most wildly known tools which shows possible weather conditions under pre-defined CO2 emission scenarios announced by IPCC. Because the study area of GCMs is the entire earth, the grid sizes of GCMs are much larger than the basin scale. To overcome the gap, a statistic downscaling technique can transform the regional scale weather factors into basin scale precipitations. The statistic downscaling technique can be divided into three categories include transfer function, weather generator and weather type. The first two categories describe the relationships between the weather factors and precipitations respectively based on deterministic algorithms, such as linear or nonlinear regression and ANN, and stochastic approaches, such as Markov chain theory and statistical distributions. In the weather type, the method has ability to cluster weather factors, which are high dimensional and continuous variables, into weather types, which are limited number of discrete states. In this study, the proposed downscaling model integrates the weather type, using the K-means clustering algorithm, and the weather generator, using the kernel density estimation. The study area is Shihmen basin in northern of Taiwan. In this study, the research process contains two steps, a calibration step and a synthesis step. Three sub-steps were used in the calibration step. First, weather factors, such as pressures, humidities and wind speeds, obtained from NCEP and the precipitations observed from rainfall stations were collected for downscaling. Second, the K-means clustering grouped the weather factors into four weather types. Third, the Markov chain transition matrixes and the

  19. Chemical ore genesis models for the precipitation of carnotite in calcrete

    International Nuclear Information System (INIS)

    Mann, A.W.

    1974-10-01

    An investigation was carried out on the chemical mechanism responsible for the precipitation of carnotite in calcrete. The correct interpretation of uranium and vanadium movement in groundwater may only be possible after a careful and detailed evaluation of the occurrence (or non-occurrence) of many other uranium-vanadium complex salts, particularly those of calcium. It is concluded that a redox controlled mechanism for the precipitation of carnotite from groundwaters seem most likely. (R.L.)

  20. Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

    Science.gov (United States)

    Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

    2014-10-01

    Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

  1. Do climate model predictions agree with long-term precipitation trends in the arid southwestern United States?

    Science.gov (United States)

    Elias, E.; Rango, A.; James, D.; Maxwell, C.; Anderson, J.; Abatzoglou, J. T.

    2016-12-01

    Researchers evaluating climate projections across southwestern North America observed a decreasing precipitation trend. Aridification was most pronounced in the cold (non-monsoonal) season, whereas downward trends in precipitation were smaller in the warm (monsoonal) season. In this region, based upon a multimodel mean of 20 Coupled Model Intercomparison Project 5 models using a business-as-usual (Representative Concentration Pathway 8.5) trajectory, midcentury precipitation is projected to increase slightly during the monsoonal time period (July-September; 6%) and decrease slightly during the remainder of the year (October-June; -4%). We use observed long-term (1915-2015) monthly precipitation records from 16 weather stations to investigate how well measured trends corroborate climate model predictions during the monsoonal and non-monsoonal timeframe. Running trend analysis using the Mann-Kendall test for 15 to 101 year moving windows reveals that half the stations showed significant (p≤0.1), albeit small, increasing trends based on the longest term record. Trends based on shorter-term records reveal a period of significant precipitation decline at all stations representing the 1950s drought. Trends from 1930 to 2015 reveal significant annual, monsoonal and non-monsoonal increases in precipitation (Fig 1). The 1960 to 2015 time window shows no significant precipitation trends. The more recent time window (1980 to 2015) shows a slight, but not significant, increase in monsoonal precipitation and a larger, significant decline in non-monsoonal precipitation. GCM precipitation projections are consistent with more recent trends for the region. Running trends from the most recent time window (mid-1990s to 2015) at all stations show increasing monsoonal precipitation and decreasing Oct-Jun precipitation, with significant trends at 6 of 16 stations. Running trend analysis revealed that the long-term trends were not persistent throughout the series length, but depended

  2. Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system

    International Nuclear Information System (INIS)

    Gao, Y; Fu, J S; Drake, J B; Liu, Y; Lamarque, J-F

    2012-01-01

    This study is the first evaluation of dynamical downscaling using the Weather Research and Forecasting (WRF) Model on a 4 km × 4 km high resolution scale in the eastern US driven by the new Community Earth System Model version 1.0 (CESM v1.0). First we examined the global and regional climate model results, and corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask. In comparison with observations, WRF shows statistically significant improvement over CESM in reproducing extreme weather events, with improvement for heat wave frequency estimation as high as 98%. The fossil fuel intensive scenario Representative Concentration Pathway (RCP) 8.5 was used to study a possible future mid-century climate extreme in 2057–9. Both the heat waves and the extreme precipitation in 2057–9 are more severe than the present climate in the Eastern US. The Northeastern US shows large increases in both heat wave intensity (3.05 °C higher) and annual extreme precipitation (107.3 mm more per year). (letter)

  3. Developing future precipitation events from historic events: An Amsterdam case study.

    Science.gov (United States)

    Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen

    2016-04-01

    Due to climate change, the frequency and intensity of extreme precipitation events is expected to increase. It is therefore of high importance to develop climate change scenarios tailored towards the local and regional needs of policy makers in order to develop efficient adaptation strategies to reduce the risks from extreme weather events. Current approaches to tailor climate scenarios are often not well adopted in hazard management, since average changes in climate are not a main concern to policy makers, and tailoring climate scenarios to simulate future extremes can be complex. Therefore, a new concept has been introduced recently that uses known historic extreme events as a basis, and modifies the observed data for these events so that the outcome shows how the same event would occur in a warmer climate. This concept is introduced as 'Future Weather', and appeals to the experience of stakeholders and users. This research presents a novel method of projecting a future extreme precipitation event, based on a historic event. The selected precipitation event took place over the broader area of Amsterdam, the Netherlands in the summer of 2014, which resulted in blocked highways, disruption of air transportation, flooded buildings and public facilities. An analysis of rain monitoring stations showed that an event of such intensity has a 5 to 15 years return period. The method of projecting a future event follows a non-linear delta transformation that is applied directly on the observed event assuming a warmer climate to produce an "up-scaled" future precipitation event. The delta transformation is based on the observed behaviour of the precipitation intensity as a function of the dew point temperature during summers. The outcome is then compared to a benchmark method using the HARMONIE numerical weather prediction model, where the boundary conditions of the event from the Ensemble Prediction System of ECMWF (ENS) are perturbed to indicate a warmer climate. The two

  4. Non-uniformity Correction of Infrared Images by Midway Equalization

    Directory of Open Access Journals (Sweden)

    Yohann Tendero

    2012-07-01

    Full Text Available The non-uniformity is a time-dependent noise caused by the lack of sensor equalization. We present here the detailed algorithm and on line demo of the non-uniformity correction method by midway infrared equalization. This method was designed to suit infrared images. Nevertheless, it can be applied to images produced for example by scanners, or by push-broom satellites. The obtained single image method works on static images, is fully automatic, having no user parameter, and requires no registration. It needs no camera motion compensation, no closed aperture sensor equalization and is able to correct for a fully non-linear non-uniformity.

  5. Fine-Tuning Nonhomogeneous Regression for Probabilistic Precipitation Forecasts: Unanimous Predictions, Heavy Tails, and Link Functions

    DEFF Research Database (Denmark)

    Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.

    2017-01-01

    functions for the optimization of regression coefficients for the scale parameter. These three refinements are tested for 10 stations in a small area of the European Alps for lead times from +24 to +144 h and accumulation periods of 24 and 6 h. Together, they improve probabilistic forecasts...... to obtain automatically corrected weather forecasts. This study applies the nonhomogenous regression framework as a state-of-the-art ensemble postprocessing technique to predict a full forecast distribution and improves its forecast performance with three statistical refinements. First of all, a novel split...... for precipitation amounts as well as the probability of precipitation events over the default postprocessing method. The improvements are largest for the shorter accumulation periods and shorter lead times, where the information of unanimous ensemble predictions is more important....

  6. Challenges in X-band Weather Radar Data Calibration

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Rasmussen, Michael R.

    2009-01-01

    Application of weather radar data in urban hydrology is evolving and radar data is now applied for both modelling, analysis and real time control purposes. In these contexts, it is all-important that the radar data well calibrated and adjusted in order to obtain valid quantitative precipitation e...... estimates. This paper compares two calibration procedures for a small marine X-band radar by comparing radar data with rain gauge data. Validation shows a very good consensus with regards to precipitation volumes, but more diverse results on peak rain intensities.......Application of weather radar data in urban hydrology is evolving and radar data is now applied for both modelling, analysis and real time control purposes. In these contexts, it is all-important that the radar data well calibrated and adjusted in order to obtain valid quantitative precipitation...

  7. U.S. Hourly Precipitation Data Publication

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This publication contains hourly precipitation amounts obtained from recording rain gages located at National Weather Service, Federal Aviation Administration, and...

  8. Special weather situations in Copenhagen-Oeresund area

    International Nuclear Information System (INIS)

    1982-01-01

    The Danish Environmental Agency has appointed a committee for studies of weather situations of Copenhgen and Oeresund strait regions in order to evaluate consequences of a potential nuclear accident at Barebaeck Power Plant in Sweden. The committee has investigated weather situations with fumigation, local wind systems at large urban areas and on the land-water boundary and precipitation role in plume transport over Oereseund. (EG)

  9. Influence of Subtropical Jetstream on Arabian Gulf Precipitation

    Science.gov (United States)

    Sandeep, S.; Pauluis, O.; Ravindran, A. M.; TP, S.

    2017-12-01

    The Arabian Gulf and surrounding regions are predominantly arid. However, this region hosts a large population due to the intense economic activity that is centered on the exploration of natural resources in and around the Arabian Gulf. Thus, few precipitation events that occur during boreal winter are important for society and ecology of this region. The mechanisms of winter precipitation over the Gulf are not well understood, partly due to a lack of long term meteorological observation. Here we explore the dynamics of Arabian Gulf winter precipitation events using available observations and a high resolution atmospheric model simulation. Our analyses show that the northern Gulf receives about six times more precipitation than the southern Gulf. Often, the southern Gulf precipitation forms as a result of downstream development of northern Gulf disturbance. The southward movement of northern Gulf disturbances is influenced by the location of subtropical jet. The probability of a northern Gulf precipitating weather system to move south is higher when the subtropical jet is located equatorward of 30°N. The equatorward position of jet favors the penetration of mid-latitude weather systems over the Arabian Peninsula, which in turn pushes the Arabian anticyclone eastward and triggers moisture transport from the Arabian Sea that is essential for southern Gulf precipitation events.

  10. ORBIT CORRECTION IN A NON-SCALING FFAG

    CERN Document Server

    Kelliher, D J; Sheehy, S L

    2010-01-01

    EMMA - the Electron Model of Many Applications - is to be built at the STFC Daresbury Laboratory in the UK and will be the first non-scaling FFAG ever constructed. The purpose of EMMA is to study beam dynamics in such an accelerator. The EMMA orbit correction scheme must deal with two characteristics of a non-scaling FFAG: i.e. the lack of a well defined reference orbit and the variation with momentum of the phase advance. In this study we present a novel orbit correction scheme that avoids the former problem by instead aiming to maximise both the symmetry of the orbit and the physical aperture of the beam. The latter problem is dealt with by optimising the corrector strengths over the energy range.

  11. Association between Precipitation and Diarrheal Disease in Mozambique.

    Science.gov (United States)

    Horn, Lindsay M; Hajat, Anjum; Sheppard, Lianne; Quinn, Colin; Colborn, James; Zermoglio, Maria Fernanda; Gudo, Eduardo S; Marrufo, Tatiana; Ebi, Kristie L

    2018-04-10

    Diarrheal diseases are a leading cause of morbidity and mortality in Africa. Although research documents the magnitude and pattern of diarrheal diseases are associated with weather in particular locations, there is limited quantification of this association in sub-Saharan Africa and no studies conducted in Mozambique. Our study aimed to determine whether variation in diarrheal disease was associated with precipitation in Mozambique. In secondary analyses we investigated the associations between temperature and diarrheal disease. We obtained weekly time series data for weather and diarrheal disease aggregated at the administrative district level for 1997-2014. Weather data include modeled estimates of precipitation and temperature. Diarrheal disease counts are confirmed clinical episodes reported to the Mozambique Ministry of Health ( n = 7,315,738). We estimated the association between disease counts and precipitation, defined as the number of wet days (precipitation > 1 mm) per week, for the entire country and for Mozambique's four regions. We conducted time series regression analyses using an unconstrained distributed lag Poisson model adjusted for time, maximum temperature, and district. Temperature was similarly estimated with adjusted covariates. Using a four-week lag, chosen a priori, precipitation was associated with diarrheal disease. One additional wet day per week was associated with a 1.86% (95% CI: 1.05-2.67%), 1.37% (95% CI: 0.70-2.04%), 2.09% (95% CI: 1.01-3.18%), and 0.63% (95% CI: 0.11-1.14%) increase in diarrheal disease in Mozambique's northern, central, southern, and coastal regions, respectively. Our study indicates a strong association between diarrheal disease and precipitation. Diarrheal disease prevention efforts should target areas forecast to experience increased rainfall. The burden of diarrheal disease may increase with increased precipitation associated with climate change, unless additional health system interventions are undertaken.

  12. Towards improving the reliability of future regional climate projections: A bias-correction method applied to precipitation over the west coast of Norway

    Science.gov (United States)

    Valved, A.; Barstad, I.; Sobolowski, S.

    2012-04-01

    The early winter of 2011/2012 in the city of Bergen, located on the west coast of Norway, was dominated by warm, wet and extreme weather. This might be a glimpse of future average climate conditions under continued atmospheric warming and an enhanced hydrological cycle. The extreme weather events have resulted in drainage/sewage problems, landslides, flooding property damage and even death. As the Municipality plans for the future they must contend with a growing population in a geographically complex area in addition to any effects attributable to climate change. While the scientific community is increasingly confident in the projections of large scale changes over the mid - high latitudes this confidence does not extend to the local - regional scale where the magnitude and even direction of change may be highly uncertain. Meanwhile it is precisely these scales that Municipalities such as Bergen require information if they are to plan effectively. Thus, there is a need for reliable, local climate projections, which can aid policy makers and planners in decision-making. Current state of the art regional climate models are capable of providing detailed simulations on the order of 1 or 10km. However, due to the increased computational demands of these simulations, large ensembles, such as those used for GCM experiments, are often not possible. Thus, greater detail, under these circumstances, does not necessarily correspond to greater reliability. One way to deal with this issue is to apply a statistical bias correction method where model results are fitted to observationally derived probability density functions (pdfs). In this way, a full distribution of potential changes may be generated which are constrained by known, observed data.This will result in a shifted model distribution with mean and spread that more closely follows observations. In short, the method temporarily removes the climate signals from the model run working on the different percentiles, fits the

  13. STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

    Science.gov (United States)

    Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

    2014-05-01

    We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present

  14. Stochastic error model corrections to improve the performance of bottom-up precipitation products for hydrologic applications

    Science.gov (United States)

    Maggioni, V.; Massari, C.; Ciabatta, L.; Brocca, L.

    2016-12-01

    Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning, and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. However, uncertainties in the SM2RAIN product are still not well known and could represent a limitation in utilizing this dataset for hydrological applications. Therefore, quantifying the uncertainty associated with SM2RAIN is necessary for enabling its use. The study is conducted over the Italian territory for a 5-yr period (2010-2014). A number of satellite precipitation error properties, typically used in error modeling, are investigated and include probability of detection, false alarm rates, missed events, spatial correlation of the error, and hit biases. After this preliminary uncertainty analysis, the potential of applying the stochastic rainfall error model SREM2D to correct SM2RAIN and to improve its performance in hydrologic applications is investigated. The use of SREM2D for

  15. Extreme weather events in southern Germany - Climatological risk and development of a large-scale identification procedure

    Science.gov (United States)

    Matthies, A.; Leckebusch, G. C.; Rohlfing, G.; Ulbrich, U.

    2009-04-01

    Extreme weather events such as thunderstorms, hail and heavy rain or snowfall can pose a threat to human life and to considerable tangible assets. Yet there is a lack of knowledge about present day climatological risk and its economic effects, and its changes due to rising greenhouse gas concentrations. Therefore, parts of economy particularly sensitve to extreme weather events such as insurance companies and airports require regional risk-analyses, early warning and prediction systems to cope with such events. Such an attempt is made for southern Germany, in close cooperation with stakeholders. Comparing ERA40 and station data with impact records of Munich Re and Munich Airport, the 90th percentile was found to be a suitable threshold for extreme impact relevant precipitation events. Different methods for the classification of causing synoptic situations have been tested on ERA40 reanalyses. An objective scheme for the classification of Lamb's circulation weather types (CWT's) has proved to be most suitable for correct classification of the large-scale flow conditions. Certain CWT's have been turned out to be prone to heavy precipitation or on the other side to have a very low risk of such events. Other large-scale parameters are tested in connection with CWT's to find out a combination that has the highest skill to identify extreme precipitation events in climate model data (ECHAM5 and CLM). For example vorticity advection in 700 hPa shows good results, but assumes knowledge of regional orographic particularities. Therefore ongoing work is focused on additional testing of parameters that indicate deviations of a basic state of the atmosphere like the Eady Growth Rate or the newly developed Dynamic State Index. Evaluation results will be used to estimate the skill of the regional climate model CLM concerning the simulation of frequency and intensity of the extreme weather events. Data of the A1B scenario (2000-2050) will be examined for a possible climate change

  16. Non-perturbative power corrections to ghost and gluon propagators

    International Nuclear Information System (INIS)

    Boucaud, Philippe; Leroy, Jean-Pierre; Yaouanc, Alain Le; Lokhov, Alexey; Micheli, Jacques; Pene, Olivier; RodrIguez-Quintero, Jose; Roiesnel, Claude

    2006-01-01

    We study the dominant non-perturbative power corrections to the ghost and gluon propagators in Landau gauge pure Yang-Mills theory using OPE and lattice simulations. The leading order Wilson coefficients are proven to be the same for both propagators. The ratio of the ghost and gluon propagators is thus free from this dominant power correction. Indeed, a purely perturbative fit of this ratio gives smaller value ( ≅ 270MeV) of Λ M-barS-bar than the one obtained from the propagators separately( ≅ 320MeV). This argues in favour of significant non-perturbative ∼ 1/q 2 power corrections in the ghost and gluon propagators. We check the self-consistency of the method

  17. Assessment of spill flow emissions on the basis of measured precipitation and waste water data

    Science.gov (United States)

    Hochedlinger, Martin; Gruber, Günter; Kainz, Harald

    2005-09-01

    Combined sewer overflows (CSOs) are substantial contributors to the total emissions into surface water bodies. The emitted pollution results from dry-weather waste water loads, surface runoff pollution and from the remobilisation of sewer deposits and sewer slime during storm events. One possibility to estimate overflow loads is a calculation with load quantification models. Input data for these models are pollution concentrations, e.g. Total Chemical Oxygen Demand (COD tot), Total Suspended Solids (TSS) or Soluble Chemical Oxygen Demand (COD sol), rainfall series and flow measurements for model calibration and validation. It is important for the result of overflow loads to model with reliable input data, otherwise this inevitably leads to bad results. In this paper the correction of precipitation measurements and the sewer online-measurements are presented to satisfy the load quantification model requirements already described. The main focus is on tipping bucket gauge measurements and their corrections. The results evidence the importance of their corrections due the effects on load quantification modelling and show the difference between corrected and not corrected data of storm events with high rain intensities.

  18. How accurate are the weather forecasts for Bierun (southern Poland)?

    Science.gov (United States)

    Gawor, J.

    2012-04-01

    Weather forecast accuracy has increased in recent times mainly thanks to significant development of numerical weather prediction models. Despite the improvements, the forecasts should be verified to control their quality. The evaluation of forecast accuracy can also be an interesting learning activity for students. It joins natural curiosity about everyday weather and scientific process skills: problem solving, database technologies, graph construction and graphical analysis. The examination of the weather forecasts has been taken by a group of 14-year-old students from Bierun (southern Poland). They participate in the GLOBE program to develop inquiry-based investigations of the local environment. For the atmospheric research the automatic weather station is used. The observed data were compared with corresponding forecasts produced by two numerical weather prediction models, i.e. COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by Naval Research Laboratory Monterey, USA; it runs operationally at the Interdisciplinary Centre for Mathematical and Computational Modelling in Warsaw, Poland and COSMO (The Consortium for Small-scale Modelling) used by the Polish Institute of Meteorology and Water Management. The analysed data included air temperature, precipitation, wind speed, wind chill and sea level pressure. The prediction periods from 0 to 24 hours (Day 1) and from 24 to 48 hours (Day 2) were considered. The verification statistics that are commonly used in meteorology have been applied: mean error, also known as bias, for continuous data and a 2x2 contingency table to get the hit rate and false alarm ratio for a few precipitation thresholds. The results of the aforementioned activity became an interesting basis for discussion. The most important topics are: 1) to what extent can we rely on the weather forecasts? 2) How accurate are the forecasts for two considered time ranges? 3) Which precipitation threshold is the most predictable? 4) Why

  19. Precipitation increases the occurrence of sporadic legionnaires' disease in Taiwan.

    Directory of Open Access Journals (Sweden)

    Nai-Tzu Chen

    Full Text Available Legionnaires' disease (LD is an acute form of pneumonia, and changing weather is considered a plausible risk factor. Yet, the relationship between weather and LD has rarely been investigated, especially using long-term daily data. In this study, daily data was used to evaluate the impacts of precipitation, temperature, and relative humidity on LD occurrence in Taiwan from 1995-2011. A time-stratified 2:1 matched-period case-crossover design was used to compare each case with self-controlled data using a conditional logistic regression analysis, and odds ratios (ORs for LD occurrence was estimated. The city, gender and age were defined as a stratum for each matched set to modify the effects. For lag day- 0 to 15, the precipitation at lag day-11 significantly affected LD occurrence (p0.05. In conclusion, in warm, humid regions, an increase of daily precipitation is likely to be a critical weather factor triggering LD occurrence where the risk is found particularly significant at an 11-day lag. Additionally, precipitation at 21-40 and 61-80 mm might make LD occurrence more likely.

  20. Error Correction for Non-Abelian Topological Quantum Computation

    Directory of Open Access Journals (Sweden)

    James R. Wootton

    2014-03-01

    Full Text Available The possibility of quantum computation using non-Abelian anyons has been considered for over a decade. However, the question of how to obtain and process information about what errors have occurred in order to negate their effects has not yet been considered. This is in stark contrast with quantum computation proposals for Abelian anyons, for which decoding algorithms have been tailor-made for many topological error-correcting codes and error models. Here, we address this issue by considering the properties of non-Abelian error correction, in general. We also choose a specific anyon model and error model to probe the problem in more detail. The anyon model is the charge submodel of D(S_{3}. This shares many properties with important models such as the Fibonacci anyons, making our method more generally applicable. The error model is a straightforward generalization of those used in the case of Abelian anyons for initial benchmarking of error correction methods. It is found that error correction is possible under a threshold value of 7% for the total probability of an error on each physical spin. This is remarkably comparable with the thresholds for Abelian models.

  1. NWP-Based Adjustment of IMERG Precipitation for Flood-Inducing Complex Terrain Storms: Evaluation over CONUS

    Directory of Open Access Journals (Sweden)

    Xinxuan Zhang

    2018-04-01

    Full Text Available This paper evaluates the use of precipitation forecasts from a numerical weather prediction (NWP model for near-real-time satellite precipitation adjustment based on 81 flood-inducing heavy precipitation events in seven mountainous regions over the conterminous United States. The study is facilitated by the National Center for Atmospheric Research (NCAR real-time ensemble forecasts (called model, the Integrated Multi-satellitE Retrievals for GPM (IMERG near-real-time precipitation product (called raw IMERG and the Stage IV multi-radar/multi-sensor precipitation product (called Stage IV used as a reference. We evaluated four precipitation datasets (the model forecasts, raw IMERG, gauge-adjusted IMERG and model-adjusted IMERG through comparisons against Stage IV at six-hourly and event length scales. The raw IMERG product consistently underestimated heavy precipitation in all study regions, while the domain average rainfall magnitudes exhibited by the model were fairly accurate. The model exhibited error in the locations of intense precipitation over inland regions, however, while the IMERG product generally showed correct spatial precipitation patterns. Overall, the model-adjusted IMERG product performed best over inland regions by taking advantage of the more accurate rainfall magnitude from NWP and the spatial distribution from IMERG. In coastal regions, although model-based adjustment effectively improved the performance of the raw IMERG product, the model forecast performed even better. The IMERG product could benefit from gauge-based adjustment, as well, but the improvement from model-based adjustment was consistently more significant.

  2. Can bias correction and statistical downscaling methods improve the skill of seasonal precipitation forecasts?

    Science.gov (United States)

    Manzanas, R.; Lucero, A.; Weisheimer, A.; Gutiérrez, J. M.

    2018-02-01

    Statistical downscaling methods are popular post-processing tools which are widely used in many sectors to adapt the coarse-resolution biased outputs from global climate simulations to the regional-to-local scale typically required by users. They range from simple and pragmatic Bias Correction (BC) methods, which directly adjust the model outputs of interest (e.g. precipitation) according to the available local observations, to more complex Perfect Prognosis (PP) ones, which indirectly derive local predictions (e.g. precipitation) from appropriate upper-air large-scale model variables (predictors). Statistical downscaling methods have been extensively used and critically assessed in climate change applications; however, their advantages and limitations in seasonal forecasting are not well understood yet. In particular, a key problem in this context is whether they serve to improve the forecast quality/skill of raw model outputs beyond the adjustment of their systematic biases. In this paper we analyze this issue by applying two state-of-the-art BC and two PP methods to downscale precipitation from a multimodel seasonal hindcast in a challenging tropical region, the Philippines. To properly assess the potential added value beyond the reduction of model biases, we consider two validation scores which are not sensitive to changes in the mean (correlation and reliability categories). Our results show that, whereas BC methods maintain or worsen the skill of the raw model forecasts, PP methods can yield significant skill improvement (worsening) in cases for which the large-scale predictor variables considered are better (worse) predicted by the model than precipitation. For instance, PP methods are found to increase (decrease) model reliability in nearly 40% of the stations considered in boreal summer (autumn). Therefore, the choice of a convenient downscaling approach (either BC or PP) depends on the region and the season.

  3. Passive Microwave Precipitation Retrieval Uncertainty Characterized based on Field Campaign Data over Complex Terrain

    Science.gov (United States)

    Derin, Y.; Anagnostou, E. N.; Anagnostou, M.; Kalogiros, J. A.; Casella, D.; Marra, A. C.; Panegrossi, G.; Sanò, P.

    2017-12-01

    Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements. Such measurements can be obtained from field campaigns facilitated by research quality sensors such as locally deployed weather radar and in situ weather stations. This study uses such high quality and resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations from three field experiments in Mid-Atlantic US East Coast (NASA IPHEX experiment), the Olympic Peninsula of Washington State (NASA OLYMPEX experiment), and the Mediterranean to characterize the error characteristics of multiple passive microwave (PMW) sensor retrievals. The study first conducts an independent error analysis of the XPOL radar reference rainfall fields against in situ rain gauges and disdrometer observations available by the field experiments. Then the study evaluates different PMW precipitation products using the XPOL datasets (GR) over the three aforementioned complex terrain study areas. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW field-of-view sampling volumes, and scaled GR parameters to the satellite products' nominal spatial resolution. The following PMW precipitation retrieval algorithms are evaluated: the NASA Goddard PROFiling algorithm (GPROF), standard and climatology-based products (V 3, 4 and 5) from four PMW sensors (SSMIS, MHS, GMI, and AMSR2), and the precipitation products based on the algorithms Cloud Dynamics and Radiation Database (CDRD) for SSMIS and Passive microwave Neural network

  4. Assessment of CLIGEN precipitation and storm pattern generation under four precipitation depth categories in China

    Science.gov (United States)

    CLIGEN (CLImate GENerator) is a widely used stochastic weather generator to simulate continuous daily precipitation and storm pattern information for hydrological and soil erosion models. Although CLIGEN has been tested in several regions in the world, thoroughly assessment before applying it to Chi...

  5. The effect of a giant wind farm on precipitation in a regional climate model

    International Nuclear Information System (INIS)

    Fiedler, B H; Bukovsky, M S

    2011-01-01

    The Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to study the effect of a giant wind farm on warm-season precipitation in the eastern two-thirds of the USA. The boundary conditions for WRF are supplied by 62 years of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) global reanalysis. In the model, the presence of a mid-west wind farm, either giant or small, can have an enormous impact on the weather and the amount of precipitation for one season, which is consistent with the known sensitivity of long-term weather forecasts to initial conditions. The effect on climate is less strong. In the average precipitation of 62 warm seasons, there is a statistically significant 1.0% enhancement of precipitation in a multi-state area surrounding and to the south-east of the wind farm.

  6. Skywatch: The Western Weather Guide.

    Science.gov (United States)

    Keen, Richard A.

    The western United States is a region of mountains and valleys with the world's largest ocean next door. Its weather is unique. This book discusses how water, wind, and environmental conditions combine to create the climatic conditions of the region. Included are sections describing: fronts; cyclones; precipitation; storms; tornadoes; hurricanes;…

  7. Rapid weather information dissemination in Florida

    Science.gov (United States)

    Martsolf, J. D.; Heinemann, P. H.; Gerber, J. F.; Crosby, F. L.; Smith, D. L.

    1984-01-01

    The development of the Florida Agricultural Services and Technology (FAST) plan to provide ports for users to call for weather information is described. FAST is based on the Satellite Frost Forecast System, which makes a broad base of weather data available to its users. The methods used for acquisition and dissemination of data from various networks under the FAST plan are examined. The system provides color coded IR or thermal maps, precipitation maps, and textural forecast information. A diagram of the system is provided.

  8. Long-Term Trend Analysis of Precipitation and Air Temperature for Kentucky, United States

    Directory of Open Access Journals (Sweden)

    Somsubhra Chattopadhyay

    2016-02-01

    Full Text Available Variation in quantities such as precipitation and temperature is often assessed by detecting and characterizing trends in available meteorological data. The objective of this study was to determine the long-term trends in annual precipitation and mean annual air temperature for the state of Kentucky. Non-parametric statistical tests were applied to homogenized and (as needed pre-whitened annual series of precipitation and mean air temperature during 1950–2010. Significant trends in annual precipitation were detected (both positive, averaging 4.1 mm/year for only two of the 60 precipitation-homogenous weather stations (Calloway and Carlisle counties in rural western Kentucky. Only three of the 42 temperature-homogenous stations demonstrated trends (all positive, averaging 0.01 °C/year in mean annual temperature: Calloway County, Allen County in southern-central Kentucky, and urbanized Jefferson County in northern-central Kentucky. In view of the locations of the stations demonstrating positive trends, similar work in adjacent states will be required to better understand the processes responsible for those trends and to properly place them in their larger context, if any.

  9. Precipitation effects on microbial pollution in a river: lag structures and seasonal effect modification.

    Directory of Open Access Journals (Sweden)

    Andreas Tornevi

    Full Text Available BACKGROUND: The river Göta Älv is a source of freshwater for 0.7 million swedes. The river is subject to contamination from sewer systems discharge and runoff from agricultural lands. Climate models projects an increase in precipitation and heavy rainfall in this region. This study aimed to determine how daily rainfall causes variation in indicators of pathogen loads, to increase knowledge of variations in river water quality and discuss implications for risk management. METHODS: Data covering 7 years of daily monitoring of river water turbidity and concentrations of E. coli, Clostridium and coliforms were obtained, and their short-term variations in relation with precipitation were analyzed with time series regression and non-linear distributed lag models. We studied how precipitation effects varied with season and compared different weather stations for predictive ability. RESULTS: Generally, the lowest raw water quality occurs 2 days after rainfall, with poor raw water quality continuing for several more days. A rainfall event of >15 mm/24-h (local 95 percentile was associated with a three-fold higher concentration of E. coli and 30% higher turbidity levels (lag 2. Rainfall was associated with exponential increases in concentrations of indicator bacteria while the effect on turbidity attenuated with very heavy rainfall. Clear associations were also observed between consecutive days of wet weather and decreased water quality. The precipitation effect on increased levels of indicator bacteria was significant in all seasons. CONCLUSIONS: Rainfall elevates microbial risks year-round in this river and freshwater source and acts as the main driver of varying water quality. Heavy rainfall appears to be a better predictor of fecal pollution than water turbidity. An increase of wet weather and extreme events with climate change will lower river water quality even more, indicating greater challenges for drinking water producers, and suggesting better

  10. On the Limitations of Variational Bias Correction

    Science.gov (United States)

    Moradi, Isaac; Mccarty, Will; Gelaro, Ronald

    2018-01-01

    Satellite radiances are the largest dataset assimilated into Numerical Weather Prediction (NWP) models, however the data are subject to errors and uncertainties that need to be accounted for before assimilating into the NWP models. Variational bias correction uses the time series of observation minus background to estimate the observations bias. This technique does not distinguish between the background error, forward operator error, and observations error so that all these errors are summed up together and counted as observation error. We identify some sources of observations errors (e.g., antenna emissivity, non-linearity in the calibration, and antenna pattern) and show the limitations of variational bias corrections on estimating these errors.

  11. Extreme climate, not extreme weather: the summer of 1816 in Geneva, Switzerland

    Directory of Open Access Journals (Sweden)

    R. Auchmann

    2012-02-01

    Full Text Available We analyze weather and climate during the "Year without Summer" 1816 using sub-daily data from Geneva, Switzerland, representing one of the climatically most severely affected regions. The record includes twice daily measurements and observations of air temperature, pressure, cloud cover, wind speed, and wind direction as well as daily measurements of precipitation. Comparing 1816 to a contemporary reference period (1799–1821 reveals that the coldness of the summer of 1816 was most prominent in the afternoon, with a shift of the entire distribution function of temperature anomalies by 3–4 °C. Early morning temperature anomalies show a smaller change for the mean, a significant decrease in the variability, and no changes in negative extremes. Analyzing cloudy and cloud-free conditions separately suggests that an increase in the number of cloudy days was to a significant extent responsible for these features. A daily weather type classification based on pressure, pressure tendency, and wind direction shows extremely anomalous frequencies in summer 1816, with only one day (compared to 20 in an average summer classified as high-pressure situation but a tripling of low-pressure situations. The afternoon temperature anomalies expected from only a change in weather types was much stronger negative in summer 1816 than in any other year. For precipitation, our analysis shows that the 80% increase in summer precipitation compared to the reference period can be explained by 80% increase in the frequency of precipitation, while no change could be found neither in the average intensity of precipitation nor in the frequency distribution of extreme precipitation. In all, the analysis shows that the regional circulation and local cloud cover played a dominant role. It also shows that the summer of 1816 was an example of extreme climate, not extreme weather.

  12. Interactive effects of warming and increased precipitation on community structure and composition in an annual forb dominated desert steppe.

    Directory of Open Access Journals (Sweden)

    Yanhui Hou

    Full Text Available To better understand how warming, increased precipitation and their interactions influence community structure and composition, a field experiment simulating hydrothermal interactions was conducted at an annual forb dominated desert steppe in northern China over 2 years. Increased precipitation increased species richness while warming significantly decreased species richness, and their effects were additive rather than interactive. Although interannual variations in weather conditions may have a major affect on plant community composition on short term experiments, warming and precipitation treatments affected individual species and functional group composition. Warming caused C4 grasses such as Cleistogenes squarrosa to increase while increased precipitation caused the proportions of non-perennial C3 plants like Artemisia capillaris to decrease and perennial C4 plants to increase.

  13. Bayesian quantitative precipitation forecasts in terms of quantiles

    Science.gov (United States)

    Bentzien, Sabrina; Friederichs, Petra

    2014-05-01

    Ensemble prediction systems (EPS) for numerical weather predictions on the mesoscale are particularly developed to obtain probabilistic guidance for high impact weather. An EPS not only issues a deterministic future state of the atmosphere but a sample of possible future states. Ensemble postprocessing then translates such a sample of forecasts into probabilistic measures. This study focus on probabilistic quantitative precipitation forecasts in terms of quantiles. Quantiles are particular suitable to describe precipitation at various locations, since no assumption is required on the distribution of precipitation. The focus is on the prediction during high-impact events and related to the Volkswagen Stiftung funded project WEX-MOP (Mesoscale Weather Extremes - Theory, Spatial Modeling and Prediction). Quantile forecasts are derived from the raw ensemble and via quantile regression. Neighborhood method and time-lagging are effective tools to inexpensively increase the ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Since an EPS provides a large amount of potentially informative predictors, a variable selection is required in order to obtain a stable statistical model. A Bayesian formulation of quantile regression allows for inference about the selection of predictive covariates by the use of appropriate prior distributions. Moreover, the implementation of an additional process layer for the regression parameters accounts for spatial variations of the parameters. Bayesian quantile regression and its spatially adaptive extension is illustrated for the German-focused mesoscale weather prediction ensemble COSMO-DE-EPS, which runs (pre)operationally since December 2010 at the German Meteorological Service (DWD). Objective out-of-sample verification uses the quantile score (QS), a weighted absolute error between quantile forecasts and observations. The QS is a proper scoring function and can be decomposed into

  14. Insurance against weather risk : use of heating degree-days from non-local stations for weather derivatives

    NARCIS (Netherlands)

    Asseldonk, van M.A.P.M.

    2003-01-01

    Weather derivatives enable policy-holders to safeguard themselves against extreme weather conditions. The effectiveness and the efficiency of the risk transfer is determined by the spatial risk basis, which is the stochastic dependency of the local weather outcome being insured and the outcome of

  15. Sub-seasonal Predictability of Heavy Precipitation Events: Implication for Real-time Flood Management in Iran

    Science.gov (United States)

    Najafi, H.; Shahbazi, A.; Zohrabi, N.; Robertson, A. W.; Mofidi, A.; Massah Bavani, A. R.

    2016-12-01

    Each year, a number of high impact weather events occur worldwide. Since any level of predictability at sub-seasonal to seasonal timescale is highly beneficial to society, international efforts is now on progress to promote reliable Ensemble Prediction Systems for monthly forecasts within the WWRP/WCRP initiative (S2S) project and North American Multi Model Ensemble (NMME). For water resources managers in the face of extreme events, not only can reliable forecasts of high impact weather events prevent catastrophic losses caused by floods but also contribute to benefits gained from hydropower generation and water markets. The aim of this paper is to analyze the predictability of recent severe weather events over Iran. Two recent heavy precipitations are considered as an illustration to examine whether S2S forecasts can be used for developing flood alert systems especially where large cascade of dams are in operation. Both events have caused major damages to cities and infrastructures. The first severe precipitation was is in the early November 2015 when heavy precipitation (more than 50 mm) occurred in 2 days. More recently, up to 300 mm of precipitation is observed within less than a week in April 2016 causing a consequent flash flood. Over some stations, the observed precipitation was even more than the total annual mean precipitation. To analyze the predictive capability, ensemble forecasts from several operational centers including (European Centre for Medium-Range Weather Forecasts (ECMWF) system, Climate Forecast System Version 2 (CFSv2) and Chinese Meteorological Center (CMA) are evaluated. It has been observed that significant changes in precipitation anomalies were likely to be predicted days in advance. The next step will be to conduct thorough analysis based on comparing multi-model outputs over the full hindcast dataset developing real-time high impact weather prediction systems.

  16. Experimental weathering rates of aluminium silicates

    International Nuclear Information System (INIS)

    Gudbrandsson, Snorri

    2013-01-01

    The chemical weathering of primary rocks and minerals in natural systems has a major impact on soil development and its composition. Chemical weathering is driven to a large extent by mineral dissolution. Through mineral dissolution, elements are released into groundwater and can readily react to precipitate secondary minerals such as clays, zeolites, and carbonates. Carbonates form from divalent cations (e.g. Ca, Fe and Mg) and CO 2 , and kaolin clay and gibbsite formation is attributed to the weathering of aluminium-rich minerals, most notably the feldspars. The CarbFix Project in Hellisheidi (SW-Iceland) aims to use natural weathering processes to form carbonate minerals by the re-injection of CO 2 from a geothermal power plant back into surrounding basaltic rocks. This process is driven by the dissolution of basaltic rocks, rich in divalent cations, which can combine with injected CO 2 to form and precipitate carbonates. This thesis focuses on the dissolution behaviour of Stapafell crystalline basalt, which consists of three major phases (plagioclase, pyroxene, and olivine) and is rich in divalent cations. Steady-state element release rates from crystalline basalt at far-from-equilibrium conditions were measured at pH from 2 to 11 and temperatures from 5 to 75 C in mixed-flow reactors. Steady-state Si and Ca release rates exhibit a U-shaped variation with pH, where rates decrease with increasing pH at acid condition but increase with increasing pH at alkaline conditions. Silicon release rates from crystalline basalt are comparable to Si release rates from basaltic glass of the same chemical composition at low pH and temperatures ≥25 C but slower at alkaline pH and temperatures ≥50 C. In contrast, Mg and Fe release rates decrease continuously with increasing pH at all temperatures. This behaviour is interpreted to stem from the contrasting dissolution behaviours of the three major minerals comprising the basalt: plagioclase, pyroxene, and olivine. Element

  17. Determining the precipitable water vapor thresholds under different rainfall strengths in Taiwan

    Science.gov (United States)

    Yeh, Ta-Kang; Shih, Hsuan-Chang; Wang, Chuan-Sheng; Choy, Suelynn; Chen, Chieh-Hung; Hong, Jing-Shan

    2018-02-01

    Precipitable Water Vapor (PWV) plays an important role for weather forecasting. It is helpful in evaluating the changes of the weather system via observing the distribution of water vapor. The ability of calculating PWV from Global Positioning System (GPS) signals is useful to understand the special weather phenomenon. In this study, 95 ground-based GPS and rainfall stations in Taiwan were utilized from 2006 to 2012 to analyze the relationship between PWV and rainfall. The PWV data were classified into four classes (no, light, moderate and heavy rainfall), and the vertical gradients of the PWV were obtained and the variations of the PWV were analyzed. The results indicated that as the GPS elevation increased every 100 m, the PWV values decreased by 9.5 mm, 11.0 mm, 12.2 mm and 12.3 mm during the no, light, moderate and heavy rainfall conditions, respectively. After applying correction using the vertical gradients mentioned above, the average PWV thresholds were 41.8 mm, 52.9 mm, 62.5 mm and 64.4 mm under the no, light, moderate and heavy rainfall conditions, respectively. This study offers another type of empirical threshold to assist the rainfall prediction and can be used to distinguish the rainfall features between different areas in Taiwan.

  18. Simulation of Daily Weather Data Using Theoretical Probability Distributions.

    Science.gov (United States)

    Bruhn, J. A.; Fry, W. E.; Fick, G. W.

    1980-09-01

    A computer simulation model was constructed to supply daily weather data to a plant disease management model for potato late blight. In the weather model Monte Carlo techniques were employed to generate daily values of precipitation, maximum temperature, minimum temperature, minimum relative humidity and total solar radiation. Each weather variable is described by a known theoretical probability distribution but the values of the parameters describing each distribution are dependent on the occurrence of rainfall. Precipitation occurrence is described by a first-order Markov chain. The amount of rain, given that rain has occurred, is described by a gamma probability distribution. Maximum and minimum temperature are simulated with a trivariate normal probability distribution involving maximum temperature on the previous day, maximum temperature on the current day and minimum temperature on the current day. Parameter values for this distribution are dependent on the occurrence of rain on the previous day. Both minimum relative humidity and total solar radiation are assumed to be normally distributed. The values of the parameters describing the distribution of minimum relative humidity is dependent on rainfall occurrence on the previous day and current day. Parameter values for total solar radiation are dependent on the occurrence of rain on the current day. The assumptions made during model construction were found to be appropriate for actual weather data from Geneva, New York. The performance of the weather model was evaluated by comparing the cumulative frequency distributions of simulated weather data with the distributions of actual weather data from Geneva, New York and Fort Collins, Colorado. For each location, simulated weather data were similar to actual weather data in terms of mean response, variability and autocorrelation. The possible applications of this model when used with models of other components of the agro-ecosystem are discussed.

  19. Powernext weather, benchmark indices for effective weather risk management

    International Nuclear Information System (INIS)

    2006-01-01

    According to the U.S. Department of Energy, an estimated 25% of the GNP is affected by weather-related events. The variations in temperature - even small ones - can also have long-lasting effects on the operational results of a company. Among other, the Energy supply sector is sensitive to weather risks: a milder or harsher than usual winter leads to a decrease or increase of energy consumption. The price of electricity on power trading facilities like Powernext is especially sensitive to odd changes in temperatures. Powernext and Meteo-France (the French meteorological agency) have joined expertise in order to promote the use of weather indices in term of decision making or underlying of hedging tools to energy actors, end users from any other sector of activity and specialists of the weather risk hedging. The Powernext Weather indices are made from information collected by Meteo-France's main observation network according to the norms of international meteorology, in areas carefully selected. The gross data are submitted to a thorough review allowing the correction of abnormalities and the reconstitution of missing data. Each index is fashioned to take into account the economic activity in the various regions of the country as represented by each region's population. This demographic information represents a fair approximation of the weight of the regional economic activity. This document presents the Powernext/Meteo France partnership for the elaboration of efficient weather-related risk management indices. (J.S.)

  20. Evaluating the use of different precipitation datasets in simulating a flood event

    Science.gov (United States)

    Akyurek, Z.; Ozkaya, A.

    2016-12-01

    Floods caused by convective storms in mountainous regions are sensitive to the temporal and spatial variability of rainfall. Space-time estimates of rainfall from weather radar, satellites and numerical weather prediction models can be a remedy to represent pattern of the rainfall with some inaccuracy. However, there is a strong need for evaluation of the performance and limitations of these estimates in hydrology. This study aims to provide a comparison of gauge, radar, satellite (Hydro-Estimator (HE)) and numerical weather prediciton model (Weather Research and Forecasting (WRF)) precipitation datasets during an extreme flood event (22.11.2014) lasting 40 hours in Samsun-Turkey. For this study, hourly rainfall data from 13 ground observation stations were used in the analyses. This event having a peak discharge of 541 m3/sec created flooding at the downstream of Terme Basin. Comparisons were performed in two parts. First the analysis were performed in areal and point based manner. Secondly, a semi-distributed hydrological model was used to assess the accuracy of the rainfall datasets to simulate river flows for the flood event. Kalman Filtering was used in the bias correction of radar rainfall data compared to gauge measurements. Radar, gauge, corrected radar, HE and WRF rainfall data were used as model inputs. Generally, the HE product underestimates the cumulative rainfall amounts in all stations, radar data underestimates the results in cumulative sense but keeps the consistency in the results. On the other hand, almost all stations in WRF mean statistics computations have better results compared to the HE product but worse than the radar dataset. Results in point comparisons indicated that, trend of the rainfall is captured by the radar rainfall estimation well but radar underestimates the maximum values. According to cumulative gauge value, radar underestimated the cumulative rainfall amount by % 32. Contrary to other datasets, the bias of WRF is positive

  1. Optimizing Placement of Weather Stations: Exploring Objective Functions of Meaningful Combinations of Multiple Weather Variables

    Science.gov (United States)

    Snyder, A.; Dietterich, T.; Selker, J. S.

    2017-12-01

    Many regions of the world lack ground-based weather data due to inadequate or unreliable weather station networks. For example, most countries in Sub-Saharan Africa have unreliable, sparse networks of weather stations. The absence of these data can have consequences on weather forecasting, prediction of severe weather events, agricultural planning, and climate change monitoring. The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to place weather stations within each country. We should consider how we can create accurate spatio-temporal maps of weather data and how to balance the desired accuracy of each weather variable of interest (precipitation, temperature, relative humidity, etc.). We can express this problem as a joint optimization of multiple weather variables, given a fixed number of weather stations. We use reanalysis data as the best representation of the "true" weather patterns that occur in the region of interest. For each possible combination of sites, we interpolate the reanalysis data between selected locations and calculate the mean average error between the reanalysis ("true") data and the interpolated data. In order to formulate our multi-variate optimization problem, we explore different methods of weighting each weather variable in our objective function. These methods include systematic variation of weights to determine which weather variables have the strongest influence on the network design, as well as combinations targeted for specific purposes. For example, we can use computed evapotranspiration as a metric that combines many weather variables in a way that is meaningful for agricultural and hydrological applications. We compare the errors of the weather station networks produced by each optimization problem formulation. We also compare these

  2. Exploring the correlation between annual precipitation and potential evaporation

    Science.gov (United States)

    Chen, X.; Buchberger, S. G.

    2017-12-01

    The interdependence between precipitation and potential evaporation is closely related to the classic Budyko framework. In this study, a systematic investigation of the correlation between precipitation and potential evaporation at the annual time step is conducted at both point scale and watershed scale. The point scale precipitation and potential evaporation data over the period of 1984-2015 are collected from 259 weather stations across the United States. The watershed scale precipitation data of 203 watersheds across the United States are obtained from the Model Parameter Estimation Experiment (MOPEX) dataset from 1983 to 2002; and potential evaporation data of these 203 watersheds in the same period are obtained from a remote-sensing algorithm. The results show that majority of the weather stations (77%) and watersheds (79%) exhibit a statistically significant negative correlation between annual precipitation and annual potential evaporation. The aggregated data cloud of precipitation versus potential evaporation follows a curve based on the combination of the Budyko-type equation and Bouchet's complementary relationship. Our result suggests that annual precipitation and potential evaporation are not independent when both Budyko's hypothesis and Bouchet's hypothesis are valid. Furthermore, we find that the wet surface evaporation, which is controlled primarily by short wave radiation as defined in Bouchet's hypothesis, exhibits less dependence on precipitation than the potential evaporation. As a result, we suggest that wet surface evaporation is a better representation of energy supply than potential evaporation in the Budyko framework.

  3. Space Weather Magnetometer Set with Automated AC Spacecraft Field Correction for GEO-KOMPSAT-2A

    Science.gov (United States)

    Auster, U.; Magnes, W.; Delva, M.; Valavanoglou, A.; Leitner, S.; Hillenmaier, O.; Strauch, C.; Brown, P.; Whiteside, B.; Bendyk, M.; Hilgers, A.; Kraft, S.; Luntama, J. P.; Seon, J.

    2016-05-01

    Monitoring the solar wind conditions, in particular its magnetic field (interplanetary magnetic field) ahead of the Earth is essential in performing accurate and reliable space weather forecasting. The magnetic condition of the spacecraft itself is a key parameter for the successful performance of the magnetometer onboard. In practice a condition with negligible magnetic field of the spacecraft cannot always be fulfilled and magnetic sources on the spacecraft interfere with the natural magnetic field measured by the space magnetometer. The presented "ready-to-use" Service Oriented Spacecraft Magnetometer (SOSMAG) is developed for use on any satellite implemented without magnetic cleanliness programme. It enables detection of the spacecraft field AC variations on a proper time scale suitable to distinguish the magnetic field variations relevant to space weather phenomena, such as sudden increase in the interplanetary field or southward turning. This is achieved through the use of dual fluxgate magnetometers on a short boom (1m) and two additional AMR sensors on the spacecraft body, which monitor potential AC disturbers. The measurements of the latter sensors enable an automated correction of the AC signal contributions from the spacecraft in the final magnetic vector. After successful development and test of the EQM prototype, a flight model (FM) is being built for the Korean satellite Geo-Kompsat 2A, with launch foreseen in 2018.

  4. Interannual Variations in Aerosol Sources and Their Impact on Orographic Precipitation over California's Central Sierra Nevada

    Science.gov (United States)

    Creamean, J.; Ault, A. P.; White, A. B.; Neiman, P. J.; Minnis, P.; Prather, K. A.

    2014-12-01

    Aerosols that serve as cloud condensation nuclei (CCN) and ice nuclei (IN) have the potential to profoundly influence precipitation processes. Furthermore, changes in orographic precipitation have broad implications for reservoir storage and flood risks. As part of the CalWater I field campaign (2009-2011), the impacts of aerosol sources on precipitation were investigated in the California Sierra Nevada Mountains. In 2009, the precipitation collected on the ground was influenced by both local biomass burning and long-range transported dust and biological particles, while in 2010, by mostly local sources of biomass burning and pollution, and in 2011 by mostly long-range transport of dust and biological particles from distant sources. Although vast differences in the sources of residues were observed from year-to-year, dust and biological residues were omnipresent (on average, 55% of the total residues combined) and were associated with storms consisting of deep convective cloud systems and larger quantities of precipitation initiated in the ice phase. Further, biological residues were dominant during storms with relatively warm cloud temperatures (up to -15°C), suggesting biological components were more efficient IN than mineral dust. On the other hand, when precipitation quantities were lower, local biomass burning and pollution residues were observed (on average 31% and 9%, respectively), suggesting these residues potentially served as CCN at the base of shallow cloud systems and that lower level polluted clouds of storm systems produced less precipitation than non-polluted (i.e., marine) clouds. The direct connection of the sources of aerosols within clouds and precipitation type and quantity can be used in models to better assess how local emissions versus long-range transported dust and biological aerosols play a role in impacting regional weather and climate, ultimately with the goal of more accurate predictive weather forecast models and water resource

  5. A new look at the decomposition of agricultural productivity growth incorporating weather effects.

    Science.gov (United States)

    Njuki, Eric; Bravo-Ureta, Boris E; O'Donnell, Christopher J

    2018-01-01

    Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960-2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time.

  6. Assessment of rock mechanical properties and seismic slope stability in variably weathered layered basalts

    Science.gov (United States)

    Greenwood, William; Clark, Marin; Zekkos, Dimitrios; Von Voigtlander, Jennifer; Bateman, Julie; Lowe, Katherine; Hirose, Mitsuhito; Anderson, Suzanne; Anderson, Robert; Lynch, Jerome

    2016-04-01

    A field and laboratory experimental study was conducted to assess the influence of weathering on the mechanical properties of basalts in the region of the Kohala volcano on the island of Hawaii. Through the systematic characterization of the weathering profiles developed in different precipitation regimes, we aim to explain the regional pattern of stability of slopes in layered basalts that were observed during the 2006 Mw 6.7 Kiholo Bay earthquake. While deeper weathering profiles on the wet side of the island might be expected to promote more and larger landslides, the distribution of landslides during the Kiholo Bay earthquake did not follow this anticipated trend. Landslide frequency (defined as number of landslides divided by total area) was similar on the steepest slopes (> 50-60) for both the dry and the wet side of the study area suggesting relatively strong ground materials irrespective of weathering. The study location is ideally suited to investigate the role of precipitation, and more broadly of climate, on the mechanical properties of the local rock units because the presence of the Kohala volcano produces a significant precipitation gradient on what are essentially identical basaltic flows. Mean annual precipitation (MAP) varies by more than an order of magnitude, from 200 mm/year on the western side of the volcano to 4000 mm/year in the eastern side. We will present results of measured shear wave velocities using a seismic surface wave methodology. These results were paired with laboratory testing on selected basalt specimens that document the sample-scale shear wave velocity and unconfined compressive strength of the basaltic rocks. Shear wave velocity and unconfined strength of the rocks are correlated and are both significantly lower in weathered rocks near the ground surface than at depth. This weathering-related reduction in shear wave velocity extends to greater depths in areas of high precipitation compared to areas of lower precipitation

  7. The role of reaction affinity and secondary minerals in regulating chemical weathering rates at the Santa Cruz Soil Chronosequence, California

    Energy Technology Data Exchange (ETDEWEB)

    Maher, K.; Steefel, C. I.; White, A.F.; Stonestrom, D.A.

    2009-02-25

    In order to explore the reasons for the apparent discrepancy between laboratory and field weathering rates and to determine the extent to which weathering rates are controlled by the approach to thermodynamic equilibrium, secondary mineral precipitation and flow rates, a multicomponent reactive transport model (CrunchFlow) was used to interpret soil profile development and mineral precipitation and dissolution rates at the 226 ka marine terrace chronosequence near Santa Cruz, CA. Aqueous compositions, fluid chemistry, transport, and mineral abundances are well characterized (White et al., 2008, GCA) and were used to constrain the reaction rates for the weathering and precipitating minerals in the reactive transport modeling. When primary mineral weathering rates are calculated with either of two experimentally determined rate constants, the nonlinear, parallel rate law formulation of Hellmann and Tisser and [2006] or the aluminum inhibition model proposed by Oelkers et al. [1994], modeling results are consistent with field-scale observations when independently constrained clay precipitation rates are accounted for. Experimental and field rates, therefore, can be reconciled at the Santa Cruz site. Observed maximum clay abundances in the argillic horizons occur at the depth and time where the reaction fronts of the primary minerals overlap. The modeling indicates that the argillic horizon at Santa Cruz can be explained almost entirely by weathering of primary minerals and in situ clay precipitation accompanied by undersaturation of kaolinite at the top of the profile. The rate constant for kaolinite precipitation was also determined based on model simulations of mineral abundances and dissolved Al, SiO{sub 2}(aq) and pH in pore waters. Changes in the rate of kaolinite precipitation or the flow rate do not affect the gradient of the primary mineral weathering profiles, but instead control the rate of propagation of the primary mineral weathering fronts and thus total

  8. Temporal high-pass non-uniformity correction algorithm based on grayscale mapping and hardware implementation

    Science.gov (United States)

    Jin, Minglei; Jin, Weiqi; Li, Yiyang; Li, Shuo

    2015-08-01

    In this paper, we propose a novel scene-based non-uniformity correction algorithm for infrared image processing-temporal high-pass non-uniformity correction algorithm based on grayscale mapping (THP and GM). The main sources of non-uniformity are: (1) detector fabrication inaccuracies; (2) non-linearity and variations in the read-out electronics and (3) optical path effects. The non-uniformity will be reduced by non-uniformity correction (NUC) algorithms. The NUC algorithms are often divided into calibration-based non-uniformity correction (CBNUC) algorithms and scene-based non-uniformity correction (SBNUC) algorithms. As non-uniformity drifts temporally, CBNUC algorithms must be repeated by inserting a uniform radiation source which SBNUC algorithms do not need into the view, so the SBNUC algorithm becomes an essential part of infrared imaging system. The SBNUC algorithms' poor robustness often leads two defects: artifacts and over-correction, meanwhile due to complicated calculation process and large storage consumption, hardware implementation of the SBNUC algorithms is difficult, especially in Field Programmable Gate Array (FPGA) platform. The THP and GM algorithm proposed in this paper can eliminate the non-uniformity without causing defects. The hardware implementation of the algorithm only based on FPGA has two advantages: (1) low resources consumption, and (2) small hardware delay: less than 20 lines, it can be transplanted to a variety of infrared detectors equipped with FPGA image processing module, it can reduce the stripe non-uniformity and the ripple non-uniformity.

  9. Application of statistical correction in extended weather forecasting in the southern region of Brazil Aplicação de correlações estatísticas nas previsões de tempo estendidas na região Sudeste do Brasil

    Directory of Open Access Journals (Sweden)

    Ana Maria Heuminski de Avila

    2012-12-01

    Full Text Available Adverse weather conditions in critical periods of vegetative plant growth affect crop productivity, being a fundamental parameter for yield forecast. An increase in weather forecasting accuracy may be obtained by applying statistical correction to remove model bias. This study used statistical correction of ensemble forecasting with the atmospheric general circulation model (Center for Weather Forecasting and Climate Studies/Center for Ocean - Land - Atmosphere Studies - CPTEC/COLA by mean error removal for three cities in the South of Brazil. Comparisons were made between corrected and original precipitation forecasts, and between these and data observed at their respective meteorological stations. Results showed that the applied statistical correction method may improve forecasting performance in some situations and that the term of forecast present high accuracy, indicating the importance of ensemble forecasting as an auxiliary tool in agricultural crop monitoring.As condições adversas do tempo, nos períodos críticos do desenvolvimento vegetativo da planta influenciam o rendimento da cultura, sendo um parâmetro fundamental para a previsão da safra. Um aumento na acurácea da previsão pode ser obtido ao se aplicar correções estatísticas para remover o erro sistemático do modelo. Neste trabalho foram realizadas correções estatísticas nas previsões de tempo por conjunto do modelo de circulação geral atmosférico (MGCA CPTEC/COLA (Centro de Previsão de Tempo e Estudos Climáticos/Center for Ocean - Land - Atmosphere Studies, através da remoção do erro médio, para três localidades do Sul do Brasil. As previsões de precipitação obtidas pelo modelo sem correção foram comparadas com as previsões corrigidas e ambas com os dados observados nas respectivas estações meteorológicas. Os resultados mostraram que a correção estatística pode melhorar o desempenho do modelo em algumas situações, sendo que ambos os

  10. A long-term variation of chemical composition in precipitation

    International Nuclear Information System (INIS)

    Yoshioka, Ryuma; Okimura, Takashi; Okumura, Takenobu

    1991-01-01

    Precipitation samples are collected at the six localities in the southwestern Japan weekly or monthly over a long period of time (1978-1989) in order to estimate chemical weathering rates and amount of weathered materials through chemical composition in natural waters. Major chemical composition is determined for the precipitation samples. Together with the data available in the literature, the following characteristics are recognized : 1) Most pH values fall in the narrow range of 4.4 to 5.4, 2) Systematic variations in pH values are observed among the precipitation samples of different geologic environments, 3) pH values become almost constant from 1984 to 1989, 4) NO 3 - concentrations gradually decrease to an almost constant value with time, and 5) ΔSO 4 2- concentrations gradually have a tendency to decrease from 1978 to 1985. The mechanism of phenomena described above is also presented. (author)

  11. Typhoon impacts on chemical weathering source provenance of a High Standing Island watershed, Taiwan

    Science.gov (United States)

    Meyer, Kevin J.; Carey, Anne E.; You, Chen-Feng

    2017-10-01

    Chemical weathering source provenance changes associated with Typhoon Mindulle (2004) were identified for the Choshui River Watershed in west-central Taiwan using radiogenic Sr isotope (87Sr/86Sr) and major ion chemistry analysis of water samples collected before, during, and following the storm event. Storm water sampling over 72 h was conducted in 3 h intervals, allowing for novel insight into weathering regime changes in response to intense rainfall events. Chemical weathering sources were determined to be bulk silicate and disseminated carbonate minerals at the surface and silicate contributions from deep thermal waters. Loss on ignition analysis of collected rock samples indicate disseminated carbonate can compose over 25% by weight of surface mineralogy, but typically makes up ∼2-3% of watershed rock. 87Sr/86Sr and major element molar ratios indicate that Typhoon Mindulle caused a weathering regime switch from normal flow incorporating a deep thermal signature to that of a system dominated by surface weathering. The data suggest release of silicate solute rich soil pore waters during storm events, creating a greater relative contribution of silicate weathering to the solute load during periods of increased precipitation and runoff. Partial depletion of this soil solute reservoir and possible erosion enhanced carbonate weathering lead to increased importance of carbonates to the weathering regime as the storm continues. Major ion data indicate that complex mica weathering (muscovite, biotite, illite, chlorite) may represent an important silicate weathering pathway in the watershed. Deep thermal waters represent an important contribution to river solutes during normal non-storm flow conditions. Sulfuric acid sourced from pyrite weathering is likely a major weathering agent in the Choshui River watershed.

  12. Seasonality in trauma admissions - Are daylight and weather variables better predictors than general cyclic effects?

    Science.gov (United States)

    Røislien, Jo; Søvik, Signe; Eken, Torsten

    2018-01-01

    Trauma is a leading global cause of death, and predicting the burden of trauma admissions is vital for good planning of trauma care. Seasonality in trauma admissions has been found in several studies. Seasonal fluctuations in daylight hours, temperature and weather affect social and cultural practices but also individual neuroendocrine rhythms that may ultimately modify behaviour and potentially predispose to trauma. The aim of the present study was to explore to what extent the observed seasonality in daily trauma admissions could be explained by changes in daylight and weather variables throughout the year. Retrospective registry study on trauma admissions in the 10-year period 2001-2010 at Oslo University Hospital, Ullevål, Norway, where the amount of daylight varies from less than 6 hours to almost 19 hours per day throughout the year. Daily number of admissions was analysed by fitting non-linear Poisson time series regression models, simultaneously adjusting for several layers of temporal patterns, including a non-linear long-term trend and both seasonal and weekly cyclic effects. Five daylight and weather variables were explored, including hours of daylight and amount of precipitation. Models were compared using Akaike's Information Criterion (AIC). A regression model including daylight and weather variables significantly outperformed a traditional seasonality model in terms of AIC. A cyclic week effect was significant in all models. Daylight and weather variables are better predictors of seasonality in daily trauma admissions than mere information on day-of-year.

  13. Atmospheric tides and periodic variations in the precipitation field

    International Nuclear Information System (INIS)

    Cevolani, G.; Bacci, P.; Bonelli, P.; Isnardi, C.

    1986-01-01

    The analysis of daily precipitations data at many weather stations in Alpes and Po Valley gives evidence of a ''tidal'' influence from luni-solar gravitational fields. The tidal influence does not appear to be strictly constant with time, as the possible results of a modulation effect of luni-solar cycles having similar periods. Time variations of daily precipitation data as a function of some particular cycles show that gravitational tides effect heavy rainfalls more than mean precipitation values

  14. Optical analysis for simplified astigmatic correction of non-imaging focusing heliostat

    Energy Technology Data Exchange (ETDEWEB)

    Chong, K.K. [Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Off Jalan Genting Kelang, Setapak, 53300 Kuala Lumpur (Malaysia)

    2010-08-15

    In the previous work, non-imaging focusing heliostat that consists of m x n facet mirrors can carry out continuous astigmatic correction during sun-tracking with the use of only (m + n - 2) controllers. For this paper, a simplified astigmatic correction of non-imaging focusing heliostat is proposed for reducing the number of controllers from (m + n - 2) to only two. Furthermore, a detailed optical analysis of the new proposal has been carried out and the simulated result has shown that the two-controller system can perform comparably well in astigmatic correction with a much simpler and more cost effective design. (author)

  15. Non-isothermal precipitation behaviors of Al-Mg-Si-Cu alloys with different Zn contents

    International Nuclear Information System (INIS)

    Guo, M.X.; Zhang, Y.; Zhang, X.K.; Zhang, J.S.; Zhuang, L.Z.

    2016-01-01

    The non-isothermal precipitation behaviors of Al–Mg–Si–Cu alloys with different Zn contents were investigated by differential scanning calorimetry (DSC) analysis, hardness measurement and high resolution transmission electron microscope characterization. The results show that Zn addition has a significant effect on the GP zone dissolution and precipitation of Al-Mg-Si-Cu alloys. And their activation energies change with the changes of Zn content and aging conditions. Precipitation kinetics can be improved by adding 0.5 wt% or 3.0 wt%Zn, while be suppressed after adding 1.5 wt%Zn. The Mg-Si precipitates (GP zones and β″) are still the main precipitates in the Al-Mg-Si-Cu alloys after heated up to 250 °C, and no Mg-Zn precipitates are observed in the Zn-added alloy due to the occurrence of Mg-Zn precipitates reversion. The measured age-hardening responses of the alloys are corresponding to the predicted results by the established precipitation kinetic equations. Additionally, a double-hump phenomenon of hardness appears in the artificial aging of pre-aged alloy with 3.0 wt% Zn addition, which resulted from the formation of pre-β″ and β″ precipitates. Finally, the precipitation mechanism of Al-Mg-Si-Cu alloys with different Zn contents was proposed based on the microstructure evolution and interaction forces between Mg, Si and Zn atoms.

  16. Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

    Directory of Open Access Journals (Sweden)

    Lili Yang

    2016-01-01

    Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

  17. The sensitivity of snowfall to weather states over Sweden

    Science.gov (United States)

    Norin, Lars; Devasthale, Abhay; L'Ecuyer, Tristan S.

    2017-09-01

    For a high-latitude country like Sweden snowfall is an important contributor to the regional water cycle. Furthermore, snowfall impacts surface properties, affects atmospheric thermodynamics, has implications for traffic and logistics management, disaster preparedness, and also impacts climate through changes in surface albedo and turbulent heat fluxes. For Sweden it has been shown that large-scale atmospheric circulation patterns, or weather states, are important for precipitation variability. Although the link between atmospheric circulation patterns and precipitation has been investigated for rainfall there are no studies focused on the sensitivity of snowfall to weather states over Sweden.In this work we investigate the response of snowfall to eight selected weather states. These weather states consist of four dominant wind directions together with cyclonic and anticyclonic circulation patterns and enhanced positive and negative phases of the North Atlantic Oscillation. The presented analysis is based on multiple data sources, such as ground-based radar measurements, satellite observations, spatially interpolated in situ observations, and reanalysis data. The data from these sources converge to underline the sensitivity of falling snow over Sweden to the different weather states.In this paper we examine both average snowfall intensities and snowfall accumulations associated with the different weather states. It is shown that, even though the heaviest snowfall intensities occur during conditions with winds from the south-west, the largest contribution to snowfall accumulation arrives with winds from the south-east. Large differences in snowfall due to variations in the North Atlantic Oscillation are shown as well as a strong effect of cyclonic and anticyclonic circulation patterns. Satellite observations are used to reveal the vertical structures of snowfall during the different weather states.

  18. Future changes in Asian summer monsoon precipitation extremes as inferred from 20-km AGCM simulations

    Science.gov (United States)

    Lui, Yuk Sing; Tam, Chi-Yung; Lau, Ngar-Cheung

    2018-04-01

    This study examines the impacts of climate change on precipitation extremes in the Asian monsoon region during boreal summer, based on simulations from the 20-km Meteorological Research Institute atmospheric general circulation model. The model can capture the summertime monsoon rainfall, with characteristics similar to those from Tropical Rainfall Measuring Mission and Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation. By comparing the 2075-2099 with the present-day climate simulations, there is a robust increase of the mean rainfall in many locations due to a warmer climate. Over southeastern China, the Baiu rainband, Bay of Bengal and central India, extreme precipitation rates are also enhanced in the future, which can be inferred from increases of the 95th percentile of daily precipitation, the maximum accumulated precipitation in 5 consecutive days, the simple daily precipitation intensity index, and the scale parameter of the fitted gamma distribution. In these regions, with the exception of the Baiu rainband, most of these metrics give a fractional change of extreme rainfall per degree increase of the lower-tropospheric temperature of 5 to 8.5% K-1, roughly consistent with the Clausius-Clapeyron relation. However, over the Baiu area extreme precipitation change scales as 3.5% K-1 only. We have also stratified the rainfall data into those associated with tropical cyclones (TC) and those with other weather systems. The AGCM gives an increase of the accumulated TC rainfall over southeastern China, and a decrease in southern Japan in the future climate. The latter can be attributed to suppressed TC occurrence in southern Japan, whereas increased accumulated rainfall over southeastern China is due to more intense TC rain rate under global warming. Overall, non-TC weather systems are the main contributor to enhanced precipitation extremes in various locations. In the future, TC activities over southeastern China tend to further

  19. Improving weather forecasts for wind energy applications

    Science.gov (United States)

    Kay, Merlinde; MacGill, Iain

    2010-08-01

    Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms-1 and around 25 ms-1. A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

  20. Improving weather forecasts for wind energy applications

    International Nuclear Information System (INIS)

    Kay, Merlinde; MacGill, Iain

    2010-01-01

    Weather forecasts play an important role in the energy industry particularly because of the impact of temperature on electrical demand. Power system operation requires that this variable and somewhat unpredictable demand be precisely met at all times and locations from available generation. As wind generation makes up a growing component of electricity supply around the world, it has become increasingly important to be able to provide useful forecasting for this highly variable and uncertain energy resource. Of particular interest are forecasts of weather events that rapidly change wind energy production from one or more wind farms. In this paper we describe work underway to improve the wind forecasts currently available from standard Numerical Weather Prediction (NWP) through a bias correction methodology. Our study has used the Australian Bureau of Meteorology MesoLAPS 5 km limited domain model over the Victoria/Tasmania region, providing forecasts for the Woolnorth wind farm, situated in Tasmania, Australia. The accuracy of these forecasts has been investigated, concentrating on the key wind speed ranges 5 - 15 ms -1 and around 25 ms -1 . A bias correction methodology was applied to the NWP hourly forecasts to help account for systematic issues such as the NWP grid point not being at the exact location of the wind farm. An additional correction was applied for timing issues by using meteorological data from the wind farm. Results to date show a reduction in spread of forecast error for hour ahead forecasts by as much as half using this double correction methodology - a combination of both bias correction and timing correction.

  1. A new approach for assimilation of 2D radar precipitation in a high-resolution NWP model

    DEFF Research Database (Denmark)

    Korsholm, Ulrik Smith; Petersen, Claus; Sass, Bent Hansen

    2015-01-01

    of precipitation, the strength of the nudging is proportional to the offset between observed and modelled precipitation, leading to increased moisture convergence. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values......A new approach for assimilation of 2D precipitation in numerical weather prediction models is presented and tested in a case with convective, heavy precipitation. In the scheme a nudging term is added to the horizontal velocity divergence tendency equation. In case of underproduction....... The method was implemented in the Danish Meteorological Institute numerical weather prediction (DMI NWP) nowcasting system, running with hourly cycles, performing a surface analysis and 3D variational analysis for upper air assimilation at each cycle restart, followed by nudging assimilation of precipitation...

  2. Properties of Extreme Precipitation and Their Uncertainties in 3-year GPM Precipitation Radar Data

    Science.gov (United States)

    Liu, N.; Liu, C.

    2017-12-01

    Extreme high precipitation rates are often related to flash floods and have devastating impacts on human society and the environments. To better understand these rare events, 3-year Precipitation Features (PFs) are defined by grouping the contiguous areas with nonzero near-surface precipitation derived using Global Precipitation Measurement (GPM) Ku band Precipitation Radar (KuPR). The properties of PFs with extreme precipitation rates greater than 20, 50, 100 mm/hr, such as the geographical distribution, volumetric precipitation contribution, seasonal and diurnal variations, are examined. In addition to the large seasonal and regional variations, the rare extreme precipitation rates often have a larger contribution to the local total precipitation. Extreme precipitation rates occur more often over land than over ocean. The challenges in the retrieval of extreme precipitation might be from the attenuation correction and large uncertainties in the Z-R relationships from near-surface radar reflectivity to precipitation rates. These potential uncertainties are examined by using collocated ground based radar reflectivity and precipitation retrievals.

  3. Quantum Corrected Non-Thermal Radiation Spectrum from the Tunnelling Mechanism

    Directory of Open Access Journals (Sweden)

    Subenoy Chakraborty

    2015-06-01

    Full Text Available The tunnelling mechanism is today considered a popular and widely used method in describing Hawking radiation. However, in relation to black hole (BH emission, this mechanism is mostly used to obtain the Hawking temperature by comparing the probability of emission of an outgoing particle with the Boltzmann factor. On the other hand, Banerjee and Majhi reformulated the tunnelling framework deriving a black body spectrum through the density matrix for the outgoing modes for both the Bose-Einstein distribution and the Fermi-Dirac distribution. In contrast, Parikh and Wilczek introduced a correction term performing an exact calculation of the action for a tunnelling spherically symmetric particle and, as a result, the probability of emission of an outgoing particle corresponds to a non-strictly thermal radiation spectrum. Recently, one of us (C. Corda introduced a BH effective state and was able to obtain a non-strictly black body spectrum from the tunnelling mechanism corresponding to the probability of emission of an outgoing particle found by Parikh and Wilczek. The present work introduces the quantum corrected effective temperature and the corresponding quantum corrected effective metric is written using Hawking’s periodicity arguments. Thus, we obtain further corrections to the non-strictly thermal BH radiation spectrum as the final distributions take into account both the BH dynamical geometry during the emission of the particle and the quantum corrections to the semiclassical Hawking temperature.

  4. Detecting weather radar clutter using satellite-based nowcasting products

    DEFF Research Database (Denmark)

    Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

    2006-01-01

    This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

  5. Understanding the roles of ligand promoted dissolution, water column saturation and hydrological properties on intense basalt weathering using reactive transport and watershed-scale hydrologic modeling

    Science.gov (United States)

    Perez Fodich, A.; Walter, M. T.; Derry, L. A.

    2016-12-01

    The interaction of rocks with rainwater generates physical and chemical changes, which ultimately culminates in soil development. The addition of catalyzers such as plants, atmospheric gases and hydrological properties will result in more intense and/or faster weathering transformations. The intensity of weathering across the Island of Hawaii is strongly correlated with exposure age and time-integrated precipitation. Intense weathering has resulted from interaction between a thermodynamically unstable lithology, high water/rock ratios, atmospheric gases (O2, CO2) and biota as an organic acid and CO2 producer. To further investigate the role of different weathering agents we have developed 1-D reactive transport models (RTM) to understand mineralogical and fluid chemistry changes in the initially basaltic porous media. The initial meso-scale heterogeneity of porosity makes it difficult for RTMs to capture changes in runoff/groundwater partitioning. Therefore, hydraulic properties (hydraulic conductivity and aquifer depth) are modeled as a watershed parameter appropriate for this system where sub-surface hydraulic data is scarce(1). Initial results agree with field data in a broad sense: different rainfall regimes and timescales show depletion of mobile cations, increasingly low pH, congruent dissolution of olivine and pyroxene, incongruent dissolution of plagioclase and basaltic glass, precipitation of non-crystalline allophane and ferrihydrite, and porosity changes due to dissolution and precipitation of minerals; ultimately Al and Fe are also exported from the system. RTM is used to examine the roles of unsaturation in the soil profile, ligand promoted dissolution of Al- and Fe-bearing phases, and Fe-oxide precipitation at the outcrop scale. Also, we aim to test the use of recession flow analysis to model watershed-scale hydrological properties to extrapolate changes in the runoff/groundwater partitioning. The coupling between weathering processes and hydrologic

  6. Evaluation of TIGGE Ensemble Forecasts of Precipitation in Distinct Climate Regions in Iran

    Science.gov (United States)

    Aminyavari, Saleh; Saghafian, Bahram; Delavar, Majid

    2018-04-01

    The application of numerical weather prediction (NWP) products is increasing dramatically. Existing reports indicate that ensemble predictions have better skill than deterministic forecasts. In this study, numerical ensemble precipitation forecasts in the TIGGE database were evaluated using deterministic, dichotomous (yes/no), and probabilistic techniques over Iran for the period 2008-16. Thirteen rain gauges spread over eight homogeneous precipitation regimes were selected for evaluation. The Inverse Distance Weighting and Kriging methods were adopted for interpolation of the prediction values, downscaled to the stations at lead times of one to three days. To enhance the forecast quality, NWP values were post-processed via Bayesian Model Averaging. The results showed that ECMWF had better scores than other products. However, products of all centers underestimated precipitation in high precipitation regions while overestimating precipitation in other regions. This points to a systematic bias in forecasts and demands application of bias correction techniques. Based on dichotomous evaluation, NCEP did better at most stations, although all centers overpredicted the number of precipitation events. Compared to those of ECMWF and NCEP, UKMO yielded higher scores in mountainous regions, but performed poorly at other selected stations. Furthermore, the evaluations showed that all centers had better skill in wet than in dry seasons. The quality of post-processed predictions was better than those of the raw predictions. In conclusion, the accuracy of the NWP predictions made by the selected centers could be classified as medium over Iran, while post-processing of predictions is recommended to improve the quality.

  7. A Radar Climatology for Germany - a 16-year high resolution precipitation data and its possibilities

    Science.gov (United States)

    Walawender, Ewelina; Winterrath, Tanja; Brendel, Christoph; Hafer, Mario; Junghänel, Thomas; Klameth, Anna; Weigl, Elmar; Becker, Andreas

    2017-04-01

    One of the main features of heavy precipitation events is their small-scale distribution. Despite a local occurrence, these intensive rainfalls may, however, cause most serious damage and have significant impact on the whole river basin area resulting in e.g. flash floods or urban flooding. Thus, it is of great importance not only to detect the life-cycle of extreme precipitation during its occurrence but also to collect precise climatological information on such events. The German weather service (Deutscher Wetterdienst) operates a very dense network of more than 2000 weather stations collecting data on precipitation. It is however not sufficient for detecting spatially limited phenomena. Thanks to radar data, current monitoring of such events is possible. A quality control process is applied to real-time radar products, however only automatic rain gauges data can be used in the adjustment procedure. To merge both radar data and all available rain gauges data, the radar climatology dataset was established. Within the framework of a project financed by the federal agencies' strategic alliance 'Adaptation to Climate Change', 16 years (2001-2016) of radar data have been reanalyzed in order to gain a homogenous, quality-controlled, high-resolution precipitation data set suitable for analyzing extreme events in a climatological approach. Additional corrections methods (e.g. clutter, spokes and beam height correction) were defined and used for the reprocessing procedure to enhance the data quality. Although the time series is still rather short for a climatology, for the first time the data set allows an insight into e.g. the distribution, size, life cycle, and duration of extreme events that cannot be measured by point measurements alone. All radar climatology products share the same spatial and temporal coverage. The whole dataset has been produced for the area of Germany. With the relatively high spatial resolution of 1km, the data can be used as a component of wide

  8. Effects of Weathering on TIR Spectra and Rock Classification

    Science.gov (United States)

    McDowell, M. L.; Hamilton, V. E.; Riley, D.

    2006-03-01

    Changes in mineralogy due to weathering are detectable in the TIR and cause misclassification of rock types. We survey samples over a range of lithologies and attempt to provide a method of correction for rock identification from weathered spectra.

  9. Estimating Tropical Cyclone Precipitation from Station Observations

    Institute of Scientific and Technical Information of China (English)

    REN Fumin; WANG Yongmei; WANG Xiaoling; LI Weijing

    2007-01-01

    In this paper, an objective technique for estimating the tropical cyclone (TC) precipitation from station observations is proposed. Based on a comparison between the Original Objective Method (OOM) and the Expert Subjective Method (ESM), the Objective Synoptic Analysis Technique (OSAT) for partitioning TC precipitation was developed by analyzing the western North Pacific (WNP) TC historical track and the daily precipitation datasets. Being an objective way of the ESM, OSAT overcomes the main problems in OOM,by changing two fixed parameters in OOM, the thresholds for the distance of the absolute TC precipitation (D0) and the TC size (D1), into variable parameters.Case verification for OSAT was also carried out by applying CMORPH (Climate Prediction Center MORPHing technique) daily precipitation measurements, which is NOAA's combined satellite precipitation measurement system. This indicates that OSAT is capable of distinguishing simultaneous TC precipitation rain-belts from those associated with different TCs or with middle-latitude weather systems.

  10. Continuous quantum error correction for non-Markovian decoherence

    International Nuclear Information System (INIS)

    Oreshkov, Ognyan; Brun, Todd A.

    2007-01-01

    We study the effect of continuous quantum error correction in the case where each qubit in a codeword is subject to a general Hamiltonian interaction with an independent bath. We first consider the scheme in the case of a trivial single-qubit code, which provides useful insights into the workings of continuous error correction and the difference between Markovian and non-Markovian decoherence. We then study the model of a bit-flip code with each qubit coupled to an independent bath qubit and subject to continuous correction, and find its solution. We show that for sufficiently large error-correction rates, the encoded state approximately follows an evolution of the type of a single decohering qubit, but with an effectively decreased coupling constant. The factor by which the coupling constant is decreased scales quadratically with the error-correction rate. This is compared to the case of Markovian noise, where the decoherence rate is effectively decreased by a factor which scales only linearly with the rate of error correction. The quadratic enhancement depends on the existence of a Zeno regime in the Hamiltonian evolution which is absent in purely Markovian dynamics. We analyze the range of validity of this result and identify two relevant time scales. Finally, we extend the result to more general codes and argue that the performance of continuous error correction will exhibit the same qualitative characteristics

  11. Global daily precipitation fields from bias-corrected rain gauge and satellite observations. Pt. 1. Design and development

    Energy Technology Data Exchange (ETDEWEB)

    Kottek, M.; Rubel, F. [Univ. of Veterinary Medicine, Vienna (Austria). Biometeorology Group

    2007-10-15

    Global daily precipitation analyses are mainly based on satellite estimates, often calibrated with monthly ground analyses or merged with model predictions. We argue here that an essential improvement of their accuracy is only possible by incorporation of daily ground measurements. In this work we apply geostatistical methods to compile a global precipitation product based on daily rain gauge measurements. The raw ground measurements, disseminated via Global Telecommunication System (GTS), are corrected for their systematic measurement errors and interpolated onto a global 1 degree grid. For interpolation ordinary block kriging is applied, with precalculated spatial auto-correlation functions (ACFs). This technique allows to incorporate additional climate information. First, monthly ACFs are calculated from the daily data; second, they are regionalised according to the five main climatic zones of the Koeppen-Geiger climate classification. The interpolation error, a by-product of kriging, is used to flag grid points as missing if the error is above a predefined threshold. But for many applications missing values constitute a problem. Due to a combination of the ground analyses with the daily multi-satellite product of the Global Precipitation Climatology Project (GPCP-1DD) not only these missing values are replaced but also the spatial structure of the satellite estimates is considered. As merging method bivariate ordinary co-kriging is applied. The ACFs necessary for the gauge and the satellite fields as well as the corresponding spatial cross-correlation functions (CCFs) are again precalculated for each of the five main climatic zones and for each individual month. As a result two new global daily data sets for the period 1996 up to today will be available on the Internet (www.gmes-geoland.info): A precipitation product over land, analysed from ground measurements; and a global precipitation product merged from this and the GPCP-1DD multi-satellite product. (orig.)

  12. Colluvial deposits as a possible weathering reservoir in uplifting mountains

    Science.gov (United States)

    Carretier, Sébastien; Goddéris, Yves; Martinez, Javier; Reich, Martin; Martinod, Pierre

    2018-03-01

    The role of mountain uplift in the evolution of the global climate over geological times is controversial. At the heart of this debate is the capacity of rapid denudation to drive silicate weathering, which consumes CO2. Here we present the results of a 3-D model that couples erosion and weathering during mountain uplift, in which, for the first time, the weathered material is traced during its stochastic transport from the hillslopes to the mountain outlet. To explore the response of weathering fluxes to progressively cooler and drier climatic conditions, we run model simulations accounting for a decrease in temperature with or without modifications in the rainfall pattern based on a simple orographic model. At this stage, the model does not simulate the deep water circulation, the precipitation of secondary minerals, variations in the pH, below-ground pCO2, and the chemical affinity of the water in contact with minerals. Consequently, the predicted silicate weathering fluxes probably represent a maximum, although the predicted silicate weathering rates are within the range of silicate and total weathering rates estimated from field data. In all cases, the erosion rate increases during mountain uplift, which thins the regolith and produces a hump in the weathering rate evolution. This model thus predicts that the weathering outflux reaches a peak and then falls, consistent with predictions of previous 1-D models. By tracking the pathways of particles, the model can also consider how lateral river erosion drives mass wasting and the temporary storage of colluvial deposits on the valley sides. This reservoir is comprised of fresh material that has a residence time ranging from several years up to several thousand years. During this period, the weathering of colluvium appears to sustain the mountain weathering flux. The relative weathering contribution of colluvium depends on the area covered by regolith on the hillslopes. For mountains sparsely covered by regolith

  13. An Improved Dynamical Downscaling Method with GCM Bias Corrections and Its Validation with 30 Years of Climate Simulations

    KAUST Repository

    Xu, Zhongfeng

    2012-09-01

    An improved dynamical downscaling method (IDD) with general circulation model (GCM) bias corrections is developed and assessed over North America. A set of regional climate simulations is performed with the Weather Research and Forecasting Model (WRF) version 3.3 embedded in the National Center for Atmospheric Research\\'s (NCAR\\'s) Community Atmosphere Model (CAM). The GCM climatological means and the amplitudes of interannual variations are adjusted based on the National Centers for Environmental Prediction (NCEP)-NCAR global reanalysis products (NNRP) before using them to drive WRF. In this study, the WRF downscaling experiments are identical except the initial and lateral boundary conditions derived from the NNRP, original GCM output, and bias-corrected GCM output, respectively. The analysis finds that the IDD greatly improves the downscaled climate in both climatological means and extreme events relative to the traditional dynamical downscaling approach (TDD). The errors of downscaled climatological mean air temperature, geopotential height, wind vector, moisture, and precipitation are greatly reduced when the GCM bias corrections are applied. In the meantime, IDD also improves the downscaled extreme events characterized by the reduced errors in 2-yr return levels of surface air temperature and precipitation. In comparison with TDD, IDD is also able to produce a more realistic probability distribution in summer daily maximum temperature over the central U.S.-Canada region as well as in summer and winter daily precipitation over the middle and eastern United States. © 2012 American Meteorological Society.

  14. Importance of resolution and model configuration when downscaling extreme precipitation

    Directory of Open Access Journals (Sweden)

    Adrian J. Champion

    2014-07-01

    Full Text Available Dynamical downscaling is frequently used to investigate the dynamical variables of extra-tropical cyclones, for example, precipitation, using very high-resolution models nested within coarser resolution models to understand the processes that lead to intense precipitation. It is also used in climate change studies, using long timeseries to investigate trends in precipitation, or to look at the small-scale dynamical processes for specific case studies. This study investigates some of the problems associated with dynamical downscaling and looks at the optimum configuration to obtain the distribution and intensity of a precipitation field to match observations. This study uses the Met Office Unified Model run in limited area mode with grid spacings of 12, 4 and 1.5 km, driven by boundary conditions provided by the ECMWF Operational Analysis to produce high-resolution simulations for the Summer of 2007 UK flooding events. The numerical weather prediction model is initiated at varying times before the peak precipitation is observed to test the importance of the initialisation and boundary conditions, and how long the simulation can be run for. The results are compared to raingauge data as verification and show that the model intensities are most similar to observations when the model is initialised 12 hours before the peak precipitation is observed. It was also shown that using non-gridded datasets makes verification more difficult, with the density of observations also affecting the intensities observed. It is concluded that the simulations are able to produce realistic precipitation intensities when driven by the coarser resolution data.

  15. A subgrid parameterization scheme for precipitation

    Directory of Open Access Journals (Sweden)

    S. Turner

    2012-04-01

    Full Text Available With increasing computing power, the horizontal resolution of numerical weather prediction (NWP models is improving and today reaches 1 to 5 km. Nevertheless, clouds and precipitation formation are still subgrid scale processes for most cloud types, such as cumulus and stratocumulus. Subgrid scale parameterizations for water vapor condensation have been in use for many years and are based on a prescribed probability density function (PDF of relative humidity spatial variability within the model grid box, thus providing a diagnosis of the cloud fraction. A similar scheme is developed and tested here. It is based on a prescribed PDF of cloud water variability and a threshold value of liquid water content for droplet collection to derive a rain fraction within the model grid. Precipitation of rainwater raises additional concerns relative to the overlap of cloud and rain fractions, however. The scheme is developed following an analysis of data collected during field campaigns in stratocumulus (DYCOMS-II and fair weather cumulus (RICO and tested in a 1-D framework against large eddy simulations of these observed cases. The new parameterization is then implemented in a 3-D NWP model with a horizontal resolution of 2.5 km to simulate real cases of precipitating cloud systems over France.

  16. Assessing changes in extreme convective precipitation from a damage perspective

    Science.gov (United States)

    Schroeer, K.; Tye, M. R.

    2016-12-01

    Projected increases in high-intensity short-duration convective precipitation are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to which, not only are extreme events rare, but such small scale events are likely to be underreported where they don't coincide with the observation network. Rather than focus solely on the convective precipitation, understanding the characteristics of these extremes which drive damage may be more effective to assess future risks. Two sources of data are used in this study. First, sub-daily precipitation observations over the Southern Alps enable an examination of seasonal and regional patterns in high-intensity convective precipitation and their relationship with weather types. Secondly, reports of private loss and damage on a household scale are used to identify which events are most damaging, or what conditions potentially enhance the vulnerability to these extremes.This study explores the potential added value from including recorded loss and damage data to understand the risks from summertime convective precipitation events. By relating precipitation generating weather types to the severity of damage we hope to develop a mechanism to assess future risks. A further benefit would be to identify from damage reports the likely occurrence of precipitation extremes where no direct observations are available and use this information to validate remotely sensed observations.

  17. Rough Precipitation Forecasts based on Analogue Method: an Operational System

    Science.gov (United States)

    Raffa, Mario; Mercogliano, Paola; Lacressonnière, Gwendoline; Guillaume, Bruno; Deandreis, Céline; Castanier, Pierre

    2017-04-01

    In the framework of the Climate KIC partnership, has been funded the project Wat-Ener-Cast (WEC), coordinated by ARIA Technologies, having the goal to adapt, through tailored weather-related forecast, the water and energy operations to the increased weather fluctuation and to climate change. The WEC products allow providing high quality forecast suited in risk and opportunities assessment dashboard for water and energy operational decisions and addressing the needs of sewage/water distribution operators, energy transport & distribution system operators, energy manager and wind energy producers. A common "energy water" web platform, able to interface with newest smart water-energy IT network have been developed. The main benefit by sharing resources through the "WEC platform" is the possibility to optimize the cost and the procedures of safety and maintenance team, in case of alerts and, finally to reduce overflows. Among the different services implemented on the WEC platform, ARIA have developed a product having the goal to support sewage/water distribution operators, based on a gradual forecast information system ( at 48hrs/24hrs/12hrs horizons) of heavy precipitation. For each fixed deadline different type of operation are implemented: 1) 48hour horizon, organisation of "on call team", 2) 24 hour horizon, update and confirm the "on call team", 3) 12 hour horizon, secure human resources and equipment (emptying storage basins, pipes manipulations …). More specifically CMCC have provided a statistical downscaling method in order to provide a "rough" daily local precipitation at 24 hours, especially when high precipitation values are expected. This statistical technique consists of an adaptation of analogue method based on ECMWF data (analysis and forecast at 24 hours). One of the most advantages of this technique concerns a lower computational burden and budget compared to running a Numerical Weather Prediction (NWP) model, also if, of course it provides only this

  18. Economic Effects of Precipitation Enhancement in the Corn Belt.

    Science.gov (United States)

    Gapcia, Philip; Changnon, Stanley; Pinar, Musa

    1990-01-01

    Policy formulation in weather modification requires an understanding of the economic effects from altered weather. The focus of this study is to provide insight into the beneficiaries of a functioning weather modification technology when applied at various spatial and temporal levels. An econometric model which links the corn/scybean production to U.S. cattle, hog and poultry sectors is used to determine the effects of precipitation enhancement in the U.S. Corn Belt, a humid climatic region. A regional supply formulation permits assessment of weather modification on production, prices, revenues to producers, and savings in consumers expenditures on meat. The results provide insight into the distribution of economic effects, emphasize the importance of careful planning in the use of weather modification technology, and provide useful information on the roles of local, state, and federal governments in the support of weather modification.

  19. Assessing the Implications of Changing Extreme Value Distributions of Weather on Carbon and Water Cycling in Grasslands

    Science.gov (United States)

    Brunsell, N. A.; Nippert, J. B.

    2011-12-01

    As the climate warms, it is generally acknowledged that the number and magnitude of extreme weather events will increase. We examined an ecophysiological model's responses to precipitation and temperature anomalies in relation to the mean and variance of annual precipitation along a pronounced precipitation gradient from eastern to western Kansas. This natural gradient creates a template of potential responses for both the mean and variance of annual precipitation to compare the timescales of carbon and water fluxes. Using data from several Ameriflux sites (KZU and KFS) and a third eddy covariance tower (K4B) along the gradient, BIOME-BGC was used to characterize water and carbon cycle responses to extreme weather events. Changes in the extreme value distributions were based on SRES A1B and A2 scenarios using an ensemble mean of 21 GCMs for the region, downscaled using a stochastic weather generator. We focused on changing the timing and magnitude of precipitation and altering the diurnal and seasonal temperature ranges. Biome-BGC was then forced with daily output from the stochastic weather generator, and we examined how potential changes in these extreme value distributions impact carbon and water cycling at the sites across the Kansas precipitation gradient at time scales ranging from daily to interannual. To decompose the time scales of response, we applied a wavelet based information theory analysis approach. Results indicate impacts in soil moisture memory and carbon allocation processes, which vary in response to both the mean and variance of precipitation along the precipitation gradient. These results suggest a more pronounced focus ecosystem responses to extreme events across a range of temporal scales in order to fully characterize the water and carbon cycle responses to global climate change.

  20. A multi-source precipitation approach to fill gaps over a radar precipitation field

    Science.gov (United States)

    Tesfagiorgis, K. B.; Mahani, S. E.; Khanbilvardi, R.

    2012-12-01

    Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products. The present work develops an approach to seamlessly blend satellite, radar, climatological and gauge precipitation products to fill gaps over ground-based radar precipitation fields. To mix different precipitation products, the bias of any of the products relative to each other should be removed. For bias correction, the study used an ensemble-based method which aims to estimate spatially varying multiplicative biases in SPEs using a radar rainfall product. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. A weighted Successive Correction Method (SCM) is proposed to make the merging between error corrected satellite and radar rainfall estimates. In addition to SCM, we use a Bayesian spatial method for merging the gap free radar with rain gauges, climatological rainfall sources and SPEs. We demonstrate the method using SPE Hydro-Estimator (HE), radar- based Stage-II, a climatological product PRISM and rain gauge dataset for several rain events from 2006 to 2008 over three different geographical locations of the United States. Results show that: the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements. The study implies that using the available radar pixels surrounding the gap area, rain gauge, PRISM and satellite products, a radar like product is achievable over radar gap areas that benefits the scientific community.

  1. Regime-dependent forecast uncertainty of convective precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Keil, Christian; Craig, George C. [Muenchen Univ. (Germany). Meteorologisches Inst.

    2011-04-15

    Forecast uncertainty of convective precipitation is influenced by all scales, but in different ways in different meteorological situations. Forecasts of the high resolution ensemble prediction system COSMO-DE-EPS of Deutscher Wetterdienst (DWD) are used to examine the dominant sources of uncertainty of convective precipitation. A validation with radar data using traditional as well as spatial verification measures highlights differences in precipitation forecast performance in differing weather regimes. When the forecast uncertainty can primarily be associated with local, small-scale processes individual members run with the same variation of the physical parameterisation driven by different global models outperform all other ensemble members. In contrast when the precipitation is governed by the large-scale flow all ensemble members perform similarly. Application of the convective adjustment time scale confirms this separation and shows a regime-dependent forecast uncertainty of convective precipitation. (orig.)

  2. Minimal and non-minimal standard models: Universality of radiative corrections

    International Nuclear Information System (INIS)

    Passarino, G.

    1991-01-01

    The possibility of describing electroweak processes by means of models with a non-minimal Higgs sector is analyzed. The renormalization procedure which leads to a set of fitting equations for the bare parameters of the lagrangian is first reviewed for the minimal standard model. A solution of the fitting equations is obtained, which correctly includes large higher-order corrections. Predictions for physical observables, notably the W boson mass and the Z O partial widths, are discussed in detail. Finally the extension to non-minimal models is described under the assumption that new physics will appear only inside the vector boson self-energies and the concept of universality of radiative corrections is introduced, showing that to a large extent they are insensitive to the details of the enlarged Higgs sector. Consequences for the bounds on the top quark mass are also discussed. (orig.)

  3. An improved non-uniformity correction algorithm and its GPU parallel implementation

    Science.gov (United States)

    Cheng, Kuanhong; Zhou, Huixin; Qin, Hanlin; Zhao, Dong; Qian, Kun; Rong, Shenghui

    2018-05-01

    The performance of SLP-THP based non-uniformity correction algorithm is seriously affected by the result of SLP filter, which always leads to image blurring and ghosting artifacts. To address this problem, an improved SLP-THP based non-uniformity correction method with curvature constraint was proposed. Here we put forward a new way to estimate spatial low frequency component. First, the details and contours of input image were obtained respectively by minimizing local Gaussian curvature and mean curvature of image surface. Then, the guided filter was utilized to combine these two parts together to get the estimate of spatial low frequency component. Finally, we brought this SLP component into SLP-THP method to achieve non-uniformity correction. The performance of proposed algorithm was verified by several real and simulated infrared image sequences. The experimental results indicated that the proposed algorithm can reduce the non-uniformity without detail losing. After that, a GPU based parallel implementation that runs 150 times faster than CPU was presented, which showed the proposed algorithm has great potential for real time application.

  4. Weather Augmented Risk Determination (WARD) System

    Science.gov (United States)

    Niknejad, M.; Mazdiyasni, O.; Momtaz, F.; AghaKouchak, A.

    2017-12-01

    Extreme climatic events have direct and indirect impacts on society, economy and the environment. Based on the United States Bureau of Economic Analysis (BEA) data, over one third of the U.S. GDP can be considered as weather-sensitive involving some degree of weather risk. This expands from a local scale concrete foundation construction to large scale transportation systems. Extreme and unexpected weather conditions have always been considered as one of the probable risks to human health, productivity and activities. The construction industry is a large sector of the economy, and is also greatly influenced by weather-related risks including work stoppage and low labor productivity. Identification and quantification of these risks, and providing mitigation of their effects are always the concerns of construction project managers. In addition to severe weather conditions' destructive effects, seasonal changes in weather conditions can also have negative impacts on human health. Work stoppage and reduced labor productivity can be caused by precipitation, wind, temperature, relative humidity and other weather conditions. Historical and project-specific weather information can improve better project management and mitigation planning, and ultimately reduce the risk of weather-related conditions. This paper proposes new software for project-specific user-defined data analysis that offers (a) probability of work stoppage and the estimated project length considering weather conditions; (b) information on reduced labor productivity and its impacts on project duration; and (c) probabilistic information on the project timeline based on both weather-related work stoppage and labor productivity. The software (WARD System) is designed such that it can be integrated into the already available project management tools. While the system and presented application focuses on the construction industry, the developed software is general and can be used for any application that involves

  5. Physical correction model for automatic correction of intensity non-uniformity in magnetic resonance imaging

    Directory of Open Access Journals (Sweden)

    Stefan Leger

    2017-10-01

    Conclusion: The proposed PCM algorithm led to a significantly improved image quality compared to the originally acquired images, suggesting that it is applicable to the correction of MRI data. Thus it may help to reduce intensity non-uniformity which is an important step for advanced image analysis.

  6. Evidence of Urban Precipitation Anomalies from Satellite and Ground-Based Measurements

    Science.gov (United States)

    Shepherd, J. Marshall; Manyin, M.; Negri, Andrew

    2004-01-01

    Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.

  7. Marine X-band Weather Radar Data Calibration

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2012-01-01

    estimates. This paper presents some of the challenges in small marine X-band radar calibration by comparing three calibration procedures for assessing the relationship between radar and rain gauge data. Validation shows similar results for precipitation volumes but more diverse results on peak rain......Application of weather radar data in urban hydrology is evolving and radar data is now applied for both modelling, analysis, and real time control purposes. In these contexts, it is allimportant that the radar data is well calibrated and adjusted in order to obtain valid quantitative precipitation...

  8. Operational quality control of daily precipitation using spatio-climatological consistency testing

    Science.gov (United States)

    Scherrer, S. C.; Croci-Maspoli, M.; van Geijtenbeek, D.; Naguel, C.; Appenzeller, C.

    2010-09-01

    Quality control (QC) of meteorological data is of utmost importance for climate related decisions. The search for an effective automated QC of precipitation data has proven difficult and many weather services still use mainly manual inspection of daily precipitation including MeteoSwiss. However, man power limitations force many weather services to move towards less labour intensive and more automated QC with the challenge to keeping data quality high. In the last decade, several approaches have been presented to objectify daily precipitation QC. Here we present a spatio-climatological approach that will be implemented operationally at MeteoSwiss. It combines the information from the event based spatial distribution of everyday's precipitation field and the historical information of the interpolation error using different precipitation intensity intervals. Expert judgement shows that the system is able to detect potential outliers very well (hardly any missed errors) without creating too many false alarms that need human inspection. 50-80% of all flagged values have been classified as real errors by the data editor. This is much better than the roughly 15-20% using standard spatial regression tests. Very helpful in the QC process is the automatic redistribution of accumulated several day sums. Manual inspection in operations can be reduced and the QC of precipitation objectified substantially.

  9. Impact of AIRS Thermodynamic Profile on Regional Weather Forecast

    Science.gov (United States)

    Chou, Shih-Hung; Zavodsky, Brad; Jedlovee, Gary

    2010-01-01

    Prudent assimilation of AIRS thermodynamic profiles and quality indicators can improve initial conditions for regional weather models. AIRS-enhanced analysis has warmer and moister PBL. Forecasts with AIRS profiles are generally closer to NAM analyses than CNTL. Assimilation of AIRS leads to an overall QPF improvement in 6-h accumulated precipitation forecasts. Including AIRS profiles in assimilation process enhances the moist instability and produces stronger updrafts and a better precipitation forecast than the CNTL run.

  10. Impacts of extreme weather events on transport infrastructure in Norway

    Science.gov (United States)

    Frauenfelder, Regula; Solheim, Anders; Isaksen, Ketil; Romstad, Bård; Dyrrdal, Anita V.; Ekseth, Kristine H. H.; Gangstø Skaland, Reidun; Harbitz, Alf; Harbitz, Carl B.; Haugen, Jan E.; Hygen, Hans O.; Haakenstad, Hilde; Jaedicke, Christian; Jónsson, Árni; Klæboe, Ronny; Ludvigsen, Johanna; Meyer, Nele K.; Rauken, Trude; Sverdrup-Thygeson, Kjetil

    2016-04-01

    With the latest results on expected future increase in air temperature and precipitation changes reported by the Intergovernmental Panel on Climate Change (IPCC), the climate robustness of important infrastructure is of raising concern in Norway, as well as in the rest of Europe. Economic consequences of natural disasters have increased considerably since 1950. In addition to the effect of demographic changes such as population growth, urbanization and more and more concentration of valuable assets, this increase is also related to an augmenting frequency of extreme events, such as storms, flooding, drought, and landslides. This change is also observable in Norway, where the increased frequency of strong precipitation has led to frequent flooding and landslide events during the last 20 years. A number of studies show that climate change causes an increase in both frequency and intensity of several types of extreme weather, especially when it comes to precipitation. Such extreme weather events greatly affect the transport infrastructure, with numerous and long closures of roads and railroads, in addition to damage and repair costs. Frequent closures of railroad and roads lead to delay or failure in delivery of goods, which again may lead to a loss of customers and/or - eventually - markets. Much of the Norwegian transport infrastructure is more than 50 years old and therefore not adequately dimensioned, even for present climatic conditions. In order to assess these problems and challenges posed to the Norwegian transport infrastructure from present-day and future extreme weather events, the project "Impacts of extreme weather events on infrastructure in Norway (InfraRisk)" was performed under the research Council of Norway program 'NORKLIMA', between 2009 and 2013. The main results of the project are: - Moderate to strong precipitation events have become more frequent and more intense in Norway over the last 50 years, and this trend continues throughout the 21st

  11. Conditional Stochastic Models in Reduced Space: Towards Efficient Simulation of Tropical Cyclone Precipitation Patterns

    Science.gov (United States)

    Dodov, B.

    2017-12-01

    Stochastic simulation of realistic and statistically robust patterns of Tropical Cyclone (TC) induced precipitation is a challenging task. It is even more challenging in a catastrophe modeling context, where tens of thousands of typhoon seasons need to be simulated in order to provide a complete view of flood risk. Ultimately, one could run a coupled global climate model and regional Numerical Weather Prediction (NWP) model, but this approach is not feasible in the catastrophe modeling context and, most importantly, may not provide TC track patterns consistent with observations. Rather, we propose to leverage NWP output for the observed TC precipitation patterns (in terms of downscaled reanalysis 1979-2015) collected on a Lagrangian frame along the historical TC tracks and reduced to the leading spatial principal components of the data. The reduced data from all TCs is then grouped according to timing, storm evolution stage (developing, mature, dissipating, ETC transitioning) and central pressure and used to build a dictionary of stationary (within a group) and non-stationary (for transitions between groups) covariance models. Provided that the stochastic storm tracks with all the parameters describing the TC evolution are already simulated, a sequence of conditional samples from the covariance models chosen according to the TC characteristics at a given moment in time are concatenated, producing a continuous non-stationary precipitation pattern in a Lagrangian framework. The simulated precipitation for each event is finally distributed along the stochastic TC track and blended with a non-TC background precipitation using a data assimilation technique. The proposed framework provides means of efficient simulation (10000 seasons simulated in a couple of days) and robust typhoon precipitation patterns consistent with observed regional climate and visually undistinguishable from high resolution NWP output. The framework is used to simulate a catalog of 10000 typhoon

  12. Engaging Earth- and Environmental-Science Undergraduates Through Weather Discussions and an eLearning Weather Forecasting Contest

    Science.gov (United States)

    Schultz, David M.; Anderson, Stuart; Seo-Zindy, Ryo

    2013-06-01

    For students who major in meteorology, engaging in weather forecasting can motivate learning, develop critical-thinking skills, improve their written communication, and yield better forecasts. Whether such advances apply to students who are not meteorology majors has been less demonstrated. To test this idea, a weather discussion and an eLearning weather forecasting contest were devised for a meteorology course taken by third-year undergraduate earth- and environmental-science students. The discussion consisted of using the recent, present, and future weather to amplify the topics of the week's lectures. Then, students forecasted the next day's high temperature and the probability of precipitation for Woodford, the closest official observing site to Manchester, UK. The contest ran for 10 weeks, and the students received credit for participation. The top students at the end of the contest received bonus points on their final grade. A Web-based forecast contest application was developed to register the students, receive their forecasts, and calculate weekly standings. Students who were successful in the forecast contest were not necessarily those who achieved the highest scores on the tests, demonstrating that the contest was possibly testing different skills than traditional learning. Student evaluations indicate that the weather discussion and contest were reasonably successful in engaging students to learn about the weather outside of the classroom, synthesize their knowledge from the lectures, and improve their practical understanding of the weather. Therefore, students taking a meteorology class, but not majoring in meteorology, can derive academic benefits from weather discussions and forecast contests. Nevertheless, student evaluations also indicate that better integration of the lectures, weather discussions, and the forecasting contests is necessary.

  13. Acute Low Back Pain? Do Not Blame the Weather-A Case-Crossover Study.

    Science.gov (United States)

    Beilken, Keira; Hancock, Mark J; Maher, Chris G; Li, Qiang; Steffens, Daniel

    2017-06-01

    To investigate the influence of various weather parameters on the risk of developing a low back pain (LBP) episode. Case-crossover study. Primary care clinics in Sydney, Australia. 981 participants with a new episode of acute LBP. Weather parameters were obtained from the Australian Bureau of Meteorology. Odds ratios (OR) and 95% confidence intervals (95% CI) were derived comparing two exposure variables in the case window-(1) the average of the weather variable for the day prior to pain onset and (2) the change in the weather variable from 2 days prior to 1 day prior to pain onset-with exposures in two control windows (1 week and 1 month before the case window). The weather parameters of precipitation, humidity, wind speed, wind gust, wind direction, and air pressure were not associated with the onset of acute LBP. For one of the four analyses, higher temperature slightly increased the odds of pain onset. Common weather parameters that had been previously linked to musculoskeletal pain, such as precipitation, humidity, wind speed, wind gust, wind direction, and air pressure, do not increase the risk of onset for LBP. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  14. Temporal variation of extreme precipitation events in Lithuania

    Directory of Open Access Journals (Sweden)

    Egidijus Rimkus

    2011-05-01

    Full Text Available Heavy precipitation events in Lithuania for the period 1961-2008 were analysed. The spatial distribution and dynamics of precipitation extremes were investigated. Positive tendencies and in some cases statistically significant trends were determined for the whole of Lithuania. Atmospheric circulation processes were derived using Hess & Brezowski's classification of macrocirculation forms. More than one third of heavy precipitation events (37% were observed when the atmospheric circulation was zonal. The location of the central part of a cyclone (WZ weather condition subtype over Lithuania is the most common synoptic situation (27% during heavy precipitation events. Climatic projections according to outputs of the CCLM model are also presented in this research. The analysis shows that the recurrence of heavy precipitation events in the 21st century will increase significantly (by up to 22% in Lithuania.

  15. There's no such thing as bad weather, just the wrong clothing: climate, weather and active school transportation in Toronto, Canada.

    Science.gov (United States)

    Mitra, Raktim; Faulkner, Guy

    2012-07-10

    Climatic conditions may enable or deter active school transportation in many North American cities, but the topic remains largely overlooked in the existing literature. This study explores the effect of seasonal climate (i.e., fall versus winter) and weekly weather conditions (i.e., temperature, precipitation) on active travelling to school across different built and policy environments. Home-to-school trips by 11-12-year-old children in the City of Toronto were examined using data from the 2006 Transportation Tomorrow Survey. Binomial logistic regressions were estimated to explore the correlates of the choice of active (i.e., walking) versus non-active (i.e., private automobile, transit and school bus) mode for school trips. Climate and weather-related variables were not associated with choice of school travel mode. Children living within the sidewalk snow-plough zone (i.e., in the inner-suburban neighbourhoods) were less likely to walk to school than children living outside of the zone (i.e., in the inner-city neighbourhoods). Given that seasonality and short-term weather conditions appear not to limit active school transportation in general, built environment interventions designed to facilitate active travel could have benefits that spill over across the entire year rather than being limited to a particular season. Educational campaigns with strategies for making the trip fun and ensuring that the appropriate clothing choices are made are also warranted in complementing built environment modifications.

  16. The importance of non-carbonate mineral weathering as a soil formation mechanism within a karst weathering profile in the SPECTRA Critical Zone Observatory, Guizhou Province, China

    Institute of Scientific and Technical Information of China (English)

    Oliver W.Moore; Heather L.Buss; Sophie M.Green; Man Liu; Zhaoliang Song

    2017-01-01

    Soil degradation,including rocky desertification,of the karst regions in China is severe.Karst landscapes are especially sensitive to soil degradation as carbonate rocks are nutrient-poor and easily eroded.Understanding the balance between soil formation and soil erosion is critical for long-term soil sustainability,yet little is known about the initial soil forming processes on karst terrain.Herein we examine the initial weathering processes of several types of carbonate bedrock containing varying amounts of non-carbonate minerals in the SPECTRA Critical Zone Observatory,Guizhou Province,Southwest China.We compared the weathering mechanisms of the bedrock to the mass transfer of mineral nutrients in a soil profile developed on these rocks and found that soil formation and nutrient contents are strongly dependent upon the weathering of interbedded layers of more silicate-rich bedrock (marls).Atmospheric inputs from dust were also detected.

  17. (ajst) the influence of weather on the insurance

    African Journals Online (AJOL)

    excessive rainfall, had a direct impact on the extent of damage on buildings and property. It also became clear ... KEY WORDS Weather Derivatives, Heating degree days, cooling degree days, Fire industrial and ... agricultural, water sectors, and horticultural and tourism ... humidity, precipitation, snow and solar radiation.

  18. Classification and correction of the radar bright band with polarimetric radar

    Science.gov (United States)

    Hall, Will; Rico-Ramirez, Miguel; Kramer, Stefan

    2015-04-01

    The annular region of enhanced radar reflectivity, known as the Bright Band (BB), occurs when the radar beam intersects a layer of melting hydrometeors. Radar reflectivity is related to rainfall through a power law equation and so this enhanced region can lead to overestimations of rainfall by a factor of up to 5, so it is important to correct for this. The BB region can be identified by using several techniques including hydrometeor classification and freezing level forecasts from mesoscale meteorological models. Advances in dual-polarisation radar measurements and continued research in the field has led to increased accuracy in the ability to identify the melting snow region. A method proposed by Kitchen et al (1994), a form of which is currently used operationally in the UK, utilises idealised Vertical Profiles of Reflectivity (VPR) to correct for the BB enhancement. A simpler and more computationally efficient method involves the formation of an average VPR from multiple elevations for correction that can still cause a significant decrease in error (Vignal 2000). The purpose of this research is to evaluate a method that relies only on analysis of measurements from an operational C-band polarimetric radar without the need for computationally expensive models. Initial results show that LDR is a strong classifier of melting snow with a high Critical Success Index of 97% when compared to the other variables. An algorithm based on idealised VPRs resulted in the largest decrease in error when BB corrected scans are compared to rain gauges and to lower level scans with a reduction in RMSE of 61% for rain-rate measurements. References Kitchen, M., R. Brown, and A. G. Davies, 1994: Real-time correction of weather radar data for the effects of bright band, range and orographic growth in widespread precipitation. Q.J.R. Meteorol. Soc., 120, 1231-1254. Vignal, B. et al, 2000: Three methods to determine profiles of reflectivity from volumetric radar data to correct

  19. A Multimedia Bibliography of Weather Materials for Schools. Climatological Publications, Bibliography Series No. 2.

    Science.gov (United States)

    Roseman, Steven, Ed.; Ray, Henry, Ed.

    This bibliography identifies multimedia weather resources for elementary and secondary schools in Arizona. Content of the materials includes weather forecasting techniques, storms, clouds, the atmosphere, wind, radar, humidity, precipitation, and world climate regions. The first section of the bibliography lists 47 books, most of which were…

  20. A DSP-based neural network non-uniformity correction algorithm for IRFPA

    Science.gov (United States)

    Liu, Chong-liang; Jin, Wei-qi; Cao, Yang; Liu, Xiu

    2009-07-01

    An effective neural network non-uniformity correction (NUC) algorithm based on DSP is proposed in this paper. The non-uniform response in infrared focal plane array (IRFPA) detectors produces corrupted images with a fixed-pattern noise(FPN).We introduced and analyzed the artificial neural network scene-based non-uniformity correction (SBNUC) algorithm. A design of DSP-based NUC development platform for IRFPA is described. The DSP hardware platform designed is of low power consumption, with 32-bit fixed point DSP TMS320DM643 as the kernel processor. The dependability and expansibility of the software have been improved by DSP/BIOS real-time operating system and Reference Framework 5. In order to realize real-time performance, the calibration parameters update is set at a lower task priority then video input and output in DSP/BIOS. In this way, calibration parameters updating will not affect video streams. The work flow of the system and the strategy of real-time realization are introduced. Experiments on real infrared imaging sequences demonstrate that this algorithm requires only a few frames to obtain high quality corrections. It is computationally efficient and suitable for all kinds of non-uniformity.

  1. GIS supported calculations of 137Cs deposition in Sweden based on precipitation data

    International Nuclear Information System (INIS)

    Almgren, Sara; Nilsson, Elisabeth; Erlandsson, Bengt; Isaksson, Mats

    2006-01-01

    It is of interest to know the spatial variation and the amount of 137 Cs e.g. in case of an accident with a radioactive discharge. In this study, the spatial distribution of the quarterly 137 Cs deposition over Sweden due to nuclear weapons fallout (NWF) during the period 1962-1966 was determined by relating the measured deposition density at a reference site to the amount of precipitation. Measured quarterly values of 137 Cs deposition density per unit precipitation at three reference sites and quarterly precipitation at 62 weather stations distributed over Sweden were used in the calculations. The reference sites were assumed to represent areas with different quarterly mean precipitation. The extent of these areas was determined from the distribution of the mean measured precipitation between 1961 and 1990 and varied according to seasonal variations in the mean precipitation pattern. Deposition maps were created by interpolation within a geographical information system (GIS). Both integrated (total) and cumulative (decay corrected) deposition densities were calculated. The lowest levels of NWF 137 Cs deposition density were noted in north-eastern and eastern parts of Sweden and the highest levels in the western parts of Sweden. Furthermore the deposition density of 137 Cs, resulting from the Chernobyl accident was determined for an area in western Sweden based on precipitation data. The highest levels of Chernobyl 137 Cs in western Sweden were found in the western parts of the area along the coast and the lowest in the east. The sum of the deposition densities from NWF and Chernobyl in western Sweden was then compared to the total activity measured in soil samples at 27 locations. Comparisons between the predicted values of this study show a good agreement with measured values and other studies

  2. Colluvial deposits as a possible weathering reservoir in uplifting mountains

    Directory of Open Access Journals (Sweden)

    S. Carretier

    2018-03-01

    Full Text Available The role of mountain uplift in the evolution of the global climate over geological times is controversial. At the heart of this debate is the capacity of rapid denudation to drive silicate weathering, which consumes CO2. Here we present the results of a 3-D model that couples erosion and weathering during mountain uplift, in which, for the first time, the weathered material is traced during its stochastic transport from the hillslopes to the mountain outlet. To explore the response of weathering fluxes to progressively cooler and drier climatic conditions, we run model simulations accounting for a decrease in temperature with or without modifications in the rainfall pattern based on a simple orographic model. At this stage, the model does not simulate the deep water circulation, the precipitation of secondary minerals, variations in the pH, below-ground pCO2, and the chemical affinity of the water in contact with minerals. Consequently, the predicted silicate weathering fluxes probably represent a maximum, although the predicted silicate weathering rates are within the range of silicate and total weathering rates estimated from field data. In all cases, the erosion rate increases during mountain uplift, which thins the regolith and produces a hump in the weathering rate evolution. This model thus predicts that the weathering outflux reaches a peak and then falls, consistent with predictions of previous 1-D models. By tracking the pathways of particles, the model can also consider how lateral river erosion drives mass wasting and the temporary storage of colluvial deposits on the valley sides. This reservoir is comprised of fresh material that has a residence time ranging from several years up to several thousand years. During this period, the weathering of colluvium appears to sustain the mountain weathering flux. The relative weathering contribution of colluvium depends on the area covered by regolith on the hillslopes. For mountains

  3. The waviness of the extratropical jet and daily weather extremes

    Science.gov (United States)

    Röthlisberger, Matthias; Martius, Olivia; Pfahl, Stephan

    2016-04-01

    In recent years the Northern Hemisphere mid-latitudes have experienced a large number of weather extremes with substantial socio-economic impact, such as the European and Russian heat waves in 2003 and 2010, severe winter floods in the United Kingdom in 2013/2014 and devastating winter storms such as Lothar (1999) and Xynthia (2010) in Central Europe. These have triggered an engaged debate within the scientific community on the role of human induced climate change in the occurrence of such extremes. A key element of this debate is the hypothesis that the waviness of the extratropical jet is linked to the occurrence of weather extremes, with a wavier jet stream favouring more extremes. Previous work on this topic is expanded in this study by analyzing the linkage between a regional measure of jet waviness and daily temperature, precipitation and wind gust extremes. We show that indeed such a linkage exists in many regions of the world, however this waviness-extremes linkage varies spatially in strength and sign. Locally, it is strong only where the relevant weather systems, in which the extremes occur, are affected by the jet waviness. Its sign depends on how the frequency of occurrence of the relevant weather systems is correlated with the occurrence of high and low jet waviness. These results go beyond previous studies by noting that also a decrease in waviness could be associated with an enhanced number of some weather extremes, especially wind gust and precipitation extremes over western Europe.

  4. Powernext weather, benchmark indices for effective weather risk management; Powernext Weather, des indices de reference pour gerer le risque meteo

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-07-01

    According to the U.S. Department of Energy, an estimated 25% of the GNP is affected by weather-related events. The variations in temperature - even small ones - can also have long-lasting effects on the operational results of a company. Among other, the Energy supply sector is sensitive to weather risks: a milder or harsher than usual winter leads to a decrease or increase of energy consumption. The price of electricity on power trading facilities like Powernext is especially sensitive to odd changes in temperatures. Powernext and Meteo-France (the French meteorological agency) have joined expertise in order to promote the use of weather indices in term of decision making or underlying of hedging tools to energy actors, end users from any other sector of activity and specialists of the weather risk hedging. The Powernext Weather indices are made from information collected by Meteo-France's main observation network according to the norms of international meteorology, in areas carefully selected. The gross data are submitted to a thorough review allowing the correction of abnormalities and the reconstitution of missing data. Each index is fashioned to take into account the economic activity in the various regions of the country as represented by each region's population. This demographic information represents a fair approximation of the weight of the regional economic activity. This document presents the Powernext/Meteo France partnership for the elaboration of efficient weather-related risk management indices. (J.S.)

  5. Seasonality in trauma admissions – Are daylight and weather variables better predictors than general cyclic effects?

    Science.gov (United States)

    Søvik, Signe; Eken, Torsten

    2018-01-01

    Background Trauma is a leading global cause of death, and predicting the burden of trauma admissions is vital for good planning of trauma care. Seasonality in trauma admissions has been found in several studies. Seasonal fluctuations in daylight hours, temperature and weather affect social and cultural practices but also individual neuroendocrine rhythms that may ultimately modify behaviour and potentially predispose to trauma. The aim of the present study was to explore to what extent the observed seasonality in daily trauma admissions could be explained by changes in daylight and weather variables throughout the year. Methods Retrospective registry study on trauma admissions in the 10-year period 2001–2010 at Oslo University Hospital, Ullevål, Norway, where the amount of daylight varies from less than 6 hours to almost 19 hours per day throughout the year. Daily number of admissions was analysed by fitting non-linear Poisson time series regression models, simultaneously adjusting for several layers of temporal patterns, including a non-linear long-term trend and both seasonal and weekly cyclic effects. Five daylight and weather variables were explored, including hours of daylight and amount of precipitation. Models were compared using Akaike’s Information Criterion (AIC). Results A regression model including daylight and weather variables significantly outperformed a traditional seasonality model in terms of AIC. A cyclic week effect was significant in all models. Conclusion Daylight and weather variables are better predictors of seasonality in daily trauma admissions than mere information on day-of-year. PMID:29425210

  6. Application and Study of Precipitation Schemes in Weather Simulation in Summer and Winter over China

    Institute of Scientific and Technical Information of China (English)

    XU Guoqiang; WAN Qilin; HUANG Liping; XUE Jishan; CHEN Dehui

    2006-01-01

    Through simulation of summer and winter precipitation cases in China, the cloud precipitation schemes of model were examined. Results indicate that it is discrepant between convective precipitation simulated by the Kain-Fritsch (KF) scheme and Betts-Miller (BM) scheme in summer, the former scheme is better than the latter in this case. The ambient atmosphere may be varied by different convective schemes. The air is wetter and the updraft is stronger in the KF scheme than in the BM scheme, which can induce the more grid scale precipitation in the KF scheme, i.e., the different cumulus schemes may have the different and important effect on the grid scale precipitation. However, there is almost no convective rain in winter in northern China, so the effect of cumulus precipitation on the grid scale precipitation can be disregarded.Therefore, the gird scale precipitation is primary in the winter of northern China.

  7. Where Does the Irrigation Water Go? An Estimate of the Contribution of Irrigation to Precipitation Using MERRA

    Science.gov (United States)

    Wei, Jiangfeng; Dirmeyer, Paul A.; Wisser, Dominik; Bosilovich, Michael G.; Mocko, David M.

    2013-01-01

    Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.

  8. Radar-derived quantitative precipitation estimation in complex terrain over the eastern Tibetan Plateau

    Science.gov (United States)

    Gou, Yabin; Ma, Yingzhao; Chen, Haonan; Wen, Yixin

    2018-05-01

    Quantitative precipitation estimation (QPE) is one of the important applications of weather radars. However, in complex terrain such as Tibetan Plateau, it is a challenging task to obtain an optimal Z-R relation due to the complex spatial and temporal variability in precipitation microphysics. This paper develops two radar QPE schemes respectively based on Reflectivity Threshold (RT) and Storm Cell Identification and Tracking (SCIT) algorithms using observations from 11 Doppler weather radars and 3264 rain gauges over the Eastern Tibetan Plateau (ETP). These two QPE methodologies are evaluated extensively using four precipitation events that are characterized by different meteorological features. Precipitation characteristics of independent storm cells associated with these four events, as well as the storm-scale differences, are investigated using short-term vertical profile of reflectivity (VPR) clusters. Evaluation results show that the SCIT-based rainfall approach performs better than the simple RT-based method for all precipitation events in terms of score comparison using validation gauge measurements as references. It is also found that the SCIT-based approach can effectively mitigate the local error of radar QPE and represent the precipitation spatiotemporal variability better than the RT-based scheme.

  9. Analysis of precipitation teleconnections in CMIP models as a measure of model fidelity in simulating precipitation

    Science.gov (United States)

    Langenbrunner, B.; Neelin, J.; Meyerson, J.

    2011-12-01

    The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

  10. Evaluation of a variable speed limit system for wet and extreme weather conditions : phase 1 report.

    Science.gov (United States)

    2012-06-01

    Weather presents considerable challenges to the highway system, both in terms of safety and operations. From a safety standpoint, weather (i.e. precipitation in the form of rain, snow or ice) reduces pavement friction, thus increasing the potential f...

  11. Atmospheric Diabatic Heating in Different Weather States and the General Circulation

    Science.gov (United States)

    Rossow, William B.; Zhang, Yuanchong; Tselioudis, George

    2016-01-01

    Analysis of multiple global satellite products identifies distinctive weather states of the atmosphere from the mesoscale pattern of cloud properties and quantifies the associated diabatic heating/cooling by radiative flux divergence, precipitation, and surface sensible heat flux. The results show that the forcing for the atmospheric general circulation is a very dynamic process, varying strongly at weather space-time scales, comprising relatively infrequent, strong heating events by ''stormy'' weather and more nearly continuous, weak cooling by ''fair'' weather. Such behavior undercuts the value of analyses of time-averaged energy exchanges in observations or numerical models. It is proposed that an analysis of the joint time-related variations of the global weather states and the general circulation on weather space-time scales might be used to establish useful ''feedback like'' relationships between cloud processes and the large-scale circulation.

  12. Implementation of an atmospheric sulfur scheme in the HIRLAM regional weather forecast model

    International Nuclear Information System (INIS)

    Ekman, Annica

    2000-02-01

    Sulfur chemistry has been implemented into the regional weather forecast model HIRLAM in order to simulate sulfur fields during specific weather situations. The model calculates concentrations of sulfur dioxide in air (SO 2 (a)), sulfate in air (SO 4 (a)), sulfate in cloud water (SO 4 (aq)) and hydrogen peroxide (H 2 O 2 ). Modeled concentrations of SO 2 (a), SO 4 (a) and SO 4 (aq) in rain water are compared with observations for two weather situations, one winter case with an extensive stratiform cloud cover and one summer case with mostly convective clouds. A comparison of the weather forecast parameters precipitation, relative humidity, geopotential and temperature with observations is also performed. The results show that the model generally overpredicts the SO 2 (a) concentration and underpredicts the SO 4 (a) concentration. The agreement between modeled and observed SO 4 (aq) in rain water is poor. Calculated turnover times are approximately 1 day for SO 2 (a) and 2-2.5 days for SO 4 (a). For SO 2 (a) this is in accordance with earlier simulated global turnover times, but for SO 4 (a) it is substantially lower. Several sensitivity simulations show that the fractional mean bias and root mean square error decreases, mainly for SO 4 (a) and SO 4 (aq), if an additional oxidant for converting SO 2 (a) to SO 4 (a) is included in the model. All weather forecast parameters, except precipitation, agree better with observations than the sulfur variables do. Wet scavenging is responsible for about half of the deposited sulfur and in addition, a major part of the sulfate production occurs through in-cloud oxidation. Hence, the distribution of clouds and precipitation must be better simulated by the weather forecast model in order to improve the agreement between observed and simulated sulfur concentrations

  13. The role of reaction affinity and secondary minerals in regulating chemical weathering rates at the Santa Cruz Soil Chronosequence, California

    Science.gov (United States)

    Maher, K.; Steefel, Carl; White, A.F.; Stonestrom, David A.

    2009-01-01

    In order to explore the reasons for the apparent discrepancy between laboratory and field weathering rates and to determine the extent to which weathering rates are controlled by the approach to thermodynamic equilibrium, secondary mineral precipitation, and flow rates, a multicomponent reactive transport model (CrunchFlow) was used to interpret soil profile development and mineral precipitation and dissolution rates at the 226 ka Marine Terrace Chronosequence near Santa Cruz, CA. Aqueous compositions, fluid chemistry, transport, and mineral abundances are well characterized [White A. F., Schulz M. S., Vivit D. V., Blum A., Stonestrom D. A. and Anderson S. P. (2008) Chemical weathering of a Marine Terrace Chronosequence, Santa Cruz, California. I: interpreting the long-term controls on chemical weathering based on spatial and temporal element and mineral distributions. Geochim. Cosmochim. Acta 72 (1), 36-68] and were used to constrain the reaction rates for the weathering and precipitating minerals in the reactive transport modeling. When primary mineral weathering rates are calculated with either of two experimentally determined rate constants, the nonlinear, parallel rate law formulation of Hellmann and Tisserand [Hellmann R. and Tisserand D. (2006) Dissolution kinetics as a function of the Gibbs free energy of reaction: An experimental study based on albite feldspar. Geochim. Cosmochim. Acta 70 (2), 364-383] or the aluminum inhibition model proposed by Oelkers et al. [Oelkers E. H., Schott J. and Devidal J. L. (1994) The effect of aluminum, pH, and chemical affinity on the rates of aluminosilicate dissolution reactions. Geochim. Cosmochim. Acta 58 (9), 2011-2024], modeling results are consistent with field-scale observations when independently constrained clay precipitation rates are accounted for. Experimental and field rates, therefore, can be reconciled at the Santa Cruz site. Additionally, observed maximum clay abundances in the argillic horizons occur at

  14. From AWE-GEN to AWE-GEN-2d: a high spatial and temporal resolution weather generator

    Science.gov (United States)

    Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

    2016-04-01

    A new weather generator, AWE-GEN-2d (Advanced WEather GENerator for 2-Dimension grid) is developed following the philosophy of combining physical and stochastic approaches to simulate meteorological variables at high spatial and temporal resolution (e.g. 2 km x 2 km and 5 min for precipitation and cloud cover and 100 m x 100 m and 1 h for other variables variable (temperature, solar radiation, vapor pressure, atmospheric pressure and near-surface wind). The model is suitable to investigate the impacts of climate variability, temporal and spatial resolutions of forcing on hydrological, ecological, agricultural and geomorphological impacts studies. Using appropriate parameterization the model can be used in the context of climate change. Here we present the model technical structure of AWE-GEN-2d, which is a substantial evolution of four preceding models (i) the hourly-point scale Advanced WEather GENerator (AWE-GEN) presented by Fatichi et al. (2011, Adv. Water Resour.) (ii) the Space-Time Realizations of Areal Precipitation (STREAP) model introduced by Paschalis et al. (2013, Water Resour. Res.), (iii) the High-Resolution Synoptically conditioned Weather Generator developed by Peleg and Morin (2014, Water Resour. Res.), and (iv) the Wind-field Interpolation by Non Divergent Schemes presented by Burlando et al. (2007, Boundary-Layer Meteorol.). The AWE-GEN-2d is relatively parsimonious in terms of computational demand and allows generating many stochastic realizations of current and projected climates in an efficient way. An example of model application and testing is presented with reference to a case study in the Wallis region, a complex orography terrain in the Swiss Alps.

  15. A study of regional trends in annual and seasonal precipitation and runoff series

    Energy Technology Data Exchange (ETDEWEB)

    Tveito, O.E.; Hisdal, H.

    1994-03-10

    In this study long and homogeneous time series of runoff and precipitation are studied to identify variations in time and space. The method of empirical orthogonal functions (EOF-method) is applied. Both annual observations, smoothed (using Gauss filter) and seasonal values are analyzed. The analysis shows that the temporal variations in runoff and precipitation coincide. The deviations occurring in the seasonal values are caused by snow accumulation and snow melt. In the filtered series temporal trends are found. A comparison between the different normal periods has been carried out for precipitation. The 1900-30 and 1960-90 periods differ from the 1930-60 period. This may be caused by different weather types dominating the different periods. The different weather types are reflected in different empirical orthogonal functions. This is verified by regional studies. The coinciding patterns in runoff and precipitation are important aspects in climate studies and for extrapolation purposes. 11 refs., 20 figs., 1 tab.

  16. Investigation of the weathering effect on Rb-Sr systematics and trace element abundances in Antarctic and non-Antarctic meteorites

    International Nuclear Information System (INIS)

    Nishikawa, Yoshiyuki; Nakamura, Noboru; Misawa, Keiji; Okano, Osamu; Yamamoto, Koshi; Kagami, Hiroo.

    1990-01-01

    In order to examine weathering effects on chondritic meteorites in Antarctic and non-Antarctic environments, the Rb-Sr isotopic ratios and abundances of REE, Ba, Sr, Rb, and K were determined for 8H-group chondrites (Yamato-790986 [H3], Yamato-74492 [H3], Grady [H3], Brownfield [H3], Clovis (No.1) [H3], Yamato-74155 [H4], Allegan [H5] [one whole-rock and two chondrules], and Yamato-74371 [H5]), and partly for the Etter (L5) chondrite. The Allegan whole-rock shows a flat REE pattern with a large negative Eu anomaly and Sr depletion. Analyses of Rb-Sr systematics of one whole-rock and two chondrules show somewhat younger age 4.38±0.12 b.y. It is suggested that REE and Rb-Sr were redistributed during the early thermal metamorphism. Except for Allegan, most other H-chondrites (finds) show the perturbation of the Rb-Sr systematics, indicating recent loss of Rb. It was found that the weathering degree is related with the Rb-Sr disturbance in Antarctic H-chondrite. In spite of different degrees of weathering, all the Antarctic H-chondrites studied (including heavily weathered ones) show flat REE patterns normal as H-chondrite with occasional occurrence of minor Eu anomalies, indicating the tough resistance of REE in H-chondrites to the Antarctic weathering. On the other hand, non-Antarctic finds (particularly the weathered chondrites) indicate light-REE enriched patterns with a large negative Ce anomaly and extreme enrichment of Ba, suggestive of terrestrial contaminations. (author)

  17. Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

    2017-01-01

    Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...... gauges in the model area. The spatiotemporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatiotemporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying on precipitation output...

  18. Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa

    Science.gov (United States)

    Grace, Kathryn; Davenport, Frank; Hanson, Heidi; Funk, Christopher C.; Shukla, Shraddhanand

    2015-01-01

    This paper examined the relationship between birth weight, precipitation, and temperature in 19 African countries. We matched recorded birth weights from Demographic and Health Surveys covering 1986 through 2010 with gridded monthly precipitation and temperature data derived from satellite and ground-based weather stations. Observed weather patterns during various stages of pregnancy were also used to examine the effect of temperature and precipitation on birth weight outcomes. In our empirical model we allowed the effect of weather factors to vary by the dominant food production strategy (livelihood zone) in a given region as well as by household wealth, mother's education and birth season. This allowed us to determine if certain populations are more or less vulnerable to unexpected weather changes after adjusting for known covariates. Finally we measured effect size by observing differences in birth weight outcomes in women who have one low birth weight experience and at least one healthy birth weight baby. The results indicated that climate does indeed impact birth weight and at a level comparable, in some cases, to the impact of increasing women's education or household electricity status.

  19. Alligator Rivers Analogue project. Weathering and its effects on uranium redistribution

    International Nuclear Information System (INIS)

    Isobe, H.; Ohnuki, T.; Yanase, N.; Sato, T.; Kimura, H.; Sekine, K.; Nagano, T.; Klessa, D.A.; Conoley, C.; Nakashima, S.; Ewing, R.C.

    1992-01-01

    In the vicinity of the uranium ore deposit at Koongarra, quartz-chlorite schist, the ore host rock, has been subjected to weathering. Although quartz is resistant to weathering, chlorite has been altered to clays and iron minerals. The chlorite weathering and the uranium association with the weathered minerals are the main topics of this study. In order to clarify the weathering of chlorite and its effects on the redistribution of uranium, the processes, mechanisms, and kinetics of the chlorite weathering, and the uranium concentrations in minerals were examined by various methods: X-ray diffraction analysis, scanning electron microscopy, electron microprobe analysis, transmission electron microscopy, autoradiography, visible spectroscopy, alpha and gamma spectrometry. The observed results were compared to those calculated, based on two different models developed for the present study. Water-rock interactions have resulted in the weathering of chlorite and precipitation and sorption of uranyl from the groundwaters with the weathering products. It is concluded that the chlorite weathering affects the uranium retardation factor, and thus uranium redistribution at Koongarra. 55 refs., 20 tabs., 120 figs

  20. 21st Century Changes in Precipitation Extremes Over the United States: Can Climate Analogues Help or Hinder?

    Science.gov (United States)

    Gao, X.; Schlosser, C. A.

    2013-12-01

    Global warming is expected to alter the frequency and/or magnitude of extreme precipitation events. Such changes could have substantial ecological, economic, and sociological consequences. However, climate models in general do not correctly reproduce the frequency and intensity distribution of precipitation, especially at the regional scale. In this study, gridded data from a dense network of surface precipitation gauges and a global atmospheric analysis at a coarser scale are combined to develop a diagnostic framework for the large-scale meteorological conditions (i.e. flow features, moisture supply) that dominate during extreme precipitation. Such diagnostic framework is first evaluated with the late 20th century simulations from an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and is found to produce more consistent (and less uncertain) total and interannaul number of extreme days with the observations than the model-based precipitation over the south-central United States and the Western United States examined in this study. The framework is then applied to the CMIP5 multi-model projections for two radiative forcing scenarios (Representative Concentration Pathways 4.5 and 8.5) to assess the potential future changes in the probability of precipitation extremes over the same study regions. We further analyze the accompanying circulation features and their changes that may be responsible for shifts in extreme precipitation in response to changed climate. The results from this study may guide hazardous weather watches and help society develop adaptive strategies for preventing catastrophic losses.

  1. Simulation of competitive Cu precipitation in steel during non-isothermal aging

    International Nuclear Information System (INIS)

    Yang, J.B.; Yamashita, T.; Sano, N.; Enomoto, M.

    2008-01-01

    A numerical model has been developed to simulate Cu precipitation in dilute bcc Fe-Cu alloys during non-isothermal aging taking into account competitive nucleation at grain boundaries, dislocations and in the matrix, and structural transformation of Cu particles that occurs during growth. The temporal evolution of number density, mean particle size and size distribution during continuous cooling is simulated and is compared with experimental observations under transmission electron microscope and three-dimensional atom probe field ion microscope. With decreasing temperature the growth and coarsening rates diminishes rapidly whereas nucleation continues to occur down to lower temperatures due to the decrease in the activation energy of nucleation and thus, distributions of fine particles can be obtained relatively easily after cooling. Precipitation and dissolution during continuous heating are simulated and are compared with experimental observations in the literature

  2. Third-order non-Coulomb correction to the S-wave quarkonium wave functions at the origin

    International Nuclear Information System (INIS)

    Beneke, M.; Kiyo, Y.; Schuller, K.

    2008-01-01

    We compute the third-order correction to the S-wave quarkonium wave functions |ψ n (0)| 2 at the origin from non-Coulomb potentials in the effective non-relativistic Lagrangian. Together with previous results on the Coulomb correction and the ultrasoft correction computed in a companion paper, this completes the third-order calculation up to a few unknown matching coefficients. Numerical estimates of the new correction for bottomonium and toponium are given

  3. Exploring the future change space for fire weather in southeast Australia

    Science.gov (United States)

    Clarke, Hamish; Evans, Jason P.

    2018-05-01

    High-resolution projections of climate change impacts on fire weather conditions in southeast Australia out to 2080 are presented. Fire weather is represented by the McArthur Forest Fire Danger Index (FFDI), calculated from an objectively designed regional climate model ensemble. Changes in annual cumulative FFDI vary widely, from - 337 (- 21%) to + 657 (+ 24%) in coastal areas and - 237 (- 12%) to + 1143 (+ 26%) in inland areas. A similar spread is projected in extreme FFDI values. In coastal regions, the number of prescribed burning days is projected to change from - 11 to + 10 in autumn and - 10 to + 3 in spring. Across the ensemble, the most significant increases in fire weather and decreases in prescribed burn windows are projected to take place in spring. Partial bias correction of FFDI leads to similar projections but with a greater spread, particularly in extreme values. The partially bias-corrected FFDI performs similarly to uncorrected FFDI compared to the observed annual cumulative FFDI (ensemble root mean square error spans 540 to 1583 for uncorrected output and 695 to 1398 for corrected) but is generally worse for FFDI values above 50. This emphasizes the need to consider inter-variable relationships when bias-correcting for complex phenomena such as fire weather. There is considerable uncertainty in the future trajectory of fire weather in southeast Australia, including the potential for less prescribed burning days and substantially greater fire danger in spring. Selecting climate models on the basis of multiple criteria can lead to more informative projections and allow an explicit exploration of uncertainty.

  4. An efficient shutter-less non-uniformity correction method for infrared focal plane arrays

    Science.gov (United States)

    Huang, Xiyan; Sui, Xiubao; Zhao, Yao

    2017-02-01

    The non-uniformity response in infrared focal plane array (IRFPA) detectors has a bad effect on images with fixed pattern noise. At present, it is common to use shutter to prevent from radiation of target and to update the parameters of non-uniformity correction in the infrared imaging system. The use of shutter causes "freezing" image. And inevitably, there exists the problems of the instability and reliability of system, power consumption, and concealment of infrared detection. In this paper, we present an efficient shutter-less non-uniformity correction (NUC) method for infrared focal plane arrays. The infrared imaging system can use the data gaining in thermostat to calculate the incident infrared radiation by shell real-timely. And the primary output of detector except the shell radiation can be corrected by the gain coefficient. This method has been tested in real infrared imaging system, reaching high correction level, reducing fixed pattern noise, adapting wide temperature range.

  5. A granulometry and secondary mineral fingerprint of chemical weathering in periglacial landscapes and its application to blockfield origins

    Science.gov (United States)

    Goodfellow, Bradley W.

    2012-12-01

    A review of published literature was undertaken to determine if there was a fingerprint of chemical weathering in regoliths subjected to periglacial conditions during their formation. If present, this fingerprint would be applied to the question of when blockfields in periglacial landscapes were initiated. These blocky diamicts are usually considered to represent remnants of regoliths that were chemically weathered under a warm, Neogene climate and therefore indicate surfaces that have undergone only a few metres to a few 10s of metres of erosion during the Quaternary. Based on a comparison of clay and silt abundances and secondary mineral assemblages from blockfields, other regoliths in periglacial settings, and regoliths from non-periglacial settings, a fingerprint of chemical weathering in periglacial landscapes was identified. A mobile regolith origin under, at least seasonal, periglacial conditions is indicated where clay(%) ≤ 0.5*silt(%) + 8 across a sample batch. This contrasts with a mobile regolith origin under non-periglacial conditions, which is indicated where clay(%) ≥ 0.5*silt(%) - 6 across a sample batch with clay(%) ≥ 0.5*silt(%) + 8 in at least one sample. A range of secondary minerals, which frequently includes interstratified minerals and indicates high local variability in leaching conditions, is also commonly present in regoliths exposed to periglacial conditions during their formation. Clay/silt ratios display a threshold response to temperature, related to the freezing point of water, but there is little response to precipitation or regolith residence time. Lithology controls clay and silt abundances, which increase from felsic, through intermediate, to mafic compositions, but does not control clay/silt ratios. Use of a sedigraph or Coulter Counter to determine regolith granulometry systematically indicates lower clay abundances and intra-site variability than use of a pipette or hydrometer. In contrast to clay/silt ratios, secondary

  6. Weather patterns and hydro-climatological precursors of extreme floods in Switzerland since 1868

    International Nuclear Information System (INIS)

    Stucki, Peter; Rickli, Ralph; Broennimann, Stefan; Martius, Olivia; Wanner, Heinz; Bern Univ.; Grebner, Dietmar; Luterbacher, Juerg

    2012-01-01

    The generation of 24 extreme floods in large catchments of the central Alps is analyzed from instrumental and documentary data, newly digitized observations of precipitation (DigiHom) and 20 th Century Reanalysis (20CR) data. Extreme floods are determined by the 95 th percentile of differences between an annual flood and a defined contemporary flood. For a selection of six events between 1868 and 1910, we describe preconditioning elements such as precipitation, temperature, and snow cover anomalies. Specific weather patterns are assessed through a subjective analysis of three-dimensional atmospheric circulation. A focus is placed on synoptic-scale features including mid-tropospheric ascent, low-level moisture transport, propagation of cyclones, and temperature anomalies. We propose a hydro-meteorological classification of all 24 investigated events according to flood-generating weather conditions. Key elements of the upper-level synoptic-scale flow are summarized by five types: (i) pivoting cut-off lows, (ii) elongated cut-off lows, (iii) elongated troughs, (iv) waves (with a kink), and (v) approximately zonal flow over the Alpine region. We found that the most extreme floods (as above, but ≥ 98 th percentile) in Switzerland since 1868 were caused by the interaction of severe hydro-climatologic conditions with a flood-inducing weather situation. The 20CR data provide plausible synoptic-scale meteorological patterns leading to heavy precipitation. The proposed catalogue of weather patterns and hydro-climatologic precursors can give direction when anticipating the possibility of severe floods in the Alpine region. (orig.)

  7. Linkages between Icelandic Low position and SE Greenland winter precipitation

    Science.gov (United States)

    Berdahl, M.; Rennermalm, A. K.; Hammann, A. C.; Mioduszewski, J.; Hameed, S.; Tedesco, M.; Stroeve, J. C.; Mote, T. L.

    2015-12-01

    Greenland's largest flux of precipitation occurs in its Southeast (SE) region. An understanding of the mechanisms controlling precipitation in this region is lacking despite its disproportionate importance in the mass balance of Greenland and the consequent contributions to sea level rise. We use weather station data from the Danish Meteorological Institute to reveal the governing influences on precipitation in SE Greenland during the winter and fall. We find that precipitation in the fall is significantly correlated to the longitude of the Icelandic Low and the NAO. Winter precipitation is correlated with the strength and longitude of the Icelandic Low, as well as the NAO. We show that in years of extreme high precipitation, onshore winds dominate, thereby advecting more moisture inland. In low precipitation years, winds are more westerly, approaching the stations from land. Understanding the controls of SE Greenland precipitation will help us predict how future precipitation in this key region may change in a warming climate.

  8. Changes in precipitation extremes projected by a 20-km mesh global atmospheric model

    Directory of Open Access Journals (Sweden)

    Akio Kitoh

    2016-03-01

    Full Text Available High-resolution modeling is necessary to project weather and climate extremes and their future changes under global warming. A global high-resolution atmospheric general circulation model with grid size about 20 km is able to reproduce climate fields as well as regional-scale phenomena such as monsoonal rainfall, tropical and extratropical cyclones, and heavy precipitation. This 20-km mesh model is applied to project future changes in weather and climate extremes at the end of the 21st century with four different spatial patterns in sea surface temperature (SST changes: one with the mean SST changes by the 28 models of the Coupled Model Intercomparison Project Phase 5 (CMIP5 under the Representative Concentration Pathways (RCP-8.5 scenario, and the other three obtained from a cluster analysis, in which tropical SST anomalies derived from the 28 CMIP5 models were grouped. Here we focus on future changes in regional precipitation and its extremes. Various precipitation indices averaged over the Twenty-two regional land domains are calculated. Heavy precipitation indices (maximum 5-day precipitation total and maximum 1-day precipitation total increase in all regional domains, even where mean precipitation decrease (Southern Africa, South Europe/Mediterranean, Central America. South Asia is the domain of the largest extreme precipitation increase. In some domains, different SST patterns result in large precipitation changes, possibly related to changes in large-scale circulations in the tropical Pacific.

  9. Modeling the influence of organic acids on soil weathering

    Science.gov (United States)

    Lawrence, Corey R.; Harden, Jennifer W.; Maher, Kate

    2014-01-01

    Biological inputs and organic matter cycling have long been regarded as important factors in the physical and chemical development of soils. In particular, the extent to which low molecular weight organic acids, such as oxalate, influence geochemical reactions has been widely studied. Although the effects of organic acids are diverse, there is strong evidence that organic acids accelerate the dissolution of some minerals. However, the influence of organic acids at the field-scale and over the timescales of soil development has not been evaluated in detail. In this study, a reactive-transport model of soil chemical weathering and pedogenic development was used to quantify the extent to which organic acid cycling controls mineral dissolution rates and long-term patterns of chemical weathering. Specifically, oxalic acid was added to simulations of soil development to investigate a well-studied chronosequence of soils near Santa Cruz, CA. The model formulation includes organic acid input, transport, decomposition, organic-metal aqueous complexation and mineral surface complexation in various combinations. Results suggest that although organic acid reactions accelerate mineral dissolution rates near the soil surface, the net response is an overall decrease in chemical weathering. Model results demonstrate the importance of organic acid input concentrations, fluid flow, decomposition and secondary mineral precipitation rates on the evolution of mineral weathering fronts. In particular, model soil profile evolution is sensitive to kaolinite precipitation and oxalate decomposition rates. The soil profile-scale modeling presented here provides insights into the influence of organic carbon cycling on soil weathering and pedogenesis and supports the need for further field-scale measurements of the flux and speciation of reactive organic compounds.

  10. Evaluation for Moroccan dynamically downscaled precipitation from GCM CHAM5 and its regional hydrologic response

    Directory of Open Access Journals (Sweden)

    Tsou Jaw

    2015-03-01

    Full Text Available Study region: Morocco (excluding Western Sahara. Study focus: This study evaluated Moroccan precipitation, dynamically downscaled (0.18-degree from three runs of the studied GCM ECHAM5/MPI-OM, under the present-day (1971–2000/20C3M and future (2036–2065/A1B climate scenarios. The spatial and quantitative properties of the downscaled precipitation were evaluated by a verified, fine-resolution reference. The effectiveness of the hydrologic responses, driven by the downscaled precipitation, was further evaluated for the study region over the upstream watershed of Oum er Rbia River located in Central Morocco. New hydrological insights for the region: The raw downscaling runs reasonably featured the spatial properties but quantitatively misrepresented the mean and extreme intensities of present-day precipitation. Two proposed bias correction approaches, namely stationary Quantile-Mapping (QM and non-stationary Equidistant CDF Matching model (EDCDFm, successfully reduced the system biases existing in the raw downscaling runs. However, both raw and corrected runs projected great diversity in terms of the quantity of future precipitation. Hydrologic simulations performed by a well-calibrated Variable Infiltration Capacity model successfully reproduced the present-day streamflow. The driven flows were identified highly correlated with the effectiveness of the downscaled precipitation. The future flows were projected to be markedly diverse, mainly due to the varied precipitation projections. Two of the three flow simulation runs projected slight to severe drying scenarios, while another projected an opposite trend for the evaluated future period. Keywords: Dynamical downscaling, Moroccan precipitation, Regional hydrology

  11. CLUJ-NAPOCA PRECIPITATION FORECAST USING WSR-98D DOPPLER RADAR

    Directory of Open Access Journals (Sweden)

    Narcis MAIER

    2011-11-01

    Full Text Available CLUJ-NAPOCA precipitation forecast using WSR-98D Doppler radar. Forecasting inundations requires accurate spatial and temporal estimation of rainfalls in an area. Depending on the Z-R relationship (reflectivity-precipitation rate, the thresholds, maximum reflectivity data processing, VIL, cloud height or speed, provided by the WSR-98D affects the estimated precipitation used in the prediction of inundations. How much precipitation receives a watershed during an extreme event and what response will result depends on the basin hydrographic characteristics. A study of summer weather events between the years 2004-2008 and a new method in establishing relations between the radar estimated and recorded precipitations led to the determination of new relations between them which will balance the connections between them.

  12. Mountain range specific analog weather forecast model for ...

    Indian Academy of Sciences (India)

    used to draw weather forecast for that mountain range in operational weather forecasting mode, three days ... various road management activities and for better .... −0.8. 1.5. 0.0. Pir Panjal range (HP). 1989–90 to 2002–03. 14. Snow day. 2.2. −4.1 ..... ed days,. S. = snow day,. N. S. = no-snow day and. P. C. = per cent correct).

  13. Development of a global fire weather database for 1980–2012

    OpenAIRE

    R. D. Field; A. C. Spessa; N. A. Aziz; A. Camia; A. Cantin; R. Carr; W. J. de Groot; A. J. Dowdy; M. D. Flannigan; K. Manomaiphiboon; F. Pappenberger; V. Tanpipat; X. Wang

    2014-01-01

    The Canadian Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily, gridded FWI System calculations from 1980–2012. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research, and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code (DC) calculations from the gridded datasets were compared to calculations ...

  14. Correction of TRMM 3B42V7 Based on Linear Regression Models over China

    Directory of Open Access Journals (Sweden)

    Shaohua Liu

    2016-01-01

    Full Text Available High temporal-spatial precipitation is necessary for hydrological simulation and water resource management, and remotely sensed precipitation products (RSPPs play a key role in supporting high temporal-spatial precipitation, especially in sparse gauge regions. TRMM 3B42V7 data (TRMM precipitation is an essential RSPP outperforming other RSPPs. Yet the utilization of TRMM precipitation is still limited by the inaccuracy and low spatial resolution at regional scale. In this paper, linear regression models (LRMs have been constructed to correct and downscale the TRMM precipitation based on the gauge precipitation at 2257 stations over China from 1998 to 2013. Then, the corrected TRMM precipitation was validated by gauge precipitation at 839 out of 2257 stations in 2014 at station and grid scales. The results show that both monthly and annual LRMs have obviously improved the accuracy of corrected TRMM precipitation with acceptable error, and monthly LRM performs slightly better than annual LRM in Mideastern China. Although the performance of corrected TRMM precipitation from the LRMs has been increased in Northwest China and Tibetan plateau, the error of corrected TRMM precipitation is still significant due to the large deviation between TRMM precipitation and low-density gauge precipitation.

  15. Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

    Directory of Open Access Journals (Sweden)

    J. Eeckman

    2017-09-01

    Full Text Available This paper provides a new representation of the effect of altitude on precipitation that represents spatial and temporal variability in precipitation in the Everest region. Exclusive observation data are used to infer a piecewise linear function for the relation between altitude and precipitation and significant seasonal variations are highlighted. An original ensemble approach is applied to provide non-deterministic water budgets for middle and high-mountain catchments. Physical processes at the soil–atmosphere interface are represented through the Interactions Soil–Biosphere–Atmosphere (ISBA surface scheme. Uncertainties associated with the model parametrization are limited by the integration of in situ measurements of soils and vegetation properties. Uncertainties associated with the representation of the orographic effect are shown to account for up to 16 % of annual total precipitation. Annual evapotranspiration is shown to represent 26 % ± 1 % of annual total precipitation for the mid-altitude catchment and 34% ± 3 % for the high-altitude catchment. Snowfall contribution is shown to be neglectable for the mid-altitude catchment, and it represents up to 44 % ± 8 % of total precipitation for the high-altitude catchment. These simulations on the local scale enhance current knowledge of the spatial variability in hydroclimatic processes in high- and mid-altitude mountain environments.

  16. More and more weather records - Is global warming to blame?

    Energy Technology Data Exchange (ETDEWEB)

    Wergen, Gregor; Krug, Joachim [Institut fuer Theoretische Physik, Koeln (Germany)

    2009-07-01

    If one believes in current media coverage it seems very simple: Due to the significant, largely anthropogenic, warming of the world's average temperature, more and more weather extremes occur. Every time we have a record breaking daily maximum temperature, or an immense amount of precipitation in a certain timespan, this is intuitively blamed on global warming. However mathematically the relation between an increasing mean value and the occurrence of records is far from trivial and not completely understood. This relation and its relevance to the analysis of weather data is the subject of this talk. Given an underlying distribution, we consider the probability that an event in a succession of events is a record, when the distribution itself is shifting, or altering its form. We found some approximations that are useful for the comparison with historical climate recordings. We obtained data for the daily maximum and daily minimum temperature and the daily precipitation amount from thousands of weather stations in Europe and the United States and analyzed them with regard to record events. The results are largely in accordance with what we predict from our calculations, but also reveal some interesting deviations.

  17. Non-stationary analysis of the frequency and intensity of heavy precipitation over Canada and their relations to large-scale climate patterns

    Science.gov (United States)

    Tan, Xuezhi; Gan, Thian Yew

    2017-05-01

    In recent years, because the frequency and severity of floods have increased across Canada, it is important to understand the characteristics of Canadian heavy precipitation. Long-term precipitation data of 463 gauging stations of Canada were analyzed using non-stationary generalized extreme value distribution (GEV), Poisson distribution and generalized Pareto (GP) distribution. Time-varying covariates that represent large-scale climate patterns such as El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific decadal oscillation (PDO) and North Pacific Oscillation (NP) were incorporated to parameters of GEV, Poisson and GP distributions. Results show that GEV distributions tend to under-estimate annual maximum daily precipitation (AMP) of western and eastern coastal regions of Canada, compared to GP distributions. Poisson regressions show that temporal clusters of heavy precipitation events in Canada are related to large-scale climate patterns. By modeling AMP time series with non-stationary GEV and heavy precipitation with non-stationary GP distributions, it is evident that AMP and heavy precipitation of Canada show strong non-stationarities (abrupt and slowly varying changes) likely because of the influence of large-scale climate patterns. AMP in southwestern coastal regions, southern Canadian Prairies and the Great Lakes tend to be higher in El Niño than in La Niña years, while AMP of other regions of Canada tends to be lower in El Niño than in La Niña years. The influence of ENSO on heavy precipitation was spatially consistent but stronger than on AMP. The effect of PDO, NAO and NP on extreme precipitation is also statistically significant at some stations across Canada.

  18. The contribution of weathering of the main Alpine rivers on the global carbon cycle

    Science.gov (United States)

    Donnini, Marco; Probst, Jean-Luc; Probst, Anne; Frondini, Francesco; Marchesini, Ivan; Guzzetti, Fausto

    2013-04-01

    classification of Meybeck (1986, 1987). Then for each basin we computed Rsil weighted average considering the surface and the mean precipitation for the surface area of each lithology. Lastly, we estimated the (Ca+Mg) originating from carbonate weathering as the remaining cations after silicate correction. Depending on time-scales of the phenomena (shorter than about 1 million year i.e., correlated to the short term carbon cycle, or longer than about 1 million years i.e., correlated to the long-term carbon cycle), we considered different equations for the quantification of the atmospheric CO2 consumed by weathering (Huh, 2010). The results show the net predominance of carbonate weathering on fixing atmospheric CO2 and that, considering the long-term carbon cycle, the amount of atmospheric CO2 uptake by weathering is about one order of magnitude lower than considering the short-term carbon cycle. Moreover, considering the short-term carbon cycle, the mean CO2 consumed by Alpine basins is of the same order of magnitude of the mean CO2 consumed by weathering by the 60 largest rivers of the world estimated by Gaillardet et al. (1999). References Amiotte-Suchet, P. "Cycle Du Carbone, Érosion Chimique Des Continents Et Transfert Vers Les Océans." Sci. Géol. Mém. Strasbourg 97 (1995): 156. Amiotte-Suchet, P., and J.-L. Probst. "Origins of dissolved inorganic carbon in the Garonne river waters: seasonal and interannual variations." Sci. Géologiques Bull. Strasbourg 49, no. 1-4 (1996): 101-126. Berner, E.K., and R.A. Berner. The Global Water Cycle. Geochemistry and Environment. Prentice Halle. Engelwood Cliffs, NJ, 1987. Drever, J.L. The Geochemistry of Natural Waters. Prentice Hall, 1982. Gaillardet, J., B. Dupré, P. Louvat, and C.J. Allègre. "Global Silicate Weathering and CO2 Consumption Rates Deduced from the Chemistry of Large Rivers." Chemical Geology 159 (1999): 3-30. Garrels, R.M., and F.T. Mackenzie. Evolution of Sedimentary Rocks. New York: W.W. Nortonand, 1971. Huh, Y

  19. Improved nowcasting of precipitation based on convective analysis fields

    Directory of Open Access Journals (Sweden)

    T. Haiden

    2007-04-01

    Full Text Available The high-resolution analysis and nowcasting system INCA (Integrated Nowcasting through Comprehensive Analysis developed at the Austrian national weather service provides three-dimensional fields of temperature, humidity, and wind on an hourly basis, and two-dimensional fields of precipitation rate in 15 min intervals. The system operates on a horizontal resolution of 1 km and a vertical resolution of 100–200 m. It combines surface station data, remote sensing data (radar, satellite, forecast fields of the numerical weather prediction model ALADIN, and high-resolution topographic data. An important application of the INCA system is nowcasting of convective precipitation. Based on fine-scale temperature, humidity, and wind analyses a number of convective analysis fields are routinely generated. These fields include convective boundary layer (CBL flow convergence and specific humidity, lifted condensation level (LCL, convective available potential energy (CAPE, convective inhibition (CIN, and various convective stability indices. Based on the verification of areal precipitation nowcasts it is shown that the pure translational forecast of convective cells can be improved by using a decision algorithm which is based on a subset of the above fields, combined with satellite products.

  20. Downscaling the Local Weather Above Glaciers in Complex Topography

    Science.gov (United States)

    Horak, Johannes; Hofer, Marlis; Gutmann, Ethan; Gohm, Alexander; Rotach, Mathias

    2017-04-01

    Glaciers have experienced a substantial ice-volume loss during the 20th century. To study their response to climate change, process-based glacier mass-balance models (PBGMs) are employed, which require a faithful representation of the state of the atmosphere above the glacier at high spatial and temporal resolution. Glaciers are usually located in complex topography where weather stations are scarce or not existent at all due to the remoteness of such sites and the associated high cost of maintenance. Furthermore. the effective resolution of global circulation models is too large to adequately capture the local topography and represent local weather, which is prerequisite for atmospheric input used by PBGMs. Dynamical downscaling is a physically consistent but computationally expensive approach to bridge the scale gap between GCM output and input needed by PBGMs, while statistical downscaling is faster but requires measurements for training. Both methods have their merits, however, a computationally frugal approach that does not rely on measurements is desirable, especially for long term studies of glacier response to future climate. In this study the intermediate complexity atmospheric research model (ICAR) is employed (Gutmann et al., 2016). It simplifies the wind field physics by relying on analytical solutions derived with linear theory. ICAR then advects atmospheric quantities within this wind field. This allows for computationally fast downscaling and yields a physically consistent set of atmospheric variables. First results obtained from downscaling air temperature, precipitation amount, relative humidity and wind speed to 4 × 4 km2 are presented. Preliminary ICAR is applied for a six month simulation period during five years and evaluated for three domains located in very distinct climates, namely the Southern Alps of New Zealand, the Cordillera Blanca in Peru and the European Alps using ERA Interim reanalysis data (ERAI) as forcing data set. The

  1. Using a weather generator to downscale spatio-temporal precipitation at urban scale

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, Ole Bøssing; Arnbjerg-Nielsen, Karsten

    In recent years, urban flooding has occurred in Denmark due to very local extreme precipitation events with very short lifetime. Several of these floods have been among the most severe ever experienced. The current study demonstrates the applicability of the Spatio-Temporal Neyman-Scott Rectangular...... the observed spatio-temporal differences at very fine scale for all measured parameters. For downscaling, perturbation with a climate change signal, precipitation from four different regional climate model simulations has been analysed. The analysed models are two runs from the ENSEMBLES (RACMO...

  2. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

    OpenAIRE

    Shi, Xingjian; Chen, Zhourong; Wang, Hao; Yeung, Dit-Yan; Wong, Wai-kin; Woo, Wang-chun

    2015-01-01

    The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined this crucial and challenging weather forecasting problem from the machine learning perspective. In this paper, we formulate precipitation nowcasting as a spatiotemporal sequence forecasting problem in which both the input and the prediction target are spatiotemporal sequences. By extending the fully connected LSTM (F...

  3. A Hybrid Framework to Bias Correct and Empirically Downscale Daily Temperature and Precipitation from Regional Climate Models

    Science.gov (United States)

    Tan, P.; Abraham, Z.; Winkler, J. A.; Perdinan, P.; Zhong, S. S.; Liszewska, M.

    2013-12-01

    Bias correction and statistical downscaling are widely used approaches for postprocessing climate simulations generated by global and/or regional climate models. The skills of these approaches are typically assessed in terms of their ability to reproduce historical climate conditions as well as the plausibility and consistency of the derived statistical indicators needed by end users. Current bias correction and downscaling approaches often do not adequately satisfy the two criteria of accurate prediction and unbiased estimation. To overcome this limitation, a hybrid regression framework was developed to both minimize prediction errors and preserve the distributional characteristics of climate observations. Specifically, the framework couples the loss functions of standard (linear or nonlinear) regression methods with a regularization term that penalizes for discrepancies between the predicted and observed distributions. The proposed framework can also be extended to generate physically-consistent outputs across multiple response variables, and to incorporate both reanalysis-driven and GCM-driven RCM outputs into a unified learning framework. The effectiveness of the framework is demonstrated using daily temperature and precipitation simulations from the North American Regional Climate Change Program (NARCCAP) . The accuracy of the framework is comparable to standard regression methods, but, unlike the standard regression methods, the proposed framework is able to preserve many of the distribution properties of the response variables, akin to bias correction approaches such as quantile mapping and bivariate geometric quantile mapping.

  4. [Evaluation, correction and impact of non-response in studies of childhood obesity].

    Science.gov (United States)

    Santiago-Pérez, María Isolina; Pérez-Ríos, Mónica; Malvar, Alberto; Suanzes, Jorge; Hervada, Xurxo

    2017-09-25

    To evaluate and correct the impact of non-response in the prevalence of underweight, overweight and obesity in children aged 6 to 15 years old using silhouette scales. Cross-sectional study carried out in 2013 among 8,145 Galician schoolchildren aged 6-15 years old. The students who agreed to participate were weighed and measured and, based on body mass index, the prevalence of underweight, overweight and obesity was estimated. Teachers rated all students using silhouette scales. The valuations were used to estimate the prevalence corrected by non-response. Using the Bayes theorem, participation rates were estimated according to weight status. The participation rate was 92.3% in the 6 -to 11-year-old group, and 90% in the 12- to 15-year old age group. In both groups, the prevalence of underweight and overweight were similar between participants and non-participants. However, obesity was higher among non-participants, especially at 12 to 15 years of age (6.3% vs. 12.2% ; p < 0.05). The prevalence did not change when corrected by the teacher's valuation. The participation rate of obese students was lower than the overall rate (82% vs. 90% at 12 to 15 years old; p < 0.05). The presence of participation bias, which was greater at 12-15 years old, was confirmed. However, the impact of the bias on prevalence was negligible due to the high participation rate. In obesity studies with objective measures, it is essential to quantify non-participation, as well as to assess its impact and correct it. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

  5. A 17-year Record of Meteorological Observations Across the Gran Campo Nevado Ice Cap in Southern Patagonia, Chile, Related to Synoptic Weather Types and Climate Modes

    Directory of Open Access Journals (Sweden)

    Stephanie S. Weidemann

    2018-05-01

    Full Text Available The network of long-term meteorological observations in Southernmost Patagonia is still sparse but crucial to improve our understanding of climatic variability, in particular in the more elevated and partially glaciated Southernmost Andes. Here we present a unique 17-year meteorological record (2000–2016 of four automatic weather stations (AWS across the Gran Campo Nevado Ice Cap (53°S in the Southernmost Andes (Chile and the conventional weather station Jorge Schythe of the Instituto de la Patagonia in Punta Arenas for comparison. We revisit the relationship between in situ observations and large-scale climate models as well as mesoscale weather patterns. For this purpose, a 37-year record of ERA Interim Reanalysis data has been used to compute a weather type classification based on a hierarchical correlation-based leader algorithm. The orographic perturbation on the predominantly westerly airflow determines the hydroclimatic response across the mountain range, leading to significant west-east gradients of precipitation, air temperature and humidity. Annual precipitation sums heavily drop within only tens of kilometers from ~7,500 mm a−1 to less than 800 mm a−1. The occurrence of high precipitation events of up to 620 mm in 5 days and wet spells of up to 61 consecutive days underscore the year-around wet conditions in the Southernmost Andes. Given the strong link between large-scale circulation and orographically controlled precipitation, the synoptic-scale weather conditions largely determine the precipitation and temperature variability on all time scales. Major synoptic weather types with distinct low-pressure cells in the Weddell Sea or Bellingshausen Sea, causing a prevailing southwesterly, northwesterly or westerly airflow, determine the weather conditions in Southernmost Patagonia during 68% of the year. At Gran Campo Nevado, more than 80% of extreme precipitation events occur during the persistence of these weather types. The

  6. Satellite navigation—Amazing technology but insidious risk: Why everyone needs to understand space weather

    Science.gov (United States)

    Hapgood, Mike

    2017-04-01

    Global navigation satellite systems (GNSS) are one of the technological wonders of the modern world. Popularly known as satellite navigation, these systems have provided global access to precision location and timing services and have thereby stimulated advances in industry and consumer services, including all forms of transport, telecommunications, financial trading, and even the synchronization of power grids. But this wonderful technology is at risk from natural phenomena in the form of space weather. GNSS signals experience a slight delay as they pass through the ionosphere. This delay varies with space weather conditions and is the most significant source of error for GNSS. Scientific efforts to correct these errors have stimulated billions of dollars of investment in systems that provide accurate correction data for suitably equipped GNSS receivers in a growing number of regions around the world. This accuracy is essential for GNSS use by aircraft and ships. Space weather also provides a further occasional but severe risk to GNSS: an extreme space weather event may deny access to GNSS as ionospheric scintillation scrambles the radio signals from satellites, and rapid ionospheric changes outstrip the ability of error correction systems to supply accurate corrections. It is vital that GNSS users have a backup for such occasions, even if it is only to hunker down and weather the storm.

  7. Losses due to weather phenomena in the bituminous concrete construction industry in Wisconsin

    Science.gov (United States)

    Kuhn, H. A. J.

    1973-01-01

    The losses (costs) due to weather phenomena as they affect the bituminous concrete industry in Wisconsin were studied. The bituminous concrete industry's response to precipitation, in the form of rain, is identified through the use of a model, albeit crude, which identifies a typical industry decision-response mechanism. Using this mechanism, historical weather data and 1969 construction activity, dollar losses resulting from rain occurrences were developed.

  8. Non-classical homogeneous precipitation mediated by compositional fluctuations in titanium alloys

    International Nuclear Information System (INIS)

    Nag, S.; Zheng, Y.; Williams, R.E.A.; Devaraj, A.; Boyne, A.; Wang, Y.; Collins, P.C.; Viswanathan, G.B.; Tiley, J.S.; Muddle, B.C.; Banerjee, R.

    2012-01-01

    This paper presents experimental evidence of homogeneous precipitation of the α-phase within the β matrix of a titanium alloy, and then accounts for this phase transformation by a new, non-classical mechanism involving compositional fluctuations, based on the pseudo-spinodal concept [1]. This mechanism involves local compositional fluctuations of small amplitude which, when of a certain magnitude, can favor thermodynamically certain regions of the β matrix to transform congruently to the α-phase but with compositions far from equilibrium. Subsequently, as measured experimentally using the tomographical atom probe, continuous diffusional partitioning between the parent β- and product α-phases during isothermal annealing drives their compositions towards equilibrium. For a given alloy composition, the decomposition mechanism is strongly temperature dependent, which would be expected for homogeneous precipitation via the compositional fluctuation-mediated mechanism but not necessarily for one based on classical nucleation theory. The applicability of this mechanism to phase transformations in general is noted.

  9. Acidic weathering of carbonate building stones: experimental assessment

    Directory of Open Access Journals (Sweden)

    Ryszard Kryza

    2009-06-01

    Full Text Available Three types of carbonate rocks, travertine, limestone and marble have been studied to determine their selected technical parameters (water absorption, resistance to salt crystallization damage and reaction to experimentally modelled acid rain weathering imitating the polluted urban atmospheric conditions. The acidic agents present in natural acid rain precipitation, H2SO4, HCl, HNO3, CH3COOH and mixture of all the acids, “Acid mix”, were tested. The initial stages of acid weathering involve, apart from chemical dissolution, particularly intense physical detachment of rock particles (granular disintegration significantly contributing to the total mass loss. Travertine was found to be most prone to salt crystallization damage and to acid weathering, and these features should be taken into account especially in external architectural usage of this stone in cold climate conditions and polluted urban atmosphere.

  10. Implementation of an atmospheric sulfur scheme in the HIRLAM regional weather forecast model

    Energy Technology Data Exchange (ETDEWEB)

    Ekman, Annica [Stockholm Univ. (Sweden). Dept. of Meteorology

    2000-02-01

    Sulfur chemistry has been implemented into the regional weather forecast model HIRLAM in order to simulate sulfur fields during specific weather situations. The model calculates concentrations of sulfur dioxide in air (SO{sub 2}(a)), sulfate in air (SO{sub 4}(a)), sulfate in cloud water (SO{sub 4}(aq)) and hydrogen peroxide (H{sub 2}O{sub 2}). Modeled concentrations of SO{sub 2}(a), SO{sub 4}(a) and SO{sub 4}(aq) in rain water are compared with observations for two weather situations, one winter case with an extensive stratiform cloud cover and one summer case with mostly convective clouds. A comparison of the weather forecast parameters precipitation, relative humidity, geopotential and temperature with observations is also performed. The results show that the model generally overpredicts the SO{sub 2}(a) concentration and underpredicts the SO{sub 4}(a) concentration. The agreement between modeled and observed SO{sub 4}(aq) in rain water is poor. Calculated turnover times are approximately 1 day for SO{sub 2}(a) and 2-2.5 days for SO{sub 4}(a). For SO{sub 2}(a) this is in accordance with earlier simulated global turnover times, but for SO{sub 4}(a) it is substantially lower. Several sensitivity simulations show that the fractional mean bias and root mean square error decreases, mainly for SO{sub 4}(a) and SO{sub 4}(aq), if an additional oxidant for converting SO{sub 2}(a) to SO{sub 4}(a) is included in the model. All weather forecast parameters, except precipitation, agree better with observations than the sulfur variables do. Wet scavenging is responsible for about half of the deposited sulfur and in addition, a major part of the sulfate production occurs through in-cloud oxidation. Hence, the distribution of clouds and precipitation must be better simulated by the weather forecast model in order to improve the agreement between observed and simulated sulfur concentrations.

  11. Method and System for Dynamic Automated Corrections to Weather Avoidance Routes for Aircraft in En Route Airspace

    Science.gov (United States)

    McNally, B. David (Inventor); Erzberger, Heinz (Inventor); Sheth, Kapil (Inventor)

    2015-01-01

    A dynamic weather route system automatically analyzes routes for in-flight aircraft flying in convective weather regions and attempts to find more time and fuel efficient reroutes around current and predicted weather cells. The dynamic weather route system continuously analyzes all flights and provides reroute advisories that are dynamically updated in real time while the aircraft are in flight. The dynamic weather route system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes.

  12. Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

    Science.gov (United States)

    Sommer, Philipp; Kaplan, Jed

    2016-04-01

    Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

  13. Adaptation of Mesoscale Weather Models to Local Forecasting

    Science.gov (United States)

    Manobianco, John T.; Taylor, Gregory E.; Case, Jonathan L.; Dianic, Allan V.; Wheeler, Mark W.; Zack, John W.; Nutter, Paul A.

    2003-01-01

    Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes

  14. LOCAL WEATHER CLASSIFICATIONS FOR ENVIRONMENTAL APPLICATIONS

    Directory of Open Access Journals (Sweden)

    Katarzyna PIOTROWICZ

    2013-03-01

    Full Text Available Two approaches of local weather type definitions are presented and illustrated for selected stations of Poland and Hungary. The subjective classification, continuing long traditions, especially in Poland, relies on diurnal values of local weather elements. The main types are defined according to temperature with some sub-types considering relative sunshine duration, diurnal precipitation totals, relative humidity and wind speed. The classification does not make a difference between the seasons of the year, but the occurrence of the classes obviously reflects the annual cycle. Another important feature of this classification is that only a minor part of the theoretically possible combination of the various types and sub-types occurs in all stations of both countries. The objective version of the classification starts from ten possible weather element which are reduced to four according to factor analysis, based on strong correlation between the elements. This analysis yields 3 to 4 factors depending on the specific criteria of selection. The further cluster analysis uses four selected weather elements belonging to different rotated factors. They are the diurnal mean values of temperature, of relative humidity, of cloudiness and of wind speed. From the possible ways of hierarchical cluster analysis (i.e. no a priori assumption on the number of classes, the method of furthest neighbours is selected, indicating the arguments of this decision in the paper. These local weather types are important tools in understanding the role of weather in various environmental indicators, in climatic generalisation of short samples by stratified sampling and in interpretation of the climate change.

  15. Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

    Science.gov (United States)

    Cannon, Alex J.

    2018-01-01

    Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin

  16. Weather forecasting for Eastern Amazon with OLAM model

    Directory of Open Access Journals (Sweden)

    Renato Ramos da Silva

    2014-12-01

    Full Text Available The OLAM model has as its characteristics the advantage to represent simultaneously the global and regional meteorological phenomena using the application of a grid refinement scheme. During the REMAM project the model was applied for a few case studies to evaluate its performance on numerical weather prediction for the eastern Amazon region. Case studies were performed for the twelve months of the year of 2009. The model results for those numerical experiments were compared with the observed data for the region of study. Precipitation data analysis showed that OLAM is able to represent the average mean accumulated precipitation and the seasonal features of the events occurrence, but can't predict the local total amount of precipitation. However, individual evaluation for a few cases had shown that OLAM was able to represent the dynamics and forecast a few days in advance the development of coastal meteorological systems such as the squall lines that are one of the most important precipitating systems of the Amazon.

  17. Universality in radiative corrections for non-supersymmetric heterotic vacua

    CERN Document Server

    Angelantonj, C; Tsulaia, Mirian

    2016-01-01

    Properties of moduli-dependent gauge threshold corrections in non-supersymmetric heterotic vacua are reviewed. In the absence of space-time supersymmetry these amplitudes are no longer protected and receive contributions from the whole tower of string states, BPS and not. Never-theless, the difference of gauge thresholds for non-Abelian gauge groups displays a remarkable universality property, even when supersymmetry is absent. We present a simple heterotic construction that shares this universal behaviour and expose the necessary conditions on the super-symmetry breaking mechanism for universality to occur.

  18. The influence of the circulation on surface temperature and precipitation patterns over Europe

    Directory of Open Access Journals (Sweden)

    P. D. Jones

    2009-06-01

    Full Text Available The atmospheric circulation clearly has an important influence on variations in surface temperature and precipitation. In this study we illustrate the spatial patterns of variation that occur for the principal circulation patterns across Europe in the standard four seasons. We use an existing classification scheme of surface pressure patterns, with the aim of considering whether the patterns of influence of specific weather types have changed over the course of the 20th century. We consider whether the long-term warming across Europe is associated with more favourable weather types or related to warming within some of the weather types. The results indicate that the latter is occurring, but not all circulation types show warming. The study also illustrates that certain circulation types can lead to marked differences in temperature and/or precipitation for relatively closely positioned sites when the sites are located in areas of high relief or near coasts.

  19. Mechanisms for chemostatic behavior in catchments: implications for CO2 consumption by mineral weathering

    Science.gov (United States)

    Clow, David W.; Mast, M. Alisa

    2010-01-01

    Concentrations of weathering products in streams often show relatively little variation compared to changes in discharge, both at event and annual scales. In this study, several hypothesized mechanisms for this “chemostatic behavior” were evaluated, and the potential for those mechanisms to influence relations between climate, weathering fluxes, and CO2 consumption via mineral weathering was assessed. Data from Loch Vale, an alpine catchment in the Colorado Rocky Mountains, indicates that cation exchange and seasonal precipitation and dissolution of amorphous or poorly crystalline aluminosilicates are important processes that help regulate solute concentrations in the stream; however, those processes have no direct effect on CO2 consumption in catchments. Hydrograph separation analyses indicate that old water stored in the subsurface over the winter accounts for about one-quarter of annual streamflow, and almost one-half of annual fluxes of Na and SiO2 in the stream; thus, flushing of old water by new water (snowmelt) is an important component of chemostatic behavior. Hydrologic flushing of subsurface materials further induces chemostatic behavior by reducing mineral saturation indices and increasing reactive mineral surface area, which stimulate mineral weathering rates. CO2 consumption by carbonic acid mediated mineral weathering was quantified using mass-balance calculations; results indicated that silicate mineral weathering was responsible for approximately two-thirds of annual CO2 consumption, and carbonate weathering was responsible for the remaining one-third. CO2 consumption was strongly dependent on annual precipitation and temperature; these relations were captured in a simple statistical model that accounted for 71% of the annual variation in CO2 consumption via mineral weathering in Loch Vale.

  20. Weather sensitivity for zoo visitation in Toronto, Canada: a quantitative analysis of historical data

    Science.gov (United States)

    Hewer, Micah J.; Gough, William A.

    2016-11-01

    Based on a case study of the Toronto Zoo (Canada), multivariate regression analysis, involving both climatic and social variables, was employed to assess the relationship between daily weather and visitation. Zoo visitation was most sensitive to weather variability during the shoulder season, followed by the off-season and, then, the peak season. Temperature was the most influential weather variable in relation to zoo visitation, followed by precipitation and, then, wind speed. The intensity and direction of the social and climatic variables varied between seasons. Temperatures exceeding 26 °C during the shoulder season and 28 °C during the peak season suggested a behavioural threshold associated with zoo visitation, with conditions becoming too warm for certain segments of the zoo visitor market, causing visitor numbers to decline. Even light amounts of precipitation caused average visitor numbers to decline by nearly 50 %. Increasing wind speeds also demonstrated a negative influence on zoo visitation.

  1. Weather and children's physical activity; how and why do relationships vary between countries?

    Science.gov (United States)

    Harrison, Flo; Goodman, Anna; van Sluijs, Esther M F; Andersen, Lars Bo; Cardon, Greet; Davey, Rachel; Janz, Kathleen F; Kriemler, Susi; Molloy, Lynn; Page, Angie S; Pate, Russ; Puder, Jardena J; Sardinha, Luis B; Timperio, Anna; Wedderkopp, Niels; Jones, Andy P

    2017-05-30

    Globally most children do not engage in enough physical activity. Day length and weather conditions have been identified as determinants of physical activity, although how they may be overcome as barriers is not clear. We aim to examine if and how relationships between children's physical activity and weather and day length vary between countries and identify settings in which children were better able to maintain activity levels given the weather conditions they experienced. In this repeated measures study, we used data from 23,451 participants in the International Children's Accelerometry Database (ICAD). Daily accelerometer-measured physical activity (counts per minute; cpm) was matched to local weather conditions and the relationships assessed using multilevel regression models. Multilevel models accounted for clustering of days within occasions within children within study-cities, and allowed us to explore if and how the relationships between weather variables and physical activity differ by setting. Increased precipitation and wind speed were associated with decreased cpm while better visibility and more hours of daylight were associated with increased cpm. Models indicated that increases in these variables resulted in average changes in mean cpm of 7.6/h of day length, -13.2/cm precipitation, 10.3/10 km visibility and -10.3/10kph wind speed (all p European countries and Melbourne, Australia were the most active, and also better maintained their activity levels given the weather conditions they experienced compared to those in the US and Western Europe. We found variation in the relationship between weather conditions and physical activity between ICAD studies and settings. Children in Northern Europe and Melbourne, Australia were not only more active on average, but also more active given the weather conditions they experienced. Future work should consider strategies to mitigate the impacts of weather conditions, especially among young children, and

  2. Non-perturbative treatment of relativistic quantum corrections in large Z atoms

    International Nuclear Information System (INIS)

    Dietz, K.; Weymans, G.

    1983-09-01

    Renormalised g-Hartree-Dirac equations incorporating Dirac sea contributions are derived. Their implications for the non-perturbative, selfconsistent calculation of quantum corrections in large Z atoms are discussed. (orig.)

  3. Validation of precipitation over Japan during 1985-2004 simulated by three regional climate models and two multi-model ensemble means

    Energy Technology Data Exchange (ETDEWEB)

    Ishizaki, Yasuhiro [Meteorological Research Institute, Tsukuba (Japan); National Institute for Environmental Studies, Tsukuba (Japan); Nakaegawa, Toshiyuki; Takayabu, Izuru [Meteorological Research Institute, Tsukuba (Japan)

    2012-07-15

    We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate. (orig.)

  4. Spatiotemporal Variations of Extreme Precipitation under a Changing Climate in the Three Gorges Reservoir Area (TGRA

    Directory of Open Access Journals (Sweden)

    Mingquan Lü

    2018-01-01

    Full Text Available The Three Gorges Dam (TGD is one of the largest hydroelectric projects in the world. Monitoring the spatiotemporal distribution of extreme precipitation offers valuable information for adaptation and mitigation strategies and reservoir management schemes. This study examined variations in extreme precipitation over the Three Gorges Reservoir area (TGRA in China to investigate the potential role of climate warming and Three Gorges Reservoir (TGR. The trends in extreme precipitation over the TGRA were investigated using the iterative-based Mann–Kendall (MK test and Sen’s slope estimator, based on weather station daily data series and TRMM (Tropical Rainfall Measuring Mission data series. The mean and density distribution of extreme precipitation indices between pre-dam and post-dam, pre-1985 and post-1985, and near and distant reservoir area were assessed by the Mann–Whitney test and the Kolmogorov–Smirnov test. The ratio of extreme precipitation to non-extreme precipitation became larger. The precipitation was characterized by increases in heavy precipitation as well as decreases in light and moderate rain. Comparing extreme precipitation indices between pre-1985 (cooling and post-1985 (warming indicated extreme precipitation has changed to become heavier. Under climate warming, the precipitation amount corresponding to more than the 95th percentile increased at the rate of 6.48%/°C. Results from comparing extreme precipitation for the pre- and post-dam, near reservoir area (NRA and away from the reservoir area (ARA imply an insignificant role of the TGR on rainfall extremes over the TGRA. Moreover, the impoundment of TGR did not exert detectable impacts on the surface relative humidity (RH and water vapor pressure (WP.

  5. Time-lagged effects of weather on plant demography: drought and Astragalus scaphoides.

    Science.gov (United States)

    Tenhumberg, Brigitte; Crone, Elizabeth E; Ramula, Satu; Tyre, Andrew J

    2018-04-01

    Temperature and precipitation determine the conditions where plant species can occur. Despite their significance, to date, surprisingly few demographic field studies have considered the effects of abiotic drivers. This is problematic because anticipating the effect of global climate change on plant population viability requires understanding how weather variables affect population dynamics. One possible reason for omitting the effect of weather variables in demographic studies is the difficulty in detecting tight associations between vital rates and environmental drivers. In this paper, we applied Functional Linear Models (FLMs) to long-term demographic data of the perennial wildflower, Astragalus scaphoides, and explored sensitivity of the results to reduced amounts of data. We compared models of the effect of average temperature, total precipitation, or an integrated measure of drought intensity (standardized precipitation evapotranspiration index, SPEI), on plant vital rates. We found that transitions to flowering and recruitment in year t were highest if winter/spring of year t was wet (positive effect of SPEI). Counterintuitively, if the preceding spring of year t - 1 was wet, flowering probabilities were decreased (negative effect of SPEI). Survival of vegetative plants from t - 1 to t was also negatively affected by wet weather in the spring of year t - 1 and, for large plants, even wet weather in the spring of t - 2 had a negative effect. We assessed the integrated effect of all vital rates on life history performance by fitting FLMs to the asymptotic growth rate, log(λt). Log(λt) was highest if dry conditions in year t - 1 were followed by wet conditions in the year t. Overall, the positive effects of wet years exceeded their negative effects, suggesting that increasing frequency of drought conditions would reduce population viability of A. scaphoides. The drought signal weakened when reducing the number of monitoring years. Substituting space for time

  6. Determination of non-uniformity correction factors for cylindrical ionization chambers close to 192Ir brachytherapy sources

    International Nuclear Information System (INIS)

    Toelli, H.; Bielajew, A. F.; Mattsson, O.; Sernbo, G.

    1995-01-01

    When ionization chambers are used in brachytherapy dosimetry, the measurements must be corrected for the non-uniformity of the incident photon fluence. The theory for determination of non-uniformity correction factors, developed by Kondo and Randolph (Rad. Res. 1960) assumes that the electron fluence within the air cavity is isotropic and does not take into account material differences in the chamber wall. The theory was extended by Bielajew (PMB 1990) using an anisotropic electron angular fluence in the cavity. In contrast to the theory by Kondo and Randolph, the anisotropic theory predicts a wall material dependence in the non-uniformity correction factors. This work presents experimental determination of non-uniformity correction factors at distances between 10 and 140 mm from an Ir-192 source. The experimental work makes use of a PTW23331-chamber and Farmer-type chambers (NE2571 and NE2581) with different materials in the walls. The results of the experiments agree well with the anisotropic theory. Due to the geometrical shape of the NE-type chambers, it is shown that the full length of the these chambers, 24.1mm, is not an appropriate input parameter when theoretical non-uniformity correction factors are evaluated

  7. Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

    DEFF Research Database (Denmark)

    Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

    gauges in the model area. The spatio-temporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatio-temporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying onprecipitation output......Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...

  8. WEATHER DERIVATIVES: THE MOST COMMON PRICING AND VALUATION METHODS

    Directory of Open Access Journals (Sweden)

    Botos Horia Mircea

    2013-07-01

    Full Text Available In recent years , weather derivatives have become a common tool in risk management for many sectors. This has its roots in that there is no unique way to determine de value and price solutions that would be generally approved by market-participants, like in the case of the Black-Scholes formula for options on non-dividend-paying stocks is the source for a constant debate between academics and practitioners. One look for fair and truly correct prices, while the others search every-day applicable solutions. To be honest... this is somehow like alchemy. This paper has as purpose the examination of statistical characteristics of weather data, data clearing and filling techniques. The study will be referring to temperatures because that is the best analyzed phenomenon, being the most common. This was also heavily influenced by energy companies and energetic interests, because the degree days were of interest ever before weather derivatives were put for sale. Main ideas are explaining what ways of pricing and valuation are, put into perspective for this financial instrument, taking into consideration that the Black-Scholes Model is not suitable. Also here, we will present the pros and cons that we found for each method. The methods are: the Burn analysis, the index value simulation method (IVSM, the daily simulation method (DSM.On the hole, this paper wants to shed light the weather derivatives pricing methods a mix of insurance pricing and standard financial models. At the end we will prospect the discounting problem, by means of the Consumption based Capital Asset Pricing Model (CCAPM.

  9. Multiresolution comparison of precipitation datasets for large-scale models

    Science.gov (United States)

    Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

    2014-12-01

    Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

  10. Experimental Simulation of Long Term Weathering in Alkaline Bauxite Residue Tailings

    Directory of Open Access Journals (Sweden)

    Talitha C. Santini

    2015-07-01

    Full Text Available Bauxite residue is an alkaline, saline tailings material generated as a byproduct of the Bayer process used for alumina refining. Developing effective plans for the long term management of potential environmental impacts associated with storage of these tailings is dependent on understanding how the chemical and mineralogical properties of the tailings will change during weathering and transformation into a soil-like material. Hydrothermal treatment of bauxite residue was used to compress geological weathering timescales and examine potential mineral transformations during weathering. Gibbsite was rapidly converted to boehmite; this transformation was examined with in situ synchrotron XRD. Goethite, hematite, and calcite all precipitated over longer weathering timeframes, while tricalcium aluminate dissolved. pH, total alkalinity, and salinity (electrical conductivity all decreased during weathering despite these experiments being performed under “closed” conditions (i.e., no leaching. This indicates the potential for auto-attenuation of the high alkalinity and salinity that presents challenges for long term environmental management, and suggests that management requirements will decrease during weathering as a result of these mineral transformations.

  11. High resolution reconstruction of monthly autumn and winter precipitation of Iberian Peninsula for last 150 years.

    Science.gov (United States)

    Cortesi, N.; Trigo, R.; González-Hidalgo, J. C.; Ramos, A.

    2012-04-01

    Precipitation over Iberian Peninsula (IP) presents large values of interannual variability and large spatial contrasts between wet mountainous regions in the north and dry regions in the southern plains. Unlike other European regions, IP was poorly monitored for precipitation during 19th century. Here we present a new approach to fill this gap. A set of 26 atmospheric circulation weather types (Trigo R.M. and DaCamara C.C., 2000) derived from a recent SLP dataset, the EMULATE (European and North Atlantic daily to multidecadal climate variability) Project, was used to reconstruct Iberian monthly precipitation from October to March during 1851-1947. Principal Component Regression Analysis was chosen to develop monthly precipitation reconstruction back to 1851 and calibrated over 1948-2003 period for 3030 monthly precipitation series of high-density homogenized MOPREDAS (Monthly Precipitation Database for Spain and Portugal) database. Validation was conducted over 1920-1947 at 15 key site locations. Results show high model performance for selected months, with a mean coefficient of variation (CV) around 0.6 during validation period. Lower CV values were achieved in western area of IP. Trigo, R. M., and DaCamara, C.C., 2000: "Circulation weather types and their impact on the precipitation regime in Portugal". Int. J. Climatol., 20, 1559-1581.

  12. Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

    KAUST Repository

    El-Samra, R.

    2017-02-15

    A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

  13. Improving Radar Quantitative Precipitation Estimation over Complex Terrain in the San Francisco Bay Area

    Science.gov (United States)

    Cifelli, R.; Chen, H.; Chandrasekar, V.

    2017-12-01

    A recent study by the State of California's Department of Water Resources has emphasized that the San Francisco Bay Area is at risk of catastrophic flooding. Therefore, accurate quantitative precipitation estimation (QPE) and forecast (QPF) are critical for protecting life and property in this region. Compared to rain gauge and meteorological satellite, ground based radar has shown great advantages for high-resolution precipitation observations in both space and time domain. In addition, the polarization diversity shows great potential to characterize precipitation microphysics through identification of different hydrometeor types and their size and shape information. Currently, all the radars comprising the U.S. National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) network are operating in dual-polarization mode. Enhancement of QPE is one of the main considerations of the dual-polarization upgrade. The San Francisco Bay Area is covered by two S-band WSR-88D radars, namely, KMUX and KDAX. However, in complex terrain like the Bay Area, it is still challenging to obtain an optimal rainfall algorithm for a given set of dual-polarization measurements. In addition, the accuracy of rain rate estimates is contingent on additional factors such as bright band contamination, vertical profile of reflectivity (VPR) correction, and partial beam blockages. This presentation aims to improve radar QPE for the Bay area using advanced dual-polarization rainfall methodologies. The benefit brought by the dual-polarization upgrade of operational radar network is assessed. In addition, a pilot study of gap fill X-band radar performance is conducted in support of regional QPE system development. This paper also presents a detailed comparison between the dual-polarization radar-derived rainfall products with various operational products including the NSSL's Multi-Radar/Multi-Sensor (MRMS) system. Quantitative evaluation of various rainfall products is achieved

  14. Non-immunological precipitation by the neutral detergent triton X-100 in agar gel diffusion.

    OpenAIRE

    Mansheim, B J; Stenstrom, M L

    1980-01-01

    Triton X-100 can be used to clarify vague immunoprecipitin lines from bacterial antigens; however, non-immunological precipitation can lead to mistaken interpretation of immunodiffusion results. If Triton X-100 is added directly to the gel during preparation rather than to the antigen well, this detergent artifact can be eliminated.

  15. Introduction and application of non-stationary standardized precipitation index considering probability distribution function and return period

    Science.gov (United States)

    Park, Junehyeong; Sung, Jang Hyun; Lim, Yoon-Jin; Kang, Hyun-Suk

    2018-05-01

    The widely used meteorological drought index, the Standardized Precipitation Index (SPI), basically assumes stationarity, but recent changes in the climate have led to a need to review this hypothesis. In this study, a new non-stationary SPI that considers not only the modified probability distribution parameter but also the return period under the non-stationary process was proposed. The results were evaluated for two severe drought cases during the last 10 years in South Korea. As a result, SPIs considered that the non-stationary hypothesis underestimated the drought severity than the stationary SPI despite that these past two droughts were recognized as significantly severe droughts. It may be caused by that the variances of summer and autumn precipitation become larger over time then it can make the probability distribution wider than before. This implies that drought expressions by statistical index such as SPI can be distorted by stationary assumption and cautious approach is needed when deciding drought level considering climate changes.

  16. Weather and Climate Indicators for Coffee Rust Disease

    Science.gov (United States)

    Georgiou, S.; Imbach, P. A.; Avelino, J.; Anzueto, F.; del Carmen Calderón, G.

    2014-12-01

    Coffee rust is a disease that has significant impacts on the livelihoods of those who are dependent on the Central American coffee sector. Our investigation has focussed on the weather and climate indicators that favoured the high incidence of coffee rust disease in Central America in 2012 by assessing daily temperature and precipitation data available from 81 weather stations in the INSIVUMEH and ANACAFE networks located in Guatemala. The temperature data were interpolated to determine the corresponding daily data at 1250 farms located across Guatemala, between 400 and 1800 m elevation. Additionally, CHIRPS five day (pentad) data has been used to assess the anomalies between the 2012 and the climatological average precipitation data at farm locations. The weather conditions in 2012 displayed considerable variations from the climatological data. In general the minimum daily temperatures were higher than the corresponding climatology while the maximum temperatures were lower. As a result, the daily diurnal temperature range was generally lower than the corresponding climatological range, leading to an increased number of days where the temperatures fell within the optimal range for either influencing the susceptibility of the coffee plants to coffee rust development during the dry season, or for the development of lesions on the coffee leaves during the wet season. The coffee rust latency period was probably shortened as a result, and farms at high altitudes were impacted due to these increases in minimum temperature. Factors taken into consideration in developing indicators for coffee rust development include: the diurnal temperature range, altitude, the environmental lapse rate and the phenology. We will present the results of our study and discuss the potential for each of the derived weather and climatological indicators to be used within risk assessments and to eventually be considered for use within an early warning system for coffee rust disease.

  17. Effect of weatherization on radon levels in Maine dwellings

    International Nuclear Information System (INIS)

    Hess, C.T.; Hill, R.C.

    1984-01-01

    A study of radon concentration in the air of 30 Maine dwellings was performed before and after weatherization during November 1982-May 1983. The average radon (.75 pCi/1) was lower than a group of houses in a previous study in October 1980-May 1981 (3.1 pCi/1). The after-weatherization levels show an increase over the before-weatherization levels. Trailers were found to have lower radon concentrations than houses. The maximum value measured was 3.2 pCi/1 before and 6.2 pCi/1 after correction for season of exposure. 13 references, 5 figures, 3 tables

  18. Disclosure of weather risks of European Utilities : Assessment of the current situation of listed utilities domiciled in Germany, France, Austria, United Kingdom and Switzerland

    OpenAIRE

    Leibfried, Peter; Schuchter, Alexander

    2010-01-01

    With regards to the scientific fact about climate change, weather risk is of increased importance to companies in weather dependent industries. Increasing volatility in temperatures and precipitation as well as unseasonal weather result in increased financial risk to weather dependent companies. This white paper assesses the current situation disclosure of weather dependency and weather risks of European exchange listed companies with the aim to promote transparency in risk reporting to ...

  19. Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

    Science.gov (United States)

    Clark, M.P.; Hay, L.E.

    2004-01-01

    This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases

  20. Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

    Science.gov (United States)

    Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

    2013-12-01

    Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so

  1. Diurnal variation of summer precipitation over the Tibetan Plateau. A cloud-resolving simulation

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Jianyu; Zhang, Bing; Wang, Minghuan [China Meteorological Administration, Wuhan (China). Wuhan Inst. of Heavy Rain; Wang, Huijuan [Weather Modification Office of Hubei Province, Wuhan (China)

    2012-07-01

    In this study, the Weather Research and Forecasting model was used to simulate the diurnal variation in summer precipitation over the Tibetan Plateau (TP) at a cloudresolving scale. Compared with the TRMM, precipitation data shows that the model can well simulate the diurnal rainfall cycle with an overall late-afternoon maximum precipitation in the central TP and a nighttime maximum in the southern edge. The simulated diurnal variations in regional circulation and thermodynamics are in good correspondence with the precipitation diurnal cycles in the central and southern edge of TP, respectively. A possible mechanism responsible for the nocturnal precipitation maximum in the southern edge has been proposed, indicating the importance of the TP in regulating the regional circulation and precipitation. (orig.)

  2. Error Correction of Meteorological Data Obtained with Mini-AWSs Based on Machine Learning

    Directory of Open Access Journals (Sweden)

    Ji-Hun Ha

    2018-01-01

    Full Text Available Severe weather events occur more frequently due to climate change; therefore, accurate weather forecasts are necessary, in addition to the development of numerical weather prediction (NWP of the past several decades. A method to improve the accuracy of weather forecasts based on NWP is the collection of more meteorological data by reducing the observation interval. However, in many areas, it is economically and locally difficult to collect observation data by installing automatic weather stations (AWSs. We developed a Mini-AWS, much smaller than AWSs, to complement the shortcomings of AWSs. The installation and maintenance costs of Mini-AWSs are lower than those of AWSs; Mini-AWSs have fewer spatial constraints with respect to the installation than AWSs. However, it is necessary to correct the data collected with Mini-AWSs because they might be affected by the external environment depending on the installation area. In this paper, we propose a novel error correction of atmospheric pressure data observed with a Mini-AWS based on machine learning. Using the proposed method, we obtained corrected atmospheric pressure data, reaching the standard of the World Meteorological Organization (WMO; ±0.1 hPa, and confirmed the potential of corrected atmospheric pressure data as an auxiliary resource for AWSs.

  3. Precipitation Dynamical Downscaling Over the Great Plains

    Science.gov (United States)

    Hu, Xiao-Ming; Xue, Ming; McPherson, Renee A.; Martin, Elinor; Rosendahl, Derek H.; Qiao, Lei

    2018-02-01

    Detailed, regional climate projections, particularly for precipitation, are critical for many applications. Accurate precipitation downscaling in the United States Great Plains remains a great challenge for most Regional Climate Models, particularly for warm months. Most previous dynamic downscaling simulations significantly underestimate warm-season precipitation in the region. This study aims to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model. To this end, WRF simulations with different physics schemes and nudging strategies are first conducted for a representative warm season. Results show that different cumulus schemes lead to more pronounced difference in simulated precipitation than other tested physics schemes. Simply choosing different physics schemes is not enough to alleviate the dry bias over the southern Great Plains, which is related to an anticyclonic circulation anomaly over the central and western parts of continental U.S. in the simulations. Spectral nudging emerges as an effective solution for alleviating the precipitation bias. Spectral nudging ensures that large and synoptic-scale circulations are faithfully reproduced while still allowing WRF to develop small-scale dynamics, thus effectively suppressing the large-scale circulation anomaly in the downscaling. As a result, a better precipitation downscaling is achieved. With the carefully validated configurations, WRF downscaling is conducted for 1980-2015. The downscaling captures well the spatial distribution of monthly climatology precipitation and the monthly/yearly variability, showing improvement over at least two previously published precipitation downscaling studies. With the improved precipitation downscaling, a better hydrological simulation over the trans-state Oologah watershed is also achieved.

  4. Non-common path aberration correction in an adaptive optics scanning ophthalmoscope.

    Science.gov (United States)

    Sulai, Yusufu N; Dubra, Alfredo

    2014-09-01

    The correction of non-common path aberrations (NCPAs) between the imaging and wavefront sensing channel in a confocal scanning adaptive optics ophthalmoscope is demonstrated. NCPA correction is achieved by maximizing an image sharpness metric while the confocal detection aperture is temporarily removed, effectively minimizing the monochromatic aberrations in the illumination path of the imaging channel. Comparison of NCPA estimated using zonal and modal orthogonal wavefront corrector bases provided wavefronts that differ by ~λ/20 in root-mean-squared (~λ/30 standard deviation). Sequential insertion of a cylindrical lens in the illumination and light collection paths of the imaging channel was used to compare image resolution after changing the wavefront correction to maximize image sharpness and intensity metrics. Finally, the NCPA correction was incorporated into the closed-loop adaptive optics control by biasing the wavefront sensor signals without reducing its bandwidth.

  5. Land surface feedbacks on spring precipitation in the Netherlands

    NARCIS (Netherlands)

    Daniels, E.E.; Hutjes, R.W.A.; Lenderink, G.; Ronda, R.J.; Holtslag, A.A.M.

    2015-01-01

    In this paper the Weather Research and Forecasting (WRF) model is used to investigate the sensitivity of precipitation to soil moisture and urban areas in the Netherlands. We analyze the average output of a four day event from 10-13 May 1999 for which the individual days had similar synoptical

  6. Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections

    Science.gov (United States)

    Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.

    2015-11-01

    Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

  7. Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.

    Science.gov (United States)

    Junk, J; Ulber, B; Vidal, S; Eickermann, M

    2015-11-01

    Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

  8. The influence of the synoptic regime on stable water isotopes in precipitation at Dome C, East Antarctica

    Science.gov (United States)

    Schlosser, Elisabeth; Dittmann, Anna; Stenni, Barbara; Powers, Jordan G.; Manning, Kevin W.; Masson-Delmotte, Valérie; Valt, Mauro; Cagnati, Anselmo; Grigioni, Paolo; Scarchilli, Claudio

    2017-10-01

    The correct derivation of paleotemperatures from ice cores requires exact knowledge of all processes involved before and after the deposition of snow and the subsequent formation of ice. At the Antarctic deep ice core drilling site Dome C, a unique data set of daily precipitation amount, type, and stable water isotope ratios is available that enables us to study in detail atmospheric processes that influence the stable water isotope ratio of precipitation. Meteorological data from both automatic weather station and a mesoscale atmospheric model were used to investigate how different atmospheric flow patterns determine the precipitation parameters. A classification of synoptic situations that cause precipitation at Dome C was established and, together with back-trajectory calculations, was utilized to estimate moisture source areas. With the resulting source area conditions (wind speed, sea surface temperature, and relative humidity) as input, the precipitation stable isotopic composition was modeled using the so-called Mixed Cloud Isotope Model (MCIM). The model generally underestimates the depletion of 18O in precipitation, which was not improved by using condensation temperature rather than inversion temperature. Contrary to the assumption widely used in ice core studies, a more northern moisture source does not necessarily mean stronger isotopic fractionation. This is due to the fact that snowfall events at Dome C are often associated with warm air advection due to amplification of planetary waves, which considerably increases the site temperature and thus reduces the temperature difference between source area and deposition site. In addition, no correlation was found between relative humidity at the moisture source and the deuterium excess in precipitation. The significant difference in the isotopic signal of hoarfrost and diamond dust was shown to disappear after removal of seasonality. This study confirms the results of an earlier study carried out at Dome

  9. Anticipated Improvements in Precipitation Physics and Understanding of Water Cycle from GPM Mission

    Science.gov (United States)

    Smith, Eric A.

    2003-01-01

    The GPM mission is currently planned for start in the late-2007 to early-2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation s orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, involving existing, pending, projected, and under-study partnerships which will link NASA and NOAA in the US, NASDA in Japan, ESA in Europe, ISRO in India, CNES in France, and possibly AS1 in Italy, KARI in South Korea, CSA in Canada, and AEB in Brazil. Additionally, the program is actively pursuing agreements with other international collaborators and

  10. Uncertainty in the area-related QPF for heavy convective precipitation

    Czech Academy of Sciences Publication Activity Database

    Řezáčová, Daniela; Zacharov, Petr, jr.; Sokol, Zbyněk

    2009-01-01

    Roč. 93, 1-3 (2009), s. 238-246 ISSN 0169-8095. [European Conference on Severe Storms /4./. Miramare -Trieste, 10.09.2007-14.09.2007] R&D Projects: GA ČR GA205/07/0905; GA MŠk OC 112 Institutional research plan: CEZ:AV0Z30420517 Keywords : Convective storm * Quantitative precipitation forecast * Uncertainty in precipitation forecasting * Ensemble forecasting * Numerical weather prediction model Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.811, year: 2009 http://www.sciencedirect.com/science/journal/01698095

  11. Radar rainfall estimation for the identification of debris-flow precipitation thresholds

    Science.gov (United States)

    Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

    2014-05-01

    Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial

  12. Stord Orographic Precipitation Experiment (STOPEX: an overview of phase I

    Directory of Open Access Journals (Sweden)

    A. Sandvik

    2007-04-01

    Full Text Available STOPEX (Stord Orographic Precipitation Experiment is a research project of the Geophysical Institute, University of Bergen, Norway, dedicated to the investigation of orographic effects on fine scale precipitation patterns by a combination of numerical modelling and tailored measurement campaigns. Between 24 September and 16 November 2005 the first field campaign STOPEX I has been performed at and around the island of Stord at the west coast of Norway, about 50 km south of Bergen. 12 rain gauges and 3 autonomous weather stations have been installed to measure the variability of precipitation and the corresponding meteorological conditions. This paper gives an overview of the projects motivation, a description of the campaign and a presentation of the precipitation measurements performed. In addition, the extreme precipitation event around 14 November with precipitation amounts up to 240 mm in less than 24 h, is described and briefly discussed. In this context preliminary results of corresponding MM5 simulations are presented, that indicate the problems as well as potential improvement strategies with respect to modelling of fine scale orographic precipitation.

  13. Evaluation of Satellite and Model Precipitation Products Over Turkey

    Science.gov (United States)

    Yilmaz, M. T.; Amjad, M.

    2017-12-01

    Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

  14. Diagnosis of inconsistencies in multi-year gridded precipitation data over mountainous areas and related impacts on hydrologic simulations

    Science.gov (United States)

    Mizukami, N.; Smith, M. B.

    2010-12-01

    It is common for the error characteristics of long-term precipitation data to change over time due to various factors such as gauge relocation and changes in data processing methods. The temporal consistency of precipitation data error characteristics is as important as data accuracy itself for hydrologic model calibration and subsequent use of the calibrated model for streamflow prediction. In mountainous areas, the generation of precipitation grids relies on sparse gage networks, the makeup of which often varies over time. This causes a change in error characteristics of the long-term precipitation data record. We will discuss the diagnostic analysis of the consistency of gridded precipitation time series and illustrate the adverse effect of inconsistent precipitation data on a hydrologic model simulation. We used hourly 4 km gridded precipitation time series over a mountainous basin in the Sierra Nevada Mountains of California from October 1988 through September 2006. The basin is part of the broader study area that served as the focus of the second phase of the Distributed Model Intercomparison Project (DMIP-2), organized by the U.S. National Weather Service (NWS) of the National Oceanographic and Atmospheric Administration (NOAA). To check the consistency of the gridded precipitation time series, double mass analysis was performed using single pixel and basin mean areal precipitation (MAP) values derived from gridded DMIP-2 and Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data. The analysis leads to the conclusion that over the entire study time period, a clear change in error characteristics in the DMIP-2 data occurred in the beginning of 2003. This matches the timing of one of the major gage network changes. The inconsistency of two MAP time series computed from the gridded precipitation fields over two elevation zones was corrected by adjusting hourly values based on the double mass analysis. We show that model

  15. Precipitation kinetics in binary Fe–Cu and ternary Fe–Cu–Ni alloys via kMC method

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2017-08-01

    Full Text Available The precipitation kinetics of coherent Cu rich precipitates (CRPs in binary Fe–Cu and ternary Fe–Cu–Ni alloys during thermal aging was modelled by the kinetic Monte Carlo method (kMC. A good agreement of the precipitation kinetics of Fe–Cu was found between the simulation and experimental results, as observed by means of advancement factor and cluster number density. This agreement was obtained owing to the correct description of the fast cluster mobility. The simulation results indicate that the effects of Ni are two-fold: Ni promotes the nucleation of Cu clusters; while the precipitation kinetics appears to be delayed by Ni addition during the coarsening stage. The apparent delayed precipitation kinetics is revealed to be related with the cluster mobility, which are reduced by Ni addition. The reduction effect of the cluster mobility weakens when the CRPs sizes increase. The results provide a view angle on the effects of solute elements upon Cu precipitation kinetics through the consideration of the non-conventional cluster growth mechanism, and kMC is verified to be a powerful approach on that.

  16. Relationships between CO2, thermodynamic limits on silicate weathering, and the strength of the silicate weathering feedback

    Science.gov (United States)

    Winnick, Matthew J.; Maher, Kate

    2018-03-01

    Recent studies have suggested that thermodynamic limitations on chemical weathering rates exert a first-order control on riverine solute fluxes and by extension, global chemical weathering rates. As such, these limitations may play a prominent role in the regulation of carbon dioxide levels (pCO2) over geologic timescales by constraining the maximum global weathering flux. In this study, we develop a theoretical scaling relationship between equilibrium solute concentrations and pCO2 based on equilibrium constants and reaction stoichiometry relating primary mineral dissolution and secondary mineral precipitation. We test this theoretical scaling relationship against reactive transport simulations of chemical weathering profiles under open- and closed-system conditions, representing partially and fully water-saturated regolith, respectively. Under open-system conditions, equilibrium bicarbonate concentrations vary as a power-law function of pCO2 (y = kxn) where n is dependent on reaction stoichiometry and k is dependent on both reaction stoichiometry and the equilibrium constant. Under closed-system conditions, bicarbonate concentrations vary linearly with pCO2 at low values and approach open-system scaling at high pCO2. To describe the potential role of thermodynamic limitations in the global silicate weathering feedback, we develop a new mathematical framework to assess weathering feedback strength in terms of both (1) steady-state atmospheric pCO2 concentrations, and (2) susceptibility to secular changes in degassing rates and transient carbon cycle perturbations, which we term 1st and 2nd order feedback strength, respectively. Finally, we discuss the implications of these results for the effects of vascular land plant evolution on feedback strength, the potential role of vegetation in controlling modern solute fluxes, and the application of these frameworks to a more complete functional description of the silicate weathering feedback. Most notably, the dependence

  17. Weather and Prey Predict Mammals' Visitation to Water.

    Directory of Open Access Journals (Sweden)

    Grant Harris

    Full Text Available Throughout many arid lands of Africa, Australia and the United States, wildlife agencies provide water year-round for increasing game populations and enhancing biodiversity, despite concerns that water provisioning may favor species more dependent on water, increase predation, and reduce biodiversity. In part, understanding the effects of water provisioning requires identifying why and when animals visit water. Employing this information, by matching water provisioning with use by target species, could assist wildlife management objectives while mitigating unintended consequences of year-round watering regimes. Therefore, we examined if weather variables (maximum temperature, relative humidity [RH], vapor pressure deficit [VPD], long and short-term precipitation and predator-prey relationships (i.e., prey presence predicted water visitation by 9 mammals. We modeled visitation as recorded by trail cameras at Sevilleta National Wildlife Refuge, New Mexico, USA (June 2009 to September 2014 using generalized linear modeling. For 3 native ungulates, elk (Cervus Canadensis, mule deer (Odocoileus hemionus, and pronghorn (Antilocapra americana, less long-term precipitation and higher maximum temperatures increased visitation, including RH for mule deer. Less long-term precipitation and higher VPD increased oryx (Oryx gazella and desert cottontail rabbits (Sylvilagus audubonii visitation. Long-term precipitation, with RH or VPD, predicted visitation for black-tailed jackrabbits (Lepus californicus. Standardized model coefficients demonstrated that the amount of long-term precipitation influenced herbivore visitation most. Weather (especially maximum temperature and prey (cottontails and jackrabbits predicted bobcat (Lynx rufus visitation. Mule deer visitation had the largest influence on coyote (Canis latrans visitation. Puma (Puma concolor visitation was solely predicted by prey visitation (elk, mule deer, oryx. Most ungulate visitation peaked during

  18. Weather and Prey Predict Mammals’ Visitation to Water

    Science.gov (United States)

    Harris, Grant; Sanderson, James G.; Erz, Jon; Lehnen, Sarah E.; Butler, Matthew J.

    2015-01-01

    Throughout many arid lands of Africa, Australia and the United States, wildlife agencies provide water year-round for increasing game populations and enhancing biodiversity, despite concerns that water provisioning may favor species more dependent on water, increase predation, and reduce biodiversity. In part, understanding the effects of water provisioning requires identifying why and when animals visit water. Employing this information, by matching water provisioning with use by target species, could assist wildlife management objectives while mitigating unintended consequences of year-round watering regimes. Therefore, we examined if weather variables (maximum temperature, relative humidity [RH], vapor pressure deficit [VPD], long and short-term precipitation) and predator-prey relationships (i.e., prey presence) predicted water visitation by 9 mammals. We modeled visitation as recorded by trail cameras at Sevilleta National Wildlife Refuge, New Mexico, USA (June 2009 to September 2014) using generalized linear modeling. For 3 native ungulates, elk (Cervus Canadensis), mule deer (Odocoileus hemionus), and pronghorn (Antilocapra americana), less long-term precipitation and higher maximum temperatures increased visitation, including RH for mule deer. Less long-term precipitation and higher VPD increased oryx (Oryx gazella) and desert cottontail rabbits (Sylvilagus audubonii) visitation. Long-term precipitation, with RH or VPD, predicted visitation for black-tailed jackrabbits (Lepus californicus). Standardized model coefficients demonstrated that the amount of long-term precipitation influenced herbivore visitation most. Weather (especially maximum temperature) and prey (cottontails and jackrabbits) predicted bobcat (Lynx rufus) visitation. Mule deer visitation had the largest influence on coyote (Canis latrans) visitation. Puma (Puma concolor) visitation was solely predicted by prey visitation (elk, mule deer, oryx). Most ungulate visitation peaked during May and

  19. Scavenging of radon daughters by precipitation from the atmosphere

    Energy Technology Data Exchange (ETDEWEB)

    Fujinami, Naoto [Kyoto Prefectural Inst. of Hygienic and Environmental Sciences (Japan)

    1997-02-01

    By the continuous measurement of the radon daughters concentration in the rain and snow water and atmosphere and the data analysis, the following results were obtained. The radon daughters concentration was almost constant in the rain and snow water in spite of the length during weather without precipitation. It has not tendency to show the high concentration of radon daughters in precipitation and snow during beginning of them. When the precipitation intensity is constant, it`s concentration does not change during precipitation and snowfall. The concentration does not depend on the amount of precipitation, but on the precipitation intensity. We did not observe a correlation between the radon daughters concentration in the rain and snow water and that in the surface air. The atmospheric concentration was decreased by precipitation and snowfall, but that of rain and snow water did not decrease. The above results seems to show that the contribution of washout under the cloud to radon daughters in rain and snow water is small and that of rainout in the cloud is large. This result is agreement with the Jacob`s experimental results. (S.Y.)

  20. Formation of halloysite from feldspar: Low temperature, artificial weathering versus natural weathering

    Science.gov (United States)

    Parham, Walter E.

    1969-01-01

    Weathering products formed on surfaces of both potassium and plagioclase feldspar (An70), which were continuously leached in a Soxhlet extraction apparatus for 140 days with 7.21 of distilled water per day at a temperature of approximately 78°C, are morphologically identical to natural products developed on potassium feldspars weathered under conditions of good drainage in the humid tropics. The new products, which first appear as tiny bumps on the feldspar surface, start to develop mainly at exposed edges but also at apparently random sites on flat cleavage surfaces. As weathering continues, the bumps grow outward from the feldspar surface to form tapered projections, which then develop into wide-based thin films or sheets. The thin sheets of many projections merge laterally to form one continuous flame-shaped sheet. The sheets formed on potassium feldspars may then roll to form tubes that are inclined at a high angle to the feldspar surface. Etch pits of triangular outline on the artificially weathered potassium feldspars serve as sites for development of continuous, non-rolled, hollow tubes. It is inferred from its morphology that this weathering product is halloysite or its primitive form. The product of naturally weathered potassium feldspars is halloysite . 4H2O.The flame-shaped films or sheets formed on artificially weathered plagioclase feldspar do not develop into hollow tubes, but instead give rise to a platy mineral that is most probably boehmite. These plates form within the flame-shaped films, and with continued weathering are released as the film deteriorates. There is no indication from this experiment that platy pseudohexagonal kaolinite forms from any of these minerals under the initial stage of weathering.

  1. Photoluminescent properties of Y2O3:Eu3+ phosphors prepared via urea precipitation in non-aqueous solution

    International Nuclear Information System (INIS)

    Sun, Y.; Qi, L.; Lee, M.; Lee, B.I.; Samuels, W.D.; Exarhos, G.J.

    2004-01-01

    Europium-doped yttrium oxide phosphors were obtained by firing precursors prepared by urea precipitation in ethanol and ethylenediamine. The precipitation in non-aqueous solution was carried out in an autoclave at 150 deg. C to allow the decomposition of urea. The photoluminescent intensities of the phosphors prepared in ethanol and ethylenediamine increased by about 30% compared to that of the phosphor prepared by the conventional urea homogeneous precipitation in aqueous solution. Amorphous carbonates and amorphous hydroxides/carbonates mixtures were identified as precursors from ethanol and ethylenediamine, respectively. The morphology and particle size were studied by SEM and dynamic laser scattering method

  2. Clay mineralogical constraints on weathering in response to early Eocene hyperthermal events in the Bighorn Basin, Wyoming (Western Interior, USA)

    NARCIS (Netherlands)

    Wang, Chaowen; Adriaens, Rieko; Hong, Hanlie; Elsen, Jan; Vandenberghe, Noël; Lourens, Lucas J.|info:eu-repo/dai/nl/125023103; Gingerich, Philip D.; Abels, Hemmo A.|info:eu-repo/dai/nl/304848018

    2017-01-01

    Series of transient greenhouse warming intervals in the early Eocene provide an opportunity to study the response of rock weathering and erosion to changes in temperature and precipitation. During greenhouse warming, chemical weathering is thought to increase the uptake of carbon from the

  3. Production of starch nanoparticles by dissolution and non-solvent precipitation for use in food-grade Pickering emulsions.

    Science.gov (United States)

    Saari, Hisfazilah; Fuentes, Catalina; Sjöö, Malin; Rayner, Marilyn; Wahlgren, Marie

    2017-02-10

    The aim of this study was to investigate non-solvent precipitation of starch to produce nanoparticles that could be used in Pickering emulsions. The material used was waxy maize, modified with octenyl succinic anhydride. Different methods of non-solvent precipitation were investigated, and a method based on direct mixing of an 8% starch solution and ethanol (ratio 1:1) was found to produce the smallest particles. The particle size was measured using AFM and AF4, and was found to be in the range 100-200nm. However, both larger particles and aggregates of nanoparticles were observed. The emulsion produced using the precipitated starch particles had a droplet size that between 0.5 and 45μm, compared to emulsions produced from waxy maize granules, in which had a size of 10-100μm. The drop in size contributed to increased stability against creaming. The amount of starch used for emulsion stabilization could also be substantially reduced. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  4. Validation of non-stationary precipitation series for site-specific impact assessment: comparison of two statistical downscaling techniques

    Science.gov (United States)

    Mullan, Donal; Chen, Jie; Zhang, Xunchang John

    2016-02-01

    Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

  5. Interacting entropy-corrected new agegraphic dark energy in the non-flat universe

    Energy Technology Data Exchange (ETDEWEB)

    Karami, Kayoomars [Department of Physics, University of Kurdistan, Pasdaran Street, Sanandaj (Iran, Islamic Republic of); Sorouri, Arash, E-mail: KKarami@uok.ac.i [Research Institute for Astronomy and Astrophysics of Maragha (RIAAM), Maragha (Iran, Islamic Republic of)

    2010-08-15

    Here, we consider the entropy-corrected version of the new agegraphic dark energy (NADE) model in the non-flat Friedmann-Robertson-Walker universe. We derive the exact differential equation that determines the evolution of the entropy-corrected NADE density parameter in the presence of interaction with dark matter. We also obtain the equation of state and deceleration parameters and present a necessary condition for the selected model to cross the phantom divide. Moreover, we reconstruct the potential and the dynamics of the phantom scalar field according to the evolutionary behavior of the interacting entropy-corrected new agegraphic model.

  6. Effects of Weather on Tourism and its Moderation

    Science.gov (United States)

    Park, J. H.; Kim, S.; Lee, D. K.

    2016-12-01

    Tourism is weather sensitive industry (Gómez Martín, 2005). As climate change has been intensifying, the concerns about negative effects of weather on tourism also have been increasing. This study attempted to find ways that mitigate the negative effects from weather on tourism, by analyzing a path of the effects of weather on intention to revisit and its moderation. The data of the study were collected by a self-recording online questionnaire survey of South Korean domestic tourists during August 2015, and 2,412 samples were gathered. A path model of effects of weather on intention to revisit that including moderating effects from physical attraction satisfaction and service satisfaction was ran. Season was controlled in the path model. The model fit was adequate (CMIN/DF=2.372(p=.000), CFI=.974, RMSEA=.024, SRMR=0.040), and the Model Comparison, which assumes that the base model to be correct with season constrained model, showed that there was a seasonal differences in the model ( DF=24, CMIN=32.430, P=.117). By the analysis, it was figured out that weather and weather expectation affected weather satisfaction, and the weather satisfaction affected intention to revisit (spring/fall: .167**, summer: .104**, and winter: .114**). Meanwhile physical attraction satisfaction (.200**), and service satisfaction (.210**) of tourism positively moderated weather satisfaction in summer, and weather satisfaction positively moderated physical attraction (.238**) satisfaction and service satisfaction (.339**). In other words, in summer, dissatisfaction from hot weather was moderated by satisfaction from physical attractions and services, and in spring/fall, comfort weather conditions promoted tourists to accept tourism experience and be satisfied from attractions and services positively. Based on the result, it was expected that if industries focus on offering the good attractions and services based on weather conditions, there would be positive effects to alleviate tourists

  7. Low-level precipitation sublimation on the coasts of East Antarctica

    Science.gov (United States)

    Grazioli, Jacopo; Genthon, Christophe; Madeleine, Jean-Baptiste; Lemonnier, Florentin; Gallée, Hubert; Krinner, Gerhard; Berne, Alexis

    2017-04-01

    The weather of East Antarctica is affected by the peculiar morphology of this large continent and by its isolation from the surroundings. The high-elevation interior of the continent, very dry in absolute terms, originates winds that can reach the coastal areas with very high speed and persistence in time. The absence of topographic barriers and the near-ground temperature inversion allow these density-driven air movements to fall from the continent towards the coasts without excessive interaction and mixing with the atmosphere aloft. Thus, the air remains dry in absolute terms, and very dry in relative terms because of the higher temperatures near the coast and the adiabatic warming due to the descent. The coasts of Antarctica are less isolated and more exposed to incoming moist air masses than the rest of the continent, and precipitation in the form of snowfall more frequently occurs. Through its descent, however, snowfall encounters the layer of dry air coming from the continent and the deficit in humidity can lead to the partial or complete sublimation of the precipitating flux. This phenomenon is named here LPS (Low-level Precipitation Sublimation) and it has been observed by means of ground-based remote sensing instruments (weather radars) and atmospheric radio-sounding balloons records in the framework of the APRES3 campaign (Antarctic Precipitation: REmote Sensing from Surface and Space) in the coastal base of Dumont d' Urville (Terre Adélie), and then examined at the continental scale thanks to numerical weather models. LPS occurs over most of the coastal locations, where the total sublimated snowfall can be a significant percentage of the total snowfall. For example, in Dumont d' Urville the total yearly snowfall at 341 m height is less than 80% of the snowfall at 941 m height (the height of maximum yearly accumulation), and at shorter time scales complete sublimation (i.e. virga) often occurs. At the scale of individual precipitation events, LPS is

  8. A non-parametric method for correction of global radiation observations

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Perers, Bengt

    2013-01-01

    in the observations are corrected. These are errors such as: tilt in the leveling of the sensor, shadowing from surrounding objects, clipping and saturation in the signal processing, and errors from dirt and wear. The method is based on a statistical non-parametric clear-sky model which is applied to both...

  9. Values of Deploying a Compact Polarimetric Radar to Monitor Extreme Precipitation in a Mountainous Area: Mineral County, Colorado

    Science.gov (United States)

    Cheong, B. L.; Kirstetter, P. E.; Yu, T. Y.; Busto, J.; Speeze, T.; Dennis, J.

    2015-12-01

    Precipitation in mountainous regions can trigger flash floods and landslides especially in areas affected by wildfire. Because of the small space-time scales required for observation, they remain poorly observed. A light-weighted X-band polarimetric radar can rapidly respond to the situation and provide continuous rainfall information with high resolution for flood forecast and emergency management. A preliminary assessment of added values to the operational practice in Mineral county, Colorado was performed in Fall 2014 and Summer 2015 with a transportable polarimetric radar deployed at the Lobo Overlook. This region is one of the numerous areas in the Rocky Mountains where the WSR-88D network does not provide sufficient weather coverage due to blockages, and the limitations have impeded forecasters and local emergency managers from making accurate predictions and issuing weather warnings. High resolution observations were collected to document the precipitation characteristics and demonstrate the added values of deploying a small weather radar in such context. The analysis of the detailed vertical structure of precipitation explain the decreased signal sampled by the operational radars. The specific microphysics analyzed though polarimetry suggest that the operational Z-R relationships may not be appropriate to monitor severe weather over this wildfire affected region. Collaboration with the local emergency managers and the National Weather Service shows the critical value of deploying mobile, polarimetric and unmanned radars in complex terrain. Several selected cases are provided in this paper for illustration.

  10. Connecting Urbanization to Precipitation: the case of Mexico City

    Science.gov (United States)

    Georgescu, Matei

    2017-04-01

    Considerable evidence exists illustrating the influence of urban environments on precipitation. We revisit this theme of significant interest to a broad spectrum of disciplines ranging from urban planning to engineering to urban numerical modeling and climate, by detailing the simulated effect of Mexico City's built environment on regional precipitation. Utilizing the Weather Research and Forecasting (WRF) system to determine spatiotemporal changes in near-surface air temperature, precipitation, and boundary layer conditions induced by the modern-day urban landscape relative to presettlement conditions, I mechanistically link the built environment-induced increase in air temperature to simulated increases in rainfall during the evening hours. This simulated increase in precipitation is in agreement with historical observations documenting observed rainfall increase. These results have important implications for understanding the meteorological conditions leading to the widespread and recurrent urban flooding that continues to plague the Mexico City Metropolitan Area.

  11. Global Precipitation Measurement Mission: Architecture and Mission Concept

    Science.gov (United States)

    Bundas, David

    2005-01-01

    The Global Precipitation Measurement (GPM) Mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA), and other partners, with the goal of monitoring the diurnal and seasonal variations in precipitation over the surface of the earth. These measurements will be used to improve current climate models and weather forecasting, and enable improved storm and flood warnings. This paper gives an overview of the mission architecture and addresses some of the key trades that have been completed, including the selection of the Core Observatory s orbit, orbit maintenance trades, and design issues related to meeting orbital debris requirements.

  12. Global Precipitation Measurement (GPM) L-6

    Science.gov (United States)

    Neeck, Steven P.; Kakar, Ramesh K.; Azarbarzin, Ardeshir A.; Hou, Arthur Y.

    2013-10-01

    The Global Precipitation Measurement (GPM) mission will advance the measurement of global precipitation, making possible high spatial resolution precipitation measurements. GPM will provide the first opportunity to calibrate measurements of global precipitation across tropical, mid-latitude, and polar regions. The GPM mission has the following scientific objectives: (1) Advance precipitation measurement capability from space through combined use of active and passive remote-sensing techniques; (2) Advance understanding of global water/energy cycle variability and fresh water availability; (3) Improve climate prediction by providing the foundation for better understanding of surface water fluxes, soil moisture storage, cloud/precipitation microphysics and latent heat release in the Earth's atmosphere; (4) Advance Numerical Weather Prediction (NWP) skills through more accurate and frequent measurements of instantaneous rain rates; and (5) Improve high impact natural hazard (flood/drought, landslide, and hurricane hazard) prediction capabilities. The GPM mission centers on the deployment of a Core Observatory carrying an advanced radar / radiometer system to measure precipitation from space and serve as a reference standard to unify precipitation measurements from a constellation of research and operational satellites. GPM, jointly led with the Japan Aerospace Exploration Agency (JAXA), involves a partnership with other international space agencies including the French Centre National d'Études Spatiales (CNES), the Indian Space Research Organisation (ISRO), the U.S. National Oceanic and Atmospheric Administration (NOAA), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), and others. The GPM Core Observatory is currently being prepared for shipment to Japan for launch. Launch is scheduled for February 2014 from JAXA's Tanegashima Space Center on an H-IIA 202 launch vehicle.

  13. Detection of trends in precipitation extremes in Zhejiang, east China

    NARCIS (Netherlands)

    Tian, Ye; Xu, YuePing; Booij, Martijn J.; Lin, Shengji; Zhang, Qingqing; Lou, Zhanghua

    2012-01-01

    Extreme weather exerts a huge impact on human beings and it is of vital importance to study the regular pattern of meteorological and hydrological factors. In this paper, a selection of seven extreme indices is used to analyze the trend of precipitation extremes of 18 meteorological stations located

  14. Weather types in the South Shetlands (Antarctica) using a circulation type approach

    Science.gov (United States)

    Mora, Carla; João Rocha, Maria; Dutra, Emanuel; Trigo, Isabel; Vieira, Gonçalo; Fragoso, Marcelo; Ramos, Miguel

    2010-05-01

    Weather types in the South Shetlands (Antarctica) were defined using an automated method based on the Lamb Weather Type classification scheme (Jones et al. 1993). This is an objective classification originally developed for the British Isles (Jones et al., 1993) and also applied to southeast (Goodess and Palutikof 1998) and northwest Spain (Lorenzo et al, 2009), Portugal (Trigo and DaCamara 2000) and Greece (Maheras et al. 2004) with good results. Daily atmospheric circulation in the South Shetlands region from 1989 to 2009 was classified using a 16-node grid of sea level pressure data from the ERA Interim. The classification is obtained through the comparison of the magnitudes of the directional and rotational components of the geostrophic flow. Basic circulation types were combined into 10 groups of weather types: four directional types (NW, N, S and SW), three anticyclonic types (A, ASW and ANW), and three cyclonic types (C, CSW and CNW). Westerly flow and cyclonic circulation are the most frequent events throughout the year. The sea level pressure field for each weather type is presented and the synoptic characteristics are described. The analysis is based on ERA-Interim fields, including mean sea level pressure, precipitation, cloud cover, humidity and air temperature. Snow thickess modelled using HTESSEL is also considered. Analysis of variance (anova) and multivariate analysis (principal component analysis) are applied to evaluate the characteristics of each weather type. This circulation-type approach showed good results in the past for the downscaling of precipitation in other regions, and we are interested in evaluating the possibilities that the classification offers for downscaling precipitation, but also for snow and air temperature. For this we will be using observational data at test sites in Livingston and Deception islands. We are also motivated by the possibility of using the circulation-type approach as a predictor in statistical downscaling

  15. Hydrological Modeling in Northern Tunisia with Regional Climate Model Outputs: Performance Evaluation and Bias-Correction in Present Climate Conditions

    Directory of Open Access Journals (Sweden)

    Asma Foughali

    2015-07-01

    Full Text Available This work aims to evaluate the performance of a hydrological balance model in a watershed located in northern Tunisia (wadi Sejnane, 378 km2 in present climate conditions using input variables provided by four regional climate models. A modified version (MBBH of the lumped and single layer surface model BBH (Bucket with Bottom Hole model, in which pedo-transfer parameters estimated using watershed physiographic characteristics are introduced is adopted to simulate the water balance components. Only two parameters representing respectively the water retention capacity of the soil and the vegetation resistance to evapotranspiration are calibrated using rainfall-runoff data. The evaluation criterions for the MBBH model calibration are: relative bias, mean square error and the ratio of mean actual evapotranspiration to mean potential evapotranspiration. Daily air temperature, rainfall and runoff observations are available from 1960 to 1984. The period 1960–1971 is selected for calibration while the period 1972–1984 is chosen for validation. Air temperature and precipitation series are provided by four regional climate models (DMI, ARP, SMH and ICT from the European program ENSEMBLES, forced by two global climate models (GCM: ECHAM and ARPEGE. The regional climate model outputs (precipitation and air temperature are compared to the observations in terms of statistical distribution. The analysis was performed at the seasonal scale for precipitation. We found out that RCM precipitation must be corrected before being introduced as MBBH inputs. Thus, a non-parametric quantile-quantile bias correction method together with a dry day correction is employed. Finally, simulated runoff generated using corrected precipitation from the regional climate model SMH is found the most acceptable by comparison with runoff simulated using observed precipitation data, to reproduce the temporal variability of mean monthly runoff. The SMH model is the most accurate to

  16. Arctic daily temperature and precipitation extremes: Observed and simulated physical behavior

    Science.gov (United States)

    Glisan, Justin Michael

    Simulations using a six-member ensemble of Pan-Arctic WRF (PAW) were produced on two Arctic domains with 50-km resolution to analyze precipitation and temperature extremes for various periods. The first study used a domain developed for the Regional Arctic Climate Model (RACM). Initial simulations revealed deep atmospheric circulation biases over the northern Pacific Ocean, manifested in pressure, geopotential height, and temperature fields. Possible remedies to correct these large biases, such as modifying the physical domain or using different initial/boundary conditions, were unsuccessful. Spectral (interior) nudging was introduced as a way of constraining the model to be more consistent with observed behavior. However, such control over numerical model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events, since the nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes---what is the minimum spectral nudging needed to correct biases while not limiting the simulation of extreme events? To determine this, we use varying degrees of spectral nudging, using WRF's standard nudging as a reference point during January and July 2007. Results suggest that there is a marked lack of sensitivity to varying degrees of nudging. Moreover, given that nudging is an artificial forcing applied in the model, an important outcome of this work is that nudging strength apparently can be considerably smaller than WRF's standard strength and still produce reliable simulations. In the remaining studies, we used the same PAW setup to analyze daily precipitation extremes simulated over a 19-year period on the CORDEX Arctic domain for winter and summer. We defined these seasons as the three-month period leading up to and including the climatological sea ice maximum and minimum, respectively. Analysis focused on four North American regions defined using

  17. The influence of the synoptic regime on stable water isotopes in precipitation at Dome C, East Antarctica

    Directory of Open Access Journals (Sweden)

    E. Schlosser

    2017-10-01

    Full Text Available The correct derivation of paleotemperatures from ice cores requires exact knowledge of all processes involved before and after the deposition of snow and the subsequent formation of ice. At the Antarctic deep ice core drilling site Dome C, a unique data set of daily precipitation amount, type, and stable water isotope ratios is available that enables us to study in detail atmospheric processes that influence the stable water isotope ratio of precipitation. Meteorological data from both automatic weather station and a mesoscale atmospheric model were used to investigate how different atmospheric flow patterns determine the precipitation parameters. A classification of synoptic situations that cause precipitation at Dome C was established and, together with back-trajectory calculations, was utilized to estimate moisture source areas. With the resulting source area conditions (wind speed, sea surface temperature, and relative humidity as input, the precipitation stable isotopic composition was modeled using the so-called Mixed Cloud Isotope Model (MCIM. The model generally underestimates the depletion of 18O in precipitation, which was not improved by using condensation temperature rather than inversion temperature. Contrary to the assumption widely used in ice core studies, a more northern moisture source does not necessarily mean stronger isotopic fractionation. This is due to the fact that snowfall events at Dome C are often associated with warm air advection due to amplification of planetary waves, which considerably increases the site temperature and thus reduces the temperature difference between source area and deposition site. In addition, no correlation was found between relative humidity at the moisture source and the deuterium excess in precipitation. The significant difference in the isotopic signal of hoarfrost and diamond dust was shown to disappear after removal of seasonality. This study confirms the results of an earlier study

  18. Sensitivity of the WRF model to the lower boundary in an extreme precipitation event - Madeira island case study

    Science.gov (United States)

    Teixeira, J. C.; Carvalho, A. C.; Carvalho, M. J.; Luna, T.; Rocha, A.

    2014-08-01

    The advances in satellite technology in recent years have made feasible the acquisition of high-resolution information on the Earth's surface. Examples of such information include elevation and land use, which have become more detailed. Including this information in numerical atmospheric models can improve their results in simulating lower boundary forced events, by providing detailed information on their characteristics. Consequently, this work aims to study the sensitivity of the weather research and forecast (WRF) model to different topography as well as land-use simulations in an extreme precipitation event. The test case focused on a topographically driven precipitation event over the island of Madeira, which triggered flash floods and mudslides in the southern parts of the island. Difference fields between simulations were computed, showing that the change in the data sets produced statistically significant changes to the flow, the planetary boundary layer structure and precipitation patterns. Moreover, model results show an improvement in model skill in the windward region for precipitation and in the leeward region for wind, in spite of the non-significant enhancement in the overall results with higher-resolution data sets of topography and land use.

  19. Evaluation of the Performance of Three Satellite Precipitation Products over Africa

    Directory of Open Access Journals (Sweden)

    Aleix Serrat-Capdevila

    2016-10-01

    Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

  20. Weather Regime-Dependent Predictability: Sequentially Linked High-Impact Weather Events over the United States during March 2016

    Science.gov (United States)

    Bosart, L. F.; Winters, A. C.; Keyser, D.

    2016-12-01

    High-impact weather events (HWEs), defined by episodes of excessive precipitation or periods of well above or well below normal temperatures, can pose important predictability challenges on medium-range (8-16 day) time scales. Furthermore, HWEs can contribute disproportionately to temperature and precipitation anomaly statistics for a particular season. This disproportionate contribution suggests that HWEs need to be considered in describing and understanding the dynamical and thermodynamic processes that operate at the weather-climate intersection. HWEs typically develop in conjunction with highly amplified flow patterns that permit an extensive latitudinal exchange of polar and tropical air masses. Highly amplified flow patterns over North America often occur in response to a reconfiguration of the large-scale upstream flow pattern over the North Pacific Ocean. The large-scale flow pattern over the North Pacific, North America, and western North Atlantic during the latter half of March 2016 was characterized by frequent cyclonic wave breaking (CWB). This large-scale flow pattern enabled three sequentially linked HWEs to develop over the continental United States. The first HWE was a challenging-to-predict cyclogenesis event on 23-24 March in the central Plains that resulted in both a major snowstorm along the Colorado Front Range and a severe weather outbreak over the central and southern Plains. The second HWE was a severe weather outbreak that occurred over the Tennessee and Ohio River Valleys on 27-28 March. The third HWE was the development of well below normal temperatures over the eastern United States that followed the formation of a high-latitude omega block over northwestern North America during 28 March-1 April. This study will examine (1) the role that CWB over the North Pacific and North America played in the evolution of the flow pattern during late-March 2016 and the development of the three HWEs and (2) the skill of GFS operational and ensemble

  1. Isotope fingerprinting of precipitation associated with western disturbances and Indian summer monsoons across the Himalayas

    Science.gov (United States)

    Jeelani, Ghulam; Deshpande, R. D.

    2017-12-01

    Precipitation samples were collected across the Himalayas from Kashmir (western Himalaya) to Assam (eastern Himalaya) to understand the variation of the stable isotopic content (δ ^{18}O and δ D) in precipitation associated with two dominant weather systems of the region: western disturbances (WDs) and Indian summer monsoon (ISM). Large spatial and temporal variations in isotopic values were noted with δ^{18}O and δ D values ranging from -30.3 to [InlineEquation not available: see fulltext.] and -228 to [InlineEquation not available: see fulltext.], respectively. The d-excess values also exhibit a large range of variation from -30 to [InlineEquation not available: see fulltext.]. In general, heavier isotopic values are observed in most of the samples in Jammu, whereas lighter values are observed in majority of the samples in Uttarakhand. Precipitation at Jammu seems to have undergone intense evaporation while that from Uttarakhand suggest normal Rayleigh fractionation/distillation of the air mass as it moves from the source region to the precipitation site and/or orographic lifting. The d-excess of rainfall in Kashmir has a distinctly higher median value of [InlineEquation not available: see fulltext.] compared to other precipitation sites with a median of [InlineEquation not available: see fulltext.]. Using distinct isotopic signatures, the regions receiving precipitation from two different weather systems have been identified.

  2. Controls of precipitation δ18O on the northwestern Tibetan Plateau: A case study at Ngari station

    Science.gov (United States)

    Guo, Xiaoyu; Tian, Lide; Wen, Rong; Yu, Wusheng; Qu, Dongmei

    2017-06-01

    The shifting atmospheric circulation between the Indian monsoon and the westerlies on the northwestern Tibetan Plateau (TP) influences precipitation as well as precipitation isotopes. Isotopic records will therefore show historical fluctuations. To understand better the factors controlling present day precipitation δ18O values on the northwestern TP, we made continuous observations of precipitation isotopes at Ngari station from 2010 to 2013. The drivers of precipitation δ18O were investigated using analyses of their statistical relations with temperature, precipitation amount, relative humidity, and convective activities based on outgoing longwave radiation (OLR) data from NOAA satellites, and downward shortwave radiation (DSR) data collected at the Ngari automatic weather station. Atmospheric circulation patterns from NCAR reanalysis, and moisture transport paths of individual events derived from the HYSPLIT model using NCEP data, were also used to trace moisture sources. The results of our study include: (1) The slope and intercept of the Local Meteoric Water Line (LMWL) at Ngari (δD = 8.51 δ18O + 11.57 (R2 = 0.97, p < 0.01)) were higher than for the Global Meteoric Water Line (GMWL), indicating drier local climatic conditions; (2) Precipitation δ18O values showed a weak ;temperature effect; and a weak ;precipitation amount effect; at Ngari; and (3) Convection (or temperature patterns) integrated over several days (0-20) preceding each event were determined to be the main driver of precipitation isotopic values in monsoon (or non-monsoon) season. The longer (shorter) periods of τm days when correlation coefficients between precipitation δ18O and OLR were at their maxima (minima) indicate deep convective activities (shorter moisture transportation pathways) in August (June, July, and September).

  3. Weather types and the regime of wildfires in Portugal

    Science.gov (United States)

    Pereira, M. G.; Trigo, R. M.; Dacamara, C. C.

    2009-04-01

    An objective classification scheme, as developed by Trigo and DaCamara (2000), was applied to classify the daily atmospheric circulation affecting Portugal between 1980 and 2007 into a set of 10 basic weather types (WTs). The classification scheme relies on a set of atmospheric circulation indices, namely southerly flow (SF), westerly flow (WF), total flow (F), southerly shear vorticity (ZS), westerly shear vorticity (ZW) and total vorticity (Z). The weather-typing approach, together with surfacemeteorological variables (e.g. intensity and direction of geostrophic wind, maximum and minimum temperature and precipitation) were then associated to wildfire events as recorded in the official Portuguese fire database consisting of information on each fire occurred in the 18 districts of Continental Portugal within the same period (>450.000 events). The objective of this study is to explore the dependence of wildfire activity on weather and climate and then evaluate the potential of WTs to discriminate among recorded wildfires on what respects to their occurrence and development. Results show that days characterised by surface flow with an eastern component (i.e. NE, E and SE) account for a high percentage of daily burnt area, as opposed to surface westerly flow (NW, W and SW), which represents about a quarter of the total number of days but only accounts for a very low percentage of active fires and of burnt area. Meteorological variables such as minimum and maximum temperatures, that are closely associated to surface wind intensity and direction, also present a good ability to discriminate between the different types of fire events.. Trigo R.M., DaCamara C. (2000) "Circulation Weather Types and their impact on the precipitation regime in Portugal". Int J of Climatology, 20, 1559-1581.

  4. Japanese Global Precipitation Measurement (GPM) mission status and application of satellite-based global rainfall map

    Science.gov (United States)

    Kachi, Misako; Shimizu, Shuji; Kubota, Takuji; Yoshida, Naofumi; Oki, Riko; Kojima, Masahiro; Iguchi, Toshio; Nakamura, Kenji

    2010-05-01

    As accuracy of satellite precipitation estimates improves and observation frequency increases, application of those data to societal benefit areas, such as weather forecasts and flood predictions, is expected, in addition to research of precipitation climatology to analyze precipitation systems. There is, however, limitation on single satellite observation in coverage and frequency. Currently, the Global Precipitation Measurement (GPM) mission is scheduled under international collaboration to fulfill various user requirements that cannot be achieved by the single satellite, like the Tropical Rainfall Measurement Mission (TRMM). The GPM mission is an international mission to achieve high-accurate and high-frequent rainfall observation over a global area. GPM is composed of a TRMM-like non-sun-synchronous orbit satellite (GPM core satellite) and constellation of satellites carrying microwave radiometer instruments. The GPM core satellite carries the Dual-frequency Precipitation Radar (DPR), which is being developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and microwave radiometer provided by the National Aeronautics and Space Administration (NASA). Development of DPR instrument is in good progress for scheduled launch in 2013, and DPR Critical Design Review has completed in July - September 2009. Constellation satellites, which carry a microwave imager and/or sounder, are planned to be launched around 2013 by each partner agency for its own purpose, and will contribute to extending coverage and increasing frequency. JAXA's future mission, the Global Change Observation Mission (GCOM) - Water (GCOM-W) satellite will be one of constellation satellites. The first generation of GCOM-W satellite is scheduled to be launched in 2011, and it carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), which is being developed based on the experience of the AMSR-E on EOS Aqua satellite

  5. Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

    DEFF Research Database (Denmark)

    Sunyer Pinya, Maria Antonia; Hundecha, Y.; Lawrence, D.

    impact studies. Four methods are based on change factors and four are bias correction methods. The change factor methods perturb the observations according to changes in precipitation properties estimated from the Regional Climate Models (RCMs). The bias correction methods correct the output from...... the RCMs. The eight methods are used to downscale precipitation output from fifteen RCMs from the ENSEMBLES project for eleven catchments in Europe. The performance of the bias correction methods depends on the catchment, but in all cases they represent an improvement compared to RCM output. The overall...... results point to an increase in extreme precipitation in all the catchments in winter and in most catchments in summer. For each catchment, the results tend to agree on the direction of the change but differ in the magnitude. These differences can be mainly explained due to differences in the RCMs....

  6. Integration of Weather Avoidance and Traffic Separation

    Science.gov (United States)

    Consiglio, Maria C.; Chamberlain, James P.; Wilson, Sara R.

    2011-01-01

    This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction

  7. Forecasting summertime surface temperature and precipitation in the Mexico City metropolitan area: sensitivity of the WRF model to land cover changes

    Science.gov (United States)

    López-Bravo, Clemente; Caetano, Ernesto; Magaña, Víctor

    2018-02-01

    Changes in the frequency and intensity of severe hydrometeorological events in recent decades in the Mexico City Metropolitan Area have motivated the development of weather warning systems. The weather forecasting system for this region was evaluated in sensitivity studies using the Weather Research and Forecasting Model (WRF) for July 2014, a summer time month. It was found that changes in the extent of the urban area and associated changes in thermodynamic and dynamic variables have induced local circulations that affect the diurnal cycles of temperature, precipitation, and wind fields. A newly implemented configuration (land cover update and Four-Dimensional Data Assimilation (FDDA)) of the WRF model has improved the adjustment of the precipitation field to the orography. However, errors related to the depiction of convection due to parameterizations and microphysics remains a source of uncertainty in weather forecasting in this region.

  8. Evaluation of Integrated Multi-satellitE Retrievals for GPM with All Weather Gauge Observations over CONUS

    Science.gov (United States)

    Chen, S.; Qi, Y.; Hu, B.; Hu, J.; Hong, Y.

    2015-12-01

    The Global Precipitation Measurement (GPM) mission is composed of an international network of satellites that provide the next-generation global observations of rain and snow. Integrated Multi-satellitE Retrievals for GPM (IMERG) is the state-of-art precipitation products with high spatio-temporal resolution of 0.1°/30min. IMERG unifies precipitation measurements from a constellation of research and operational satellites with the core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI) on board a "Core" satellite. Additionally, IMERG blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. In this study, the final run post real-time IMERG is evaluated with all-weather manual gauge observations over CONUS from June 2014 through May 2015. Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of IMERG. The performance of IMERG in estimating snowfall precipitation is highlighted in the study. This timely evaluation with all-weather gauge observations is expected to offer insights into performance of IMERG and thus provide useful feedback to the algorithm developers as well as the GPM data users.

  9. Some observations on precipitation measurement on forested experimental watersheds

    Science.gov (United States)

    Raymond E. Leonard; Kenneth G. Reinhart

    1963-01-01

    Measurement of precipitation on forested experimental watersheds presents difficulties other than those associated with access to and from the gages in all kinds of weather. For instance, the tree canopy must be cleared above the gage. The accepted practice of keeping an unobstructed sky view of 45" around the gage involves considerable tree cutting. On a level...

  10. Modulation of precipitation by conditional symmetric instability release

    Science.gov (United States)

    Glinton, Michael R.; Gray, Suzanne L.; Chagnon, Jeffrey M.; Morcrette, Cyril J.

    2017-03-01

    Although many theoretical and observational studies have investigated the mechanism of conditional symmetric instability (CSI) release and associated it with mesoscale atmospheric phenomena such as frontal precipitation bands, cloud heads in rapidly developing extratropical cyclones and sting jets, its climatology and contribution to precipitation have not been extensively documented. The aim of this paper is to quantify the contribution of CSI release, yielding slantwise convection, to climatological precipitation accumulations for the North Atlantic and western Europe. Case studies reveal that CSI release could be common along cold fronts of mature extratropical cyclones and the North Atlantic storm track is found to be a region with large CSI according to two independent CSI metrics. Correlations of CSI with accumulated precipitation are also large in this region and CSI release is inferred to be occurring about 20% of the total time over depths of over 1 km. We conclude that the inability of current global weather forecast and climate prediction models to represent CSI release (due to insufficient resolution yet lack of subgrid parametrization schemes) may lead to errors in precipitation distributions, particularly in the region of the North Atlantic storm track.

  11. Weather based risks and insurances for crop production in Belgium

    Science.gov (United States)

    Gobin, Anne

    2014-05-01

    Extreme weather events such as late frosts, droughts, heat waves and rain storms can have devastating effects on cropping systems. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The impact of extreme weather events particularly during the sensitive periods of the farming calendar requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event. The risk of soil moisture deficit increases towards harvesting, such that drought stress occurs in spring and summer. Conversely, waterlogging occurs mostly during early spring and autumn. Risks of temperature stress appear during winter and spring for chilling and during summer for heat. Since crop development is driven by thermal time and photoperiod, the regional crop model REGCROP (Gobin, 2010) enabled to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. The risk profiles were subsequently confronted with yields, yield losses and insurance claims for different crops. Physically based crop models such as REGCROP assist in understanding the links between different factors causing crop damage as demonstrated for cropping systems in Belgium. Extreme weather events have already precipitated contraction of insurance coverage in some markets (e.g. hail insurance), and the process can be expected to continue if the losses or damages from such events increase in the future. Climate

  12. Thermo-kinetic prediction of metastable and stable phase precipitation in Al–Zn–Mg series aluminium alloys during non-isothermal DSC analysis

    International Nuclear Information System (INIS)

    Lang, Peter; Wojcik, Tomasz; Povoden-Karadeniz, Erwin; Falahati, Ahmad; Kozeschnik, Ernst

    2014-01-01

    Highlights: • Comparison of laboratory Al–Zn–Mg alloy to industrial Al 7xxx series. • Heat flow evolution during non-isothermal DSC analysis is calculated. • TEM investigations of laboratory Al–Zn–Mg alloy at three pronounced temperatures. • Simulation and modelling of precipitation sequence. • Calculation and prediction of heat flow curves of Al 7xxx series. - Abstract: The technological properties of heat treatable Al–Zn–Mg alloys originate in the morphology and distribution of metastable particles. Starting from the solution-annealed condition, this paper describes the precipitate evolution during non-isothermal temperature changes, namely continuous heating differential scanning calorimetry (DSC) analysis. The distribution and the morphology of the metastable and stable precipitates and the heat flow accompanying the precipitation process is investigated experimentally and calculated by numerical thermo-kinetic simulations. The computer simulation results of the sizes and distributions are confirmed by transmission electron microscopy (TEM). The theoretical background and the results of the investigations are discussed

  13. Thermo-kinetic prediction of metastable and stable phase precipitation in Al–Zn–Mg series aluminium alloys during non-isothermal DSC analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lang, Peter, E-mail: pl404@cam.ac.uk [Department of Materials Science and Metallurgy, University of Cambridge, Charles Babbage Road 27, Cambridge CB3 0FS (United Kingdom); Wojcik, Tomasz [Institute of Materials Science and Technology, Vienna University of Technology, Favoritenstraße 9-11, Vienna 1040 (Austria); Povoden-Karadeniz, Erwin [Institute of Materials Science and Technology, Vienna University of Technology, Favoritenstraße 9-11, Vienna 1040 (Austria); Christian Doppler Laboratory “Early Stages of Precipitation”, Institute of Materials Science and Technology, Vienna University of Technology, Favoritenstraße 9-11, Vienna 1040 (Austria); Falahati, Ahmad [Institute of Materials Science and Technology, Vienna University of Technology, Favoritenstraße 9-11, Vienna 1040 (Austria); Kozeschnik, Ernst [Institute of Materials Science and Technology, Vienna University of Technology, Favoritenstraße 9-11, Vienna 1040 (Austria); Christian Doppler Laboratory “Early Stages of Precipitation”, Institute of Materials Science and Technology, Vienna University of Technology, Favoritenstraße 9-11, Vienna 1040 (Austria)

    2014-10-01

    Highlights: • Comparison of laboratory Al–Zn–Mg alloy to industrial Al 7xxx series. • Heat flow evolution during non-isothermal DSC analysis is calculated. • TEM investigations of laboratory Al–Zn–Mg alloy at three pronounced temperatures. • Simulation and modelling of precipitation sequence. • Calculation and prediction of heat flow curves of Al 7xxx series. - Abstract: The technological properties of heat treatable Al–Zn–Mg alloys originate in the morphology and distribution of metastable particles. Starting from the solution-annealed condition, this paper describes the precipitate evolution during non-isothermal temperature changes, namely continuous heating differential scanning calorimetry (DSC) analysis. The distribution and the morphology of the metastable and stable precipitates and the heat flow accompanying the precipitation process is investigated experimentally and calculated by numerical thermo-kinetic simulations. The computer simulation results of the sizes and distributions are confirmed by transmission electron microscopy (TEM). The theoretical background and the results of the investigations are discussed.

  14. Precipitable water and surface humidity over global oceans from special sensor microwave imager and European Center for Medium Range Weather Forecasts

    Science.gov (United States)

    Liu, W. T.; Tang, Wenqing; Wentz, Frank J.

    1992-01-01

    Global fields of precipitable water W from the special sensor microwave imager were compared with those from the European Center for Medium Range Weather Forecasts (ECMWF) model. They agree over most ocean areas; both data sets capture the two annual cycles examined and the interannual anomalies during an ENSO episode. They show significant differences in the dry air masses over the eastern tropical-subtropical oceans, particularly in the Southern Hemisphere. In these regions, comparisons with radiosonde data indicate that overestimation by the ECMWF model accounts for a large part of the differences. As a check on the W differences, surface-level specific humidity Q derived from W, using a statistical relation, was compared with Q from the ECMWF model. The differences in Q were found to be consistent with the differences in W, indirectly validating the Q-W relation. In both W and Q, SSMI was able to discern clearly the equatorial extension of the tongues of dry air in the eastern tropical ocean, while both ECMWF and climatological fields have reduced spatial gradients and weaker intensity.

  15. Error suppression and error correction in adiabatic quantum computation: non-equilibrium dynamics

    International Nuclear Information System (INIS)

    Sarovar, Mohan; Young, Kevin C

    2013-01-01

    While adiabatic quantum computing (AQC) has some robustness to noise and decoherence, it is widely believed that encoding, error suppression and error correction will be required to scale AQC to large problem sizes. Previous works have established at least two different techniques for error suppression in AQC. In this paper we derive a model for describing the dynamics of encoded AQC and show that previous constructions for error suppression can be unified with this dynamical model. In addition, the model clarifies the mechanisms of error suppression and allows the identification of its weaknesses. In the second half of the paper, we utilize our description of non-equilibrium dynamics in encoded AQC to construct methods for error correction in AQC by cooling local degrees of freedom (qubits). While this is shown to be possible in principle, we also identify the key challenge to this approach: the requirement of high-weight Hamiltonians. Finally, we use our dynamical model to perform a simplified thermal stability analysis of concatenated-stabilizer-code encoded many-body systems for AQC or quantum memories. This work is a companion paper to ‘Error suppression and error correction in adiabatic quantum computation: techniques and challenges (2013 Phys. Rev. X 3 041013)’, which provides a quantum information perspective on the techniques and limitations of error suppression and correction in AQC. In this paper we couch the same results within a dynamical framework, which allows for a detailed analysis of the non-equilibrium dynamics of error suppression and correction in encoded AQC. (paper)

  16. Test stand for non-uniformity correction of microbolometer focal plane arrays used in thermal cameras

    Science.gov (United States)

    Krupiński, Michał; Bareła, Jaroslaw; Firmanty, Krzysztof; Kastek, Mariusz

    2013-10-01

    Uneven response of particular detectors (pixels) to the same incident power of infrared radiation is an inherent feature of microbolometer focal plane arrays. As a result an image degradation occurs, known as Fixed Pattern Noise (FPN), which distorts the thermal representation of an observed scene and impairs the parameters of a thermal camera. In order to compensate such non-uniformity, several NUC correction methods are applied in digital data processing modules implemented in thermal cameras. Coefficients required to perform the non-uniformity correction procedure (NUC coefficients) are determined by calibrating the camera against uniform radiation sources (blackbodies). Non-uniformity correction is performed in a digital processing unit in order to remove FPN pattern in the registered thermal images. Relevant correction coefficients are calculated on the basis of recorded detector responses to several values of radiant flux emitted from reference IR radiation sources (blackbodies). The measurement of correction coefficients requires specialized setup, in which uniform, extended radiation sources with high temperature stability are one of key elements. Measurement stand for NUC correction developed in Institute of Optoelectronics, MUT, comprises two integrated extended blackbodies with the following specifications: area 200×200 mm, stabilized absolute temperature range +15 °C÷100 °C, and uniformity of temperature distribution across entire surface +/-0.014 °C. Test stand, method used for the measurement of NUC coefficients and the results obtained during the measurements conducted on a prototype thermal camera will be presented in the paper.

  17. 76 FR 39341 - Encouraging New Markets Tax Credit Non-Real Estate Investments; Correction

    Science.gov (United States)

    2011-07-06

    ... DEPARTMENT OF THE TREASURY Internal Revenue Service 26 CFR Part 1 [REG-114206-11] RIN 1545-BK21 Encouraging New Markets Tax Credit Non-Real Estate Investments; Correction AGENCY: Internal Revenue Service... how the new markets tax credit program may be amended to encourage non-real estate investments. FOR...

  18. IDF-curves for precipitation In Belgium

    International Nuclear Information System (INIS)

    Mohymont, Bernard; Demarde, Gaston R.

    2004-01-01

    The Intensity-Duration-Frequency (IDF) curves for precipitation constitute a relationship between the intensity, the duration and the frequency of rainfall amounts. The intensity of precipitation is expressed in mm/h, the duration or aggregation time is the length of the interval considered while the frequency stands for the probability of occurrence of the event. IDF-curves constitute a classical and useful tool that is primarily used to dimension hydraulic structures in general, as e.g., sewer systems and which are consequently used to assess the risk of inundation. In this presentation, the IDF relation for precipitation is studied for different locations in Belgium. These locations correspond to two long-term, high-quality precipitation networks of the RMIB: (a) the daily precipitation depths of the climatological network (more than 200 stations, 1951-2001 baseline period); (b) the high-frequency 10-minutes precipitation depths of the hydro meteorological network (more than 30 stations, 15 to 33 years baseline period). For the station of Uccle, an uninterrupted time-series of more than one hundred years of 10-minutes rainfall data is available. The proposed technique for assessing the curves is based on maximum annual values of precipitation. A new analytical formula for the IDF-curves was developed such that these curves stay valid for aggregation times ranging from 10 minutes to 30 days (when fitted with appropriate data). Moreover, all parameters of this formula have physical dimensions. Finally, adequate spatial interpolation techniques are used to provide nationwide extreme values precipitation depths for short- to long-term durations With a given return period. These values are estimated on the grid points of the Belgian ALADIN-domain used in the operational weather forecasts at the RMIB.(Author)

  19. Stochastic simulation experiment to assess radar rainfall retrieval uncertainties associated with attenuation and its correction

    Directory of Open Access Journals (Sweden)

    R. Uijlenhoet

    2008-03-01

    Full Text Available As rainfall constitutes the main source of water for the terrestrial hydrological processes, accurate and reliable measurement and prediction of its spatial and temporal distribution over a wide range of scales is an important goal for hydrology. We investigate the potential of ground-based weather radar to provide such measurements through a theoretical analysis of some of the associated observation uncertainties. A stochastic model of range profiles of raindrop size distributions is employed in a Monte Carlo simulation experiment to investigate the rainfall retrieval uncertainties associated with weather radars operating at X-, C-, and S-band. We focus in particular on the errors and uncertainties associated with rain-induced signal attenuation and its correction for incoherent, non-polarimetric, single-frequency, operational weather radars. The performance of two attenuation correction schemes, the (forward Hitschfeld-Bordan algorithm and the (backward Marzoug-Amayenc algorithm, is analyzed for both moderate (assuming a 50 km path length and intense Mediterranean rainfall (for a 30 km path. A comparison shows that the backward correction algorithm is more stable and accurate than the forward algorithm (with a bias in the order of a few percent for the former, compared to tens of percent for the latter, provided reliable estimates of the total path-integrated attenuation are available. Moreover, the bias and root mean square error associated with each algorithm are quantified as a function of path-averaged rain rate and distance from the radar in order to provide a plausible order of magnitude for the uncertainty in radar-retrieved rain rates for hydrological applications.

  20. Weatherization Innovation Pilot Program (WIPP): Technical Assistance Summary

    Energy Technology Data Exchange (ETDEWEB)

    Hollander, A.

    2014-09-01

    The U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy (EERE) Weatherization and Intergovernmental Programs Office (WIPO) launched the Weatherization Innovation Pilot Program (WIPP) to accelerate innovations in whole-house weatherization and advance DOE's goal of increasing the energy efficiency and health and safety of low-income residences without the utilization of additional taxpayer funding. Sixteen WIPP grantees were awarded a total of $30 million in Weatherization Assistance Program (WAP) funds in September 2010. These projects focused on: including nontraditional partners in weatherization service delivery; leveraging significant non-federal funding; and improving the effectiveness of low-income weatherization through the use of new materials, technologies, behavior-change models, and processes.

  1. Controls on Weathering of Pyrrhotite in a Low-Sulfide, Granitic Mine-Waste Rock in the Canadian Arctic

    Science.gov (United States)

    Langman, J. B.; Holland, S.; Sinclair, S.; Blowes, D.

    2013-12-01

    Increased environmental risk is incurred with expansion of mineral extraction in the Arctic. A greater understanding of geochemical processes associated with hard-rock mining in this cold climate is needed to evaluate and mitigate these risks. A laboratory and in-situ experiment was conducted to examine mineral weathering and the generation of acid rock drainage in a low-sulfide, run-of-mine waste rock in an Arctic climate. Rock with different concentrations of sulfides (primarily pyrrhotite [Fe7S8] containing small amounts of Co and Ni) and carbonates were weathered in the laboratory and in-situ, large-scale test piles to examine leachate composition and mineral weathering. The relatively larger sulfide-containing rock produced sufficient acid to overcome carbonate buffering and produced a declining pH environment with concomitant release of SO4, Fe, Co, and Ni. Following carbonate consumption, aluminosilicate buffering stabilized the pH above 4 until a reduction in acid generation. Results from the laboratory experiment assisted in determining that after consumption of 1.6 percent of the total sulfide, the larger sulfide-concentration test pile likely is at an internal steady-state or maximal weathering rate after seven years of precipitation input and weathering that is controlled by an annual freeze-thaw cycle. Further weathering of the test pile should be driven by external factors of temperature and precipitation in this Arctic, semi-arid region instead of internal factors of wetting and non-equilibrium buffering. It is predicted that maximal weathering will continue until at least 20 percent of the total sulfide is consumed. Using the identified evolution of sulfide consumption in this Arctic climate, a variable rate factor can now be assessed for the possible early evolution and maximal weathering of larger scale waste-rock piles and seasonal differences because of changes in the volume of a waste-rock pile undergoing active weathering due to the freeze

  2. The potential impacts of climate variability and change on health impacts of extreme weather events in the United States.

    Science.gov (United States)

    Greenough, G; McGeehin, M; Bernard, S M; Trtanj, J; Riad, J; Engelberg, D

    2001-05-01

    Extreme weather events such as precipitation extremes and severe storms cause hundreds of deaths and injuries annually in the United States. Climate change may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation.

  3. The non-uniformity correction factor for the cylindrical ionization chambers in dosimetry of an HDR 192Ir brachytherapy source

    International Nuclear Information System (INIS)

    Majumdar, Bishnu; Patel, Narayan Prasad; Vijayan, V.

    2006-01-01

    The aim of this study is to derive the non-uniformity correction factor for the two therapy ionization chambers for the dose measurement near the brachytherapy source. The two ionization chambers of 0.6 cc and 0.1 cc volume were used. The measurement in air was performed for distances between 0.8 cm and 20 cm from the source in specially designed measurement jig. The non-uniformity correction factors were derived from the measured values. The experimentally derived factors were compared with the theoretically calculated non-uniformity correction factors and a close agreement was found between these two studies. The experimentally derived non-uniformity correction factor supports the anisotropic theory. (author)

  4. On the relationship between Indian monsoon withdrawal and Iran's fall precipitation onset

    Science.gov (United States)

    Babaeian, Iman; Rezazadeh, Parviz

    2017-09-01

    Indian monsoon is the most prominent of the world's monsoon systems which primarily affects synoptic patterns of India and adjacent countries such as Iran in interaction with large-scale weather systems. In this article, the relationship between the withdrawal date of the Indian monsoon and the onset of fall precipitation in Iran has been studied. Data included annual time series of withdrawal dates of the Indian monsoon prepared by the Indian Institute for Tropical Meteorology, and time series of the first date of 25 mm accumulated precipitation over Iran's synoptic weather stations in a 10-day period which is the basis for the cultivation date. Both time series were considered in Julian calendar with the starting date on August 1. The studied period is 1960-2014 which covers 55 years of data from 36 meteorological stations in Iran. By classifying the withdrawal dates of the Indian monsoon in three stages of late, normal, and early withdrawals, its relation with the onset of fall precipitation in western, southwestern, southern, eastern, central, and northern regions of Iran was studied. Results demonstrated that in four out of the six mentioned regions, the late withdrawal of the Indian monsoon postpones the onset of fall precipitation over Iran. No significant relation was found between the onset of fall precipitation in central region of Iran and the monsoon's withdrawal date. In the western, southwestern, southern, and eastern regions of Iran, the late monsoon delays the onset of fall's precipitation; while in the south Caspian Sea coastal area, it causes the early onset of autumnal precipitation. The lag in onset of fall precipitation in Iran which is coordinated with the late withdrawal of monsoon is accompanied with prolonged subtropical high settling over Iran's plateau that prevents the southward movement of polar jet frontal systems. Such conditions enhance northerly wind currents over the Caspian Sea which, in turn, increase the precipitation in Caspian

  5. Weather variability affects the Peregrine Falcon (F. p. tundrius) breeding success in South Greenland

    DEFF Research Database (Denmark)

    Carlzon, Linnéa; Karlsson, Amanda; Falk, Knud

    Global warming is affecting the Arctic at a much higher rate than the rest of the globe, causing a rapidly changing environment for Arctic biota. Climate change is already causing increased variability and extremes in precipitation. Although the peregrine falcon is a well-studied top predator...... in the Arctic only a few studies have identified how the changing weather patterns affect the breeding populations. Therefore, in order to understand the effects of climate change on the peregrine’s future prospects, we investigated the relationship between weather variability (“extreme weather”) and breeding......’ and total days with ‘extreme weather’ during the pre-laying and incubation period also had significant negative correlation with breeding success. Contrary to expectations (and other studies), we found no significant effect of precipitation during the nesting period. Results also indicate that other factors...

  6. Kinetic corrections from analytic non-Maxwellian distribution functions in magnetized plasmas

    Energy Technology Data Exchange (ETDEWEB)

    Izacard, Olivier, E-mail: izacard@llnl.gov [Lawrence Livermore National Laboratory, 7000 East Avenue, L-637, Livermore, California 94550 (United States)

    2016-08-15

    In magnetized plasma physics, almost all developed analytic theories assume a Maxwellian distribution function (MDF) and in some cases small deviations are described using the perturbation theory. The deviations with respect to the Maxwellian equilibrium, called kinetic effects, are required to be taken into account especially for fusion reactor plasmas. Generally, because the perturbation theory is not consistent with observed steady-state non-Maxwellians, these kinetic effects are numerically evaluated by very central processing unit (CPU)-expensive codes, avoiding the analytic complexity of velocity phase space integrals. We develop here a new method based on analytic non-Maxwellian distribution functions constructed from non-orthogonal basis sets in order to (i) use as few parameters as possible, (ii) increase the efficiency to model numerical and experimental non-Maxwellians, (iii) help to understand unsolved problems such as diagnostics discrepancies from the physical interpretation of the parameters, and (iv) obtain analytic corrections due to kinetic effects given by a small number of terms and removing the numerical error of the evaluation of velocity phase space integrals. This work does not attempt to derive new physical effects even if it could be possible to discover one from the better understandings of some unsolved problems, but here we focus on the analytic prediction of kinetic corrections from analytic non-Maxwellians. As applications, examples of analytic kinetic corrections are shown for the secondary electron emission, the Langmuir probe characteristic curve, and the entropy. This is done by using three analytic representations of the distribution function: the Kappa distribution function, the bi-modal or a new interpreted non-Maxwellian distribution function (INMDF). The existence of INMDFs is proved by new understandings of the experimental discrepancy of the measured electron temperature between two diagnostics in JET. As main results, it

  7. Does weather affect daily pain intensity levels in patients with acute low back pain? A prospective cohort study.

    Science.gov (United States)

    Duong, Vicky; Maher, Chris G; Steffens, Daniel; Li, Qiang; Hancock, Mark J

    2016-05-01

    The aim of this study was to investigate the influence of various weather parameters on pain intensity levels in patients with acute low back pain (LBP). We performed a secondary analysis using data from the PACE trial that evaluated paracetamol (acetaminophen) in the treatment of acute LBP. Data on 1604 patients with LBP were included in the analysis. Weather parameters (precipitation, temperature, relative humidity, and air pressure) were obtained from the Australian Bureau of Meteorology. Pain intensity was assessed daily on a 0-10 numerical pain rating scale over a 2-week period. A generalised estimating equation analysis was used to examine the relationship between daily pain intensity levels and weather in three different time epochs (current day, previous day, and change between previous and current days). A second model was adjusted for important back pain prognostic factors. The analysis did not show any association between weather and pain intensity levels in patients with acute LBP in each of the time epochs. There was no change in strength of association after the model was adjusted for prognostic factors. Contrary to common belief, the results demonstrated that the weather parameters of precipitation, temperature, relative humidity, and air pressure did not influence the intensity of pain reported by patients during an episode of acute LBP.

  8. Multi-year and reference year weather data for building energy labelling in north Italy climates

    NARCIS (Netherlands)

    Pernigotto, G.; Prada, A.; Costola, D.; Gasparella, A.; Hensen, J.L.M.

    2014-01-01

    Representative weather information is essential for a reliable building energy performance evaluation. Even if detailed energy analyses can be carried out considering the multi-year weather data, generally a single reference year is adopted. Thus, this artificial year has to correctly approximate

  9. Multifactorial effects of ambient temperature, precipitation, farm management, and environmental factors determine the level of generic Escherichia coli contamination on preharvested spinach.

    Science.gov (United States)

    Park, Sangshin; Navratil, Sarah; Gregory, Ashley; Bauer, Arin; Srinath, Indumathi; Szonyi, Barbara; Nightingale, Kendra; Anciso, Juan; Jun, Mikyoung; Han, Daikwon; Lawhon, Sara; Ivanek, Renata

    2015-04-01

    A repeated cross-sectional study was conducted to identify farm management, environment, weather, and landscape factors that predict the count of generic Escherichia coli on spinach at the preharvest level. E. coli was enumerated for 955 spinach samples collected on 12 farms in Texas and Colorado between 2010 and 2012. Farm management and environmental characteristics were surveyed using a questionnaire. Weather and landscape data were obtained from National Resources Information databases. A two-part mixed-effect negative binomial hurdle model, consisting of a logistic and zero-truncated negative binomial part with farm and date as random effects, was used to identify factors affecting E. coli counts on spinach. Results indicated that the odds of a contamination event (non-zero versus zero counts) vary by state (odds ratio [OR] = 108.1). Odds of contamination decreased with implementation of hygiene practices (OR = 0.06) and increased with an increasing average precipitation amount (mm) in the past 29 days (OR = 3.5) and the application of manure (OR = 52.2). On contaminated spinach, E. coli counts increased with the average precipitation amount over the past 29 days. The relationship between E. coli count and the average maximum daily temperature over the 9 days prior to sampling followed a quadratic function with the highest bacterial count at around 24°C. These findings indicate that the odds of a contamination event in spinach are determined by farm management, environment, and weather factors. However, once the contamination event has occurred, the count of E. coli on spinach is determined by weather only. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  10. Response of surface water chemistry to reduced levels of acid precipitation: Comparison of trends in two regions of New York, USA

    Science.gov (United States)

    Burns, Douglas A.; McHale, M.R.; Driscoll, C.T.; Roy, K.M.

    2006-01-01

    In light of recent reductions in sulphur (S) and nitrogen (N) emissions mandated by Title IV of the Clean Air Act Amendments of 1990, temporal trends and trend coherence in precipitation (1984-2001 and 1992-2001) and surface water chemistry (1992-2001) were determined in two of the most acid-sensitive regions of North America, i.e. the Catskill and Adirondack Mountains of New York. Precipitation chemistry data from six sites located near these regions showed decreasing sulphate (SO42-), nitrate (NO3-), and base cation (CB) concentrations and increasing pH during 1984-2001, but few significant trends during 1992-2001. Data from five Catskill streams and 12 Adirondack lakes showed decreasing trends in SO42- concentrations at all sites, and decreasing trends in NO3-, CB, and H+ concentrations and increasing trends in dissolved organic carbon at most sites. In contrast, acid-neutralizing capacity (ANC increased significantly at only about half the Adirondack lakes and in one of the Catskill streams. Flow correction prior to trend analysis did not change any trend directions and had little effect on SO42- trends, but it caused several significant non-flow-corrected trends in NO3- and ANC to become non-significant, suggesting that trend results for flow-sensitive constituents are affected by flow-related climate variation. SO42- concentrations showed high temporal coherence in precipitation, surface waters, and in precipitation-surface water comparisons, reflecting a strong link between S emissions, precipitation SO42- concentrations, and the processes that affect S cycling within these regions. NO3- and H+ concentrations and ANC generally showed weak coherence, especially in surface waters and in precipitation-surface water comparisons, indicating that variation in local-scale processes driven by factors such as climate are affecting trends in acid-base chemistry in these two regions. Copyright ?? 2005 John Wiley & Sons, Ltd.

  11. Differential Precipitation and Solubilization of Proteins.

    Science.gov (United States)

    Ryan, Barry J; Kinsella, Gemma K

    2017-01-01

    Differential protein precipitation is a rapid and economical step in protein purification and is based on exploiting the inherent physicochemical properties of the polypeptide. Precipitation of recombinant proteins, lysed from the host cell, is commonly used to concentrate the protein of choice before further polishing steps with more selective purification columns (e.g., His-Tag, Size Exclusion, etc.). Recombinant proteins can also precipitate naturally as inclusion bodies due to various influences during overexpression in the host cell. Although this phenomenon permits easier initial separation from native proteins, these inclusion bodies must carefully be differentially solubilized so as to reform functional, correctly folded proteins. Here, appropriate bioinformatics tools to aid in understanding a protein's propensity to aggregate and solubilize are explored as a backdrop for a typical protein extraction, precipitation, and selective resolubilization procedure, based on a recombinantly expressed protein.

  12. High-Resolution Modeling of ENSO-Induced Precipitation in the Tropical Andes: Implications for Proxy Interpretation.

    Science.gov (United States)

    Kiefer, J.; Karamperidou, C.

    2017-12-01

    Clastic sediment flux into high-elevation Andean lakes is controlled by glacial processes and soil erosion caused by high precipitation events, making these lakes suitable archives of past climate. To wit, sediment records from Laguna Pallcacocha in Ecuador have been interpreted as proxies of ENSO variability, owing to increased precipitation in the greater region during El Niño events. However, the location of the lake's watershed, the presence of glaciers, and the different impacts of ENSO on precipitation in the eastern vs western Andes have challenged the suitability of the Pallcacocha record as an ENSO proxy. Here, we employ WRF, a high-resolution regional mesoscale weather prediction model, to investigate the circulation dynamics, sources of moisture, and resulting precipitation response in the L. Pallcacocha region during different flavors of El Niño and La Niña events, and in the presence or absence of ice caps. In patricular, we investigate Eastern Pacific (EP), Central Pacific (CP), coastal El Niño, and La Niña events. We validate the model simulations against spatially interpolated station measurements and reanalysis data. We find that during EP events, moisture is primarily advected from the Pacific, whereas during CP events, moisture primarily originates from the Atlantic. More moisture is available during EP events, which implies higher precipitation rates. Furthermore, we find that precipitation during EP events is mostly non-convective in contrast to primarily convective precipitation during CP events. Finally, a synthesis of the sedimentary record and the EP:CP ratio of accumulated precipitation and specific humidity in the L. Pallcacocha region allows us to assess whether past changes in the relative frequency of the two ENSO flavors may have been recorded in paleoclimate archives in this region.

  13. Aerosol radiative effects on mesoscale cloud-precipitation variables over Northeast Asia during the MAPS-Seoul 2015 campaign

    Science.gov (United States)

    Park, Shin-Young; Lee, Hyo-Jung; Kang, Jeong-Eon; Lee, Taehyoung; Kim, Cheol-Hee

    2018-01-01

    The online model, Weather Research and Forecasting Model with Chemistry (WRF-Chem) is employed to interpret the effects of aerosol-cloud-precipitation interaction on mesoscale meteorological fields over Northeast Asia during the Megacity Air Pollution Study-Seoul (MAPS-Seoul) 2015 campaign. The MAPS-Seoul campaign is a pre-campaign of the Korea-United States Air Quality (KORUS-AQ) campaign conducted over the Korean Peninsula. We validated the WRF-Chem simulations during the campaign period, and analyzed aerosol-warm cloud interactions by diagnosing both aerosol direct, indirect, and total effects. The results demonstrated that aerosol directly decreased downward shortwave radiation up to -44% (-282 W m-2) for this period and subsequently increased downward longwave radiation up to +15% (∼52 W m-2) in the presence of low-level clouds along the thematic area. Aerosol increased cloud fraction indirectly up to ∼24% with the increases of both liquid water path and the droplet number mixing ratio. Precipitation properties were altered both directly and indirectly. Direct effects simply changed cloud-precipitation quantities via simple updraft process associated with perturbed radiation and temperature, while indirect effects mainly suppressed precipitation, but sometimes increased precipitation in the higher relative humidity atmosphere or near vapor-saturated condition. The total aerosol effects caused a time lag of the precipitation rate with the delayed onset time of up to 9 h. This implies the importance of aerosol effects in improving mesoscale precipitation rate prediction in the online approach in the presence of non-linear warm cloud.

  14. Coincidence detection FDG-PET (Co-PET) in the management of oncological patients: attenuation correction versus non-attenuation correction

    International Nuclear Information System (INIS)

    Chan, W.L.; Freund, J.; Pocock, N.; Szeto, E.; Chan, F.; Sorensen, B.; McBride, B.

    2000-01-01

    Full text: This study was to determine if attenuation correction (AC) in FDG Co-PET improved image quality, lesion detection, patient staging and management of various malignant neoplasms, compared to non-attenuation-corrected (NAC) images. Thirty patients (25 men, 5 women, mean age 58 years) with known or suspected malignant neoplasms, including non-small-cell lung cancer, non Hodgkin's and Hodgkin's lymphoma, carcinoma of the breast, head and neck cancer and melanoma, underwent FDG Co-PET, which was correlated with histopathology, CT and other conventional imaging modalities and clinical follow-up. Whole body tomography was performed (ADAC Vertex MCD) 60 min after 200 MBq of 18 F-FDG (>6h fasting). The number and location of FDG avid lesions detected on the AC images and NAC Co-PET images were blindly assessed by two independent observers. Semi-quantitative grading of image clarity and lesion-to-background quality was performed. This revealed markedly improved image clarity and lesion-to-background quality, in the AC versus NAC images. AC and NAC Co-PET were statistically different in relation to lesion detection (p<0.01) and tumour staging (p<0.0 1). NAC Co-PET demonstrated 51 of the 65 lesions (78%) detected by AC Co-PET. AC Co-PET staging was correct in 27 patients (90%), compared with NAC Co-PET in 22 patients (73%). AC Co-PET altered tumour staging in five of 30 patients (16%) and NAC Co-PET did not alter tumour staging in any of the patients- management was altered in only two of these five patients (7%). In conclusion, AC Co-PET resulted in better image quality with significantly improved lesion detectability and tumour staging compared to NAC Co-PET. Its additional impact on patient management in this relatively small sample was minor. Copyright (2000) The Australian and New Zealand Society of Nuclear Medicine Inc

  15. Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

    Science.gov (United States)

    Sheth, Kapil; Wang, Easter Mayan Chan

    2016-01-01

    Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

  16. A meteo-hydrological prediction system based on a multi-model approach for precipitation forecasting

    Directory of Open Access Journals (Sweden)

    S. Davolio

    2008-02-01

    Full Text Available The precipitation forecasted by a numerical weather prediction model, even at high resolution, suffers from errors which can be considerable at the scales of interest for hydrological purposes. In the present study, a fraction of the uncertainty related to meteorological prediction is taken into account by implementing a multi-model forecasting approach, aimed at providing multiple precipitation scenarios driving the same hydrological model. Therefore, the estimation of that uncertainty associated with the quantitative precipitation forecast (QPF, conveyed by the multi-model ensemble, can be exploited by the hydrological model, propagating the error into the hydrological forecast.

    The proposed meteo-hydrological forecasting system is implemented and tested in a real-time configuration for several episodes of intense precipitation affecting the Reno river basin, a medium-sized basin located in northern Italy (Apennines. These episodes are associated with flood events of different intensity and are representative of different meteorological configurations responsible for severe weather affecting northern Apennines.

    The simulation results show that the coupled system is promising in the prediction of discharge peaks (both in terms of amount and timing for warning purposes. The ensemble hydrological forecasts provide a range of possible flood scenarios that proved to be useful for the support of civil protection authorities in their decision.

  17. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Science.gov (United States)

    Zhang, Ying; Moges, Semu; Block, Paul

    2018-01-01

    Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  18. On the non-existence of a Bartlett correction for unit root tests

    DEFF Research Database (Denmark)

    Jensen, Jens Ledet; Wood, Andrew T.A.

    1997-01-01

    There has been considerable recent interest in testing for a unit root in autoregressive models, especially in the context of cointegration models in econometrics. The likelihood ratio test for a unit root has non-standard asymptotic behaviour. In particular, when the errors are Gaussian, the lim...... for improved distributional approximations, and the question of whether W admits a Bartlett correction is of interest. In this note we establish that a Bartlett correction does not exist in the simplest unit root model. © 1997 Elsevier Science B.V....

  19. Attenuation correction for the large non-human primate brain imaging using microPET

    International Nuclear Information System (INIS)

    Naidoo-Variawa, S; Lehnert, W; Kassiou, M; Banati, R; Meikle, S R

    2010-01-01

    Assessment of the biodistribution and pharmacokinetics of radiopharmaceuticals in vivo is often performed on animal models of human disease prior to their use in humans. The baboon brain is physiologically and neuro-anatomically similar to the human brain and is therefore a suitable model for evaluating novel CNS radioligands. We previously demonstrated the feasibility of performing baboon brain imaging on a dedicated small animal PET scanner provided that the data are accurately corrected for degrading physical effects such as photon attenuation in the body. In this study, we investigated factors affecting the accuracy and reliability of alternative attenuation correction strategies when imaging the brain of a large non-human primate (papio hamadryas) using the microPET Focus 220 animal scanner. For measured attenuation correction, the best bias versus noise performance was achieved using a 57 Co transmission point source with a 4% energy window. The optimal energy window for a 68 Ge transmission source operating in singles acquisition mode was 20%, independent of the source strength, providing bias-noise performance almost as good as for 57 Co. For both transmission sources, doubling the acquisition time had minimal impact on the bias-noise trade-off for corrected emission images, despite observable improvements in reconstructed attenuation values. In a [ 18 F]FDG brain scan of a female baboon, both measured attenuation correction strategies achieved good results and similar SNR, while segmented attenuation correction (based on uncorrected emission images) resulted in appreciable regional bias in deep grey matter structures and the skull. We conclude that measured attenuation correction using a single pass 57 Co (4% energy window) or 68 Ge (20% window) transmission scan achieves an excellent trade-off between bias and propagation of noise when imaging the large non-human primate brain with a microPET scanner.

  20. Total and non-seasalt sulfate and chloride measured in bulk precipitation samples from the Kilauea Volcano area, Hawaii

    Science.gov (United States)

    Scholl, M.A.; Ingebritsen, S.E.

    1995-01-01

    Six-month cumulative precipitation samples provide estimates of bulk deposition of sulfate and chloride for the southeast part of the Island of Hawaii during four time periods: August 1991 to February 1992, February 1992 to September 1992, March 1993 to September 1993, and September 1993 to February 1994. Total estimated bulk deposition rates for sulfate ranged from 0.12 to 24 grams per square meter per 180 days, and non-seasalt sulfate deposition ranged from 0.06 to 24 grams per square meter per 180 days. Patterns of non-seasalt sulfate deposition were generally related to prevailing wind directions and the proximity of the collection site to large sources of sulfur gases, namely Kilauea Volcano's summit and East Rift Zone eruption. Total chloride deposition from bulk precipitation samples ranged from 0.01 to 17 grams per square meter per 180 days. Chloride appeared to be predominantly from oceanic sources, as non- seasalt chloride deposition was near zero for most sites.

  1. Explaining the road accident risk: weather effects.

    Science.gov (United States)

    Bergel-Hayat, Ruth; Debbarh, Mohammed; Antoniou, Constantinos; Yannis, George

    2013-11-01

    This research aims to highlight the link between weather conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road safety monitoring at a national level. It is based on some case studies carried out in Work Package 7 on "Data analysis and synthesis" of the EU-FP6 project "SafetyNet-Building the European Road Safety Observatory", which illustrate the use of weather variables for analysing changes in the number of road injury accidents. Time series analysis models with explanatory variables that measure the weather quantitatively were used and applied to aggregate datasets of injury accidents for France, the Netherlands and the Athens region, over periods of more than 20 years. The main results reveal significant correlations on a monthly basis between weather variables and the aggregate number of injury accidents, but the magnitude and even the sign of these correlations vary according to the type of road (motorways, rural roads or urban roads). Moreover, in the case of the interurban network in France, it appears that the rainfall effect is mainly direct on motorways--exposure being unchanged, and partly indirect on main roads--as a result of changes in exposure. Additional results obtained on a daily basis for the Athens region indicate that capturing the within-the-month variability of the weather variables and including it in a monthly model highlights the effects of extreme weather. Such findings are consistent with previous results obtained for France using a similar approach, with the exception of the negative correlation between precipitation and the number of injury accidents found for the Athens region, which is further investigated. The outlook for the approach and its added value are discussed in the conclusion. Copyright © 2013. Published by Elsevier Ltd.

  2. Realistic natural atmospheric phenomena and weather effects for interactive virtual environments

    Science.gov (United States)

    McLoughlin, Leigh

    Clouds and the weather are important aspects of any natural outdoor scene, but existing dynamic techniques within computer graphics only offer the simplest of cloud representations. The problem that this work looks to address is how to provide a means of simulating clouds and weather features such as precipitation, that are suitable for virtual environments. Techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems are computationally expensive, give more numerical accuracy than we require for graphics and are restricted to the laws of physics. Within computer graphics, we often need to direct and adjust physical features or to bend reality to meet artistic goals, which is a key difference between the subjects of computer graphics and physical science. Pure physically-based simulations, however, evolve their solutions according to pre-set rules and are notoriously difficult to control. The challenge then is for the solution to be computationally lightweight and able to be directed in some measure while at the same time producing believable results. This work presents a lightweight physically-based cloud simulation scheme that simulates the dynamic properties of cloud formation and weather effects. The system simulates water vapour, cloud water, cloud ice, rain, snow and hail. The water model incorporates control parameters and the cloud model uses an arbitrary vertical temperature profile, with a tool described to allow the user to define this. The result of this work is that clouds can now be simulated in near real-time complete with precipitation. The temperature profile and tool then provide a means of directing the resulting formation..

  3. Identification of Robust Terminal-Area Routes in Convective Weather

    Science.gov (United States)

    Pfeil, Diana Michalek; Balakrishnan, Hamsa

    2012-01-01

    Convective weather is responsible for large delays and widespread disruptions in the U.S. National Airspace System, especially during summer. Traffic flow management algorithms require reliable forecasts of route blockage to schedule and route traffic. This paper demonstrates how raw convective weather forecasts, which provide deterministic predictions of the vertically integrated liquid (the precipitation content in a column of airspace) can be translated into probabilistic forecasts of whether or not a terminal area route will be blocked. Given a flight route through the terminal area, we apply techniques from machine learning to determine the likelihood that the route will be open in actual weather. The likelihood is then used to optimize terminalarea operations by dynamically moving arrival and departure routes to maximize the expected capacity of the terminal area. Experiments using real weather scenarios on stormy days show that our algorithms recommend that a terminal-area route be modified 30% of the time, opening up 13% more available routes that were forecast to be blocked during these scenarios. The error rate is low, with only 5% of cases corresponding to a modified route being blocked in reality, whereas the original route is in fact open. In addition, for routes predicted to be open with probability 0.95 or greater by our method, 96% of these routes (on average over time horizon) are indeed open in the weather that materializes

  4. An operational weather radar-based Quantitative Precipitation Estimation and its application in catchment water resources modeling

    DEFF Research Database (Denmark)

    He, Xin; Vejen, Flemming; Stisen, Simon

    2011-01-01

    of precipitation compared with rain-gauge-based methods, thus providing the basis for better water resources assessments. The radar QPE algorithm called ARNE is a distance-dependent areal estimation method that merges radar data with ground surface observations. The method was applied to the Skjern River catchment...... in western Denmark where alternative precipitation estimates were also used as input to an integrated hydrologic model. The hydrologic responses from the model were analyzed by comparing radar- and ground-based precipitation input scenarios. Results showed that radar QPE products are able to generate...... reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream discharge results. Also, groundwater recharge was shown to be sensitive...

  5. Phased Array Radar Network Experiment for Severe Weather

    Science.gov (United States)

    Ushio, T.; Kikuchi, H.; Mega, T.; Yoshikawa, E.; Mizutani, F.; Takahashi, N.

    2017-12-01

    Phased Array Weather Radar (PAWR) was firstly developed in 2012 by Osaka University and Toshiba under a grant of NICT using the Digital Beamforming Technique, and showed a impressive thunderstorm behavior with 30 second resolution. After that development, second PAWR was installed in Kobe city about 60 km away from the first PAWR site, and Tokyo Metropolitan University, Osaka Univeristy, Toshiba and the Osaka Local Government started a new project to develop the Osaka Urban Demonstration Network. The main sensor of the Osaka Network is a 2-node Phased Array Radar Network and lightning location system. Data products that are created both in local high performance computer and Toshiba Computer Cloud, include single and multi-radar data, vector wind, quantitative precipitation estimation, VIL, nowcasting, lightning location and analysis. Each radar node is calibarated by the baloon measurement and through the comparison with the GPM (Global Precipitation Measurement)/ DPR (Dual Frequency Space borne Radar) within 1 dB. The attenuated radar reflectivities obtained by the Phased Array Radar Network at X band are corrected based on the bayesian scheme proposed in Shimamura et al. [2016]. The obtained high resolution (every 30 seconds/ 100 elevation angles) 3D reflectivity and rain rate fields are used to nowcast the surface rain rate up to 30 minutes ahead. These new products are transferred to Osaka Local Government in operational mode and evaluated by several section in Osaka Prefecture. Furthermore, a new Phased Array Radar with polarimetric function has been developed in 2017, and will be operated in the fiscal year of 2017. In this presentation, Phased Array Radar, network architecuture, processing algorithm, evalution of the social experiment and first Multi-Prameter Phased Array Radar experiment are presented.

  6. Statistical-Dynamical Seasonal Forecasts of Central-Southwest Asian Winter Precipitation.

    Science.gov (United States)

    Tippett, Michael K.; Goddard, Lisa; Barnston, Anthony G.

    2005-06-01

    Interannual precipitation variability in central-southwest (CSW) Asia has been associated with East Asian jet stream variability and western Pacific tropical convection. However, atmospheric general circulation models (AGCMs) forced by observed sea surface temperature (SST) poorly simulate the region's interannual precipitation variability. The statistical-dynamical approach uses statistical methods to correct systematic deficiencies in the response of AGCMs to SST forcing. Statistical correction methods linking model-simulated Indo-west Pacific precipitation and observed CSW Asia precipitation result in modest, but statistically significant, cross-validated simulation skill in the northeast part of the domain for the period from 1951 to 1998. The statistical-dynamical method is also applied to recent (winter 1998/99 to 2002/03) multimodel, two-tier December-March precipitation forecasts initiated in October. This period includes 4 yr (winter of 1998/99 to 2001/02) of severe drought. Tercile probability forecasts are produced using ensemble-mean forecasts and forecast error estimates. The statistical-dynamical forecasts show enhanced probability of below-normal precipitation for the four drought years and capture the return to normal conditions in part of the region during the winter of 2002/03.May Kabul be without gold, but not without snow.—Traditional Afghan proverb

  7. Intensity changes in future extreme precipitation: A statistical event-based approach.

    Science.gov (United States)

    Manola, Iris; van den Hurk, Bart; de Moel, Hans; Aerts, Jeroen

    2017-04-01

    Short-lived precipitation extremes are often responsible for hazards in urban and rural environments with economic and environmental consequences. The precipitation intensity is expected to increase about 7% per degree of warming, according to the Clausius-Clapeyron (CC) relation. However, the observations often show a much stronger increase in the sub-daily values. In particular, the behavior of the hourly summer precipitation from radar observations with the dew point temperature (the Pi-Td relation) for the Netherlands suggests that for moderate to warm days the intensification of the precipitation can be even higher than 21% per degree of warming, that is 3 times higher than the expected CC relation. The rate of change depends on the initial precipitation intensity, as low percentiles increase with a rate below CC, the medium percentiles with 2CC and the moderate-high and high percentiles with 3CC. This non-linear statistical Pi-Td relation is suggested to be used as a delta-transformation to project how a historic extreme precipitation event would intensify under future, warmer conditions. Here, the Pi-Td relation is applied over a selected historic extreme precipitation event to 'up-scale' its intensity to warmer conditions. Additionally, the selected historic event is simulated in the high-resolution, convective-permitting weather model Harmonie. The initial and boundary conditions are alternated to represent future conditions. The comparison between the statistical and the numerical method of projecting the historic event to future conditions showed comparable intensity changes, which depending on the initial percentile intensity, range from below CC to a 3CC rate of change per degree of warming. The model tends to overestimate the future intensities for the low- and the very high percentiles and the clouds are somewhat displaced, due to small wind and convection changes. The total spatial cloud coverage in the model remains, as also in the statistical

  8. Local weather is associated with rates of online searches for musculoskeletal pain symptoms.

    Directory of Open Access Journals (Sweden)

    Scott Telfer

    Full Text Available Weather conditions are commonly believed to influence musculoskeletal pain, however the evidence for this is mixed. This study aimed to examine the relationship between local meteorological conditions and online search trends for terms related to knee pain, hip pain, and arthritis. Five years of relative online search volumes for these terms were obtained for the 50 most populous cities in the contiguous United States, along with corresponding local weather data for temperature, relative humidity, barometric pressure, and precipitation. Methods from the climate econometrics literature were used to assess the casual impact of these meteorological variables on the relative volumes of searches for pain. For temperatures between -5°C and 30°C, search volumes for hip pain increased by 12 index points, and knee pain increased by 18 index points. Precipitation had a negative effect on search volumes for these terms. At temperatures >30°C, search volumes for arthritis related pain decreased by 7 index points. These patterns were not seen for pain searches unrelated to the musculoskeletal system. In summary, selected local weather conditions are significantly associated with online search volumes for specific musculoskeletal pain symptoms. We believe the predominate driver for this to be the relative changes in physical activity levels associated with meteorological conditions.

  9. ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) Field Campaign Report

    Energy Technology Data Exchange (ETDEWEB)

    Leung, L Ruby [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-03-01

    The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) field campaign contributes to CalWater 2015, a multi-agency field campaign that aims to improve understanding of atmospheric rivers and aerosol sources and transport that influence cloud and precipitation processes. The ultimate goal is to reduce uncertainties in weather predictions and climate projections of droughts and floods in California. With the DOE G-1 aircraft and ARM Mobile Facility 2 (AMF2) well equipped for making aerosol and cloud measurements, ACAPEX focuses specifically on understanding how aerosols from local pollution and long-range transport affect the amount and phase of precipitation associated with atmospheric rivers. ACAPEX took place between January 12, 2015 and March 8, 2015 as part of CalWater 2015, which included four aircraft (DOE G-1, National Oceanic and Atmospheric Administration [NOAA] G-IV and P-3, and National Aeronautics and Space Administration [NASA] ER-2), the NOAA research ship Ron Brown, carrying onboard the AMF2, National Science Foundation (NSF)-sponsored aerosol and precipitation measurements at Bodega Bay, and the California Department of Water Resources extreme precipitation network.

  10. Non-uniform versus uniform attenuation correction in brain perfusion SPET of healthy volunteers

    International Nuclear Information System (INIS)

    Van Laere, K.; Versijpt, J.; Dierckx, R.; Koole, M.

    2001-01-01

    Although non-uniform attenuation correction (NUAC) can supply more accurate absolute quantification, it is not entirely clear whether NUAC provides clear-cut benefits in the routine clinical practice of brain SPET imaging. The aim of this study was to compare the effect of NUAC versus uniform attenuation correction (UAC) on volume of interest (VOI)-based semi-quantification of a large age- and gender-stratified brain perfusion normal database. Eighty-nine healthy volunteers (46 females and 43 males, aged 20-81 years) underwent standardised high-resolution single-photon emission tomography (SPET) with 925 MBq 99m Tc-ethyl cysteinate dimer (ECD) on a Toshiba GCA-9300A camera with 153 Gd or 99m Tc transmission CT scanning. Emission images were reconstructed by filtered back-projection and scatter corrected using the triple-energy window correction method. Both non-uniform Chang attenuation correction (one iteration) and uniform Sorenson correction (attenuation coefficient 0.09 cm -1 ) were applied. Images were automatically re-oriented to a stereotactic template on which 35 predefined VOIs were defined for semi-quantification (normalisation on total VOI counts). Small but significant differences between relative VOI uptake values for NUAC versus UAC in the infratentorial region were found. VOI standard deviations were significantly smaller for UAC, 4.5% (range 2.6-7.5), than for NUAC, 5.0% (2.3-9.0) (P 99m Tc-ECD uptake values in healthy volunteers to those obtained with NUAC, although values for the infratentorial region are slightly lower. NUAC produces a slight increase in inter-subject variability. Further study is necessary in various patient populations to establish the full clinical impact of NUAC in brain perfusion SPET. (orig.)

  11. Climate change, weather and road deaths.

    Science.gov (United States)

    Robertson, Leon

    2018-06-01

    In 2015, a 7% increase in road deaths per population in the USA reversed the 35-year downward trend. Here I test the hypothesis that weather influenced the change in trend. I used linear regression to estimate the effect of temperature and precipitation on miles driven per capita in urbanizedurbanised areas of the USA during 2010. I matched date and county of death with temperature on that date and number of people exposed to that temperature to calculate the risk per persons exposed to specific temperatures. I employed logistic regression analysis of temperature, precipitation and other risk factors prevalent in 2014 to project expected deaths in 2015 among the 100 most populous counties in the USA. Comparison of actual and projected deaths provided an estimate of deaths expected without the temperature increase. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  12. The Use of Convolutional Neural Network in Relating Precipitation to Circulation

    Science.gov (United States)

    Pan, B.; Hsu, K. L.; AghaKouchak, A.; Sorooshian, S.

    2017-12-01

    Precipitation prediction in dynamical weather and climate models depends on 1) the predictability of pressure or geopotential height for the forecasting period and 2) the successive work of interpreting the pressure field in terms of precipitation events. The later task is represented as parameterization schemes in numerical models, where detailed computing inevitably blurs the hidden cause-and-effect relationship in precipitation generation. The "big data" provided by numerical simulation, reanalysis and observation networks requires better causation analysis for people to digest and realize their use. While classic synoptical analysis methods are very-often insufficient for spatially distributed high dimensional data, a Convolutional Neural Network(CNN) is developed here to directly relate precipitation with circulation. Case study carried over west coast United States during boreal winter showed that CNN can locate and capture key pressure zones of different structures to project precipitation spatial distribution with high accuracy across hourly to monthly scales. This direct connection between atmospheric circulation and precipitation offers a probe for attributing precipitation to the coverage, location, intensity and spatial structure of characteristic pressure zones, which can be used for model diagnosis and improvement.

  13. Strontium stable isotope behaviour accompanying basalt weathering

    Science.gov (United States)

    Burton, K. W.; Parkinson, I. J.; Gíslason, S. G. R.

    2016-12-01

    The strontium (Sr) stable isotope composition of rivers is strongly controlled by the balance of carbonate to silicate weathering (Krabbenhöft et al. 2010; Pearce et al. 2015). However, rivers draining silicate catchments possess distinctly heavier Sr stable isotope values than their bedrock compositions, pointing to significant fractionation during weathering. Some have argued for preferential release of heavy Sr from primary phases during chemical weathering, others for the formation of secondary weathering minerals that incorporate light isotopes. This study presents high-precision double-spike Sr stable isotope data for soils, rivers, ground waters and estuarine waters from Iceland, reflecting both natural weathering and societal impacts on those environments. The bedrock in Iceland is dominantly basaltic, d88/86Sr ≈ +0.27, extending to lighter values for rhyolites. Geothermal waters range from basaltic Sr stable compositions to those akin to seawater. Soil pore waters reflect a balance of input from primary mineral weathering, precipitation and litter recycling and removal into secondary phases and vegetation. Rivers and ground waters possess a wide range of d88/86Sr compositions from +0.101 to +0.858. Elemental and isotope data indicate that this fractionation primarily results from the formation or dissolution of secondary zeolite (d88/86Sr ≈ +0.10), but also carbonate (d88/86Sr ≈ +0.22) and sometimes anhydrite (d88/86Sr ≈ -0.73), driving the residual waters to heavier or lighter values, respectively. Estuarine waters largely reflect mixing with seawater, but are also be affected by adsorption onto particulates, again driving water to heavy values. Overall, these data indicate that the stability and nature of secondary weathering phases, exerts a strong control on the Sr stable isotope composition of silicate rivers. [1] Krabbenhöft et al. (2010) Geochim. Cosmochim. Acta 74, 4097-4109. [2] Pearce et al. (2015) Geochim. Cosmochim. Acta 157, 125-146.

  14. static correction parameters in the lower flood plain of the central ...

    African Journals Online (AJOL)

    DJFLEX

    which can be used for stratigraphic interpretation. (Marsden, 1993). atum static correction requires that the velocity and thickness of the weathering layer be known for the accurate mapping of the underlying structures for oil and gas exploration. Analysis of the weathering layer properties can reveal how they vary vertically ...

  15. VHF signal power suppression in stratiform and convective precipitation

    Directory of Open Access Journals (Sweden)

    A. J. McDonald

    2006-03-01

    Full Text Available Previous studies have indicated that VHF clear-air radar return strengths are reduced during periods of precipitation. This study aims to examine whether the type of precipitation, stratiform and convective precipitation types are identified, has any impact on the relationships previously observed and to examine the possible mechanisms which produce this phenomenon. This study uses a combination of UHF and VHF wind-profiler data to define periods associated with stratiform and convective precipitation. This identification is achieved using an algorithm which examines the range squared corrected signal to noise ratio of the UHF returns for a bright band signature for stratiform precipitation. Regions associated with convective rainfall have been defined by identifying regions of enhanced range corrected signal to noise ratio that do not display a bright band structure and that are relatively uniform until a region above the melting layer. This study uses a total of 68 days, which incorporated significant periods of surface rainfall, between 31 August 2000 and 28 February 2002 inclusive from Aberystwyth (52.4° N, 4.1° W. Examination suggests that both precipitation types produce similar magnitude reductions in VHF signal power on average. However, the frequency of occurrence of statistically significant reductions in VHF signal power are very different. In the altitude range 2-4 km stratiform precipitation is related to VHF signal suppression approximately 50% of the time while in convective precipitation suppression is observed only 27% of the time. This statistical result suggests that evaporation, which occurs more often in stratiform precipitation, is important in reducing the small-scale irregularities in humidity and thereby the radio refractive index. A detailed case study presented also suggests that evaporation reducing small-scale irregularities in humidity may contribute to the observed VHF signal suppression.

  16. VHF signal power suppression in stratiform and convective precipitation

    Directory of Open Access Journals (Sweden)

    A. J. McDonald

    2006-03-01

    Full Text Available Previous studies have indicated that VHF clear-air radar return strengths are reduced during periods of precipitation. This study aims to examine whether the type of precipitation, stratiform and convective precipitation types are identified, has any impact on the relationships previously observed and to examine the possible mechanisms which produce this phenomenon. This study uses a combination of UHF and VHF wind-profiler data to define periods associated with stratiform and convective precipitation. This identification is achieved using an algorithm which examines the range squared corrected signal to noise ratio of the UHF returns for a bright band signature for stratiform precipitation. Regions associated with convective rainfall have been defined by identifying regions of enhanced range corrected signal to noise ratio that do not display a bright band structure and that are relatively uniform until a region above the melting layer.

    This study uses a total of 68 days, which incorporated significant periods of surface rainfall, between 31 August 2000 and 28 February 2002 inclusive from Aberystwyth (52.4° N, 4.1° W. Examination suggests that both precipitation types produce similar magnitude reductions in VHF signal power on average. However, the frequency of occurrence of statistically significant reductions in VHF signal power are very different. In the altitude range 2-4 km stratiform precipitation is related to VHF signal suppression approximately 50% of the time while in convective precipitation suppression is observed only 27% of the time. This statistical result suggests that evaporation, which occurs more often in stratiform precipitation, is important in reducing the small-scale irregularities in humidity and thereby the radio refractive index. A detailed case study presented also suggests that evaporation reducing small-scale irregularities in humidity may contribute to the observed VHF signal

  17. Intensity and duration of chemical weathering: An example from soil clays of the southeastern Koolau Mountains, Oahu, Hawaii

    Science.gov (United States)

    Johnsson, Mark J.; Ellen, Stephen D.; McKittrick, Mary Anne

    1993-01-01

    Orographic precipitation on the southern flank of the southeastern Koolau Mountains produces a pronounced precipitation gradient. The corresponding gradient in the intensity of the chemical weathering environment provides an opportunity to address the effects of varying chemical weathering intensity on the composition of clay-size weathering products in soils developed on basalt. In addition, little-modified remnants of the constructional surface of the Koolau Volcano, isolated by stream dissection, remain as facets on the southern ends of the parallel ridges of the study area. By comparing clay mineralogy of soils developed on these older geomorphic surfaces with those developed on the younger sharp-crested ridges and steep side slopes, the effects of weathering duration on clay mineralogy can also be addressed.Soil clays in this part of the Koolau Mountains are mineralogically complex; principal phases include smectite, kaolinite, and halloysite, but pure end member phases are uncommon. Rather, most phases contain some amount of mixed layering. Smectite may contain small (Volcano are markedly more leached than those from younger landscapes in the same precipitation regime. Although smectite may be present, kaolinite is the dominant phase, and accumulations of Fe and Ti occur in the uppermost soil levels. Enrichment of Zr and Ti in these soils, as compared to concentrations in the original basaltic parent material, indicates that as much as 75% of the parent material has been lost. Thus weathering duration may affect soil clay composition in the same way as weathering intensity.Because smectite and halloysite are expandable clay minerals, their presence in soils may decrease slope stability and influence the nature of slope processes. Soil avalanches occur on steep slopes throughout the study area, whereas slow-moving landslides appear to be restricted to gentler slopes in drier parts of the study area where smectite is abundant. The clay mineralogy of soils thus

  18. Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

    Science.gov (United States)

    Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

    2016-01-01

    Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

  19. Weathering rind formation in buried terrace cobbles during periods of up to 300ka

    International Nuclear Information System (INIS)

    Yoshida, H.; Metcalfe, R.; Nishimoto, S.; Yamamoto, H.; Katsuta, N.

    2011-01-01

    Highlights: → Weathering rinds in sandstone and basalt cobbles buried for up to 300 ka have been investigated. → The aim was to determine the formation process and elemental mass balances during rind development. → Elemental mass balances across the rinds were determined by using open system mass balance (τ i,j ) calculations. → The formation rates are slower than the tropical areas due to the lower rainfall in the studied area. - Abstract: Weathering rinds formed in Mesozoic sandstone and basalt cobbles buried in terrace deposits for up to 300 ka have been investigated. The aim was to determine the formation process and elemental mass balances during rind development. The ages of terraces distributed in the western part of Fukui prefecture, central Japan have been determined as 50 ka, 120 ka and 300 ka based on a tephro-stratigraphic method. Detailed investigations across the weathering rinds, consisting of microscopic observations, porosity measurements, and mineralogical and geochemical analyses using X-ray diffractometry (XRD), X-ray fluorescence (XRF), secondary X-ray analytical microscopy (SXAM), scanning electron microanalyser (SEM) and electron probe microanalysis (EPMA) have been carried out. The results revealed that the Fe concentrations in the weathering rind of a basalt cobble slightly decreased from the cobble's surface (rim) towards the unweathered core. In contrast, in a sandstone cobble formed under the same environmental conditions over the same period of time there is an Fe-rich layer at some distance below the cobble's surface. Elemental mass balances across the rinds were determined by using open system mass balance (τ i,j ) calculations and show that the Fe was precipitated as Fe-oxyhydroxides in the basalt cobbles, although Fe was slightly removed from the rims. In sandstone cobbles, on the other hand, Fe migrated along a Fe concentration gradient by diffusion and precipitated as Fe-oxyhydroxide minerals to form the weathering rinds

  20. Influence of weather variables and plant communities on grasshopper density in the Southern Pampas, Argentina.

    Science.gov (United States)

    de Wysiecki, María Laura; Arturi, Marcelo; Torrusio, Sandra; Cigliano, María Marta

    2011-01-01

    A study was conducted to evaluate the influence of weather (precipitation and temperature) and plant communities on grasshopper density over a 14-year period (1996-2009) in Benito Juárez County, Southern Pampas, Argentina. Total density strongly varied among plant communities. Highest values were registered in 2001 and 2003 in highly disturbed pastures and in 2002 and 2009 in halophilous grasslands. Native grasslands had the lowest density values. Seasonal precipitation and temperature had no significant effect on total grasshopper density. Dichroplus elongatus (Giglio-Tos) (Orthoptera: Acridoidea), Covasacris pallidinota (Bruner), Dichroplus pratensis Bruner, Scotussa lemniscata Stål, Borellia bruneri (Rehn) and Dichroplus maculipennis (Blanchard) comprised, on average, 64% of the grasshopper assemblages during low density years and 79% during high density years. Dichroplus elongatus, S. lemniscata and C. pallidinota were the most abundant species in 2001, 2002 and 2003, while D. elongatus, B. brunneri and C. pallidinota in 2009. Dichroplus elongatus and D. pratensis, mixed feeders species, were positively affected by summer rainfall. This suggests that the increase in summer precipitation had a positive effect on the quantity and quality forage production, affecting these grasshopper populations. Scotussa lemniscata and C. pallidinota were negatively affected by winter and fall temperature, possibly affecting the embryonic development before diapause and hatching. Dichroplus elongatus and D. pratensis were associated with highly disturbed pastures, S. lemniscata with pastures and B. bruneri and D. maculipennis with halophilous grasslands. Covasacris pallidinota was closely associated with halophilous grasslands and moderately disturbed pastures. Weather conditions changed over the years, with 2001, 2002 and 2003 having excessive rainfall while 2008 and 2009 were the driest years since the study started. We suggest that although seasonal precipitation and

  1. Variability of extreme weather events over the equatorial East Africa, a case study of rainfall in Kenya and Uganda

    Science.gov (United States)

    Ongoma, Victor; Chen, Haishan; Omony, George William

    2018-01-01

    This study investigates the variability of extreme rainfall events over East Africa (EA), using indices from the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis was based on observed daily rainfall from 23 weather stations, with length varying within 1961 and 2010. The indices considered are: wet days ( R ≥1 mm), annual total precipitation in wet days (PRCPTOT), simple daily intensity index (SDII), heavy precipitation days ( R ≥ 10 mm), very heavy precipitation days ( R ≥ 20 mm), and severe precipitation ( R ≥ 50 mm). The non-parametric Mann-Kendall statistical analysis was carried out to identify trends in the data. Temporal precipitation distribution was different from station to station. Almost all indices considered are decreasing with time. The analysis shows that the PRCPTOT, very heavy precipitation, and severe precipitation are generally declining insignificantly at 5 % significant level. The PRCPTOT is evidently decreasing over Arid and Semi-Arid Land (ASAL) as compared to other parts of EA. The number of days that recorded heavy rainfall is generally decreasing but starts to rise in the last decade although the changes are insignificant. Both PRCPTOT and heavy precipitation show a recovery in trend starting in the 1990s. The SDII shows a reduction in most areas, especially the in ASAL. The changes give a possible indication of the ongoing climate variability and change which modify the rainfall regime of EA. The results form a basis for further research, utilizing longer datasets over the entire region to reduce the generalizations made herein. Continuous monitoring of extreme events in EA is critical, given that rainfall is projected to increase in the twenty-first century.

  2. Global Precipitation Measurement (GPM) Mission Core Spacecraft Systems Engineering Challenges

    Science.gov (United States)

    Bundas, David J.; ONeill, Deborah; Field, Thomas; Meadows, Gary; Patterson, Peter

    2006-01-01

    The Global Precipitation Measurement (GPM) Mission is a collaboration between the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA), and other US and international partners, with the goal of monitoring the diurnal and seasonal variations in precipitation over the surface of the earth. These measurements will be used to improve current climate models and weather forecasting, and enable improved storm and flood warnings. This paper gives an overview of the mission architecture and addresses the status of some key trade studies, including the geolocation budgeting, design considerations for spacecraft charging, and design issues related to the mitigation of orbital debris.

  3. Weathering as the limiting factor of denudation in the Western escarpment of the Andes

    Science.gov (United States)

    Abbühl, L. M.; Schlunegger, F.; Kracht, O.; Ramseyer, K.; Rieke-Zapp, D.; Aldahan, A.; von Blanckenburg, F.

    2009-04-01

    A crucial issue in process geomorphology is the search for the scale and the extent to which precipitation, and climate in general, influences the nature and the rates of sediment transfer (weathering, erosion, sediment transport and deposition). We present an analysis of the possible interplay between precipitation, weathering and denudation rates for the western Andean slope between the Cordillera and the Pacific coast. It is based on morphometric studies and quantitative 10Be denudation rate estimates of three transverse river systems (Piura at 5°S, Pisco at 13°S, and Lluta at 18°S) draining the Western escarpment of the Peruvian and North Chilean Andes. The systems originate at elevations >3000 m above sea level, cover an area between 3000 and 10'000 km2 and discharge into the Pacific Ocean. The precipitation rate pattern implies a hyperarid climate at the coast, and semi-arid to semi-humid conditions in the Cordillera where the streams rise. There, climatic conditions are generally controlled by the easterlies that deliver moisture from the Atlantic Ocean via the low level Andean jet. The precipitation rate pattern of the Cordillera shows a North-South decreasing trend, from ca. 1000 mm/yr in Northern Peru to 150 mm/yr in Northern Chile. In these higher regions of the drainage basins, hillslopes are convex with nearly constant curvatures and are mantled by a >1 m thick regolith cover. In addition, hillslope erosion is limited to the regolith-bedrock interface. We interpret these geomorphic features to indicate weathering-controlled sediment discharge. In the lower river segments, beyond tectonic knickzones, regular precipitation is almost absent. For the case of the Piura river in Northern Peru, precipitation in this segment occurs in relation to highly episodic El Niño events related to the westerlies. This results in a supply-limited sediment discharge, leading to predominance of channelized processes on the hillslopes, a spare regolith cover and an

  4. Evaluation of a weather generator-based method for statistically downscaling non-stationary climate scenarios for impact assessment at a point scale

    Science.gov (United States)

    The non-stationarity is a major concern for statistically downscaling climate change scenarios for impact assessment. This study is to evaluate whether a statistical downscaling method is fully applicable to generate daily precipitation under non-stationary conditions in a wide range of climatic zo...

  5. Weather derivatives: Business hedge instrument from weather risks

    Directory of Open Access Journals (Sweden)

    Đorđević Bojan S.

    2014-01-01

    Full Text Available In the late 1990s, a new financial market was developed - a market for weather derivatives, so that the risk managers could hedge their exposure to weather risk. After a rather slow start, the weather derivatives market had started to grow rapidly. Risk managers could no longer blame poor financial results on the weather. Weather risk could now be removed by hedging procedure. This paper will explain briefly what the weather derivatives are and will point out at some of the motives for use of derivatives. Thereafter we will look at the history of the weather risk market, how the weather derivatives market has developed in recent years and also who are the current and potential players in the weather derivatives market.

  6. Fission track dating of authigenic quartz in red weathering crusts of carbonate rocks in Guizhou province

    International Nuclear Information System (INIS)

    Liu Xiuming; Wang Shijie; Zhang Feng

    2004-01-01

    The Cenozoic evolution history of Guizhou Province, which is located on the southeastern flank of the Qinghai-Tibet Plateau, is unclear because of the lack of sedimentation records. The red weathering crusts widespread on the Yunnan-Guizhou Plateau may bear critical information about their evolution history. This work firstly determined the ages of four red weathering crusts in eastern, central and northern Guizhou. The material used in fission track dating is well-crystallized quartz occurring in many in-situ weathering crusts of carbonate rocks. The results showed that the fission track ages of quartz vary over a wide range from 1 Ma to 25 Ma in the four profiles, significantly younger than the ages of Triassic and Cambrian parent rocks. In combination with the regionally geological evolution history during the period from 25 Ma to 1 Ma, the ages of quartz can exclude the possibility that the origin of quartz has nothing to do with primary clastic minerals in parent rocks, authigenesis during diagenesis and hydrothermal precipitation or replacement by volcanic activities. It is deduced that the well-crystallized quartz was precipitated from Si-rich weathering fluids during weathering processes of carbonate rocks. The recorded ages of quartz from the four profiles are consistent with the episodes of planation surfaces on the Qinghai-Tibet Plateau, the stages of red soil in the tropics of South China, the tectonically stable periods in Guizhou, and the ages of weathering in other parts of the world during the Cenozoic era. That is to say, the ages of authigenic quartz dated by the fission track method are well feasible and credible. (authors)

  7. Object-Based Assessment of Satellite Precipitation Products

    Directory of Open Access Journals (Sweden)

    Jingjing Li

    2016-06-01

    Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

  8. Producing Daily and Embedded Hourly Rainfall Data Using a Novel Weather Generator

    Directory of Open Access Journals (Sweden)

    Ching-Pin Tung

    2013-01-01

    Full Text Available The number of worldwide extreme drought and flood events has risen significantly in recent years. Many studies confer that climate change may cause more intensive and extreme events. Simulating the impact of climate change often requires weather data as inputs to assessment models. Stochastic weather generators have been developed to produce weather data with the same temporal resolution based on the outputs of GCMs. Reservoir simulation normally uses operational rules in daily and hourly time steps for water supply and flood reduction, respectively. Simulating consecutive drought and flood events simultaneously requires a weather generator to produce different temporal resolution data. This work develops a continuous weather generator to generate daily and hourly precipitation data for regular wet days and severe storms, respectively. Daily rainfall data is generated for regular wet days using Exponential distribution or Weibull distribution, while the total rainfall data for severe storms is generated using the Pearson type III or Log Pearson type III distribution. Moreover, hourly rainfall is determined based on generated hyetographs. Simulation results indicate that the proposed continuous weather generator can generate daily and hourly rainfall reasonably. The proposed weather generator is thus highly promising for use in evaluating how climate change impacts reservoir operations that are significantly influenced by more frequent and intensive consecutive drought and flood events.

  9. Interpolating precipitation and its relation to runoff and non-point source pollution.

    Science.gov (United States)

    Chang, Chia-Ling; Lo, Shang-Lien; Yu, Shaw-L

    2005-01-01

    When rainfall spatially varies, complete rainfall data for each region with different rainfall characteristics are very important. Numerous interpolation methods have been developed for estimating unknown spatial characteristics. However, no interpolation method is suitable for all circumstances. In this study, several methods, including the arithmetic average method, the Thiessen Polygons method, the traditional inverse distance method, and the modified inverse distance method, were used to interpolate precipitation. The modified inverse distance method considers not only horizontal distances but also differences between the elevations of the region with no rainfall records and of its surrounding rainfall stations. The results show that when the spatial variation of rainfall is strong, choosing a suitable interpolation method is very important. If the rainfall is uniform, the precipitation estimated using any interpolation method would be quite close to the actual precipitation. When rainfall is heavy in locations with high elevation, the rainfall changes with the elevation. In this situation, the modified inverse distance method is much more effective than any other method discussed herein for estimating the rainfall input for WinVAST to estimate runoff and non-point source pollution (NPSP). When the spatial variation of rainfall is random, regardless of the interpolation method used to yield rainfall input, the estimation errors of runoff and NPSP are large. Moreover, the relationship between the relative error of the predicted runoff and predicted pollutant loading of SS is high. However, the pollutant concentration is affected by both runoff and pollutant export, so the relationship between the relative error of the predicted runoff and the predicted pollutant concentration of SS may be unstable.

  10. Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

    Directory of Open Access Journals (Sweden)

    Bin Guo

    2016-03-01

    Full Text Available Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD. Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years and inter-decadal scale (quasi-12 and quasi-23 years. Moreover, the 2–3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements.

  11. Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition.

    Science.gov (United States)

    Guo, Bin; Chen, Zhongsheng; Guo, Jinyun; Liu, Feng; Chen, Chuanfa; Liu, Kangli

    2016-03-21

    Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960-2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD). Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years) and inter-decadal scale (quasi-12 and quasi-23 years). Moreover, the 2-3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements.

  12. The Fluvial Geochemistry of the Rivers of Eastern Siberia and Implications for the Effect of Climate on Weathering

    National Research Council Canada - National Science Library

    Huh, Youngsook

    1998-01-01

    The dependence of weathering on climate (temperature and precipitation) forms the core of a negative feedback proposed to have maintained the Earth's atmospheric CO2 within habitable limits for most of...

  13. Chemical weathering as a mechanism for the climatic control of bedrock river incision

    Science.gov (United States)

    Murphy, Brendan P.; Johnson, Joel P. L.; Gasparini, Nicole M.; Sklar, Leonard S.

    2016-04-01

    Feedbacks between climate, erosion and tectonics influence the rates of chemical weathering reactions, which can consume atmospheric CO2 and modulate global climate. However, quantitative predictions for the coupling of these feedbacks are limited because the specific mechanisms by which climate controls erosion are poorly understood. Here we show that climate-dependent chemical weathering controls the erodibility of bedrock-floored rivers across a rainfall gradient on the Big Island of Hawai‘i. Field data demonstrate that the physical strength of bedrock in streambeds varies with the degree of chemical weathering, which increases systematically with local rainfall rate. We find that incorporating the quantified relationships between local rainfall and erodibility into a commonly used river incision model is necessary to predict the rates and patterns of downcutting of these rivers. In contrast to using only precipitation-dependent river discharge to explain the climatic control of bedrock river incision, the mechanism of chemical weathering can explain strong coupling between local climate and river incision.

  14. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Directory of Open Access Journals (Sweden)

    Y. Zhang

    2018-01-01

    Full Text Available Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS values of up to 0.5 and 33 %, respectively. The general skill (after bias correction of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  15. Radar-based summer precipitation climatology of the Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Bližňák, Vojtěch; Kašpar, Marek; Müller, Miloslav

    2018-01-01

    Roč. 38, č. 2 (2018), s. 677-691 ISSN 0899-8418 R&D Projects: GA ČR GA17-23773S; GA MZe QJ1520265 Institutional support: RVO:68378289 Keywords : weather radar * rain gauges * adjustment * precipitation climatology * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 3.760, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/joc.5202/full

  16. Assimilating Non-linear Effects of Customized Large-Scale Climate Predictors on Downscaled Precipitation over the Tropical Andes

    Science.gov (United States)

    Molina, J. M.; Zaitchik, B. F.

    2016-12-01

    Recent findings considering high CO2 emission scenarios (RCP8.5) suggest that the tropical Andes may experience a massive warming and a significant precipitation increase (decrease) during the wet (dry) seasons by the end of the 21st century. Variations on rainfall-streamflow relationships and seasonal crop yields significantly affect human development in this region and make local communities highly vulnerable to climate change and variability. We developed an expert-informed empirical statistical downscaling (ESD) algorithm to explore and construct robust global climate predictors to perform skillful RCP8.5 projections of in-situ March-May (MAM) precipitation required for impact modeling and adaptation studies. We applied our framework to a topographically-complex region of the Colombian Andes where a number of previous studies have reported El Niño-Southern Oscillation (ENSO) as the main driver of climate variability. Supervised machine learning algorithms were trained with customized and bias-corrected predictors from NCEP reanalysis, and a cross-validation approach was implemented to assess both predictive skill and model selection. We found weak and not significant teleconnections between precipitation and lagged seasonal surface temperatures over El Niño3.4 domain, which suggests that ENSO fails to explain MAM rainfall variability in the study region. In contrast, series of Sea Level Pressure (SLP) over American Samoa -likely associated with the South Pacific Convergence Zone (SPCZ)- explains more than 65% of the precipitation variance. The best prediction skill was obtained with Selected Generalized Additive Models (SGAM) given their ability to capture linear/nonlinear relationships present in the data. While SPCZ-related series exhibited a positive linear effect in the rainfall response, SLP predictors in the north Atlantic and central equatorial Pacific showed nonlinear effects. A multimodel (MIROC, CanESM2 and CCSM) ensemble of ESD projections revealed

  17. Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

    Science.gov (United States)

    Schroeer, K.; Kirchengast, G.

    2018-06-01

    Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.

  18. Walker Branch Throughfall Displacement Experiment Data Report: Site Characterization, System Performance, Weather, Species Composition, and Growth

    Energy Technology Data Exchange (ETDEWEB)

    Hanson, P.J.

    2001-09-04

    This numeric data package provides data sets, and accompanying documentation, on site characterization, system performance, weather, species composition, and growth for the Throughfall Displacement Experiment, which was established in the Walker Branch Watershed of East Tennessee to provide data on the responses of forests to altered precipitation regimes. The specific data sets include soil water content and potential, coarse fraction of the soil profile, litter layer temperature, soil temperature, monthly weather, daily weather, hourly weather, species composition of trees and saplings, mature tree and sapling annual growth, and relative leaf area index. Fortran and SAS{trademark} access codes are provided to read the ASCII data files. The data files and this documentation are available without charge on a variety of media and via the Internet from the Carbon Dioxide Information Analysis Center (CDIAC).

  19. Opportunities and challenges for evaluating precipitation estimates during GPM mission

    Energy Technology Data Exchange (ETDEWEB)

    Amitai, E. [George Mason Univ. and NASA Goddard Space Flight Center, Greenbelt, MD (United States); NASA Goddard Space Flight Center, Greenbelt, MD (United States); Llort, X.; Sempere-Torres, D. [GRAHI/Univ. Politecnica de Catalunya, Barcelona (Spain)

    2006-10-15

    Data assimilation in conjunction with numerical weather prediction and a variety of hydrologic applications now depend on satellite observations of precipitation. However, providing values of precipitation is not sufficient unless they are accompanied by the associated uncertainty estimates. The main approach of quantifying satellite precipitation uncertainties generally requires establishment of reliable uncertainty estimates for the ground validation rainfall products. This paper discusses several of the relevant validation concepts evolving from the tropical rainfall measuring mission (TRMM) era to the global precipitation measurement mission (GPM) era in the context of determining and reducing uncertainties of ground and space-based radar rainfall estimates. From comparisons of probability distribution functions of rain rates derived from TRMM precipitation radar and co-located ground based radar data - using the new NASA TRMM radar rainfall products (version 6) - this paper provides (1) a brief review of the importance of comparing pdfs of rain rate for statistical and physical verification of space-borne radar estimates of precipitation; (2) a brief review of how well the ground validation estimates compare to the TRMM radar retrieved estimates; and (3) discussion on opportunities and challenges to determine and reduce the uncertainties in space-based and ground-based radar estimates of rain rate distributions. (orig.)

  20. 76 FR 39343 - New Markets Tax Credit Non-Real Estate Investments; Correction

    Science.gov (United States)

    2011-07-06

    ... DEPARTMENT OF THE TREASURY Internal Revenue Service 26 CFR Part 1 [REG-101826-11] RIN 1545-BK04 New Markets Tax Credit Non-Real Estate Investments; Correction AGENCY: Internal Revenue Service (IRS... Tuesday, June 7, 2011 (76 FR 32882) modifying the new markets tax credit program to facilitate and...

  1. New Approach To Hour-By-Hour Weather Forecast

    Science.gov (United States)

    Liao, Q. Q.; Wang, B.

    2017-12-01

    Fine hourly forecast in single station weather forecast is required in many human production and life application situations. Most previous MOS (Model Output Statistics) which used a linear regression model are hard to solve nonlinear natures of the weather prediction and forecast accuracy has not been sufficient at high temporal resolution. This study is to predict the future meteorological elements including temperature, precipitation, relative humidity and wind speed in a local region over a relatively short period of time at hourly level. By means of hour-to-hour NWP (Numeral Weather Prediction)meteorological field from Forcastio (https://darksky.net/dev/docs/forecast) and real-time instrumental observation including 29 stations in Yunnan and 3 stations in Tianjin of China from June to October 2016, predictions are made of the 24-hour hour-by-hour ahead. This study presents an ensemble approach to combine the information of instrumental observation itself and NWP. Use autoregressive-moving-average (ARMA) model to predict future values of the observation time series. Put newest NWP products into the equations derived from the multiple linear regression MOS technique. Handle residual series of MOS outputs with autoregressive (AR) model for the linear property presented in time series. Due to the complexity of non-linear property of atmospheric flow, support vector machine (SVM) is also introduced . Therefore basic data quality control and cross validation makes it able to optimize the model function parameters , and do 24 hours ahead residual reduction with AR/SVM model. Results show that AR model technique is better than corresponding multi-variant MOS regression method especially at the early 4 hours when the predictor is temperature. MOS-AR combined model which is comparable to MOS-SVM model outperform than MOS. Both of their root mean square error and correlation coefficients for 2 m temperature are reduced to 1.6 degree Celsius and 0.91 respectively. The

  2. Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

    Science.gov (United States)

    Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

    2016-04-01

    Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

  3. Statistically extrapolated nowcasting of summertime precipitation over the Eastern Alps

    Science.gov (United States)

    Chen, Min; Bica, Benedikt; Tüchler, Lukas; Kann, Alexander; Wang, Yong

    2017-07-01

    This paper presents a new multiple linear regression (MLR) approach to updating the hourly, extrapolated precipitation forecasts generated by the INCA (Integrated Nowcasting through Comprehensive Analysis) system for the Eastern Alps. The generalized form of the model approximates the updated precipitation forecast as a linear response to combinations of predictors selected through a backward elimination algorithm from a pool of predictors. The predictors comprise the raw output of the extrapolated precipitation forecast, the latest radar observations, the convective analysis, and the precipitation analysis. For every MLR model, bias and distribution correction procedures are designed to further correct the systematic regression errors. Applications of the MLR models to a verification dataset containing two months of qualified samples, and to one-month gridded data, are performed and evaluated. Generally, MLR yields slight, but definite, improvements in the intensity accuracy of forecasts during the late evening to morning period, and significantly improves the forecasts for large thresholds. The structure-amplitude-location scores, used to evaluate the performance of the MLR approach, based on its simulation of morphological features, indicate that MLR typically reduces the overestimation of amplitudes and generates similar horizontal structures in precipitation patterns and slightly degraded location forecasts, when compared with the extrapolated nowcasting.

  4. What is a Proper Resolution of Weather Radar Precipitation Estimates for Urban Drainage Modelling?

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Rasmussen, Michael R.; Thorndahl, Søren Liedtke

    2012-01-01

    The resolution of distributed rainfall input for drainage models is the topic of this paper. The study is based on data from high resolution X-band weather radar used together with an urban drainage model of a medium size Danish village. The flow, total run-off volume and CSO volume are evaluated...

  5. Computation of rainfall erosivity from daily precipitation amounts.

    Science.gov (United States)

    Beguería, Santiago; Serrano-Notivoli, Roberto; Tomas-Burguera, Miquel

    2018-10-01

    Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. NOAA's Strategy to Improve Operational Weather Prediction Outlooks at Subseasonal Time Range

    Science.gov (United States)

    Schneider, T.; Toepfer, F.; Stajner, I.; DeWitt, D.

    2017-12-01

    NOAA is planning to extend operational global numerical weather prediction to sub-seasonal time range under the auspices of its Next Generation Global Prediction System (NGGPS) and Extended Range Outlook Programs. A unification of numerical prediction capabilities for weather and subseasonal to seasonal (S2S) timescales is underway at NOAA using the Finite Volume Cubed Sphere (FV3) dynamical core as the basis for the emerging unified system. This presentation will overview NOAA's strategic planning and current activities to improve prediction at S2S time-scales that are ongoing in response to the Weather Research and Forecasting Innovation Act of 2017, Section 201. Over the short-term, NOAA seeks to improve the operational capability through improvements to its ensemble forecast system to extend its range to 30 days using the new FV3 Global Forecast System model, and by using this system to provide reforecast and re-analyses. In parallel, work is ongoing to improve NOAA's operational product suite for 30 day outlooks for temperature, precipitation and extreme weather phenomena.

  7. A space and time scale-dependent nonlinear geostatistical approach for downscaling daily precipitation and temperature

    KAUST Repository

    Jha, Sanjeev Kumar; Mariethoz, Gregoire; Evans, Jason; McCabe, Matthew; Sharma, Ashish

    2015-01-01

    precipitation and daily temperature over several years. Here, the training image consists of daily rainfall and temperature outputs from the Weather Research and Forecasting (WRF) model at 50 km and 10 km resolution for a twenty year period ranging from 1985

  8. Non perturbative method for radiative corrections applied to lepton-proton scattering

    International Nuclear Information System (INIS)

    Chahine, C.

    1979-01-01

    We present a new, non perturbative method to effect radiative corrections in lepton (electron or muon)-nucleon scattering, useful for existing or planned experiments. This method relies on a spectral function derived in a previous paper, which takes into account both real soft photons and virtual ones and hence is free from infrared divergence. Hard effects are computed perturbatively and then included in the form of 'hard factors' in the non peturbative soft formulas. Practical computations are effected using the Gauss-Jacobi integration method which reduce the relevant integrals to a rapidly converging sequence. For the simple problem of the radiative quasi-elastic peak, we get an exponentiated form conjectured by Schwinger and found by Yennie, Frautschi and Suura. We compare also our results with the peaking approximation, which we derive independantly, and with the exact one-photon emission formula of Mo and Tsai. Applications of our method to the continuous spectrum include the radiative tail of the Δ 33 resonance in e + p scattering and radiative corrections to the Feynman scale invariant F 2 structure function for the kinematics of two recent high energy muon experiments

  9. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

    Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

  10. Innovative precipitation in emulsion process: toward a non-nuclear industrial application

    International Nuclear Information System (INIS)

    Ollivier, M.; Borda, G.; Charton, S.; Flouret, J.

    2016-01-01

    A precipitation in emulsion process has been proposed by Borda et al. in 2008 for the continuous precipitation of lanthanides or actinides as oxalate, in order to either increase the production capacity or allow the precipitation of long-life radioactive elements under optimum safety conditions. During research/development tests, a strong correlation between the emulsion's properties and those of the particles produced have been evidenced, thus enabling the size and morphology of the powder to be tuned by varying the droplets properties, the latter being controlled by the column operating conditions. This process thus appears as an attractive alternative to conventional processes for the synthesis of high-value precipitates; as it offers interesting intensification capabilities. In this context, the feasibility of the precipitation of bismuth subnitrate (BSN), for which the emulsion route for precipitation seems to be particularly attractive, has been studied. Indeed, the division of the reacting volume into droplets may allow efficient temperature regulation of the exothermic reaction. In addition, an improvement of the product appearance is expected. This first phase of the feasibility study focused on the choice of the organic phase and the sensitivity of the droplets and solid particles properties to the operating conditions. Following the encouraging results observed in stirred-tank reactor, we successfully tested the implementation in a pulsed column, at lab-scale. (authors)

  11. Innovative precipitation in emulsion process: toward a non-nuclear industrial application

    Energy Technology Data Exchange (ETDEWEB)

    Ollivier, M.; Borda, G.; Charton, S. [CEA, Centre de Marcoule, DEN,DTEC,SGCS, F-30207 Bagnols-sur-Ceze (France); Flouret, J. [OCM, ZI Quai Jean Jaures, 197 Avenue Marie Curie, 07800 La Voulte-sur-Rhone (France)

    2016-07-01

    A precipitation in emulsion process has been proposed by Borda et al. in 2008 for the continuous precipitation of lanthanides or actinides as oxalate, in order to either increase the production capacity or allow the precipitation of long-life radioactive elements under optimum safety conditions. During research/development tests, a strong correlation between the emulsion's properties and those of the particles produced have been evidenced, thus enabling the size and morphology of the powder to be tuned by varying the droplets properties, the latter being controlled by the column operating conditions. This process thus appears as an attractive alternative to conventional processes for the synthesis of high-value precipitates; as it offers interesting intensification capabilities. In this context, the feasibility of the precipitation of bismuth subnitrate (BSN), for which the emulsion route for precipitation seems to be particularly attractive, has been studied. Indeed, the division of the reacting volume into droplets may allow efficient temperature regulation of the exothermic reaction. In addition, an improvement of the product appearance is expected. This first phase of the feasibility study focused on the choice of the organic phase and the sensitivity of the droplets and solid particles properties to the operating conditions. Following the encouraging results observed in stirred-tank reactor, we successfully tested the implementation in a pulsed column, at lab-scale. (authors)

  12. A generalised chemical precipitation modelling approach in wastewater treatment applied to calcite

    DEFF Research Database (Denmark)

    Mbamba, Christian Kazadi; Batstone, Damien J.; Flores Alsina, Xavier

    2015-01-01

    , the present study aims to identify a broadly applicable precipitation modelling approach. The study uses two experimental platforms applied to calcite precipitating from synthetic aqueous solutions to identify and validate the model approach. Firstly, dynamic pH titration tests are performed to define...... an Arrhenius-style correction of kcryst. The influence of magnesium (a common and representative added impurity) on kcryst was found to be significant but was considered an optional correction because of a lesser influence as compared to that of temperature. Other variables such as ionic strength and pH were...

  13. Chemical Alteration of Soils on Earth as a Function of Precipitation: Insights Into Weathering Processes Relevant to Mars

    Science.gov (United States)

    Amundson, R.; Chadwick, O.; Ewing, S.; Sutter, B.; Owen, J.; McKay, C.

    2004-12-01

    Soils lie at the interface of the atmosphere and lithosphere, and the rates of chemical and physical processes that form them hinge on the availability of water. Here we quantify the effect of these processes on soil volume and mass in different rainfall regimes. We then use the results of this synthesis to compare with the growing chemical dataset for soils on Mars in order to identify moisture regimes on Earth that may provide crude analogues for past Martian weathering conditions. In this synthesis, the rates of elemental gains/losses, and corresponding volumetric changes, were compared for soils in nine soil chronosequences (sequences of soils of differing ages) - sequences formed in climates ranging from ~1 to ~4500 mm mean annual precipitation (MAP). Total elemental chemistry of soils and parent materials were determined via XRF, ICP-MS, and/or ICP-OES, and the absolute elemental gains or losses (and volume changes) were determined by normalizing data to an immobile index element. For the chronosequences examined, the initial stages of soil formation (103^ to 104^ yr), regardless of climate, generally show volumetric expansion due to (1) reduction in bulk density by biological/physical turbation, (2) addition of organic matter, (3) accumulation of water during clay mineral synthesis, and/or (4) accumulation of atmospheric salts and dust. Despite large differences in parent materials (basalt, sandstone, granitic alluvium), there was a systematic relationship between long-term (105^ to 106^ yr) volumetric change and rainfall, with an approximate cross-over point between net expansion (and accumulation of atmospheric solutes and dust) and net collapse (net losses of Si, Al, and alkaline earths and alkali metals) between approximately 20 and 100 mm MAP. Recently published geochemical data of soils at Gusev Crater (Gellert et al. 2004. Science 305:829), when normalized to Ti, show apparent net losses of Si and Al that range between 5 and 50% of values relative to

  14. Spatio-temporal variability of several eco-precipitation indicators in China

    Science.gov (United States)

    Guo, B. B.; Zhang, J.; Wang, F.

    2016-12-01

    Climate change is expected to have large impacts on the eco-hydrological processes. Precipitation as one of the most important meteorological factors is a significant parameter in ecohydrology. Many studies and precipitation indexes focused on the long-term precipitation variability have been put forward. However, these former studies did not consider the vegetation response and these indexes could not reflect it efficiently. Eco-precipitation indicators reflecting the features and patterns of precipitations and serving as significant input parameters of eco-hydrological models are of paramount significance to the studies of these models. Therefore we proposed 4 important eco-precipitation indicators—Precipitation Variability Index (PVI), Precipitation Occurrence Rate (λ), Mean Precipitation Depth (1/θ) and Annual Precipitation (AP). The PVI index depicts the precipitation variability with a value of zero for perfectly uniform and increases as precipitation events become more sporadic. The λ, 1/θ and AP depict the precipitation frequency, intensity and annual amount, respectively. With large precipitation and vegetation discrepancies, China is selected as a study area. Firstly, these indicators are calculated separately with 55-years (1961-2015) daily precipitation time-series from 693 weather stations in China. Then, the temporal trend is analyzed through Mann-Kendall (MK) test and parametric t-test in annual time scale. Furthermore, the spatial distribution is analyzed through the spatial interpolation tools ANUsplin. The result shows that: (1) 1/θ increased significantly (4.59cm/10yr) while λ decreased significantly (1.54 days/10yr), which means there is an increasing trend of extreme precipitation events; (2)there is a significant downward trend of PVI, which means the rhythm of precipitation has a uniform and concentrated trend; (3) AP increased insignificantly (0.57mm/10yr); and (4)the MK test of these indicators shows that there is saltation of

  15. Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA

    Directory of Open Access Journals (Sweden)

    Haramis Linn

    2010-03-01

    Full Text Available Abstract Background Models of the effects of environmental factors on West Nile virus disease risk have yielded conflicting outcomes. The role of precipitation has been especially difficult to discern from existing studies, due in part to habitat and behavior characteristics of specific vector species and because of differences in the temporal and spatial scales of the published studies. We used spatial and statistical modeling techniques to analyze and forecast fine scale spatial (2000 m grid and temporal (weekly patterns of West Nile virus mosquito infection relative to changing weather conditions in the urban landscape of the greater Chicago, Illinois, region for the years from 2004 to 2008. Results Increased air temperature was the strongest temporal predictor of increased infection in Culex pipiens and Culex restuans mosquitoes, with cumulative high temperature differences being a key factor distinguishing years with higher mosquito infection and higher human illness rates from those with lower rates. Drier conditions in the spring followed by wetter conditions just prior to an increase in infection were factors in some but not all years. Overall, 80% of the weekly variation in mosquito infection was explained by prior weather conditions. Spatially, lower precipitation was the most important variable predicting stronger mosquito infection; precipitation and temperature alone could explain the pattern of spatial variability better than could other environmental variables (79% explained in the best model. Variables related to impervious surfaces and elevation differences were of modest importance in the spatial model. Conclusion Finely grained temporal and spatial patterns of precipitation and air temperature have a consistent and significant impact on the timing and location of increased mosquito infection in the northeastern Illinois study area. The use of local weather data at multiple monitoring locations and the integration of mosquito

  16. Correction of experimental photon pencil-beams for the effects of non-uniform and non-parallel measurement conditions

    International Nuclear Information System (INIS)

    Ceberg, Crister P.; Bjaerngard, Bengt E.

    1995-01-01

    An approximate experimental determination of photon pencil-beams can be based on the reciprocity theorem. The scatter part of the pencil-beam is then essentially the derivative with respect to the field radius of measured scatter-to-primary ratios in circular fields. Obtained in this way, however, the pencil-beam implicitly carries the influence from the lateral fluence and beam quality variations of the incident photons, as well as the effects of the divergence of the beam. In this work we show how these effects can be corrected for. The procedure was to calculate scatter-to-primary ratios using an analytical expression for the pencil-beam. By disregarding one by one the effects of the divergence and the fluence and beam quality variations, the influence of these effects were separated and quantified. For instance, for a 6 MV beam of 20x20 cm 2 field size, at 20 cm depth and a source distance of 100 cm, the total effect was 3.9%; 2.0% was due to the non-uniform incident profile, 1.0% due to the non-uniform beam quality, and 0.9% due to the divergence of the beam. At a source distance of 400 cm, all these effects were much lower, adding up to a total of 0.3 %. Using calculated correction factors like these, measured scatter-to-primary ratios were then stripped from the effects of non-uniform and non-parallel measurement conditions, and the scatter part of the pencil-beam was determined using the reciprocity theorem without approximations

  17. High resolution forecast of heavy precipitation with Lokal Modell: analysis of two case studies in the Alpine area

    Directory of Open Access Journals (Sweden)

    M. Elementi

    2005-01-01

    Full Text Available Northern Italy is frequently affected by severe precipitation conditions often inducing flood events with associated loss of properties, damages and casualties. The capability of correctly forecast these events, strongly required for an efficient support to civil protection actions, is still nowadays a challenge. This difficulty is also related with the complex structure of the precipitation field in the Alpine area and, more generally, over the Italian territory. Recently a new generation of non-hydrostatic meteorological models, suitable to be used at very high spatial resolution, has been developed. In this paper the performance of the non-hydrostatic Lokal Modell developed by the COSMO Consortium, is analysed with regard to a couple of intense precipitation events occurred in the Piemonte region in Northern Italy. These events were selected among the reference cases of the Hydroptimet/INTERREG IIIB project. LM run at the operational resolution of 7km provides a good forecast of the general rain structure, with an unsatisfactory representation of the precipitation distribution across the mountain ranges. It is shown that the inclusion of the new prognostic equations for cloud ice, rain and snow produces a remarkable improvement, reducing the precipitation in the upwind side and extending the intense rainfall area to the downwind side. The unrealistic maxima are decreased towards observed values. The use of very high horizontal resolution (2.8 km improves the general shape of the precipitation field in the flat area of the Piemonte region but, keeping active the moist convection scheme, sparse and more intense rainfall peaks are produced. When convective precipitation is not parametrised but explicitly represented by the model, this negative effect is removed.

  18. Precipitation observations for operational flood forecasting in Scotland: Data availability, limitations and the impact of observational uncertainty

    Science.gov (United States)

    Parry, Louise; Neely, Ryan, III; Bennett, Lindsay; Collier, Chris; Dufton, David

    2017-04-01

    The Scottish Environment Protection Agency (SEPA) has a statutory responsibility to provide flood warning across Scotland. It achieves this through an operational partnership with the UK Met Office wherein meteorological forecasts are applied to a national distributed hydrological model, Grid- to- Grid (G2G), and catchment specific lumped PDM models. Both of these model types rely on observed precipitation input for model development and calibration, and operationally for historical runs to generate initial conditions. Scotland has an average annual precipitation of 1430mm per annum (1971-2000), but the spatial variability in totals is high, predominantly in relation to the topography and prevailing winds, which poses different challenges to both radar and point measurement methods of observation. In addition, the high elevations mean that in winter a significant proportion of precipitation falls as snow. For the operational forecasting models, observed rainfall data is provided in Near Real Time (NRT) from SEPA's network of approximately 260 telemetered TBR gauges and 4 UK Met Office C-band radars. Both data sources have their strengths and weaknesses, particularly in relation to the orography and spatial representativeness, but estimates of rainfall from the two methods can vary greatly. Northern Scotland, particularly near Inverness, is a comparatively sparse part of the radar network. Rainfall totals and distribution in this area are determined by the Northern Western Highlands and Cairngorms mountain ranges, which also have a negative impact on radar observations. In recognition of this issue, the NCAS mobile X-band weather radar (MXWR) was deployed in this area between February and August 2016. This study presents a comparison of rainfall estimates for the Inverness and Moray Firth region generated from the operational radar network, the TBR network, and the MXWR. Quantitative precipitation estimates (QPEs) from both sources of radar data were compared to

  19. Pulmonary Blastomycosis in Vilas County, Wisconsin: Weather, Exposures and Symptoms

    Directory of Open Access Journals (Sweden)

    Dennis J. Baumgardner

    2015-01-01

    Full Text Available Purpose: Blastomycosis is a serious fungal infection contracted by inhalation of Blastomyces spores from the environment. Case occurrence in dogs in Vilas County, Wisconsin, has been associated with antecedent weather. We aimed to explore the effects of weather on the occurrence of human pulmonary blastomycosis in this area, and update exposure factors and symptoms since last published reports. Methods: Mandatory case reports were reviewed. Chi-square test was used for categorical data of exposures, comparing 1979–1996 (n=101 versus 1997–June 2013 (n=95. Linear regression was used to model local weather data (available 1990–2013; n=126; Southern Oscillation Index (SOI, North Atlantic Oscillation Index (NAOI, and Wisconsin River water discharge (WRD from the adjacent county (all available for 1984–2013; n=174; and case counts of known onset by warm (April–September and cold (October–March 6-month periods. Results: Distribution of pulmonary blastomycosis cases did not vary by season. Environmental exposures for the 1997–June 2013 group (mean age 45, 59% male were: residence(76%, excavation (42% and gardening (31%, all similar to the 1979–1996 group. Fishing (23% vs. 37%; P=0.09 and hunting (15% vs. 26%; P=0.13 exposures were less common in 1997–June 2013, but not significantly different. Overall, 69% of cases recalled some prior soil-disturbing activities. Considering the 6-month warm/cold periods, 19% of variation is explained by a direct relationship with total precipitation from two periods prior (P=0.005. There was no association of case occurrence with SOI, NAOI or WRD. Estimated annual incidence of blastomycosis for 1997–June 2013 was 27/100,000 compared with 44/100,000 for 1984–1996. Several symptoms were significantly less frequent in 2002–June 2013 compared to earlier years. Conclusions: As with dogs, human pulmonary blastomycosis occurrence is partially determined by antecedent precipitation. It is unclear if

  20. A novel scene-based non-uniformity correction method for SWIR push-broom hyperspectral sensors

    Science.gov (United States)

    Hu, Bin-Lin; Hao, Shi-Jing; Sun, De-Xin; Liu, Yin-Nian

    2017-09-01

    A novel scene-based non-uniformity correction (NUC) method for short-wavelength infrared (SWIR) push-broom hyperspectral sensors is proposed and evaluated. This method relies on the assumption that for each band there will be ground objects with similar reflectance to form uniform regions when a sufficient number of scanning lines are acquired. The uniform regions are extracted automatically through a sorting algorithm, and are used to compute the corresponding NUC coefficients. SWIR hyperspectral data from airborne experiment are used to verify and evaluate the proposed method, and results show that stripes in the scenes have been well corrected without any significant information loss, and the non-uniformity is less than 0.5%. In addition, the proposed method is compared to two other regular methods, and they are evaluated based on their adaptability to the various scenes, non-uniformity, roughness and spectral fidelity. It turns out that the proposed method shows strong adaptability, high accuracy and efficiency.

  1. Extreme weather-year sequences have nonadditive effects on environmental nitrogen losses.

    Science.gov (United States)

    Iqbal, Javed; Necpalova, Magdalena; Archontoulis, Sotirios V; Anex, Robert P; Bourguignon, Marie; Herzmann, Daryl; Mitchell, David C; Sawyer, John E; Zhu, Qing; Castellano, Michael J

    2018-01-01

    The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, the sequence of extreme weather years (e.g., wet-dry vs. dry-wet) may affect cumulative N losses. We calibrated and validated the DAYCENT ecosystem process model with a comprehensive set of biogeophysical measurements from a corn-soybean rotation managed at three N fertilizer inputs with and without a winter cover crop in Iowa, USA. Our objectives were to determine: (i) how 2-year sequences of extreme weather affect 2-year cumulative N losses across the crop rotation, and (ii) if N fertilizer management and the inclusion of a winter cover crop between corn and soybean mitigate the effect of extreme weather on N losses. Using historical weather (1951-2013), we created nine 2-year scenarios with all possible combinations of the driest ("dry"), wettest ("wet"), and average ("normal") weather years. We analyzed the effects of these scenarios following several consecutive years of relatively normal weather. Compared with the normal-normal 2-year weather scenario, 2-year extreme weather scenarios affected 2-year cumulative NO 3 - leaching (range: -93 to +290%) more than N 2 O emissions (range: -49 to +18%). The 2-year weather scenarios had nonadditive effects on N losses: compared with the normal-normal scenario, the dry-wet sequence decreased 2-year cumulative N 2 O emissions while the wet-dry sequence increased 2-year cumulative N 2 O emissions. Although dry weather decreased NO 3 - leaching and N 2 O emissions in isolation, 2-year cumulative N losses from the wet-dry scenario were greater than the dry-wet scenario. Cover crops reduced the effects of extreme weather on NO 3 - leaching but had a lesser effect on N 2 O emissions. As the frequency of extreme weather is expected to increase, these data suggest that the sequence of interannual weather

  2. The relevance and legibility of radio/TV weather reports to the Austrian public

    Science.gov (United States)

    Keul, A. G.; Holzer, A. M.

    2013-03-01

    The communicative quality of media weather reports, especially warnings, can be evaluated by user research. It is an interdisciplinary field, still uncoordinated after 35 years. The authors suggest to shift from a cognitive learning model to news processing, qualitative discourse and usability models as the media audience is in an edutainment situation where it acts highly selective. A series of field surveys 2008-2011 tested the relevance and legibility of Austrian radio and television weather reports on fair weather and in warning situations. 247 laypeople heard/saw original, mostly up-to-date radio/TV weather reports and recalled personally relevant data. Also, a questionnaire on weather knowledge was answered by 237 Austrians. Several research hypotheses were tested. The main results were (a) a relatively high level of meteorological knowledge of the general population, with interest and participation of German-speaking migrants, (b) a pluralistic media usage with TV, radio and internet as the leading media, (c) higher interest and attention (also for local weather) after warnings, but a risk of more false recalls after long warnings, (d) more recall problems with radio messages and a wish that the weather elements should always appear in the same order to faciliate processing for the audience. In their narrow time windows, radio/TV weather reports should concentrate on main features (synoptic situation, tomorrow's temperature and precipitation, possible warnings), keep a verbal “speed limit” and restrict show elements to serve the active, selective, multioptional, multicultural audience.

  3. Improving Weather Radar Precipitation Estimates by Combining two Types of Radars

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2014-01-01

    This paper presents a demonstration of how Local Area Weather Radar (LAWR) X-band measurements can be combined with meteorological C–band measurements into a single radar product. For this purpose, a blending method has been developed which combines the strengths of the two radar systems. Combining...... the two radar types achieves a radar product with both long range and high temporal resolution. It is validated that the blended radar product performs better than the individual radars based on ground observations from laser disdrometers. However, the data combination is challenged by lower performance...... of the LAWR. Although both radars benefits from the data combination, it is also found that advection based temporal interpolation is a more favourable method for increasing the temporal resolution of meteorological C–band measurements....

  4. Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

    Science.gov (United States)

    Besha, A. A.; Steele, C. M.; Fernald, A.

    2014-12-01

    Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

  5. Effect of urbanization on the winter precipitation distribution in Beijing area

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    According to the urbanization extent of Beijing area, and with 1980 as a turning point, the duration from 1961 to 2000 is divided into two periods: one is defined as the slow urbanization period from 1961 to 1980, and other one as the fast urbanization period from 1981 to 2000. Based on the 40-year’s precipi-tation data of 14 standard weather stations in Beijing area, the effect of urbanization on precipitation distribution is studied. It is found that there has been a noticeable and systematic change of winter precipitation distribution pattern between these two periods in Beijing area: in the slow urbanization period, the precipitation in the southern part of Beijing is more than that in the northern part; but in the fast urbanization period, the precipitation distribution pattern is reverse, i.e. the precipitation in the southern part is less than that in the northern part; But in other seasons, the precipitation distribution pattern did not change remarkably in general. The possible cause resulting in the change of winter precipitation distribution pattern, might be that with urban area extension, the effects of "urban heat island" and "urban dry island" become more and more intensified, and increase hydrometeors evapo-ration below precipitable cloud, and then cause less precipitation received on the ground surface in the downtown and the southern part. It is also noteworthy to further research why the precipitation distri-bution pattern does not change systematically in other seasons except winter after intense urbaniza-tion in Beijing area.

  6. User's guide to the weather model: a component of the western spruce budworm modeling system.

    Science.gov (United States)

    W. P. Kemp; N. L. Crookston; P. W. Thomas

    1989-01-01

    A stochastic model useful in simulating daily maximum and minimum temperature and precipitation developed by Bruhn and others has been adapted for use in the western spruce budworm modeling system. This document describes how to use the weather model and illustrates some aspects of its behavior.

  7. Weathering and the mobility of phosphorus in the catchments and forefields of the Rhône and Oberaar glaciers, central Switzerland: Implications for the global phosphorus cycle on glacial-interglacial timescales

    Science.gov (United States)

    Föllmi, Karl B.; Hosein, Rachel; Arn, Kaspar; Steinmann, Philipp

    2009-04-01

    In this study we evaluate the dynamics of the biophile element phosphorus (P) in the catchment and proglacial areas of the Rhône and Oberaar glaciers (central Switzerland). We analysed erosion and dissolution rates of P-containing minerals in the subglacial environment by sampling water and suspended sediment in glacier outlets during three ablation and two accumulation seasons. We also quantified biogeochemical weathering rates of detrital P in proglacial sedimentary deposits using two chronosequences of samples of fresh, suspended, material obtained from the Oberaar and Rhône water outlets, Little-Ice-Age (LIA) moraines and Younger Dryas (YD) tills in each catchment. Subglacial P weathering is mainly a physical process and detrital P represents more than 99% of the precipitation-corrected total P denudation flux (234 and 540 kg km -2 yr -1 for the Rhône and Oberaar catchments, respectively). The calculated detrital P flux rates are three to almost five times higher than the world average flux. The precipitation-corrected soluble reactive P (SRP) flux corresponds to 1.88-1.99 kg km -2 yr -1 (Rhône) and 2.12-2.44 kg km -2 yr -1 (Oberaar), respectively. These fluxes are comparable to those of tropical rivers draining transport-limited, tectonically inactive weathering areas. In order to evaluate the efficiency of detrital P weathering in the Rhône and Oberaar proglacial areas, we systematically graded apatite grains extracted from the chronosequence in each catchment relative to weathering-induced changes in their surface morphologies (grades 1-4). Fresh apatite grains are heavily indented and dissolution rounded (grade 1). LIA grains from two 0-10 cm deep moraine samples show extensive dissolution etching, similar to surface grains from the YD profile (mean grades 2.7, 3.5 and 3.5, respectively). In these proglacial deposits, the weathering front deepens progressively as a function of time due to biocorrosion in the evolving acidic pedosphere , with mechanical

  8. Long-term impacts of aerosols on precipitation and lightning over the Pearl River Delta megacity area in China

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2011-12-01

    Full Text Available Seven-year measurements of precipitation, lightning flashes, and visibility from 2000 to 2006 have been analyzed in the Pearl River Delta (PRD region, China, with a focus on the Guangzhou megacity area. Statistical analysis shows that the occurrence of heavy rainfall (>25 mm per day and frequency of lightning strikes are reversely correlated to visibility during this period. To elucidate the effects of aerosols on cloud processes, precipitation, and lightning activity, a cloud resolving – Weather Research and Forecasting (CR-WRF model with a two-moment bulk microphysical scheme is employed to simulate a mesoscale convective system occurring on 28 Match 2009 in the Guangzhou megacity area. The model predicted evolutions of composite radar reflectivity and accumulated precipitation are in agreement with measurements from S-band weather radars and automatic gauge stations. The calculated lightning potential index (LPI exhibits temporal and spatial consistence with lightning flashes recorded by a local lightning detection network. Sensitivity experiments have been performed to reflect aerosol conditions representative of polluted and clean cases. The simulations suggest that precipitation and LPI are enhanced by about 16% and 50%, respectively, under the polluted aerosol condition. Our results suggest that elevated aerosol loading suppresses light and moderate precipitation (less than 25 mm per day, but enhances heavy precipitation. The responses of hydrometeors and latent heat release to different aerosol loadings reveal the physical mechanism for the precipitation and lightning enhancement in the Guangzhou megacity area, showing more efficient mixed phase processes and intensified convection under the polluted aerosol condition.

  9. Quadratic Regression-based Non-uniform Response Correction for Radiochromic Film Scanners

    International Nuclear Information System (INIS)

    Jeong, Hae Sun; Kim, Chan Hyeong; Han, Young Yih; Kum, O Yeon

    2009-01-01

    In recent years, several types of radiochromic films have been extensively used for two-dimensional dose measurements such as dosimetry in radiotherapy as well as imaging and radiation protection applications. One of the critical aspects in radiochromic film dosimetry is the accurate readout of the scanner without dose distortion. However, most of charge-coupled device (CCD) scanners used for the optical density readout of the film employ a fluorescent lamp or a coldcathode lamp as a light source, which leads to a significant amount of light scattering on the active layer of the film. Due to the effect of the light scattering, dose distortions are produced with non-uniform responses, although the dose is uniformly irradiated to the film. In order to correct the distorted doses, a method based on correction factors (CF) has been reported and used. However, the prediction of the real incident doses is difficult when the indiscreet doses are delivered to the film, since the dose correction with the CF-based method is restrictively used in case that the incident doses are already known. In a previous study, therefore, a pixel-based algorithm with linear regression was developed to correct the dose distortion of a flatbed scanner, and to estimate the initial doses. The result, however, was not very good for some cases especially when the incident dose is under approximately 100 cGy. In the present study, the problem was addressed by replacing the linear regression with the quadratic regression. The corrected doses using this method were also compared with the results of other conventional methods

  10. A Analysis of the Development of Weather Concepts

    Science.gov (United States)

    Mroz, Paul John

    Weather information in all forms is poorly understood and often misinterpreted by the general public. Weather literacy is necessary for everyone if critical weather messages, designed to save lives and protect property, are to be effective. The purpose of this study was to seek content and causal evidence for a developmental concept of Weather Information Processing that was consistent with Piagetian Cognitive Stages of Development. Three ordinal Content Stages Of Weather Information Processing (phenomena, process and mechanism) and three ordinal Causal Explanation Stages Of Weather Information Processing (non-real, natural, and scientifically valid abstract ideas) were explored for their relationship with Piaget's Pre-Operational, Concrete and Formal Stages of Development. One hundred and fifty -five elementary and secondary school students from two school districts were administered a written Piagetian exam. Commonly available television weather programs were categorized, randomly assigned and viewed by 42 randomly selected students who were administered three Piagetian tasks. Students were clinically interviewed for the level of content information and causal explanations (reasoning). Results indicated that content information and causal reasoning of students to televised weather information is significantly related (p Cognitive Stages of Development. Two Piagetian logic operations (seriation and correlation) were established as significantly different (p Information Processing and have implications for teaching and presenting weather information to the public.

  11. Benefits Analysis of Multi-Center Dynamic Weather Routes

    Science.gov (United States)

    Sheth, Kapil; McNally, David; Morando, Alexander; Clymer, Alexis; Lock, Jennifer; Petersen, Julien

    2014-01-01

    Dynamic weather routes are flight plan corrections that can provide airborne flights more than user-specified minutes of flying-time savings, compared to their current flight plan. These routes are computed from the aircraft's current location to a flight plan fix downstream (within a predefined limit region), while avoiding forecasted convective weather regions. The Dynamic Weather Routes automation has been continuously running with live air traffic data for a field evaluation at the American Airlines Integrated Operations Center in Fort Worth, TX since July 31, 2012, where flights within the Fort Worth Air Route Traffic Control Center are evaluated for time savings. This paper extends the methodology to all Centers in United States and presents benefits analysis of Dynamic Weather Routes automation, if it was implemented in multiple airspace Centers individually and concurrently. The current computation of dynamic weather routes requires a limit rectangle so that a downstream capture fix can be selected, preventing very large route changes spanning several Centers. In this paper, first, a method of computing a limit polygon (as opposed to a rectangle used for Fort Worth Center) is described for each of the 20 Centers in the National Airspace System. The Future ATM Concepts Evaluation Tool, a nationwide simulation and analysis tool, is used for this purpose. After a comparison of results with the Center-based Dynamic Weather Routes automation in Fort Worth Center, results are presented for 11 Centers in the contiguous United States. These Centers are generally most impacted by convective weather. A breakdown of individual Center and airline savings is presented and the results indicate an overall average savings of about 10 minutes of flying time are obtained per flight.

  12. Non-equilibrium grain boundary segregation of boron in austenitic stainless steel - IV. Precipitation behaviour and distribution of elements at grain boundaries

    International Nuclear Information System (INIS)

    Karlsson, L.; Norden, H.

    1988-01-01

    The distribution of elements and the precipitation behaviour at grain boundaries have been studied in boron containing AISI 316L and ''Mo-free AISI 316L'' type austenitic stainless steels. A combination of microanalytical techniques was used to study the boundary regions after cooling at 0.29-530 0 C/s from 800, 1075 or 1250 0 C. Tetragonal M/sub 2/B, M/sub 5/B/sub 3/ and M/sub 3/B/sub 2/, all rich in Fe, Cr and Mo, precipitated in the ''high B'' (40 ppm) AISI 316L steel whereas orthorhombic M/sub 2/B, rich in Cr and Fe was found in the ''Mo-free steel'' with 23 ppm B. In the ''high B steel'' a thin (<2nm), continuous layer, containing B, Cr, Mo and Fe and having a stoichiometry of typically M/sub 9/B, formed at boundaries after cooling at intermediate cooling rates. For both types of steels a boundary zone was found, after all heat treatments, with a composition differing significantly from the bulk composition. The differences were most marked after cooling at intermediate cooling rates. In both types of steel boundary depletion of Cr and enrichment of B and C occurred. It was found that non-equilibrium grain boundary segregation of boron can affect the precipitation behaviour by making the boundary composition enter a new phase field ''Non-equilibrium phases'' might also form. The synergistic effect of B and Mo on the boundary composition and precipitation behaviour, and the observed indications of C non-equilibrium segregation are discussed

  13. Calculation of the Pitot tube correction factor for Newtonian and non-Newtonian fluids.

    Science.gov (United States)

    Etemad, S Gh; Thibault, J; Hashemabadi, S H

    2003-10-01

    This paper presents the numerical investigation performed to calculate the correction factor for Pitot tubes. The purely viscous non-Newtonian fluids with the power-law model constitutive equation were considered. It was shown that the power-law index, the Reynolds number, and the distance between the impact and static tubes have a major influence on the Pitot tube correction factor. The problem was solved for a wide range of these parameters. It was shown that employing Bernoulli's equation could lead to large errors, which depend on the magnitude of the kinetic energy and energy friction loss terms. A neural network model was used to correlate the correction factor of a Pitot tube as a function of these three parameters. This correlation is valid for most Newtonian, pseudoplastic, and dilatant fluids at low Reynolds number.

  14. Revisiting the extended spring indices using gridded weather data and machine learning

    Science.gov (United States)

    Mehdipoor, Hamed; Izquierdo-Verdiguier, Emma; Zurita-Milla, Raul

    2016-04-01

    The extended spring indices or SI-x [1] have been successfully used to predict the timing of spring onset at continental scales. The SI-x models were created by combining lilac and honeysuckle volunteered phenological observations, temperature data (from weather stations) and latitudinal information. More precisely, these models use a linear regression to predict the day of year of first leaf and first bloom for these two indicator species. In this contribution we revisit both the data and the method used to calibrate the SI-x models to check whether the addition of new input data or the use of non-linear regression methods could lead to improments in the model outputs. In particular, we use a recently published dataset [2] of volunteered observations on cloned and common lilac over longer period of time (1980-2014) and we replace the weather station data by 54 features derived from Daymet [3], which provides 1 by 1 km gridded estimates of daily weather parameters (maximum and minimum temperatures, precipitation, water vapor pressure, solar radiation, day length, snow water equivalent) for North America. These features consist of both daily weather values and their long- and short-term accumulations and elevation. we also replace the original linear regression by a non-linear method. Specifically, we use random forests to both identify the most important features and to predict the day of year of the first leaf of cloned and common lilacs. Preliminary results confirm the importance of the SI-x features (maximum and minimum temperatures and day length). However, our results show that snow water equivalent and water vapor pressure are also necessary to properly model leaf onset. Regarding the predictions, our results indicate that Random Forests yield comparable results to those produced by the SI-x models (in terms of root mean square error -RMSE). For cloned and common lilac, the models predict the day of year of leafing with 16 and 15 days of accuracy respectively

  15. Coding a Weather Model: DOE-FIU Science & Technology Workforce Development Program.

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, Jon David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    DOE Fellow, Andres Cremisini, completed a 10-week internship with Sandia National Laboratories (SNL) in Albuquerque, New Mexico. Under the management of Kristopher Klingler and the mentorship of Jon Bradley, he was tasked with conceiving and coding a realistic weather model for use in physical security applications. The objective was to make a weather model that could use real data to accurately predict wind and precipitation conditions at any location of interest on the globe at any user-determined time. The intern received guidance on software design, the C++ programming language and clear communication of project goals and ongoing progress. In addition, Mr. Cremisini was given license to structure the program however he best saw fit, an experience that will benefit ongoing research endeavors.

  16. Intense air-sea exchanges and heavy orographic precipitation over Italy: The role of Adriatic sea surface temperature uncertainty

    Science.gov (United States)

    Stocchi, Paolo; Davolio, Silvio

    2017-11-01

    Strong and persistent low-level winds blowing over the Adriatic basin are often associated with intense precipitation events over Italy. Typically, in case of moist southeasterly wind (Sirocco), rainfall affects northeastern Italy and the Alpine chain, while with cold northeasterly currents (Bora) precipitations are localized along the eastern slopes of the Apennines and central Italy coastal areas. These events are favoured by intense air-sea interactions and it is reasonable to hypothesize that the Adriatic sea surface temperature (SST) can affect the amount and location of precipitation. High-resolution simulations of different Bora and Sirocco events leading to severe precipitation are performed using a convection-permitting model (MOLOCH). Sensitivity experiments varying the SST initialization field are performed with the aim of evaluating the impact of SST uncertainty on precipitation forecasts, which is a relevant topic for operational weather predictions, especially at local scales. Moreover, diagnostic tools to compute water vapour fluxes across the Italian coast and atmospheric water budget over the Adriatic Sea have been developed and applied in order to characterize the air mass that feeds the precipitating systems. Finally, the investigation of the processes through which the SST influences location and intensity of heavy precipitation allows to gain a better understanding on mechanisms conducive to severe weather in the Mediterranean area and in the Adriatic basin in particular. Results show that the effect of the Adriatic SST (uncertainty) on precipitation is complex and can vary considerably among different events. For both Bora and Sirocco events, SST does not influence markedly the atmospheric water budget or the degree of moistening of air that flows over the Adriatic Sea. SST mainly affects the stability of the atmospheric boundary layer, thus influencing the flow dynamics and the orographic flow regime, and in turn, the precipitation pattern.

  17. Extreme weather events in Iran under a changing climate

    Science.gov (United States)

    Alizadeh-Choobari, Omid; Najafi, M. S.

    2018-01-01

    Observations unequivocally show that Iran has been rapidly warming over recent decades, which in sequence has triggered a wide range of climatic impacts. Meteorological records of several ground stations across Iran with daily temporal resolution for the period 1951-2013 were analyzed to investigate the climate change and its impact on some weather extremes. Iran has warmed by nearly 1.3 °C during the period 1951-2013 (+0.2 °C per decade), with an increase of the minimum temperature at a rate two times that of the maximum. Consequently, an increase in the frequency of heat extremes and a decrease in the frequency of cold extremes have been observed. The annual precipitation has decreased by 8 mm per decade, causing an expansion of Iran's dry zones. Previous studies have pointed out that warming is generally associated with more frequent heavy precipitation because a warmer air can hold more moisture. Nevertheless, warming in Iran has been associated with more frequent light precipitation, but less frequent moderate, heavy and extremely heavy precipitation. This is because in the subtropical dry zones, a longer time is required to recharge the atmosphere with water vapour in a warmer climate, causing more water vapour to be transported from the subtropics to high latitudes before precipitations forms. In addition, the altitude of the condensation level increases in a warmer climate in subtropical regions, causing an overall decrease of precipitation. We argue that changing in the frequency of heavy precipitation in response to warming varies depending on the geographical location. Warming over the dry subtropical regions is associated with a decrease in the frequency of heavy precipitation, while an increase is expected over both subpolar and tropical regions. The warmer climate has also led to the increase in the frequency of both thunderstorms (driven by convective heating) and dust events over Iran.

  18. Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

    Science.gov (United States)

    Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

    2018-01-01

    Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

  19. Objective description of precipitation fields on the basis of a composition from synop- and satellite data

    OpenAIRE

    Langer, Ines

    2010-01-01

    This work will contribute to the scale-dependent verification of precipitation forecasts of the German Weather Service’s Lokal-Modell (LM). A new observational dataset separating stratiform and convective precipitation at a one-hour temporal resolution was produced for Germany for the year 2004. The underlaying idea of this work is to connect rain producing cloud types taken from synoptic observations and derived cloud types from Meteosat data by the interpolation scheme. The accuracy of the ...

  20. Utilizing the Vertical Variability of Precipitation to Improve Radar QPE

    Science.gov (United States)

    Gatlin, Patrick N.; Petersen, Walter A.

    2016-01-01

    Characteristics of the melting layer and raindrop size distribution can be exploited to further improve radar quantitative precipitation estimation (QPE). Using dual-polarimetric radar and disdrometers, we found that the characteristic size of raindrops reaching the ground in stratiform precipitation often varies linearly with the depth of the melting layer. As a result, a radar rainfall estimator was formulated using D(sub m) that can be employed by polarimetric as well as dual-frequency radars (e.g., space-based radars such as the GPM DPR), to lower the bias and uncertainty of conventional single radar parameter rainfall estimates by as much as 20%. Polarimetric radar also suffers from issues associated with sampling the vertical distribution of precipitation. Hence, we characterized the vertical profile of polarimetric parameters (VP3)-a radar manifestation of the evolving size and shape of hydrometeors as they fall to the ground-on dual-polarimetric rainfall estimation. The VP3 revealed that the profile of ZDR in stratiform rainfall can bias dual-polarimetric rainfall estimators by as much as 50%, even after correction for the vertical profile of reflectivity (VPR). The VP3 correction technique that we developed can improve operational dual-polarimetric rainfall estimates by 13% beyond that offered by a VPR correction alone.

  1. Comparison of radar and numerical weather model rainfall forecasts in the perspective of urban flood prediction

    DEFF Research Database (Denmark)

    Lovring, Maite Monica; Löwe, Roland; Courdent, Vianney Augustin Thomas

    An early flood warning system has been developed for urban catchments and is currently running in online operation in Copenhagen. The system is highly dependent on the quality of rainfall forecast inputs. An investigation of precipitation inputs from Radar Nowcast (RN), Numerical Weather Prediction...

  2. Computer Simulation of the Formation of Non-Metallic Precipitates During a Continuous Casting of Steel

    Directory of Open Access Journals (Sweden)

    Kalisz D.

    2016-03-01

    Full Text Available The authors own computer software, based on the Ueshima mathematical model with taking into account the back diffusion, determined from the Wołczyński equation, was developed for simulation calculations. The applied calculation procedure allowed to determine the chemical composition of the non-metallic phase in steel deoxidised by means of Mn, Si and Al, at the given cooling rate. The calculation results were confirmed by the analysis of samples taken from the determined areas of the cast ingot. This indicates that the developed computer software can be applied for designing the steel casting process of the strictly determined chemical composition and for obtaining the required non-metallic precipitates.

  3. Trends in precipitation extremes and long-term memory of runoff records in Zhejiang, East China

    NARCIS (Netherlands)

    Tian, Y.; Tian, Ye; Xu, YuePing; Booij, Martijn J.; Zhang, Qingqing; Lin, Shengji; Franks, Steward W.; Boegh, Eva; Blyth, Eleanor; Hannah, David M.; Yilmaz, Koray K.

    2011-01-01

    Extreme weather events have a huge impact on human beings and therefore it is of vital importance to investigate trends in relevant climatological and hydrological variables. In this study, precipitation and streamflow trends in Zhejiang Province in east China are analysed. Trends in annual and

  4. Decadal Variation of Precipitation in Saudi Arabia induced by Agricultural Irrigation

    Science.gov (United States)

    Lo, M. H.; Wey, H. W.; Wada, Y.; IM, E. S.; Chien, R. Y.; Wu, R. J.

    2017-12-01

    Decadal variation of wet-season precipitation has been found in the arid region of central Saudi Arabia. 1980s has been a rather wet decade compared with the decades before. Previous studies have mentioned that the irrigation moisture may contribute to the precipitation anomalies in Saudi Arabia. In the current study, we show from observational data that the contribution of the variation comes mostly from February to May. As the irrigation is a localized forcing, we therefore use the Weather Research and Forecasting (WRF) Model to simulate the response of the land-atmosphere interaction to the wet soil moisture resulted from additional irrigation moisture supply. Preliminary result shows in the irrigated simulation that precipitation in central Saudi Arabia is enhanced, indicating the possible link between irrigation expansion in the 1980s and the decadal precipitation variation over central Saudi Arabia. We propose it is the anomalous convergence induced by irrigation as well as additional moisture that contribute to the enhanced precipitation over heavily irrigation region in the central Saudi Arabian. In addition, analysis on the daily precipitation from the WRF outputs indicates that positive rainfall anomalies tend to happen when there is rainfall originally; that is, irrigation enhances rainfall but not creates rainfall.

  5. Spatial analysis of precipitation time series over the Upper Indus Basin

    Science.gov (United States)

    Latif, Yasir; Yaoming, Ma; Yaseen, Muhammad

    2018-01-01

    The upper Indus basin (UIB) holds one of the most substantial river systems in the world, contributing roughly half of the available surface water in Pakistan. This water provides necessary support for agriculture, domestic consumption, and hydropower generation; all critical for a stable economy in Pakistan. This study has identified trends, analyzed variability, and assessed changes in both annual and seasonal precipitation during four time series, identified herein as: (first) 1961-2013, (second) 1971-2013, (third) 1981-2013, and (fourth) 1991-2013, over the UIB. This study investigated spatial characteristics of the precipitation time series over 15 weather stations and provides strong evidence of annual precipitation by determining significant trends at 6 stations (Astore, Chilas, Dir, Drosh, Gupis, and Kakul) out of the 15 studied stations, revealing a significant negative trend during the fourth time series. Our study also showed significantly increased precipitation at Bunji, Chitral, and Skardu, whereas such trends at the rest of the stations appear insignificant. Moreover, our study found that seasonal precipitation decreased at some locations (at a high level of significance), as well as periods of scarce precipitation during all four seasons. The observed decreases in precipitation appear stronger and more significant in autumn; having 10 stations exhibiting decreasing precipitation during the fourth time series, with respect to time and space. Furthermore, the observed decreases in precipitation appear robust and more significant for regions at high elevation (>1300 m). This analysis concludes that decreasing precipitation dominated the UIB, both temporally and spatially including in the higher areas.

  6. WEATHER INDEX- THE BASIS OF WEATHER DERIVATIVES

    Directory of Open Access Journals (Sweden)

    Botos Horia Mircea

    2011-07-01

    Full Text Available This paper approaches the subject of Weather Derivatives, more exactly their basic element the weather index. The weather index has two forms, the Heating Degree Day (HDD and the Cooling Degree Day (CDD. We will try to explain their origin, use and the relationship between the two forms of the index. In our research we started from the analysis of the weather derivatives and what they are based on. After finding out about weather index, we were interested in understanding exactly how they work and how they influence the value of the contract. On the national level the research in the field is scares, but foreign materials available. The study for this paper was based firstly on reading about Weather Derivative, and then going in the meteorogical field and determining the way by which the indices were determined. After this, we went to the field with interest in the indices, such as the energy and gas industries, and figured out how they determined the weather index. For the examples we obtained data from the weather index database, and calculated the value for the period. The study is made on a period of five years, in 8 cities of the European Union. The result of this research is that we can now understand better the importance of the way the indices work and how they influence the value of the Weather Derivatives. This research has an implication on the field of insurance, because of the fact that weather derivative are at the convergence point of the stock markets and the insurance market. The originality of the paper comes from the personal touch given to the theoretical aspect and through the analysis of the HDD and CDD index in order to show their general behaviour and relationship.

  7. Artificial weathering of oils by rotary evaporator

    International Nuclear Information System (INIS)

    Fieldhouse, B.; Hollebone, B.P.; Singh, N.R.; Tong, T.S.; Mullin, J.

    2009-01-01

    percentages of the oil should be corrected for water content to represent the degree of oil weathering only. Further investigation into the evaporation of water from heavy crude oil was recommended because the variation in water content may be sufficient to affect oil properties. 10 refs., 6 tabs., 9 figs.

  8. Characteristics of autumn-winter extreme precipitation on the Norwegian west coast identified by cluster analysis

    Energy Technology Data Exchange (ETDEWEB)

    Heikkilae, U. [Bjerknes Centre for Climate Research, Uni Bjerknes Centre, Bergen (Norway); Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW (Australia); Sorteberg, A. [University of Bergen, Geophysical Institute, Bergen (Norway); University of Bergen, Bjerknes Centre for Climate Research, Bergen (Norway)

    2012-08-15

    Extremely high autumn and winter precipitation events on the European west coast are often driven by low-pressure systems in the North Atlantic. Climate projections suggest the number and intensity of these events is likely to increase far more than the mean precipitation. In this study we investigate the autumn-winter extreme precipitation on the Norwegian west coast and the connection between its spatial distribution and sea level pressure (SLP) patterns using the k-means cluster analysis. We use three relatively high resolved downscalings of one global coupled model: the Arpege global atmospheric model (stretched grid with 35-km horizontal resolution over Norway) and the WRF-downscaled Arpege model (30 and 10-km) for the 30-year periods of 1961-1990 and 2021-2050. The cluster analysis finds three main SLP patterns responsible for extreme precipitation in different parts of the country. The SLP patterns found are similar to the NAO positive pattern known to strengthen the westerly flow towards European coast. We then apply the method to investigate future change in extreme precipitation. We find an increase in the number of days with extreme precipitation of 15, 39 and 35% in the two simulations (Arpege 35-km and WRF 30 and 10-km, respectively). We do not find evidence of a significant change in the frequency of weather patterns between the present and the future periods. Rather, it is the probability of a given weather pattern to cause extreme precipitation which is increased in the future, probably due to higher temperatures and an increased moisture content of the air. The WRF model predicts the increase in this probability caused by the most important SLP patterns to be >50%. The Arpege model does not predict such a significant change because the general increase in extreme precipitation predicted is smaller, probably due to its coarser resolution over ocean which leads to smoother representation of the low pressure systems. (orig.)

  9. Iron and silicon isotope behaviour accompanying weathering in Icelandic soils, and the implications for iron export from peatlands

    Science.gov (United States)

    Opfergelt, S.; Williams, H. M.; Cornelis, J. T.; Guicharnaud, R. A.; Georg, R. B.; Siebert, C.; Gislason, S. R.; Halliday, A. N.; Burton, K. W.

    2017-11-01

    Incipient warming of peatlands at high latitudes is expected to modify soil drainage and hence the redox conditions, which has implications for Fe export from soils. This study uses Fe isotopes to assess the processes controlling Fe export in a range of Icelandic soils including peat soils derived from the same parent basalt, where Fe isotope variations principally reflect differences in weathering and drainage. In poorly weathered, well-drained soils (non-peat soils), the limited Fe isotope fractionation in soil solutions relative to the bulk soil (Δ57Fesolution-soil = -0.11 ± 0.12‰) is attributed to proton-promoted mineral dissolution. In the more weathered poorly drained soils (peat soils), the soil solutions are usually lighter than the bulk soil (Δ57Fesolution-soil = -0.41 ± 0.32‰), which indicates that Fe has been mobilised by reductive mineral dissolution and/or ligand-controlled dissolution. The results highlight the presence of Fe-organic complexes in solution in anoxic conditions. An additional constraint on soil weathering is provided by Si isotopes. The Si isotope composition of the soil solutions relative to the soil (Δ30Sisolution-soil = 0.92 ± 0.26‰) generally reflects the incorporation of light Si isotopes in secondary aluminosilicates. Under anoxic conditions in peat soils, the largest Si isotope fractionation in soil solutions relative to the bulk soil is observed (Δ30Sisolution-soil = 1.63 ± 0.40‰) and attributed to the cumulative contribution of secondary clay minerals and amorphous silica precipitation. Si supersaturation in solution with respect to amorphous silica is reached upon freezing when Al availability to form aluminosilicates is limited by the affinity of Al for metal-organic complexes. Therefore, the precipitation of amorphous silica in peat soils indirectly supports the formation of metal-organic complexes in poorly drained soils. These observations highlight that in a scenario of decreasing soil drainage with

  10. Extreme Precipitation, Stormwater, and Flooding in King County: Co-producing Research to Support Adaptation

    Science.gov (United States)

    Mauger, G. S.; Lorente-Plazas, R.; Salathe, E. P., Jr.; Mitchell, T. P.; Simmonds, J.; Lee, S. Y.; Hegewisch, K.; Warner, M.; Won, J.

    2017-12-01

    King County has experienced 12 federally declared flood disasters since 1990, and tens of thousands of county residents commute through, live, and work in floodplains. In addition to flooding, stormwater is a critical management challenge, exacerbated by aging infrastructure, combined sewer and drainage systems, and continued development. Even absent the effects of climate change these are challenging management issues. Recent studies clearly point to an increase in precipitation extremes for the Pacific Northwest (e.g., Warner et al. 2015). Yet very little information is available on the magnitude and spatial distribution of this change. Others clearly show that local-scale changes in extreme precipitation can only be accurately quantified with dynamical downscaling, i.e.: using a regional climate model. This talk will describe a suite of research and adaptation efforts developed in a close collaboration between King County and the UW Climate Impacts Group. Building on past collaborations, research efforts were defined in collaboration with King County managers, addressing three key science questions: (1) How are the mesoscale variations in extreme precipitation modulated by changes in large-scale weather conditions? (2) How will precipitation extremes change? This was assessed via two new high-resolution regional model projections using the Weather Research and Forecasting (WRF) mesoscale model (Skamarock et al. 2005). (3) What are the implications for stormwater and flooding in King County? This was assessed by both exploring the statistics of hourly precipitation extremes in the new projections, as well as new hydrologic modeling to assess the implications for river flooding. The talk will present results from these efforts, review the implications for King County planning and infrastructure, and synthesize lessons learned and opportunities for additional work.

  11. A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

    Science.gov (United States)

    Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

    2017-07-01

    Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

  12. Assessing non-linear variation of temperature and precipitation for different growth periods of maize and their impacts on phenology in the Midwest of Jilin Province, China

    Science.gov (United States)

    Guo, Enliang; Zhang, Jiquan; Wang, Yongfang; Alu, Si; Wang, Rui; Li, Danjun; Ha, Si

    2018-05-01

    In the past two decades, the regional climate in China has undergone significant change, resulting in crop yield reduction and complete failure. The goal of this study is to detect the variation of temperature and precipitation for different growth periods of maize and assess their impact on phenology. The daily meteorological data in the Midwest of Jilin Province during 1960-2014 were used in the study. The ensemble empirical mode decomposition method was adopted to analyze the non-linear trend and fluctuation in temperature and precipitation, and the sensitivity of the length of the maize growth period to temperature and precipitation was analyzed by the wavelet cross-transformation method. The results show that the trends of temperature and precipitation change are non-linear for different growth periods of maize, and the average temperature in the sowing-jointing stage was different from that in the other growth stages, showing a slight decrease trend, while the variation amplitude of maximum temperature is smaller than that of the minimum temperature. This indicates that the temperature difference between day and night shows a gradually decreasing trend. Precipitation in the growth period also showed a decreasing non-linear trend, while the inter-annual variability with period of quasi-3-year and quasi-6-year dominated the variation of temperature and precipitation. The whole growth period was shortened by 10.7 days, and the sowing date was advanced by approximately 11 days. We also found that there was a significant resonance period among temperature, precipitation, and phenology. Overall, a negative correlation between phenology and temperature is evident, while a positive correlation with precipitation is exhibited. The results illustrate that the climate suitability for maize has reduced over the past decades.

  13. Influence of bulk microphysics schemes upon Weather Research and Forecasting (WRF) version 3.6.1 nor'easter simulations

    Science.gov (United States)

    Nicholls, Stephen D.; Decker, Steven G.; Tao, Wei-Kuo; Lang, Stephen E.; Shi, Jainn J.; Mohr, Karen I.

    2017-03-01

    This study evaluated the impact of five single- or double-moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven intense wintertime cyclones impacting the mid-Atlantic United States; 5-day long WRF simulations were initialized roughly 24 h prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (five BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities led to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatiotemporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF simulations demonstrate low-to-moderate (0.217-0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude diagrams (CFADs) reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions.

  14. Spatial bias and uncertainty in numerical weather predictions for urban runoff forecasts with long time horizons

    DEFF Research Database (Denmark)

    Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

    2017-01-01

    Numerical Weather Predictions (NWP) can be used to forecast urban runoff with long lead times. However, NWP exhibit large spatial uncertainties and using forecasted precipitation directly above the catchment might therefore not be an ideal approach in an online setup. We use the Danish...... Meteorological Institute’s NWP ensemble and investigate a large spatial neighborhood around the catchment over a two-year period. When compared against in-sewer observations, runoff forecasts forced with precipitation from north-east of the catchment are most skillful. This highlights spatial biases...

  15. Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

    Science.gov (United States)

    Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

    2018-05-01

    Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

  16. Predictability of extreme weather events for NE U.S.: improvement of the numerical prediction using a Bayesian regression approach

    Science.gov (United States)

    Yang, J.; Astitha, M.; Anagnostou, E. N.; Hartman, B.; Kallos, G. B.

    2015-12-01

    Weather prediction accuracy has become very important for the Northeast U.S. given the devastating effects of extreme weather events in the recent years. Weather forecasting systems are used towards building strategies to prevent catastrophic losses for human lives and the environment. Concurrently, weather forecast tools and techniques have evolved with improved forecast skill as numerical prediction techniques are strengthened by increased super-computing resources. In this study, we examine the combination of two state-of-the-science atmospheric models (WRF and RAMS/ICLAMS) by utilizing a Bayesian regression approach to improve the prediction of extreme weather events for NE U.S. The basic concept behind the Bayesian regression approach is to take advantage of the strengths of two atmospheric modeling systems and, similar to the multi-model ensemble approach, limit their weaknesses which are related to systematic and random errors in the numerical prediction of physical processes. The first part of this study is focused on retrospective simulations of seventeen storms that affected the region in the period 2004-2013. Optimal variances are estimated by minimizing the root mean square error and are applied to out-of-sample weather events. The applicability and usefulness of this approach are demonstrated by conducting an error analysis based on in-situ observations from meteorological stations of the National Weather Service (NWS) for wind speed and wind direction, and NCEP Stage IV radar data, mosaicked from the regional multi-sensor for precipitation. The preliminary results indicate a significant improvement in the statistical metrics of the modeled-observed pairs for meteorological variables using various combinations of the sixteen events as predictors of the seventeenth. This presentation will illustrate the implemented methodology and the obtained results for wind speed, wind direction and precipitation, as well as set the research steps that will be

  17. Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results

    Directory of Open Access Journals (Sweden)

    Ehsan Sharifi

    2016-02-01

    Full Text Available The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellitE Retrievals for GPM (IMERG product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42 and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF against the Iran Meteorological Organization (IMO daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD, Critical Success Index (CSI and False Alarm Ratio (FAR in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (>15 mm/day, IMERG is superior to

  18. Non-linear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation

    International Nuclear Information System (INIS)

    Hamann, Jan; Hannestad, Steen; Melchiorri, Alessandro; Wong, Yvonne Y Y

    2008-01-01

    We explore and compare the performances of two non-linear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-ΛCDM (CDM: cold dark matter) cosmologies. The first model is the well known Q model, first applied in the analysis of Two-degree Field Galaxy Redshift Survey data. The second, the P model, is inspired by the halo model, in which non-linear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while the two models perform equally well in providing adequate correction for a range of galaxy clustering data in standard ΛCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalization, a technique sometimes used in the marginalization of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended non-linear correction model also because of its physical transparency

  19. Non-linear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation

    Science.gov (United States)

    Hamann, Jan; Hannestad, Steen; Melchiorri, Alessandro; Wong, Yvonne Y. Y.

    2008-07-01

    We explore and compare the performances of two non-linear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-ΛCDM (CDM: cold dark matter) cosmologies. The first model is the well known Q model, first applied in the analysis of Two-degree Field Galaxy Redshift Survey data. The second, the P model, is inspired by the halo model, in which non-linear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while the two models perform equally well in providing adequate correction for a range of galaxy clustering data in standard ΛCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalization, a technique sometimes used in the marginalization of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended non-linear correction model also because of its physical transparency.

  20. Effective assimilation of global precipitation: simulation experiments

    Directory of Open Access Journals (Sweden)

    Guo-Yuan Lien

    2013-07-01

    Full Text Available Past attempts to assimilate precipitation by nudging or variational methods have succeeded in forcing the model precipitation to be close to the observed values. However, the model forecasts tend to lose their additional skill after a few forecast hours. In this study, a local ensemble transform Kalman filter (LETKF is used to effectively assimilate precipitation by allowing ensemble members with better precipitation to receive higher weights in the analysis. In addition, two other changes in the precipitation assimilation process are found to alleviate the problems related to the non-Gaussianity of the precipitation variable: (a transform the precipitation variable into a Gaussian distribution based on its climatological distribution (an approach that could also be used in the assimilation of other non-Gaussian observations and (b only assimilate precipitation at the location where at least some ensemble members have precipitation. Unlike many current approaches, both positive and zero rain observations are assimilated effectively. Observing system simulation experiments (OSSEs are conducted using the Simplified Parametrisations, primitivE-Equation DYnamics (SPEEDY model, a simplified but realistic general circulation model. When uniformly and globally distributed observations of precipitation are assimilated in addition to rawinsonde observations, both the analyses and the medium-range forecasts of all model variables, including precipitation, are significantly improved as compared to only assimilating rawinsonde observations. The effect of precipitation assimilation on the analyses is retained on the medium-range forecasts and is larger in the Southern Hemisphere (SH than that in the Northern Hemisphere (NH because the NH analyses are already made more accurate by the denser rawinsonde stations. These improvements are much reduced when only the moisture field is modified by the precipitation observations. Both the Gaussian transformation and