WorldWideScience

Sample records for satellite-based estimates ncep

  1. Sea surface freshwater flux estimates from GECCO, HOAPS and NCEP

    Science.gov (United States)

    Romanova, V.; Köhl, A.; Stammer, D.; Klepp, C.; Andersson, A.; Bakan, S.

    2010-08-01

    Surface net freshwater flux fields, estimated from the GECCO ocean state estimation effort over the 50 yr period 1951-2001, are compared to purely satellite-based HOAPS freshwater flux estimates and to the NCEP atmospheric re-analysis net surface freshwater flux fields to assess the quality of all flux products and to improve our understanding of the time-mean surface freshwater flux distribution as well as its temporal variability. Surface flux fields are adjusted by the GECCO state estimation procedure together with initial temperature and salinity conditions so that the model simulation becomes consistent with ocean observations. The entirely independent HOAPS net surface freshwater flux fields result from the difference between SSM/I based precipitation estimates and fields of evaporation resulting from a bulk aerodynamic approach using SSM/I data and the Pathfinder SST. All three products agree well on a global scale. However, overall GECCO seems to have moved away from the NCEP/NCAR first guess surface fluxes and is often closer to the HOAPS data set. This holds for the time mean as well as for the seasonal cycle.

  2. Groundwater Modelling For Recharge Estimation Using Satellite Based Evapotranspiration

    Science.gov (United States)

    Soheili, Mahmoud; (Tom) Rientjes, T. H. M.; (Christiaan) van der Tol, C.

    2017-04-01

    Groundwater movement is influenced by several factors and processes in the hydrological cycle, from which, recharge is of high relevance. Since the amount of aquifer extractable water directly relates to the recharge amount, estimation of recharge is a perquisite of groundwater resources management. Recharge is highly affected by water loss mechanisms the major of which is actual evapotranspiration (ETa). It is, therefore, essential to have detailed assessment of ETa impact on groundwater recharge. The objective of this study was to evaluate how recharge was affected when satellite-based evapotranspiration was used instead of in-situ based ETa in the Salland area, the Netherlands. The Methodology for Interactive Planning for Water Management (MIPWA) model setup which includes a groundwater model for the northern part of the Netherlands was used for recharge estimation. The Surface Energy Balance Algorithm for Land (SEBAL) based actual evapotranspiration maps from Waterschap Groot Salland were also used. Comparison of SEBAL based ETa estimates with in-situ abased estimates in the Netherlands showed that these SEBAL estimates were not reliable. As such results could not serve for calibrating root zone parameters in the CAPSIM model. The annual cumulative ETa map produced by the model showed that the maximum amount of evapotranspiration occurs in mixed forest areas in the northeast and a portion of central parts. Estimates ranged from 579 mm to a minimum of 0 mm in the highest elevated areas with woody vegetation in the southeast of the region. Variations in mean seasonal hydraulic head and groundwater level for each layer showed that the hydraulic gradient follows elevation in the Salland area from southeast (maximum) to northwest (minimum) of the region which depicts the groundwater flow direction. The mean seasonal water balance in CAPSIM part was evaluated to represent recharge estimation in the first layer. The highest recharge estimated flux was for autumn

  3. Development and validation of satellite based estimates of surface visibility

    Science.gov (United States)

    Brunner, J.; Pierce, R. B.; Lenzen, A.

    2015-10-01

    A satellite based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5% for classifying Clear (V ≥ 30 km), Moderate (10 km ≤ V skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  4. Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms

    Science.gov (United States)

    Yao, Yunjun; Liang, Shunlin; Yu, Jian; Zhao, Shaohua; Lin, Yi; Jia, Kun; Zhang, Xiaotong; Cheng, Jie; Xie, Xianhong; Sun, Liang; Wang, Xuanyu; Zhang, Lilin

    2017-04-01

    Accurate estimates of terrestrial latent heat of evaporation (LE) for different biomes are essential to assess energy, water and carbon cycles. Different satellite- based Priestley-Taylor (PT) algorithms have been developed to estimate LE in different biomes. However, there are still large uncertainties in LE estimates for different PT algorithms. In this study, we evaluated differences in estimating terrestrial water flux in different biomes from three satellite-based PT algorithms using ground-observed data from eight eddy covariance (EC) flux towers of China. The results reveal that large differences in daily LE estimates exist based on EC measurements using three PT algorithms among eight ecosystem types. At the forest (CBS) site, all algorithms demonstrate high performance with low root mean square error (RMSE) (less than 16 W/m2) and high squared correlation coefficient (R2) (more than 0.9). At the village (HHV) site, the ATI-PT algorithm has the lowest RMSE (13.9 W/m2), with bias of 2.7 W/m2 and R2 of 0.66. At the irrigated crop (HHM) site, almost all models algorithms underestimate LE, indicating these algorithms may not capture wet soil evaporation by parameterization of the soil moisture. In contrast, the SM-PT algorithm shows high values of R2 (comparable to those of ATI-PT and VPD-PT) at most other (grass, wetland, desert and Gobi) biomes. There are no obvious differences in seasonal LE estimation using MODIS NDVI and LAI at most sites. However, all meteorological or satellite-based water-related parameters used in the PT algorithm have uncertainties for optimizing water constraints. This analysis highlights the need to improve PT algorithms with regard to water constraints.

  5. Eliminating Obliquity Error from the Estimation of Ionospheric Delay in a Satellite-Based Augmentation System

    Science.gov (United States)

    Sparks, Lawrence

    2013-01-01

    Current satellite-based augmentation systems estimate ionospheric delay using algorithms that assume the electron density of the ionosphere is non-negligible only in a thin shell located near the peak of the actual profile. In its initial operating capability, for example, the Wide Area Augmentation System incorporated the thin shell model into an estimation algorithm that calculates vertical delay using a planar fit. Under disturbed conditions or at low latitude where ionospheric structure is complex, however, the thin shell approximation can serve as a significant source of estimation error. A recent upgrade of the system replaced the planar fit algorithm with an algorithm based upon kriging. The upgrade owes its success, in part, to the ability of kriging to mitigate the error due to this approximation. Previously, alternative delay estimation algorithms have been proposed that eliminate the need for invoking the thin shell model altogether. Prior analyses have compared the accuracy achieved by these methods to the accuracy achieved by the planar fit algorithm. This paper extends these analyses to include a comparison with the accuracy achieved by kriging. It concludes by examining how a satellite-based augmentation system might be implemented without recourse to the thin shell approximation.

  6. Characterization of satellite based proxies for estimating nucleation mode particles over South Africa

    Directory of Open Access Journals (Sweden)

    A.-M. Sundström

    2014-10-01

    Full Text Available In this work satellite observations from the NASA's A-Train constellation were used to derive the values of primary emission and regional nucleation proxies over South Africa to estimate the potential for new particle formation. As derived in Kulmala et al. (2011, the satellite based proxies consist of source terms (NO2, SO2 and UV-B radiation, and a sink term describing the pre-existing aerosols. The first goal of this work was to study in detail the use of satellite aerosol optical depth (AOD as a substitute to the in situ based condensation sink (CS. One of the major factors affecting the agreement of CS and AOD was the elevated aerosol layers that increased the value of column integrated AOD but not affected the in situ CS. However, when the AOD in the proxy sink was replaced by an estimate from linear bivariate fit between AOD and CS, the agreement with the actual nucleation mode number concentration improved somewhat. The second goal of the work was to estimate how well the satellite based proxies can predict the potential for new particle formation. For each proxy the highest potential for new particle formation were observed over the Highveld industrial area, where the emissions were high but the sink due to pre-existing aerosols was relatively low. Best agreement between the satellite and in situ based proxies were obtained for NO2/AOD and UV-B/AOD2, whereas proxies including SO2 in the source term had lower correlation. Even though the OMI SO2 boundary layer product showed reasonable spatial pattern and detected the major sources over the study area, some of the known minor point sources were not detected. When defining the satellite proxies only for days when new particle formation event was observed, it was seen that for all the satellite based proxies the event day medians were higher than the entire measurement period median.

  7. Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, M.; Gotseff, P.

    2013-12-01

    This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.

  8. Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

    Science.gov (United States)

    Yang, Zhongwen; Hsu, Kuolin; Sorooshian, Soroosh; Xu, Xinyi; Braithwaite, Dan; Verbist, Koen M. J.

    2016-04-01

    Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009-2014. The historical data (satellite and gauge) for 2009-2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide.

  9. Bias reduction for Satellite Based Precipitation Estimates using statistical transformations in Guiana Shield

    Science.gov (United States)

    Ringard, Justine; Becker, Melanie; Seyler, Frederique; Linguet, Laurent

    2016-04-01

    Currently satellite-based precipitation estimates exhibit considerable biases, and there have been many efforts to reduce these biases by merging surface gauge measurements with satellite-based estimates. In Guiana Shield all products exhibited better performances during the dry season (August- December). All products greatly overestimate very low intensities (50 mm). Moreover the responses of each product are different according to hydro climatic regimes. The aim of this study is to correct spatially the bias of precipitation, and compare various correction methods to define the best methods depending on the rainfall characteristic correcting (intensity, frequency). Four satellites products are used: Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product (3B42V7) and real time product (3B42RT), the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network (PERSIANN) and the NOAA Climate Prediction Center (CPC) Morphing technique (CMORPH), for six hydro climatic regimes between 2001 and 2012. Several statistical transformations are used to correct the bias. Statistical transformations attempt to find a function h that maps a simulated variable Ps such that its new distribution equals the distribution of the observed variable Po. The first is the use of a distribution derived transformations which is a mixture of the Bernoulli and the Gamma distribution, where the Bernoulli distribution is used to model the probability of precipitation occurrence and the Gamma distribution used to model precipitation intensities. The second a quantile-quantile relation using parametric transformation, and the last one is a common approach using the empirical CDF of observed and modelled values instead of assuming parametric distributions. For each correction 30% of both, simulated and observed data sets, are used to calibrate and the other part used to validate. The validation are test with statistical

  10. Estimating crop yield using a satellite-based light use efficiency model

    DEFF Research Database (Denmark)

    Yuan, Wenping; Chen, Yang; Xia, Jiangzhou

    2016-01-01

    for simulating crops’ GPP. At both irrigated and rainfed sites, the EC-LUE model exhibits a similar level of performance. However, large errors are found when simulating yield based on crop harvest index. This analysis highlights the need to improve the representation of the harvest index and carbon allocation...... primary production (GPP) and yield of crops. The EC-LUE model can explain on average approximately 90% of the variability in GPP for 36 FLUXNET sites globally. The results indicate that a universal set of parameters, independent of crop species (except for C4 crops), can be adopted in the EC-LUE model...... for improving crop yield estimations from satellite-based methods....

  11. Evaluation of satellite-based precipitation estimates in winter season using an object-based approach

    Science.gov (United States)

    Li, J.; Hsu, K.; AghaKouchak, A.; Sorooshian, S.

    2012-12-01

    Verification has become an integral component of satellite precipitation algorithms and products. A number of object-based verification methods have been proposed to provide diagnostic information regarding the precipitation products' ability to capture the spatial pattern, intensity, and placement of precipitation. However, most object-based methods are not capable of investigating precipitation objects at the storm-scale. In this study, an image processing approach known as watershed segmentation was adopted to detect the storm-scale rainfall objects. Then, a fuzzy logic-based technique was utilized to diagnose and analyze storm-scale object attributes, including centroid distance, area ratio, intersection area ratio and orientation angle difference. Three verification metrics (i.e., false alarm ratio, missing ratio and overall membership score) were generated for validation and verification. Three satellite-based precipitation products, including PERSIANN, CMORPH, 3B42RT, were evaluated against NOAA stage IV MPE multi-sensor composite rain analysis at 0.25° by 0.25° on a daily scale in the winter season of 2010 over the contiguous United States. Winter season is dominated by frontal systems which usually have larger area coverage. All three products and the stage IV observation tend to find large size storm objects. With respect to the evaluation attributes, PERSIANN tends to obtain larger area ratio and consequently has larger centroid distance to the stage IV observations, while 3B42RT are found to be closer to the stage IV for the object size. All evaluation products give small orientation angle differences but vary significantly for the missing ratio and false alarm ratio. This implies that satellite estimates can fail to detect storms in winter. The overall membership scores are close for all three different products which indicate that all three satellite-based precipitation products perform well for capturing the spatial and geometric characteristics of

  12. Comparison of Historical Satellite-Based Estimates of Solar Radiation Resources with Recent Rotating Shadowband Radiometer Measurements: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Myers, D. R.

    2009-03-01

    The availability of rotating shadow band radiometer measurement data at several new stations provides an opportunity to compare historical satellite-based estimates of solar resources with measurements. We compare mean monthly daily total (MMDT) solar radiation data from eight years of NSRDB and 22 years of NASA hourly global horizontal and direct beam solar estimates with measured data from three stations, collected after the end of the available resource estimates.

  13. South African Weather Service operational satellite based precipitation estimation technique: applications and improvements

    Directory of Open Access Journals (Sweden)

    E. de Coning

    2010-11-01

    Full Text Available Extreme weather related to heavy or more frequent precipitation events seem to be a likely possibility for the future of our planet. While precipitation measurements can be done by means of rain gauges, the obvious disadvantages of point measurements are driving meteorologists towards remotely sensed precipitation methods. In South Africa more sophisticated and expensive nowcasting technology such as radar and lightning networks are available, supported by a fairly dense rain gauge network of about 1500 gauges. In the rest of southern Africa rainfall measurements are more difficult to obtain. The availability of the local version of the Unified Model and the Meteosat Second Generation satellite data make these products ideal components of precipitation measurement in data sparse regions such as Africa. In this article the local version of the Hydroestimator (originally from NOAA/NESDIS is discussed as well as its applications for precipitation measurement in this region. Hourly accumulations of the Hydroestimator are currently used as a satellite based precipitation estimator for the South African Flash Flood Guidance system. However, the Hydroestimator is by no means a perfect representation of the real rainfall. In this study the Hydroestimator and the stratiform rainfall field from the Unified Model are both bias corrected and then combined into a new precipitation field which can feed into the South African Flash Flood Guidance system. This new product should provide a more accurate and comprehensive input to the Flash Flood Guidance systems in South Africa as well as southern Africa. In this way the southern African region where data is sparse and very few radars are available can have access to more accurate flash flood guidance.

  14. Satellite-based Estimates of Ambient Air Pollution and Global Variations in Childhood Asthma Prevalence

    Science.gov (United States)

    Anderson, H. Ross; Butland, Barbara K.; Donkelaar, Aaron Matthew Van; Brauer, Michael; Strachan, David P.; Clayton, Tadd; van Dingenen, Rita; Amann, Marcus; Brunekreef, Bert; Cohen, Aaron; Dentener, Frank; Lai, Christopher; Lamsal, Lok N.; Martin, Randall V.

    2012-01-01

    Background: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear. Objectives: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001-2003). Results: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was -0.043 [95% confidence interval (CI): -0.139, 0.053] and 0.017 (95% CI: -0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was -0.116 (95% CI: -0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was -0.139 (95% CI: -0.347, 0.068). The corresponding association with ozone (per ppbV) was -0.171 (95% CI: -0.275, -0.067). Conclusion: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level.

  15. Assessing the utility of satellite-based whitecap fraction to estimate sea spray production and CO2 transfer velocity

    Science.gov (United States)

    Anguelova, M. D.

    2016-05-01

    The utility of a satellite-based whitecap database for estimates of surface sea spray production and bubble-mediated gas transfer on a global scale is presented. Existing formulations of sea spray production and bubble-mediated CO2 transfer velocity involve whitecap fraction parametrization as a function of wind speed at 10 m reference height W(U 10) based on photographic measurements of whitecaps. Microwave radiometric measurements of whitecaps from satellites provide whitecap fraction data over the world oceans for all seasons. Parametrizations W(U 10) based on such radiometric data are thus applicable for a wide range of conditions and can account for influences secondary to the primary forcing factor, the wind speed. Radiometric satellite-based W(U 10) relationship was used as input to: (i) the Coupled Ocean-Atmosphere Response Experiment Gas transfer (COAREG) algorithm to obtain CO2 transfer velocity and total CO2 flux; and (ii) the sea spray source function (SSSF) recommended by Andreas in 2002 to obtain fluxes of sea spray number and mass. The outputs of COAREG and SSSF obtained with satellite-based W(U 10) are compared with respective outputs obtained with the nominal W(U 10) relationship based on photographic data. Good comparisons of the gas and sea spray fluxes with direct measurements and previous estimates imply that the satellite- based whitecap database can be useful to obtain surface fluxes of particles and gases in regions and conditions difficult to access and sample in situ. Satellite and in situ estimates of surface sea spray production and bubble-mediated gas transfer thus complement each other: accurate in situ observations can constrain radiometric whitecap fraction and mass flux estimates, while satellite observations can provide global coverage of whitecap fraction and mass flux estimates.

  16. Using satellite-based evapotranspiration estimates to improve the structure of a simple conceptual rainfall-runoff model

    Science.gov (United States)

    Roy, Tirthankar; Gupta, Hoshin V.; Serrat-Capdevila, Aleix; Valdes, Juan B.

    2017-02-01

    Daily, quasi-global (50° N-S and 180° W-E), satellite-based estimates of actual evapotranspiration at 0.25° spatial resolution have recently become available, generated by the Global Land Evaporation Amsterdam Model (GLEAM). We investigate the use of these data to improve the performance of a simple lumped catchment-scale hydrologic model driven by satellite-based precipitation estimates to generate streamflow simulations for a poorly gauged basin in Africa. In one approach, we use GLEAM to constrain the evapotranspiration estimates generated by the model, thereby modifying daily water balance and improving model performance. In an alternative approach, we instead change the structure of the model to improve its ability to simulate actual evapotranspiration (as estimated by GLEAM). Finally, we test whether the GLEAM product is able to further improve the performance of the structurally modified model. Results indicate that while both approaches can provide improved simulations of streamflow, the second approach also improves the simulation of actual evapotranspiration significantly, which substantiates the importance of making diagnostic structural improvements to hydrologic models whenever possible.

  17. Air-sea fluxes and satellite-based estimation of water masses formation

    Science.gov (United States)

    Sabia, Roberto; Klockmann, Marlene; Fernandez-Prieto, Diego; Donlon, Craig

    2015-04-01

    Recent work linking satellite-based measurements of sea surface salinity (SSS) and sea surface temperature (SST) with traditional physical oceanography has demonstrated the capability of generating routinely satellite-derived surface T-S diagrams [1] and analyze the distribution/dynamics of SSS and its relative surface density with respect to in-situ measurements. Even more recently [2,3], this framework has been extended by exploiting these T-S diagrams as a diagnostic tool to derive water masses formation rates and areas. A water mass describes a water body with physical properties distinct from the surrounding water, formed at the ocean surface under specific conditions which determine its temperature and salinity. The SST and SSS (and thus also density) at the ocean surface are largely determined by fluxes of heat and freshwater. The surface density flux is a function of the latter two and describes the change of the density of seawater at the surface. To obtain observations of water mass formation is of great interest, since they serve as indirect observations of the thermo-haline circulation. The SSS data which has become available through the SMOS [4] and Aquarius [5] satellite missions will provide the possibility of studying also the effect of temporally-varying SSS fields on water mass formation. In the present study, the formation of water masses as a function of SST and SSS is derived from the surface density flux by integrating the latter over a specific area and time period in bins of SST and SSS and then taking the derivative of the total density flux with respect to density. This study presents a test case using SMOS SSS, OSTIA SST, as well as Argo ISAS SST and SSS for comparison, heat fluxes from the NOCS Surface Flux Data Set v2.0, OAFlux evaporation and CMORPH precipitation. The study area, initially referred to the North Atlantic, is extended over two additional ocean basins and the study period covers the 2011-2012 timeframe. Yearly, seasonal

  18. Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

    Science.gov (United States)

    Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

    2017-08-01

    Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM2.5 is a promising way to fill the areas that are not covered by ground PM2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R(2) = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM2.5 estimates.

  19. Development and validation of satellite-based estimates of surface visibility

    Science.gov (United States)

    Brunner, J.; Pierce, R. B.; Lenzen, A.

    2016-02-01

    A satellite-based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5 % for classifying clear (V ≥ 30 km), moderate (10 km ≤ V skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear-sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

  20. Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

    Science.gov (United States)

    Olson, William S.; Grecu, Mircea; Yang, Song; Tao, Wei-Kuo

    2004-01-01

    In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression

  1. Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

    Science.gov (United States)

    Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

    2017-07-01

    Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

  2. Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

    Science.gov (United States)

    Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

    2016-12-01

    Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

  3. Estimating Particulate Matter using satellite based aerosol optical depth and meteorological variables in Malaysia

    Science.gov (United States)

    Kamarul Zaman, Nurul Amalin Fatihah; Kanniah, Kasturi Devi; Kaskaoutis, Dimitris G.

    2017-09-01

    The insufficient number of ground-based stations for measuring Particulate Matter training are performed via comparison with measured PM10 at 29 stations over Malaysia and reveal that the ANN provides slightly higher accuracy with R2 = 0.71 and RMSE = 11.61 μg m- 3 compared to the MLR method (R2 = 0.66 and RMSE = 12.39 μg m- 3). Stepwise regression analysis performed on the MLR method reveals that the MODIS AOD550 is the most important parameter for PM10 estimations (R2 = 0.59 and RMSE = 13.61 μg m- 3); however, the inclusion of the meteorological parameters in the MLR increases the accuracy of the retrievals (R2 = 0.66, RMSE = 12.39 μg m- 3). The estimated PM10 concentrations are finally validated against surface measurements at 16 stations resulting in similar performance from the ANN model (R2 = 0.58, RMSE = 10.16 μg m- 3) and MLR technique (R2 = 0.56, RMSE = 10.58 μg m- 3). The significant accuracy that has been attained in PM10 estimations from space allows us to assess the pollution levels in Malaysia and map the PM10 distribution at large spatial and temporal scales. Supplementary Figure 2: Seasonal-mean Terra-MODIS AOD550 values at 10 x 10 km over the 45 air-pollution monitoring stations in Malaysia during 2007 - 2011 for (a) dry season (June - September), (b) wet season (November - March), (c) April - May and (d) October.

  4. Carbon export fluxes in the Southern Ocean: results from inverse modeling and comparison with satellite-based estimates

    Science.gov (United States)

    Schlitzer, Reiner

    The use of dissolved nutrients and carbon for photosynthesis in the euphotic zone and the subsequent downward transport of particulate and dissolved organic material strongly affect carbon concentrations in surface water and thus the air-sea exchange of CO 2. Efforts to quantify the downward carbon flux for the whole ocean or on basin-scales are hampered by the sparseness of direct productivity or flux measurements. Here, a global ocean circulation, biogeochemical model is used to determine rates of export production and vertical carbon fluxes in the Southern Ocean. The model exploits the existing large sets of hydrographic, oxygen, nutrient and carbon data that contain information on the underlying biogeochemical processes. The model is fitted to the data by systematically varying circulation, air-sea fluxes, production, and remineralization rates simultaneously. Use of the adjoint method yields model property simulations that are in very good agreement with measurements. In the model, the total integrated export flux of particulate organic matter necessary for the realistic reproduction of nutrient data is significantly larger than export estimates derived from primary productivity maps. Of the 10,000 TgC yr -1(10 GtC yr -1) required globally, the Southern Ocean south of 30°S contributes about 3000 TgC yr -1 (33%), most of it occurring in a zonal belt along the Antarctic Circumpolar Current and in the Peru, Chile and Namibia coastal upwelling regions. The export flux of POC for the area south of 50°S amounts to 1000±210 TgC yr -1, and the particle flux in 1000 m for the same area is 115±20 TgC yr -1. Unlike for the global ocean, the contribution of the downward flux of dissolved organic carbon is significant in the Southern Ocean in the top 500 m of the water column. Comparison with satellite-based productivity estimates (CZCS and SeaWiFS) shows a relatively good agreement over most of the ocean except for the Southern Ocean south of 50°S, where the model

  5. Estimating Total Discharge in the Yangtze River Basin Using Satellite-Based Observations

    Directory of Open Access Journals (Sweden)

    Samuel A. Andam‑Akorful

    2013-07-01

    Full Text Available The measurement of total basin discharge along coastal regions is necessary for understanding the hydrological and oceanographic issues related to the water and energy cycles. However, only the observed streamflow (gauge-based observation is used to estimate the total fluxes from the river basin to the ocean, neglecting the portion of discharge that infiltrates to underground and directly discharges into the ocean. Hence, the aim of this study is to assess the total discharge of the Yangtze River (Chang Jiang basin. In this study, we explore the potential response of total discharge to changes in precipitation (from the Tropical Rainfall Measuring Mission—TRMM, evaporation (from four versions of the Global Land Data Assimilation—GLDAS, namely, CLM, Mosaic, Noah and VIC, and water-storage changes (from the Gravity Recovery and Climate Experiment—GRACE by using the terrestrial water budget method. This method has been validated by comparison with the observed streamflow, and shows an agreement with a root mean square error (RMSE of 14.30 mm/month for GRACE-based discharge and 20.98 mm/month for that derived from precipitation minus evaporation (P − E. This improvement of approximately 32% indicates that monthly terrestrial water-storage changes, as estimated by GRACE, cannot be considered negligible over Yangtze basin. The results for the proposed method are more accurate than the results previously reported in the literature.

  6. A Novel Sampling Method for Satellite-Based Offshore Wind Resource Estimation

    DEFF Research Database (Denmark)

    Badger, Merete; Badger, Jake; Hasager, Charlotte Bay

    Synthetic aperture radar (SAR) measurements from satellites can be used to estimate the spatial wind speed variation offshore in great detail. The radar senses cm-scale roughness at the sea surface which can be translated to wind speed at the height 10 m using an empirical geophysical model......-based wind climatology have improved gradually as more data were collected. The satellite scenes have been treated as random samples and weighted equally in our previous analyses. Here we introduce a novel sampling strategy based on the wind class methodology that is normally applied in numerical modeling...... climatologically representative large-scale meteorological conditions for the region of interest. The wind classes are used to make the most representative selection of satellite images from the ENVISAT image catalogue. A minimum of one satellite image is chosen per wind class. The frequency of occurrence of each...

  7. Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau

    Science.gov (United States)

    Peng, Jian; Loew, Alexander; Chen, Xuelong; Ma, Yaoming; Su, Zhongbo

    2016-08-01

    The Tibetan Plateau (TP) plays a major role in regional and global climate. The understanding of latent heat (LE) flux can help to better describe the complex mechanisms and interactions between land and atmosphere. Despite its importance, accurate estimation of evapotranspiration (ET) over the TP remains challenging. Satellite observations allow for ET estimation at high temporal and spatial scales. The purpose of this paper is to provide a detailed cross-comparison of existing ET products over the TP. Six available ET products based on different approaches are included for comparison. Results show that all products capture the seasonal variability well with minimum ET in the winter and maximum ET in the summer. Regarding the spatial pattern, the High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) ET demonstrator dataset is very similar to the LandFlux-EVAL dataset (a benchmark ET product from the Global Energy and Water Cycle Experiment), with decreasing ET from the south-east to north-west over the TP. Further comparison against the LandFlux-EVAL over different sub-regions that are decided by different intervals of normalised difference vegetation index (NDVI), precipitation, and elevation reveals that HOLAPS agrees best with LandFlux-EVAL having the highest correlation coefficient (R) and the lowest root mean square difference (RMSD). These results indicate the potential for the application of the HOLAPS demonstrator dataset in understanding the land-atmosphere-biosphere interactions over the TP. In order to provide more accurate ET over the TP, model calibration, high accuracy forcing dataset, appropriate in situ measurements as well as other hydrological data such as runoff measurements are still needed.

  8. Satellite-based estimate of aerosol direct radiative effect over the South-East Atlantic

    Directory of Open Access Journals (Sweden)

    L. Costantino

    2013-09-01

    Full Text Available The net effect of aerosol Direct Radiative Forcing (DRF is the balance between the scattering effect that reflects solar radiation back to space (cooling, and the absorption that decreases the reflected sunlight (warming. The amplitude of these two effects and their balance depends on the aerosol load, its absorptivity, the cloud fraction and the respective position of aerosol and cloud layers. In this study, we use the information provided by CALIOP (CALIPSO satellite and MODIS (AQUA satellite instruments as input data to a Rapid Radiative Transfer Model (RRTM and quantify the shortwave (SW aerosol direct atmospheric forcing, over the South-East Atlantic. The combination of the passive and active measurements allows estimates of the horizontal and vertical distributions of the aerosol and cloud parameters. We use a parametrization of the Single Scattering Albedo (SSA based on the satellite-derived Angstrom coefficient. The South East Atlantic is a particular region, where bright stratocumulus clouds are often topped by absorbing smoke particles. Results from radiative transfer simulations confirm the similar amplitude of the cooling effect, due to light scattering by the aerosols, and the warming effect, due to the absorption by the same particles. Over six years of satellite retrievals, from 2005 to 2010, the South-East Atlantic all-sky SW DRF is −0.03 W m−2, with a spatial standard deviation of 8.03 W m−2. In good agreement with previous estimates, statistics show that a cloud fraction larger than 0.5 is generally associated with positive all-sky DRF. In case of cloudy-sky and aerosol located only above the cloud top, a SSA larger than 0.91 and cloud optical thickness larger than 4 can be considered as threshold values, beyond which the resulting radiative forcing becomes positive.

  9. Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

    Directory of Open Access Journals (Sweden)

    B. Ford

    2015-09-01

    Full Text Available The negative impacts of fine particulate matter (PM2.5 exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the datasets and methodology. Satellite observations of aerosol optical depth (AOD have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and datasets, and explain sources of discrepancies among values in the literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model. We contrast results in the United States and China for the years 2004–2011. We estimate that in the United States, exposure to PM2.5 accounts for approximately 4 % of total deaths compared to 22 % in China (using satellite-based exposure, which falls within the range of previous estimates. The difference in estimated mortality burden based solely on a global model vs. that derived from satellite is approximately 9 % for the US and 4 % for China on a nationwide basis, although regionally the differences can be much greater. This difference is overshadowed by the uncertainty in the methodology for deriving PM2.5 burden from satellite observations, which we quantify to be on order of 20 % due to uncertainties in the AOD-to-surface-PM2.5 relationship, 10 % due to the satellite observational uncertainty, and 30 % or greater uncertainty associated with the application of concentration response functions to estimated exposure.

  10. Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

    Science.gov (United States)

    Ford, Bonne; Heald, Colette L.

    2016-03-01

    The negative impacts of fine particulate matter (PM2.5) exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the data sets and methodology. Satellite observations of aerosol optical depth (AOD) have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and data sets, and explain sources of discrepancies among values in the literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model. We contrast results in the United States and China for the years 2004-2011. Using the Burnett et al. (2014) integrated exposure response function, we estimate that in the United States, exposure to PM2.5 accounts for approximately 2 % of total deaths compared to 14 % in China (using satellite-based exposure), which falls within the range of previous estimates. The difference in estimated mortality burden based solely on a global model vs. that derived from satellite is approximately 14 % for the US and 2 % for China on a nationwide basis, although regionally the differences can be much greater. This difference is overshadowed by the uncertainty in the methodology for deriving PM2.5 burden from satellite observations, which we quantify to be on the order of 20 % due to uncertainties in the AOD-to-surface-PM2.5 relationship, 10 % due to the satellite observational uncertainty, and 30 % or greater uncertainty associated with the application of concentration response functions to estimated exposure.

  11. Satellite based classification (haze, fog) and affected area estimation over Indo - Pak Sub-Continent

    Science.gov (United States)

    Ghauri, Badar; Zafar, Sumaira

    2016-07-01

    Northern Pakistan and bordering Indian Punjab experience intense smog and fog during fall and winters. Environmentalists have been raising their voices over the situation and demanded control over regional emissions to save the livelihood of millions of dwellers whose trade, commerce and agriculture is at stake because of long smog/ fog spells.. This paper estimates the area affected by haze, smog and fog during 2006- 2010. MODIS (geo-referenced MODIS subsets India1, 2 &3) of the area in Pakistan and India from 2006 to 2010 for the period October to February) were analyzed using state of the art software ENVI 4.2 and ArcGIS 10.2. This process resulted in area belonging to each class that is; haze, smog and fog. On the basis of density, haze and fog cover was determined. Variations in fog cover, its density and identification of location of fog initiation process were also determined using near real time (30 minutes) METEOSAT-7 IODC data where actually fog formation started and then extended to the area of favorable conditions. Haze has been noticed to intensify due to massive burning of agricultural waste (rice husk) in India and Pakistan towards the end of October each year. MODIS thermal anomalies/fire data (MYD 14) were also used to verify this activity on the ground, which results in hazy conditions at regional level during fall months. Haze-affected area during 2006 to 2010 in Pakistan ranged from 155,000 Km2 to 354,000 Km2 and in India it ranged from 333,000 Km2 to 846,000 Km2. Similarly winter fog cover during this period in Pakistan varied from 136,000 Km2 to 381,000 Km2 and in India it was estimated at 327,000 Km2 to 566,000 Km2. This phenomenon was more prominent in India than in Pakistan where and fog cover was at least twice than that was observed in Pakistan. It has been noted that area covered by fog, smog and haze doubled during the study period in the region. Atmospheric dimming during autumn/ fall also reduces the mixing height leading to greater

  12. A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE for Satellite-Based Actual Evapotranspiration Estimation

    Directory of Open Access Journals (Sweden)

    Hua Zhang

    2016-09-01

    Full Text Available The estimation of spatially-variable actual evapotranspiration (AET is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE, to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges. Compared to traditional triangle methods, TAVE introduces three unique features: (i the discretization of the domain as overlapping elevation zones; (ii a variable wet edge that is a function of elevation zone; and (iii variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA and a global AET product (MOD16 over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%, in contrast to substantial overestimation by TA (+234% and underestimation by MOD16 (−50%. In forested (non-irrigated, water consuming regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

  13. Satellite-based estimates of light-use efficiency in a subtropical mangrove forest equipped with CO2 eddy covariance

    Directory of Open Access Journals (Sweden)

    D. O. Fuller

    2012-11-01

    Full Text Available Despite the importance of mangrove ecosystems in the global carbon budget, the relationships between environmental drivers and carbon dynamics in these forests remain poorly understood. This limited understanding is partly a result of the challenges associated with in situ flux studies. Tower-based carbon dioxide eddy covariance (EC systems are installed in only a few mangrove forests worldwide and the longest EC record from the Florida Everglades contains less than 9 yr of observations. A primary goal of the present study was to develop a methodology to estimate canopy-scale photosynthetic light use efficiency in this forest. These tower-based observations represent a basis for associating CO2 fluxes with canopy light use properties, and thus provide the means for utilizing satellite-based reflectance data for larger-scale investigations. We present a model for mangrove canopy light use efficiency utilizing the enhanced green vegetation index (EVI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS that is capable of predicting changes in mangrove forest CO2 fluxes caused by a hurricane disturbance and changes in regional environmental conditions, including temperature and salinity. Model parameters are solved for in a Bayesian framework. The model structure requires estimates of ecosystem respiration (RE and we present the first-ever tower-based estimates of mangrove forest RE derived from night-time CO2 fluxes. Our investigation is also the first to show the effects of salinity on mangrove forest CO2 uptake, which declines 5% per each 10 parts per thousand (ppt increases in salinity. Light use efficiency in this forest declines with increasing daily photosynthetic active radiation, which is an important departure from the assumption of constant light use efficiency typically applied in satellite-driven models. The model developed here provides a framework for estimating CO2 uptake by these forests from reflectance data and

  14. Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate

    Science.gov (United States)

    Wang, Lei; Sun, Litao; Shrestha, Maheswor; Li, Xiuping; Liu, Wenbin; Zhou, Jing; Yang, Kun; Lu, Hui; Chen, Deliang

    2016-10-01

    In distributed hydrological modeling, surface air temperature (Tair) is of great importance in simulating cold region processes, while the near-surface-air-temperature lapse rate (NLR) is crucial to prepare Tair (when interpolating Tair from site observations to model grids). In this study, a distributed biosphere hydrological model with improved snow physics (WEB-DHM-S) was rigorously evaluated in a typical cold, large river basin (e.g., the upper Yellow River basin), given a mean monthly NLRs. Based on the validated model, we have examined the influence of the NLR on the simulated snow processes and streamflows. We found that the NLR has a large effect on the simulated streamflows, with a maximum difference of greater than 24% among the various scenarios for NLRs considered. To supplement the insufficient number of monitoring sites for near-surface-air-temperature at developing/undeveloped mountain regions, the nighttime Moderate Resolution Imaging Spectroradiometer land surface temperature is used as an alternative to derive the approximate NLR at a finer spatial scale (e.g., at different elevation bands, different land covers, different aspects, and different snow conditions). Using satellite-based estimation of NLR, the modeling of snow processes has been greatly refined. Results show that both the determination of rainfall/snowfall and the snowpack process were significantly improved, contributing to a reduced summer evapotranspiration and thus an improved streamflow simulation.

  15. Estimation and calibration of observation impact signals using the Lanczos method in NOAA/NCEP data assimilation system

    Directory of Open Access Journals (Sweden)

    M. Wei

    2012-09-01

    Full Text Available Despite the tremendous progress that has been made in data assimilation (DA methodology, observing systems that reduce observation errors, and model improvements that reduce background errors, the analyses produced by the best available DA systems are still different from the truth. Analysis error and error covariance are important since they describe the accuracy of the analyses, and are directly related to the future forecast errors, i.e., the forecast quality. In addition, analysis error covariance is critically important in building an efficient ensemble forecast system (EFS.

    Estimating analysis error covariance in an ensemble-based Kalman filter DA is straightforward, but it is challenging in variational DA systems, which have been in operation at most NWP (Numerical Weather Prediction centers. In this study, we use the Lanczos method in the NCEP (the National Centers for Environmental Prediction Gridpoint Statistical Interpolation (GSI DA system to look into other important aspects and properties of this method that were not exploited before. We apply this method to estimate the observation impact signals (OIS, which are directly related to the analysis error variances. It is found that the smallest eigenvalue of the transformed Hessian matrix converges to one as the number of minimization iterations increases. When more observations are assimilated, the convergence becomes slower and more eigenvectors are needed to retrieve the observation impacts. It is also found that the OIS over data-rich regions can be represented by the eigenvectors with dominant eigenvalues.

    Since only a limited number of eigenvectors can be computed due to computational expense, the OIS is severely underestimated, and the analysis error variance is consequently overestimated. It is found that the mean OIS values for temperature and wind components at typical model levels are increased by about 1.5 times when the number of eigenvectors is doubled

  16. Satellite based radar interferometry to estimate large-scale soil water depletion from clay shrinkage: possibilities and limitations

    NARCIS (Netherlands)

    Brake, te B.; Hanssen, R.F.; Ploeg, van der M.J.; Rooij, de G.H.

    2013-01-01

    Satellite-based radar interferometry is a technique capable of measuring small surface elevation changes at large scales and with a high resolution. In vadose zone hydrology, it has been recognized for a long time that surface elevation changes due to swell and shrinkage of clayey soils can serve as

  17. Satellite based radar interferometry to estimate large-scale soil water depletion from clay shrinkage: possibilities and limitations

    NARCIS (Netherlands)

    Brake, te B.; Hanssen, R.F.; Ploeg, van der M.J.; Rooij, de G.H.

    2013-01-01

    Satellite-based radar interferometry is a technique capable of measuring small surface elevation changes at large scales and with a high resolution. In vadose zone hydrology, it has been recognized for a long time that surface elevation changes due to swell and shrinkage of clayey soils can serve as

  18. Estimation of snowpack matching ground-truth data and MODIS satellite-based observations by using regression kriging

    Science.gov (United States)

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

    2016-04-01

    The estimation of Snow Water Equivalent (SWE) is essential for an appropriate assessment of the available water resources in Alpine catchment. The hydrologic regime in these areas is dominated by the storage of water in the snowpack, which is discharged to rivers throughout the melt season. An accurate estimation of the resources will be necessary for an appropriate analysis of the system operation alternatives using basin scale management models. In order to obtain an appropriate estimation of the SWE we need to know the spatial distribution snowpack and snow density within the Snow Cover Area (SCA). Data for these snow variables can be extracted from in-situ point measurements and air-borne/space-borne remote sensing observations. Different interpolation and simulation techniques have been employed for the estimation of the cited variables. In this paper we propose to estimate snowpack from a reduced number of ground-truth data (1 or 2 campaigns per year with 23 observation point from 2000-2014) and MODIS satellite-based observations in the Sierra Nevada Mountain (Southern Spain). Regression based methodologies has been used to study snowpack distribution using different kind of explicative variables: geographic, topographic, climatic. 40 explicative variables were considered: the longitude, latitude, altitude, slope, eastness, northness, radiation, maximum upwind slope and some mathematical transformation of each of them [Ln(v), (v)^-1; (v)^2; (v)^0.5). Eight different structure of regression models have been tested (combining 1, 2, 3 or 4 explicative variables). Y=B0+B1Xi (1); Y=B0+B1XiXj (2); Y=B0+B1Xi+B2Xj (3); Y=B0+B1Xi+B2XjXl (4); Y=B0+B1XiXk+B2XjXl (5); Y=B0+B1Xi+B2Xj+B3Xl (6); Y=B0+B1Xi+B2Xj+B3XlXk (7); Y=B0+B1Xi+B2Xj+B3Xl+B4Xk (8). Where: Y is the snow depth; (Xi, Xj, Xl, Xk) are the prediction variables (any of the 40 variables); (B0, B1, B2, B3) are the coefficients to be estimated. The ground data are employed to calibrate the multiple regressions. In

  19. NCEP Internal Office Notes

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Centers for Environmental Prediction (NCEP) and its predecessors have produced internal publications, known as Office Notes, since the mid-1950's. In...

  20. Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

    Science.gov (United States)

    Zambrano-Bigiarini, Mauricio; Nauditt, Alexandra; Birkel, Christian; Verbist, Koen; Ribbe, Lars

    2017-03-01

    Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate - for the first time - the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25° grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4-43.7° S) and Central Chile (32.18-36.4° S), in particular at low- and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere

  1. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

    Energy Technology Data Exchange (ETDEWEB)

    Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

    2014-04-01

    Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m-2 yr-1 and total NPP in the range of 318–490 Tg C yr-1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m-2 yr-1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m-2 yr-1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

  2. Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

    Science.gov (United States)

    Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

    2014-01-01

    Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

  3. The relationship between cloud condensation nuclei (CCN concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates

    Directory of Open Access Journals (Sweden)

    Y. Shinozuka

    2015-01-01

    Full Text Available We examine the relationship between the number concentration of boundary-layer cloud condensation nuclei (CCN and light extinction to investigate underlying aerosol processes and satellite-based CCN estimates. Regression applied to a variety of airborne and ground-based measurements identifies the CCN (cm−3 at 0.4 ± 0.1% supersaturation with 100.3α +1.3 σ0.75 where σ (M m−1 is the 500 nm extinction coefficient by dried particles and α is the Angstrom exponent. The deviation of one kilometer horizontal average data from this approximation is typically within a factor of 2.0. ∂ log CCN/∂ log σ is less than unity because, among other explanations, aerosol growth processes generally make particles scatter more light without increasing their number. This, barring extensive data aggregation and special meteorology-aerosol connections, associates doubling of aerosol optical depth with less than doubling of CCN, contrary to common assumptions in satellite-based analysis of aerosol-cloud interactions.

  4. AQA-PM: Extension of the Air-Quality Model For Austria with Satellite based Particulate Matter Estimates

    Science.gov (United States)

    Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Triebnig, Gerhard; Flandorfer, Claudia

    2013-04-01

    Air quality is a key element for the well-being and quality of life of European citizens. Air pollution measurements and modeling tools are essential for assessment of air quality according to EU legislation. The responsibilities of ZAMG as the national weather service of Austria include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. The Air Quality model for Austria (AQA) is operated at ZAMG in cooperation with the University of Natural Resources and Life Sciences in Vienna (BOKU) by order of the regional governments since 2005. AQA conducts daily forecasts of gaseous and particulate (PM10) air pollutants over Austria. In the frame of the project AQA-PM (funded by FFG), satellite measurements of the Aerosol Optical Thickness (AOT) and ground-based PM10-measurements are combined to highly-resolved initial fields using regression- and assimilation techniques. For the model simulations WRF/Chem is used with a resolution of 3 km over the alpine region. Interfaces have been developed to account for the different measurements as input data. The available local emission inventories provided by the different Austrian regional governments were harmonized and used for the model simulations. An episode in February 2010 is chosen for the model evaluation. During that month exceedances of PM10-thresholds occurred at many measurement stations of the Austrian network. Different model runs (only model/only ground stations assimilated/satellite and ground stations assimilated) are compared to the respective measurements. The goal of this project is to improve the PM10-forecasts for Austria with the integration of satellite based measurements and to provide a comprehensive product-platform.

  5. Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

    Science.gov (United States)

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-01-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  6. Tree canopy light interception estimates in almond and a walnut orchards using ground, low flying aircraft, and satellite based methods to improve irrigation scheduling programs.

    Science.gov (United States)

    Rosecrance, R. C.; Johnson, L.; Soderstrom, D.

    2016-12-01

    Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

  7. Tree Canopy Light Interception Estimates in Almond and a Walnut Orchards Using Ground, Low Flying Aircraft, and Satellite Based Methods to Improve Irrigation Scheduling Programs

    Science.gov (United States)

    Rosecrance, Richard C.; Johnson, Lee; Soderstrom, Dominic

    2016-01-01

    Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.

  8. Do agrometeorological data improve optical satellite-based estimations of the herbaceous yield in Sahelian semi-arid ecosystems?

    DEFF Research Database (Denmark)

    Diouf, Abdoul Aziz; Hiernaux, Pierre; Brandt, Martin Stefan;

    2016-01-01

    Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed Photosyn......Quantitative estimates of forage availability at the end of the growing season in rangelands are helpful for pastoral livestock managers and for local, national and regional stakeholders in natural resource management. For this reason, remote sensing data such as the Fraction of Absorbed...... evapotranspiration satellite gridded data to estimate the annual herbaceous yield in the semi-arid areas of Senegal. It showed that a machine-learning model combining FAPAR seasonal metrics with various agrometeorological data provided better estimations of the in situ annual herbaceous yield (R2 = 0.69; RMSE = 483...

  9. Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island

    Directory of Open Access Journals (Sweden)

    Julien Morel

    2014-07-01

    Full Text Available Estimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1 an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2 the Kumar-Monteith efficiency model, and (3 a forced-coupling method with a sugarcane crop model (MOSICAS and satellite-derived fraction of absorbed photosynthetically active radiation. These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t∙ha−1. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. The main limitation is the acquisition of a minimum of five satellite images. The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.

  10. Understanding satellite-based monthly-to-seasonal reservoir outflow estimation as a function of hydrologic controls

    Science.gov (United States)

    Bonnema, Matthew; Sikder, Safat; Miao, Yabin; Chen, Xiaodong; Hossain, Faisal; Ara Pervin, Ismat; Mahbubur Rahman, S. M.; Lee, Hyongki

    2016-05-01

    Growing population and increased demand for water is causing an increase in dam and reservoir construction in developing nations. When rivers cross international boundaries, the downstream stakeholders often have little knowledge of upstream reservoir operation practices. Satellite remote sensing in the form of radar altimetry and multisensor precipitation products can be used as a practical way to provide downstream stakeholders with the fundamentally elusive upstream information on reservoir outflow needed to make important and proactive water management decisions. This study uses a mass balance approach of three hydrologic controls to estimate reservoir outflow from satellite data at monthly and annual time scales: precipitation-induced inflow, evaporation, and reservoir storage change. Furthermore, this study explores the importance of each of these hydrologic controls to the accuracy of outflow estimation. The hydrologic controls found to be unimportant could potentially be neglected from similar future studies. Two reservoirs were examined in contrasting regions of the world, the Hungry Horse Reservoir in a mountainous region in northwest U.S. and the Kaptai Reservoir in a low-lying, forested region of Bangladesh. It was found that this mass balance method estimated the annual outflow of both reservoirs with reasonable skill. The estimation of monthly outflow from both reservoirs was however less accurate. The Kaptai basin exhibited a shift in basin behavior resulting in variable accuracy across the 9 year study period. Monthly outflow estimation from Hungry Horse Reservoir was compounded by snow accumulation and melt processes, reflected by relatively low accuracy in summer and fall, when snow processes control runoff. Furthermore, it was found that the important hydrologic controls for reservoir outflow estimation at the monthly time scale differs between the two reservoirs, with precipitation-induced inflow being the most important control for the Kaptai

  11. Comparison of NCEP performance specifications for triglycerides, HDL-, and LDL-cholesterol with operating specifications based on NCEP clinical and analytical goals.

    Science.gov (United States)

    Fallest-Strobl, P C; Olafsdottir, E; Wiebe, D A; Westgard, J O

    1997-11-01

    The National Cholesterol Education Program (NCEP) performance specifications for methods that measure triglycerides, HDL-cholesterol, and LDL-cholesterol have been evaluated by deriving operating specifications from the NCEP analytical total error requirements and the clinical requirements for interpretation of the tests. We determined the maximum imprecision and inaccuracy that would be allowable to control routine methods with commonly used single and multirule quality-control procedures having 2 and 4 control measurements per run, and then compared these estimates with the NCEP guidelines. The NCEP imprecision specifications meet the operating imprecision necessary to assure meeting the NCEP clinical quality requirements for triglycerides and HDL-cholesterol but not for LDL-cholesterol. More importantly, the NCEP imprecision specifications are not adequate to assure meeting the NCEP analytical total error requirements for any of these three tests. Our findings indicate that the NCEP recommendations fail to adequately consider the quality-control requirements necessary to detect medically important systematic errors.

  12. Blending Model Output with satellite-based and in-situ observations to produce high-resolution estimates of population exposure to wildfire smoke

    Science.gov (United States)

    Lassman, William

    In the western US, emissions from wildfires and prescribed fire have been associated with degradation of regional air quality. Whereas atmospheric aerosol particles with aerodynamic diameters less than 2.5 mum (PM2.5) have known impacts on human health, there is uncertainty in how particle composition, concentrations, and exposure duration impact the associated health response. Due to changes in climate and land-management, wildfires have increased in frequency and severity, and this trend is expected to continue. Consequently, wildfires are expected to become an increasingly important source of PM2.5 in the western US. While composition and source of the aerosol is thought to be an important factor in the resulting human health-effects, this is currently not well-understood; therefore, there is a need to develop a quantitative understanding of wildfire-smoke-specific health effects. A necessary step in this process is to determine who was exposed to wildfire smoke, the concentration of the smoke during exposure, and the duration of the exposure. Three different tools are commonly used to assess exposure to wildfire smoke: in-situ measurements, satellite-based observations, and chemical-transport model (CTM) simulations, and each of these exposure-estimation tools have associated strengths and weakness. In this thesis, we investigate the utility of blending these tools together to produce highly accurate estimates of smoke exposure during the 2012 fire season in Washington for use in an epidemiological case study. For blending, we use a ridge regression model, as well as a geographically weighted ridge regression model. We evaluate the performance of the three individual exposure-estimate techniques and the two blended techniques using Leave-One-Out Cross-Validation. Due to the number of in-situ monitors present during this time period, we find that predictions based on in-situ monitors were more accurate for this particular fire season than the CTM simulations and

  13. Satellite based estimates of reduced CO and CO2 emissions due to traffic restrictions during the 2008 Beijing Olympics

    Science.gov (United States)

    Worden, H. M.; Cheng, Y.; Pfister, G.; Carmichael, G. R.; Zhang, Q.; Streets, D. G.; Deeter, M. N.; Edwards, D. P.; Gille, J. C.; Worden, J.

    2012-12-01

    We present estimates of the reductions in CO and CO2 emissions resulting from the control measures on the Beijing transportation sector taken during the 2008 Beijing Olympics. This study used MOPITT (Measurements Of Pollution In The Troposphere) multispectral satellite measurements of near surface CO along with WRF Chem (Weather Research and Forecasting model with Chemistry) simulations for Beijing during August, 2007 and 2008 to estimate changes in CO due to meteorology and emissions. Using fractional changes in the emissions inventory transportation sector along with a reported CO/CO2 emission ratio for Beijing vehicles, we find the corresponding reduction in CO2 emissions. We then compare this reduction to target CO2 emissions in the RCP (representative concentration pathway) scenarios being considered for the IPCC AR5 (Intergovernmental Panel on Climate Change, 5th Assessment Report). Our result suggests that urban traffic reductions could play a significant role in meeting target cuts for global CO2 emissions, even for the most aggressive control scenario (RCP2.6).

  14. Satellite-based estimates of reduced CO and CO2 emissions due to traffic restrictions during the 2008 Beijing Olympics

    Science.gov (United States)

    Worden, Helen M.; Cheng, Yafang; Pfister, Gabriele; Carmichael, Gregory R.; Zhang, Qiang; Streets, David G.; Deeter, Merritt; Edwards, David P.; Gille, John C.; Worden, John R.

    2012-07-01

    During the 2008 Olympics, the Chinese government made a significant effort to improve air quality in Beijing, including restrictions on traffic. Here we estimate the reductions in carbon monoxide (CO) and carbon dioxide (CO2) emissions resulting from the control measures on Beijing transportation. Using MOPITT (Measurements Of Pollution In The Troposphere) multispectral satellite observations of near-surface CO along with WRF-Chem (Weather Research and Forecasting model with Chemistry) simulations for Beijing during August, 2007 and 2008, we estimate changes in CO due to meteorology and transportation sector emissions. Applying a reported CO/CO2 emission ratio for fossil fuels, we find the corresponding reduction in CO2, 60 ± 36 Gg[CO2]/day. As compared to emission scenarios being considered for the IPCC AR5 (Intergovernmental Panel on Climate Change, 5th Assessment Report), this result suggests that urban traffic controls on the Beijing Olympics scale could play a significant role in meeting target reductions for global CO2 emissions.

  15. Assessing the potential of satellite-based precipitation estimates for flood frequency analysis in ungauged or poorly gauged tributaries of China's Yangtze River basin

    Science.gov (United States)

    Gao, Zhen; Long, Di; Tang, Guoqiang; Zeng, Chao; Huang, Jiesheng; Hong, Yang

    2017-07-01

    Flood frequency analysis (FFA) is critical for water resources engineering projects, particularly the design of hydraulic structures such as dams and reservoirs. However, it is often difficult to implement FFA in ungauged or poorly gauged basins because of the lack of consistent and long-term records of streamflow observations. The objective of this study was to evaluate the utility of satellite-based precipitation estimates for performing FFA in two presumably ungauged tributaries, the Jialing and Tuojiang Rivers, of the upper Yangtze River. Annual peak flow series were simulated using the Coupled Routing and Excess STorage (CREST) hydrologic model. Flood frequency was estimated by fitting the Pearson type III distribution of both observed and modeled streamflow with historic floods. Comparison of satellite-based precipitation products with a ground-based daily precipitation dataset for the period 2002-2014 reveals that 3B42V7 outperformed 3B42RT. The 3B42V7 product also shows consistent reliability in streamflow simulation and FFA (e.g., relative errors -20%-5% in the Jialing River). The results also indicate that complex terrain, drainage area, and reservoir construction are important factors that impact hydrologic model performance. The larger basin (156,736 km2) is more likely to produce satisfactory results than the small basin (19,613 km2) under similar circumstances (e.g., Jialing/Tuojiang calibrated by 3B42V7 for the calibration period: NSCE = 0.71/0.56). Using the same calibrated parameter sets from the entire Jialing River basin, the 3B42V7/3B42RT-driven hydrologic model performs better for two tributaries of the Jialing River (e.g., for the calibration period, NSCE = 0.71/0.60 in the Qujiang River basin and 0.54/0.38 in the Fujiang River basin) than for the upper mainstem of the Jialing River (NSCE = 0.34/0.32), which has more cascaded reservoirs with all these tributaries treated as ungauged basins for model validation. Overall, this study underscores

  16. Satellite-based estimation of watershed groundwater storage dynamics in a freeze-thaw area under intensive agricultural development

    Science.gov (United States)

    Ouyang, Wei; Liu, Bing; Wu, Yuyang

    2016-06-01

    Understanding the temporal-spatial characteristics of groundwater storage is critical for agricultural planning and management in the future, thereby causing more challenges in water resource management. However, the special hydrological features of the snow water equivalent, soil moisture, and total canopy water storage in the freeze-thawing agricultural area requires the innovative methods for the water resource analysis. The watershed land cover variation and the expanding pattern of the farmlands over a decade were identified using the TM-Landsat series data. Combined with the traditional measurements of the water resource, the monthly gravity field data from the Gravity Recovery And Climate Experiment (GRACE) was validated and applied. The water resources distribution based on the remotely sensed data demonstrated that the forest in the watershed center had a larger amount of water storage. The inter-annual and seasonal variability of total water storage (TWS) over the agricultural area was analyzed and the higher value appeared in the thawing period of April. The correlations of the TWS streamflow, soil moisture and snow water equivalent with precipitation were all identified. The precipitation was the dominant factor for the watershed TWS and the groundwater dynamics. Under the similar precipitation condition, the lower groundwater storage in recent years was the consequence of the expanding of farmland. The watershed averaged decrease rate of groundwater level from 2003 to 2012 was 1.06 mm/year, which was much lower than the rates in other agricultural areas. The freeze-thawing process with smelt snow and rainfall in summer had more time and chance to recharge the groundwater resource and provided the sustainable water resource. This study proved that the application of GRACE was an effective method for the temporal-spatial estimation of the TWS anomalies in the freeze-thawing agricultural area.

  17. Single-source surface energy balance algorithms to estimate evapotranspiration from satellite-based remotely sensed data

    Science.gov (United States)

    Bhattarai, Nishan

    The flow of water and energy fluxes at the Earth's surface and within the climate system is difficult to quantify. Recent advances in remote sensing technologies have provided scientists with a useful means to improve characterization of these complex processes. However, many challenges remain that limit our ability to optimize remote sensing data in determining evapotranspiration (ET) and energy fluxes. For example, periodic cloud cover limits the operational use of remotely sensed data from passive sensors in monitoring seasonal fluxes. Additionally, there are many remote sensing-based single-source surface energy balance (SEB) models, but no clear guidance on which one to use in a particular application. Two widely used models---surface energy balance algorithm for land (SEBAL) and mapping ET at high resolution with internalized calibration (METRIC)---need substantial human-intervention that limits their applicability in broad-scale studies. This dissertation addressed some of these challenges by proposing novel ways to optimize available resources within the SEB-based ET modeling framework. A simple regression-based Landsat-Moderate Resolution Imaging Spectroradiometer (MODIS) fusion model was developed to integrate Landsat spatial and MODIS temporal characteristics in calculating ET. The fusion model produced reliable estimates of seasonal ET at moderate spatial resolution while mitigating the impact that cloud cover can have on image availability. The dissertation also evaluated five commonly used remote sensing-based single-source SEB models and found the surface energy balance system (SEBS) may be the best overall model for use in humid subtropical climates. The study also determined that model accuracy varies with land cover type, for example, all models worked well for wet marsh conditions, but the SEBAL and simplified surface energy balance index (S-SEBI) models worked better than the alternatives for grass cover. A new automated approach based on

  18. A Satellite-Based Estimation of Evapotranspiration Using Vegetation Index-Temperature Trapezoid Concept: A Case Study in Southern Florida, U.S.A.

    Science.gov (United States)

    Yagci, A. L.; Santanello, J. A., Jr.; Jones, J. W.

    2015-12-01

    One of the key surface variables for hydrological applications, monitoring of natural and anthropogenic water consumption, closing energy balance and water budgets and drought identification is evapotranspiration (ET). There is currently a strong need for high temporal and spatial resolution ET products for climate and hydrological modelers. A satellite-based retrieval method based on vegetation index-temperature trapezoid (VITT) concept has been developed. This model has the ability to generate accurate ET estimates at high temporal and spatial resolutions by taking advantage of key remotely sensed parameters such as vegetation indices (VIs) and land surface temperature (LST) acquired by satellites as well as routinely-measured meteorological variables such as air temperature (Ta) and net radiation. For local-scale applications, the model has been successfully implemented in Python programming language and tested using Landsat satellite products at an eddy covariance flux tower in Florida. It is fully functional and automated such that there is no need of user intervention to run the model. The model development for continental-scale applications using VI and LST products from NASA satellites such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) is currently in progress. The results for local-scale application and early results for continental-scale (US) will be presented and discussed.

  19. Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

    Science.gov (United States)

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

    2015-12-01

    A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each

  20. SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

    Directory of Open Access Journals (Sweden)

    G. Snider

    2014-07-01

    Full Text Available Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5 at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD. We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of global regions, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by an order of magnitude. Initial measurements indicate that the AOD column to PM2.5 ratio is driven temporally primarily by the vertical profile of aerosol scattering; and spatially by a~ more complex interaction

  1. NCEP North American Regional Reanalysis (NARR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NARR dataset is an extension of the NCEP Global Reanalysis which is run over the North American Region. The NARR model uses the very high resolution NCEP Eta...

  2. Satellite-based terrestrial production efficiency modeling

    Directory of Open Access Journals (Sweden)

    Obersteiner Michael

    2009-09-01

    Full Text Available Abstract Production efficiency models (PEMs are based on the theory of light use efficiency (LUE which states that a relatively constant relationship exists between photosynthetic carbon uptake and radiation receipt at the canopy level. Challenges remain however in the application of the PEM methodology to global net primary productivity (NPP monitoring. The objectives of this review are as follows: 1 to describe the general functioning of six PEMs (CASA; GLO-PEM; TURC; C-Fix; MOD17; and BEAMS identified in the literature; 2 to review each model to determine potential improvements to the general PEM methodology; 3 to review the related literature on satellite-based gross primary productivity (GPP and NPP modeling for additional possibilities for improvement; and 4 based on this review, propose items for coordinated research. This review noted a number of possibilities for improvement to the general PEM architecture - ranging from LUE to meteorological and satellite-based inputs. Current PEMs tend to treat the globe similarly in terms of physiological and meteorological factors, often ignoring unique regional aspects. Each of the existing PEMs has developed unique methods to estimate NPP and the combination of the most successful of these could lead to improvements. It may be beneficial to develop regional PEMs that can be combined under a global framework. The results of this review suggest the creation of a hybrid PEM could bring about a significant enhancement to the PEM methodology and thus terrestrial carbon flux modeling. Key items topping the PEM research agenda identified in this review include the following: LUE should not be assumed constant, but should vary by plant functional type (PFT or photosynthetic pathway; evidence is mounting that PEMs should consider incorporating diffuse radiation; continue to pursue relationships between satellite-derived variables and LUE, GPP and autotrophic respiration (Ra; there is an urgent need for

  3. A review of satellite-based methods of estimating live fuel moisture content for fire danger assessment: moving towards operational products

    Science.gov (United States)

    One of the primary variables affecting ignition and spread of wildfire is fuel moisture content (FMC), which is the ratio of water mass to dry mass in living and dead plant material. Because dead FMC may be estimated from available weather data, remote sensing is needed to monitor the spatial distr...

  4. Optimizing Satellite-Based Precipitation Estimation for Nowcasting of Rainfall and Flash Flood Events over the South African Domain

    OpenAIRE

    Estelle de Coning

    2013-01-01

    The South African Weather Service is mandated to issue warnings of hazardous weather events, including those related to heavy precipitation, in order to safeguard life and property. Flooding and flash flood events are common in South Africa. Frequent updates and real-time availability of precipitation data are crucial to support hydrometeorological warning services. Satellite rainfall estimation provides a very important data source for flash flood guidance systems as well as nowcasting of pr...

  5. Evaluation of monthly turbulent heat fluxes from WHOI analysis and NCEP reanalysis in the tropical Atlantic

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The biases and their sources in monthly turbulent heat fluxes from the Woods Hole Oceanographic Institution (WHOI) analysis, and the National Centers for Environmental Prediction- National Center for Atmospheric Research reanalyses 1 and 2 (NCEP1 and NCEP2) are checked in the climatically representative regions in the tropical Atlantic using the fluxes from the Southampton Oceanographic Centre (SOC) and the pilot research moored array in the tropical Atlantic (PIRATA) as references. For the WHOI analysis, the biases in turbulent heat fluxes mainly exist in equatorial regions which are due to the overestimated sea surface temperature and the underestimated 2 m air humidity. For the NCEP2 reanalysis, the maximum biases, about (40 ± 5) W/m2, exist in southeast and northeast trade wind regions, which are mainly caused by the flux algorithm used because the biases in wind speed and air-sea humidity difference are relatively small. In the equatorial regions, the flux biases in the NCEP2 derived from both flux-related basic variables and algorithm are equally large. Although the estimations of time series trends and air-sea humidity difference of the NCEP1 are improved greatly in the NCEP2, the biases of latent heat flux in the NCEP2 are about 20 W/m2 greater than those from the NCEP1 in the trade wind regions. The result shows that the climatologies and monthly variabilities of the turbulent heat fluxes from the WHOI are more accurate than those from the NCEP1 and NCEP2 in the tropical Atlantic, especially on outside of the equatorial regions.

  6. 14 CFR 141.91 - Satellite bases.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... assistant chief instructor is designated for each satellite base, and that assistant chief instructor...

  7. NCEP-DOE AMIP-II Reanalysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NCEP-DOE Reanalysis 2 project is using a state-of-the-art analysis/forecast system to perform data assimilation using past data from 1979 through near present....

  8. Satellite-Based Sunshine Duration for Europe

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-06-01

    Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

  9. Multi-spectral band selection for satellite-based systems

    Energy Technology Data Exchange (ETDEWEB)

    Clodius, W.B.; Weber, P.G.; Borel, C.C.; Smith, B.W.

    1998-09-01

    The design of satellite based multispectral imaging systems requires the consideration of a number of tradeoffs between cost and performance. The authors have recently been involved in the design and evaluation of a satellite based multispectral sensor operating from the visible through the long wavelength IR. The criteria that led to some of the proposed designs and the modeling used to evaluate and fine tune the designs will both be discussed. These criteria emphasized the use of bands for surface temperature retrieval and the correction of atmospheric effects. The impact of cost estimate changes on the final design will also be discussed.

  10. Satellite-Based Quantum Communications

    Energy Technology Data Exchange (ETDEWEB)

    Hughes, Richard J [Los Alamos National Laboratory; Nordholt, Jane E [Los Alamos National Laboratory; McCabe, Kevin P [Los Alamos National Laboratory; Newell, Raymond T [Los Alamos National Laboratory; Peterson, Charles G [Los Alamos National Laboratory

    2010-09-20

    Single-photon quantum communications (QC) offers the attractive feature of 'future proof', forward security rooted in the laws of quantum physics. Ground based quantum key distribution (QKD) experiments in optical fiber have attained transmission ranges in excess of 200km, but for larger distances we proposed a methodology for satellite-based QC. Over the past decade we have devised solutions to the technical challenges to satellite-to-ground QC, and we now have a clear concept for how space-based QC could be performed and potentially utilized within a trusted QKD network architecture. Functioning as a trusted QKD node, a QC satellite ('QC-sat') could deliver secret keys to the key stores of ground-based trusted QKD network nodes, to each of which multiple users are connected by optical fiber or free-space QC. A QC-sat could thereby extend quantum-secured connectivity to geographically disjoint domains, separated by continental or inter-continental distances. In this paper we describe our system concept that makes QC feasible with low-earth orbit (LEO) QC-sats (200-km-2,000-km altitude orbits), and the results of link modeling of expected performance. Using the architecture that we have developed, LEO satellite-to-ground QKD will be feasible with secret bit yields of several hundred 256-bit AES keys per contact. With multiple ground sites separated by {approx} 100km, mitigation of cloudiness over any single ground site would be possible, potentially allowing multiple contact opportunities each day. The essential next step is an experimental QC-sat. A number of LEO-platforms would be suitable, ranging from a dedicated, three-axis stabilized small satellite, to a secondary experiment on an imaging satellite. to the ISS. With one or more QC-sats, low-latency quantum-secured communications could then be provided to ground-based users on a global scale. Air-to-ground QC would also be possible.

  11. NOAA/NCEP Global Forecast System (GFS) Atmospheric Model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — U.S. National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) numerical weather...

  12. Intercomparison of the South Asian High in NCEP1, NCEP2, and ERA-40 Reanalyses and in Station Observations

    Institute of Scientific and Technical Information of China (English)

    FU Jian-Jian; LI Shuanglin

    2012-01-01

    The South Asian Highs (SAHs) at 100 hPa over China in the three reanalysis datasets NCEP1, NCEP2, and ERA-40 are evaluated by using station observation data. The results demonstrate a substantial discrepancy even between the reanalyses. First, the data of the three reanalyses generally underestimate the intensity of the SAH in the China domain. Second, there are interdecadal changes in the SAH, with highs in the 1960s and 1980s and lows in the 1970s, 1990s, and 2000s. This interdecadal variation of the SAH can be well depicted with NCEP1 data, but the high in the 1980s is missed by ERA-40. The NCEP2 corresponds well with NCEP 1 and captures the decreasing trend after 1979. Furthermore, the NCEP1 reanalysis overestimates the interdecadal changes of SAH, while ERA-40 underestimates the interdecadal changes. This work suggests that much caution should be exerted when the reanalysis datasets are adopted to study the interdecadal variability of SAH.

  13. Fault Diagnosis of Satellite Based on IMM and Moving Horizon Estimation%基于多模型滚动时域估计的卫星故障诊断

    Institute of Scientific and Technical Information of China (English)

    赵石磊; 吴丽娜

    2011-01-01

    This paper studies the fault diagnosis problems of the satellite attitude control system. Since the satellite works in space, the attitude control system of satellite is easy to be effected by uncertainties and disturbances in the harsh working environment. Interacting Multiple Model (IMM) is one of the effective fault diagnosis methods of the satellite control system but it is subjected to strong noise or wrong data. For this reason, this paper proposes to combine the moving horizon estimation instead of the Kahnan filter with the IMM algorithm. The moving horizon estimation, which adopts not the estimation error of one time but the interval estimation error of a time span, is used to estimate the system states and the transition probabilities. So it could effectively decrease the influences of the wrong data or strong noise. Finally, the mathematical simulation results for diagnosis problem of the satellite attitude control system are presented to show the effectiveness of the proposed scheme.%研究了卫星姿态控制系统故障诊断问题,将滚动时域估计与交互式多模型(IMM)方法相结合,利用滚动时域估计方法对系统状态进行估计,系统转换概率也相应地利用了一个时间段的估计误差作为依据,而不是只考虑一个时刻的估计误差,因此有效减少了大噪声以及个别错误测量对诊断结果的影响.最后的仿真结果证明了该算法的有效性.

  14. Satellite-Based actual evapotranspiration over drying semiarid terrain in West-Africa

    NARCIS (Netherlands)

    Schuttemeyer, D.; Schillings, Ch.; Moene, A.F.; Bruin, de H.A.R.

    2007-01-01

    A simple satellite-based algorithm for estimating actual evaporation based on Makkink¿s equation is applied to a seasonal cycle in 2002 at three test sites in Ghana, West Africa: at a location in the humid tropical southern region and two in the drier northern region. The required input for the algo

  15. Development of JPSS VIIRS Global Gridded Vegetation Index products for NOAA NCEP Environmental Modeling Systems

    Science.gov (United States)

    Vargas, Marco; Miura, Tomoaki; Csiszar, Ivan; Zheng, Weizhong; Wu, Yihua; Ek, Michael

    2017-04-01

    The first Joint Polar Satellite System (JPSS) mission, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was successfully launched in October, 2011, and it will be followed by JPSS-1, slated for launch in 2017. JPSS provides operational continuity of satellite-based observations and products for NOAA's Polar Operational Environmental Satellites (POES). Vegetation products derived from satellite measurements are used for weather forecasting, land modeling, climate research, and monitoring the environment including drought, the health of ecosystems, crop monitoring and forest fires. The operationally produced S-NPP VIIRS Vegetation Index (VI) Environmental Data Record (EDR) includes two vegetation indices: the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), and the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI). For JPSS-1, the S-NPP Vegetation Index EDR algorithm has been updated to include the TOC NDV. The current JPSS operational VI products are generated in granule style at 375 meter resolution at nadir, but these products in granule format cannot be ingested into NOAA operational monitoring and decision making systems. For that reason, the NOAA JPSS Land Team is developing a new global gridded Vegetation Index (VI) product suite for operational use by the NOAA National Centers for Environmental Prediction (NCEP). The new global gridded VIs will be used in the Multi-Physics (MP) version of the Noah land surface model (Noah-MP) in NCEP NOAA Environmental Modeling System (NEMS) for plant growth and data assimilation and to describe vegetation coverage and density in order to model the correct surface energy partition. The new VI 4km resolution global gridded products (TOA NDVI, TOC NDVI and TOC EVI) are being designed to meet the needs of directly ingesting vegetation index variables without the need to develop local gridding and compositing procedures. These VI products will be consistent with the already

  16. Use of COSMIC Radio Occultation Observations in the NOAA/NCEP Data Assimilation System

    Science.gov (United States)

    Cucurull, L.; Derber, J.; Treadon, R.; Purser, J.

    2006-12-01

    The COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) mission launched six small satellites in April 2006, each carrying a GPS radio occultation (RO) receiver. At final orbit, COSMIC will provide 2,500~3,000 RO soundings per day uniformly distributed around the globe in near real time. The US National Weather Service (NOAA/NWS) is planning to assimilate GPS RO observations from the COSMIC mission (and other future GPS RO satellites) into its next-generation NCEP Global Data Assimilation System. The assimilation of the GPS RO data requires the development of an appropriate forward model, the adjoint of the forward model, appropriate observational and representativeness error estimates, quality control procedures, data handling routines and data monitoring software. In preparation for the use of COSMIC data in operations, the NCEP Environmental Modeling Center (EMC) has successfully developed the capability to assimilate soundings of (ionospheric-compensated) bending angle and derived refractivity profiles. A priori, derived profiles of bending angle are preferred for assimilation because they are less processed data and they are not weighted with climatology. In this presentation, the infrastructure developed at NCEP/EMC to assimilate GPS RO observations, including forward models, observational and representativeness errors and quality control procedures will be described. The advantages of using a forward operator for bending angle vs. refractivity will be discussed and some preliminary results on the benefits of the COSMIC GPS RO in weather analysis and forecasts will be presented. The different strategies adopted at NCEP/EMC to assimilate GPS RO data are aimed to select the most appropriate forward operator in our operational data assimilation system when COSMIC products are stable and routinely used in operations in Numerical Weather Centers.

  17. NCEP and GISS solar radiation data sets available for ecosystem modeling: Description, differences, and impacts on net primary production

    Science.gov (United States)

    Hicke, Jeffrey A.

    2005-06-01

    Downwelling surface solar radiation is an important input to ecosystem models, and global models require spatially extensive data sets that vary interannually to capture effects that potentially drive changes in ecosystem function. In this paper, I describe and compare solar radiation data sets from two representative sources, National Centers for Environmental Prediction (NCEP) reanalyses and Goddard Institute for Space Studies (GISS) calculations that included satellite observations of cloud properties. The CASA ecosystem model, which uses solar radiation and satellite-derived vegetation information, was run with the two solar radiation data sets to explore how differences affect estimated net primary production (NPP). GISS solar radiation matched ground-based observations better than NCEP solar radiation. Mean global NCEP solar radiation exceeded that from GISS by 16%, likely as a result of lower cloudiness within the NCEP reanalyses compared to satellite observations. Neither data set resulted in a significant trend over the study period (1984-2000). Locally, relative differences were up to 40% in the mean and 10% in the trend of solar radiation and NPP, and varied in sign across the globe. Because reanalysis solar radiation is only indirectly constrained by observations in contrast to the satellite-derived data, it is recommended that studies use the GISS solar radiation when possible.

  18. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

    Vrieling, A.; Sterk, G.; Jong, S.M. de

    2010-01-01

    Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge data.

  19. Satellite-based annual evaporation estimates of invasive alien plant ...

    African Journals Online (AJOL)

    2013-12-17

    Dec 17, 2013 ... Water (WFW) programme, have on total evaporation (ET) and the availability of water resources in two highly-invaded ... on water resources were based on the results from the paired catchment ...... Tourism, Pretoria. 85 pp.

  20. Evaluating the hydrological consistency of satellite based water cycle components

    KAUST Repository

    Lopez Valencia, Oliver M.

    2016-06-15

    Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological

  1. DIFFERENCES OF SOUTH CHINA SEA SUMMER MONSOON DERIVED BY NCEP AND ECMWF REANALYSIS DATA

    Institute of Scientific and Technical Information of China (English)

    ZHENG Bin; GU De-jun; LI Chun-hui

    2006-01-01

    @@ 1 INTRODUCTION Due to long-term time series and many elements,reanalysis data of National Centers for Environmental Prediction (NCEP) and European Center for MediumRange Weather Forecasts (ECMWF) are widely used in present climate studies. Even so, there are discrepancies between NCEP and ECMWF reanalysis.Some climate fields may be better reproduced by NCEP than by ECMWF.

  2. Co-Channel Interference Mitigation Using Satellite Based Receivers

    Science.gov (United States)

    2014-12-01

    While there is some phase noise present in the continuous time-shifted signal, it is important to recognize that this signal is plotted over the [−π...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS CO-CHANNEL INTERFERENCE MITIGATION USING SATELLITE BASED RECEIVERS by John E. Patterson...07-02-2012 to 12-19-2014 4. TITLE AND SUBTITLE CO-CHANNEL INTERFERENCE MITIGATION USING SATELLITE BASED RE- CEIVERS 5. FUNDING NUMBERS 6. AUTHOR(S

  3. Satellite-based assessment of climate controls on US burned area

    OpenAIRE

    D. C. Morton; G. J. Collatz; Wang, D.; Randerson, J. T.; Giglio, L.; Chen, Y.

    2013-01-01

    Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate–fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burne...

  4. Assimilation of Quality Controlled AIRS Temperature Profiles using the NCEP GFS

    Science.gov (United States)

    Susskind, Joel; Reale, Oreste; Iredell, Lena; Rosenberg, Robert

    2013-01-01

    We have previously conducted a number of data assimilation experiments using AIRS Version-5 quality controlled temperature profiles as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The data assimilation and forecast system we used was the Goddard Earth Observing System Model , Version-5 (GEOS-5) Data Assimilation System (DAS), which represents a combination of the NASA GEOS-5 forecast model with the National Centers for Environmental Prediction (NCEP) operational Grid Point Statistical Interpolation (GSI) global analysis scheme. All analyses and forecasts were run at a 0.5deg x 0.625deg spatial resolution. Data assimilation experiments were conducted in four different seasons, each in a different year. Three different sets of data assimilation experiments were run during each time period: Control; AIRS T(p); and AIRS Radiance. In the "Control" analysis, all the data used operationally by NCEP was assimilated, but no AIRS data was assimilated. Radiances from the Aqua AMSU-A instrument were also assimilated operationally by NCEP and are included in the "Control". The AIRS Radiance assimilation adds AIRS observed radiance observations for a select set of channels to the data set being assimilated, as done operationally by NCEP. In the AIRS T(p) assimilation, all information used in the Control was assimilated as well as Quality Controlled AIRS Version-5 temperature profiles, i.e., AIRS T(p) information was substituted for AIRS radiance information. The AIRS Version-5 temperature profiles were presented to the GSI analysis as rawinsonde profiles, assimilated down to a case-by-case appropriate pressure level p(sub best) determined using the Quality Control procedure. Version-5 also determines case-by-case, level-by-level error estimates of the temperature profiles, which were used as the uncertainty of each temperature measurement. These experiments using GEOS-5 have shown that forecasts

  5. Validation of an Innovative Satellite-Based UV Dosimeter

    Science.gov (United States)

    Morelli, Marco; Masini, Andrea; Simeone, Emilio; Khazova, Marina

    2016-08-01

    We present an innovative satellite-based UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in-vivo assessment of the erythemal effects on some volunteers having a controlled exposure to solar radiation.Both validations showed that the satellite-based UV dosimeter has a good accuracy and reliability needed for health-related applications.The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. This app will be launched on the global market by siHealth Ltd in May 2016 under the name of "HappySun" and available both for Android and for iOS devices (more info on http://www.happysun.co.uk).Extensive R&D activities are on-going for further improvement of the satellite-based UV dosimeter's accuracy.

  6. Satellite based wind resource assessment over the South China Sea

    DEFF Research Database (Denmark)

    Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay

    2014-01-01

    modeling to develop procedures and best practices for satellite based wind resource assessment offshore. All existing satellite images from the Envisat Advanced SAR sensor by the European Space Agency (2002-12) have been collected over a domain in the South China Sea. Wind speed is first retrieved from...

  7. Satellite Based Extrusion Rates for the 2006 Augustine Eruption

    Science.gov (United States)

    Dehn, J.; Bailey, J. E.; Dean, K. G.; Skoog, R.; Valcic, L.

    2006-12-01

    include pyroclastic deposits or ashfall, which are included in the DEM subtraction approach. However the pyroclastics should only account for a small amount of the extruded volume. In spite of its limitations, satellite based extrusion modeling provides a reasonable and safe method to monitor volcanoes and detect change in eruption style in near real time.

  8. Satellite-based RAR performance simulation for measuring directional ocean wave spectrum based on SAR inversion spectrum

    Institute of Scientific and Technical Information of China (English)

    REN Lin; MAO Zhihua; HUANG Haiqing; GONG Fang

    2010-01-01

    Some missions have been carried out to measure wave directional spectrum by synthetic aperture radar (SAR) and airborne real aperture radar (RAR) at a low incidence. Both them have their own advantages and limitations. Scientists hope that SAR and satellite-based RAR can complement each other for the research on wave properties in the future. For this study, the authors aim to simulate the satellite-based RAR system to validate performance for measuring the directional wave spectrum. The principal measurements are introduced and the simulation methods based on the one developed by Hauser are adopted and slightly modified. To enhance the authenticity of input spectrum and the wave spectrum measuring consistency for SAR and satellite-based RAR, the wave height spectrum inversed from Envisat ASAR data by cross spectrum technology is used as the input spectrum of the simulation system. In the process of simulation, the sea surface, backscattering signal, modulation spectrum and the estimated wave height spectrum are simulated in each look direction. Directional wave spectrum are measured based on the simulated observations from 0° to 360~. From the estimated wave spectrum, it has an 180° ambiguity like SAR, but it has no special high wave number cut off in all the direction. Finally, the estimated spectrum is compared with the input one in terms of the dominant wave wavelength, direction and SWH and the results are promising. The simulation shows that satellite-based RAR should be capable of measuring the directional wave properties. Moreover, it indicates satellite-based RAR basically can measure waves that SAR can measure.

  9. Global trends in satellite-based emergency mapping.

    Science.gov (United States)

    Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

    2016-07-15

    Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

  10. Global trends in satellite-based emergency mapping

    Science.gov (United States)

    Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

    2016-01-01

    Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

  11. Global trends in satellite-based emergency mapping

    Science.gov (United States)

    Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

    2016-07-01

    Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

  12. Trellis-coded CPM for satellite-based mobile communications

    Science.gov (United States)

    Abrishamkar, Farrokh; Biglieri, Ezio

    1988-01-01

    Digital transmission for satellite-based land mobile communications is discussed. To satisfy the power and bandwidth limitations imposed on such systems, a combination of trellis coding and continuous-phase modulated signals are considered. Some schemes based on this idea are presented, and their performance is analyzed by computer simulation. The results obtained show that a scheme based on directional detection and Viterbi decoding appears promising for practical applications.

  13. A satellite based telemetry link for a UAV application

    Science.gov (United States)

    Bloise, Anthony

    1995-01-01

    The requirements for a satellite based communication facility to service the needs of the Geographical Information System (GIS) data collection community are addressed in this paper. GIS data is supplied in the form of video imagery at sub-television rates in one or more spectral bands / polarizations laced with a position correlated data stream. The limitations and vicissitudes of using a terrestrial based telecommunications link to collect GIS data are illustrated from actual mission scenarios. The expectations from a satellite based communications link by the geophysical data collection community concerning satellite architecture, operating bands, bandwidth, footprint agility, up link and down link hardware configurations on the UAV, the Mobile Control Vehicle and at the Central Command and Data Collection Facility comprise the principle issues discussed in the first section of this paper. The final section of the paper discusses satellite based communication links would have an increased volume and scope of services the GIS data collection community could make available to the GIS user community, and the price the data collection community could afford to pay for access to the communication satellite described in the paper.

  14. Satellite-based assessment of yield variation and its determinants in smallholder African systems

    Science.gov (United States)

    Lobell, David B.

    2017-01-01

    The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest (R2 up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods. PMID:28202728

  15. Operational Testing of Satellite based Hydrological Model (SHM)

    Science.gov (United States)

    Gaur, Srishti; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghavendra P.

    2017-04-01

    Incorporation of the concept of transposability in model testing is one of the prominent ways to check the credibility of a hydrological model. Successful testing ensures ability of hydrological models to deal with changing conditions, along with its extrapolation capacity. For a newly developed model, a number of contradictions arises regarding its applicability, therefore testing of credibility of model is essential to proficiently assess its strength and limitations. This concept emphasizes to perform 'Hierarchical Operational Testing' of Satellite based Hydrological Model (SHM), a newly developed surface water-groundwater coupled model, under PRACRITI-2 program initiated by Space Application Centre (SAC), Ahmedabad. SHM aims at sustainable water resources management using remote sensing data from Indian satellites. It consists of grid cells of 5km x 5km resolution and comprises of five modules namely: Surface Water (SW), Forest (F), Snow (S), Groundwater (GW) and Routing (ROU). SW module (functions in the grid cells with land cover other than forest and snow) deals with estimation of surface runoff, soil moisture and evapotranspiration by using NRCS-CN method, water balance and Hragreaves method, respectively. The hydrology of F module is dependent entirely on sub-surface processes and water balance is calculated based on it. GW module generates baseflow (depending on water table variation with the level of water in streams) using Boussinesq equation. ROU module is grounded on a cell-to-cell routing technique based on the principle of Time Variant Spatially Distributed Direct Runoff Hydrograph (SDDH) to route the generated runoff and baseflow by different modules up to the outlet. For this study Subarnarekha river basin, flood prone zone of eastern India, has been chosen for hierarchical operational testing scheme which includes tests under stationary as well as transitory conditions. For this the basin has been divided into three sub-basins using three flow

  16. The Madden-Julian Oscillation in NCEP Coupled Model Simulation

    Directory of Open Access Journals (Sweden)

    Wanqiu Wang Kyong-Hwan Seo

    2009-01-01

    Full Text Available This study documents a detailed analysis on the Madden-Julian Oscillation (MJO simulated by the National Centers for Environmental Prediction (NCEP using the Global Forecast System (GFS model version 2003 coupled with the Climate Forecast System model (CFS consisting of the 2003 version of GFS and the Geophysical Fluid Dynamics Laboratory (GFDL Modular Ocean Model V.3 (MOM3. The analyses are based upon a 21-year simulation of AMIP-type with GFS and CMIP-type with CFS. It is found that air-sea coupling in CFS is shown to improve the coherence between convection and large-scale circulation associated with the MJO. The too fast propagation of convection from the Indian Ocean to the maritime continents and the western Pacific in GFS is improved (slowed down in CFS. Both GFS and CFS produce too strong intraseasonal convective heating and circulation anomalies in the central-eastern Pacific; further, the air-sea coupling in CFS enhances this unrealistic feature. The simulated mean slow phase speed of east ward propagating low-wavenumber components shown in the wavenumber-frequency spectra is due to the slow propagation in the central-eastern Pacific in both GFS and CFS. Errors in model climatology may have some effect upon the simulated MJO and two possible influences are: (i CFS fails to simulate the westerlies over maritime continents and western Pacific areas, resulting in an unrealistic representation of surface latent heat flux associated with the MJO; and (ii vertical easterly wind shear from the Indian Ocean to the western Pacific in CFS is much weaker than that in the observation and in GFS, which may adversely affect the eastward propagation of the simulated MJO.

  17. Assessment of simulation of radiation in NCEP Climate Forecasting System (CFS V2)

    Science.gov (United States)

    Goswami, Tanmoy; Rao, Suryachandra A.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Dhakate, Ashish; Salunke, Kiran; Mahapatra, Somnath

    2017-09-01

    The objective of this study is to identify and document the radiation biases in the latest National Centers for Environment Prediction (NCEP), Climate Forecasting System (CFSv2) and to investigate the probable reasons for these biases. This analysis is made over global and Indian domain under all-sky and clear-sky conditions. The impact of increasing the horizontal resolution of the atmospheric model on these biases is also investigated by comparing results of two different horizontal resolution versions of CFSv2 namely T126 and T382. The difference between the top of the atmosphere and surface energy imbalance in T126 (T382) is 3.49 (2.78) W/m2. This reduction of bias in the high resolution model is achieved due to lesser low cloud cover, resulting more surface insolation, and due to more latent heat fluxes at the surface. Compared to clear sky simulations, all sky simulations exhibit larger biases suggesting that the cloud covers are not simulated well in the model. The annual mean high level cloud cover is over estimated over the global as well as the Indian domain. This overestimation over the Indian domain is also present during JJAS. There is also evidence that both of the models have insufficient water vapour in their atmosphere. This study suggests that in order to improve the model's mean radiation climatology, simulation of clouds in the model also needs to be improved, and future model development activities should focus on this aspect.

  18. Satellite-Based EMI Detection, Identification, and Mitigation

    Science.gov (United States)

    Stottler, R.; Bowman, C.

    2016-09-01

    Commanding, controlling, and maintaining the health of satellites requires a clear operating spectrum for communications. Electro Magnetic Interference (EMI) from other satellites can interfere with these communications. Determining which satellite is at fault improves space situational awareness and can be used to avoid the problem in the future. The Rfi detection And Prediction Tool, Optimizing Resources (RAPTOR) monitors the satellite communication antenna signals to detect EMI (also called RFI for Radio Frequency Interference) using a neural network trained on past cases of both normal communications and EMI events. RAPTOR maintains a database of satellites that have violated the reserved spectrum in the past. When satellite-based EMI is detected, RAPTOR first checks this list to determine if any are angularly close to the satellite being communicated with. Additionally, RAPTOR checks the Space Catalog to see if any of its active satellites are angularly close. RAPTOR also consults on-line databases to determine if the described operating frequencies of the satellites match the detected EMI and recommends candidates to be added to the known offenders database, accordingly. Based on detected EMI and predicted orbits and frequencies, RAPTOR automatically reschedules satellite communications to avoid current and future satellite-based EMI. It also includes an intuitive display for a global network of satellite communications antennas and their statuses including the status of their EM spectrum. RAPTOR has been prototyped and tested with real data (amplitudes versus frequency over time) for both satellite communication signals and is currently undergoing full-scale development. This paper describes the RAPTOR technologies and results of testing.

  19. Satellite-based detection of volcanic sulphur dioxide from recent eruptions in Central and South America

    Directory of Open Access Journals (Sweden)

    D. Loyola

    2008-01-01

    Full Text Available Volcanic eruptions can emit large amounts of rock fragments and fine particles (ash into the atmosphere, as well as several gases, including sulphur dioxide (SO2. These ejecta and emissions are a major natural hazard, not only to the local population, but also to the infrastructure in the vicinity of volcanoes and to aviation. Here, we describe a methodology to retrieve quantitative information about volcanic SO2 plumes from satellite-borne measurements in the UV/Visible spectral range. The combination of a satellite-based SO2 detection scheme and a state-of-the-art 3D trajectory model enables us to confirm the volcanic origin of trace gas signals and to estimate the plume height and the effective emission height. This is demonstrated by case-studies for four selected volcanic eruptions in South and Central America, using the GOME, SCIAMACHY and GOME-2 instruments.

  20. Trellis coding with Continuous Phase Modulation (CPM) for satellite-based land-mobile communications

    Science.gov (United States)

    1989-01-01

    This volume of the final report summarizes the results of our studies on the satellite-based mobile communications project. It includes: a detailed analysis, design, and simulations of trellis coded, full/partial response CPM signals with/without interleaving over various Rician fading channels; analysis and simulation of computational cutoff rates for coherent, noncoherent, and differential detection of CPM signals; optimization of the complete transmission system; analysis and simulation of power spectrum of the CPM signals; design and development of a class of Doppler frequency shift estimators; design and development of a symbol timing recovery circuit; and breadboard implementation of the transmission system. Studies prove the suitability of the CPM system for mobile communications.

  1. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2011-02-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved estimates of surface soil moisture at global scale. We develop and evaluate a methodology that takes advantage of the retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates to produce an improved soil moisture product. First, volumetric soil water content (m3 m−3 from AMSR-E and degree of saturation (% from ASCAT are rescaled against a reference land surface model data set using a cumulative distribution function matching approach. While this imposes any bias of the reference on the rescaled satellite products, it adjusts them to the same range and preserves the dynamics of original satellite-based products. Comparison with in situ measurements demonstrates that where the correlation coefficient between rescaled AMSR-E and ASCAT is greater than 0.65 ("transitional regions", merging the different satellite products increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT, respectively, are used for the merged product. Therefore the merged product carries the advantages of better spatial coverage overall and increased number of observations, particularly for the transitional regions. The combination method developed has the potential to be applied to existing microwave satellites as well as to new missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  2. A local ensemble transform Kalman filter data assimilation system for the NCEP global model

    Science.gov (United States)

    Szunyogh, Istvan; Kostelich, Eric J.; Gyarmati, Gyorgyi; Kalnay, Eugenia; Hunt, Brian R.; Ott, Edward; Satterfield, Elizabeth; Yorke, James A.

    2008-01-01

    The accuracy and computational efficiency of a parallel computer implementation of the Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme on the model component of the 2004 version of the Global Forecast System (GFS) of the National Centers for Environmental Prediction (NCEP) is investigated. Numerical experiments are carried out at model resolution T62L28. All atmospheric observations that were operationally assimilated by NCEP in 2004, except for satellite radiances, are assimilated with the LETKF. The accuracy of the LETKF analyses is evaluated by comparing it to that of the Spectral Statistical Interpolation (SSI), which was the operational global data assimilation scheme of NCEP in 2004. For the selected set of observations, the LETKF analyses are more accurate than the SSI analyses in the Southern Hemisphere extratropics and are comparably accurate in the Northern Hemisphere extratropics and in the Tropics. The computational wall-clock times achieved on a Beowulf cluster of 3.6 GHz Xeon processors make our implementation of the LETKF on the NCEP GFS a widely applicable analysis-forecast system, especially for research purposes. For instance, the generation of four daily analyses at the resolution of the NCAR-NCEP reanalysis (T62L28) for a full season (90 d), using 40 processors, takes less than 4 d of wall-clock time.

  3. Interoperability of satellite-based augmentation systems for aircraft navigation

    Science.gov (United States)

    Dai, Donghai

    The Federal Aviation Administration (FAA) is pioneering a transformation of the national airspace system from its present ground based navigation and landing systems to a satellite based system using the Global Positioning System (GPS). To meet the critical safety-of-life aviation positioning requirements, a Satellite-Based Augmentation System (SBAS), the Wide Area Augmentation System (WAAS), is being implemented to support navigation for all phases of flight, including Category I precision approach. The system is designed to be used as a primary means of navigation, capable of meeting the Required Navigation Performance (RNP), and therefore must satisfy the accuracy, integrity, continuity and availability requirements. In recent years there has been international acceptance of Global Navigation Satellite Systems (GNSS), spurring widespread growth in the independent development of SBASs. Besides the FAA's WAAS, the European Geostationary Navigation Overlay Service System (EGNOS) and the Japan Civil Aviation Bureau's MTSAT-Satellite Augmentation System (MSAS) are also being actively developed. Although all of these SBASs can operate as stand-alone, regional systems, there is increasing interest in linking these SBASs together to reduce costs while improving service coverage. This research investigated the coverage and availability improvements due to cooperative efforts among regional SBAS networks. The primary goal was to identify the optimal interoperation strategies in terms of performance, complexity and practicality. The core algorithms associated with the most promising concepts were developed and demonstrated. Experimental verification of the most promising concepts was conducted using data collected from a joint international test between the National Satellite Test Bed (NSTB) and the EGNOS System Test Bed (ESTB). This research clearly shows that a simple switch between SBASs made by the airborne equipment is the most effective choice for achieving the

  4. SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

    Science.gov (United States)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

    2016-04-01

    Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

  5. A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

    Science.gov (United States)

    Maidment, Ross I.; Grimes, David; Black, Emily; Tarnavsky, Elena; Young, Matthew; Greatrex, Helen; Allan, Richard P.; Stein, Thorwald; Nkonde, Edson; Senkunda, Samuel; Alcántara, Edgar Misael Uribe

    2017-05-01

    Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets.

  6. Satellite-based detection of global urban heat-island temperature influence

    Science.gov (United States)

    Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

    2002-01-01

    This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

  7. NCEP-ATP III and IDF criteria for metabolic syndrome predict type 2 diabetes mellitus

    Directory of Open Access Journals (Sweden)

    Eva Sulistiowati

    2016-05-01

    Full Text Available Background Subjects with metabolic syndrome (MetS have a greater risk for acquiring type 2 diabetes mellitus (type 2 DM. The MetS criteria usually used are those of the National Cholesterol Education Program Expert Panel (NCEP and Adult Treatment Panel III (ATP III and of the International Diabetes Federation (IDF. This study aimed to evaluate the modified NCEP-ATP III and IDF criteria as predictor of type 2 DM among subjects with MetS.   Methods A cohort study was conducted among 4240 subjects with MetS. MetS was determined according to the modified NCEP-ATP III and IDF criteria. The study followed up 3324 non-diabetic subjects of the cohort study of non-communicable disease (NCD risk factors (NCD study during a 2-year period. Type 2 DM was determined from the diagnosis by health personnel or from fasting blood glucose of ≥126 mg/dL or blood glucose of ≥200 mg/dL, 2 hours after 75g glucose loading.   Results The MetS prevalence based on modified NCEP ATP III and IDF criteria in non-DM subjects was 17.1% and 15.6%, respectively. The risk for DM in subjects with MetS using modified NCEP ATP III and IDF criteria was 4.7 (CI 95%: 3.4-6.5 and 4.1 (CI 95%: 3.0-5.7, respectively.   Conclusions Both MetS criteria can be used as predictors of the occurrence of DM type 2, but the modified NCEP-ATP III is more properly applied than the IDF criteria in subjects with MetS. Screening programs and routine monitoring of MetS components are required for early detection of type 2 DM.

  8. An intercomparison between the surface heat flux feedback in five coupled models, COADS and the NCEP reanalysis

    Energy Technology Data Exchange (ETDEWEB)

    Frankignoul, C.; Kestenare, E. [Universite Pierre et Marie Curie, Institute Pierre-Simon Laplace, Laboratoire d' Oceanographie Dynamique et de Climatologie, 4 place Jussieu, 75252 Paris Cedex 05 (France); Botzet, M. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Carril, A.F. [Istituto Nazionale di Geofisica e Vulcanologia, Bologna (Italy); Drange, H. [Nansen Environmental and Remote Sensing Center, Bergen (Norway); Pardaens, A. [Hadley Centre for Climate Prediction and Research, Met Office (United Kingdom); Terray, L.; Sutton, R. [Department of Meteorology, University of Reading (United Kingdom)

    2004-04-01

    The surface heat flux feedback is estimated in the Atlantic and the extra-tropical Indo-Pacific, using monthly heat flux and sea surface temperature anomaly data from control simulations with five global climate models, and it is compared to estimates derived from COADS and the NCEP reanalysis. In all data sets, the heat flux feedback is negative nearly everywhere and damps the sea surface temperature anomalies. At extra-tropical latitudes, it is strongly dominated by the turbulent fluxes. The radiative feedback can be positive or negative, depending on location and season, but it remains small, except in some models in the tropical Atlantic. The negative heat flux feedback is strong in the mid-latitude storm tracks, exceeding 40 W m{sup -2} K{sup -1} at place, but in the Northern Hemisphere it is substantially underestimated in several models. The negative feedback weakens at high latitudes, although the models do not reproduce the weak positive feedback found in NCEP in the northern North Atlantic. The main differences are found in the tropical Atlantic where the heat flux feedback is weakly negative in some models, as in the observations, and strongly negative in others where it can exceed 30 W m{sup -2} K{sup -1} at large scales, in part because of a strong contribution of the radiative fluxes, in particular during spring. A comparison between models with similar atmospheric or oceanic components suggests that the atmospheric model is primarily responsible for the heat flux feedback differences at extra-tropical latitudes. In the tropical Atlantic, the ocean behavior plays an equal role. The differences in heat flux feedback in the tropical Atlantic are reflected in the sea surface temperature anomaly persistence, which is too small in models where the heat flux damping is large. A good representation of the heat flux feedback is thus required to simulate climate variability realistically. (orig.)

  9. Surface Turbulent Fluxes, 1x1 deg Yearly Climatology, Set1 and NCEP V2c

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-2c Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie...

  10. Surface Turbulent Fluxes, 1x1 deg Seasonal Climatology, Set1 and NCEP V2c

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-2c Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  11. Performance evaluation of NCEP climate forecast system for the prediction of winter temperatures over India

    Science.gov (United States)

    Nageswararao, M. M.; Mohanty, U. C.; Kiran Prasad, S.; Osuri, Krishna K.; Ramakrishna, S. S. V. S.

    2016-11-01

    The surface air temperature during the winter season (December-February) in India adversely affects agriculture as well as day-to-day life. Therefore, the accurate prediction of winter temperature in extended range is of utmost importance. The National Center for Environmental Prediction (NCEP) has been providing climatic variables from the fully coupled global climate model, known as Climate Forecast System version 1 (CFSv1) on monthly to seasonal scale since 2004, and it has been upgraded to CFSv2 subsequently in 2011. In the present study, the performance of CFSv1 and CFSv2 in simulating the winter 2 m maximum, minimum, and mean temperatures ( T max, T min, and T mean, respectively) over India is evaluated with respect to India Meteorological Department (IMD) 1° × 1° observations. The hindcast data obtained from both versions of CFS from 1982 to 2009 (27 years) with November initial conditions (lead-1) are used. The analyses of winter ( T max, T min, and T mean) temperatures revealed that CFSv1 and CFSv2 are able to replicate the patterns of observed climatology, interannual variability, and coefficient of variation with a slight negative bias. Of the two, CFSv2 is appreciable in capturing increasing trends of winter temperatures like observed. The T max, T min, and T mean correlations from CFSv2 is significantly high (0.35, 0.53, and 0.51, respectively), while CFSv1 correlations are less (0.29, 0.15, and 0.12) and insignificant. This performance of CFSv2 may be due to the better estimation of surface heat budget terms and realistic CO2 concentration, which were absent in CFSv1. CFSv2 proved to have a high probability of detection in predicting different categories (below, near, and above normal) for winter T min, which are required for crop yield and public utility services, over north India.

  12. Bias correction of daily precipitation in south-central Chile using NCEP CFSv2

    Science.gov (United States)

    Maass, T.; castro Heredia, L. M.; Suarez, F. I.; Fernandez, B.

    2015-12-01

    Hydroelectric power plant operations are heavily influenced by the streamflow forecasts on their basins. In Chile, these forecasts are based on historical observations. However, this approach has reached its limit of quality and reliability, being difficult to adapt to current weather conditions (climate change), to extreme weather conditions, and to ungauged basins. In this work, we evaluated the bias correction of NCEP-CSv2 daily precipitation with the aim of incorporating this forecast into a real-time hydrological forecasting system. Bias correction was performed using two approaches of the Quantile Mapping (QM) method: a) a polynomial fit (APo) applied to the differences between the forecasted and observed cumulative distribution functions (CDFs) for the training period; and b) using a Gamma probability distribution (APb) to fit the forecasted and observed CDFs. The bias correction was applied at two locations in south-central Chile: over the valley and in the Andes mountains. To estimate the CDFs and the QM fitting models in the training period, historical records and data from the CFSv2 Reforecast model (between 1995 and 2009) were used. The bias correction evaluation was done between 2011 and 2014 with the forecast of the CFSv2 model. The uncorrected CFSv2 results show that the mid-term forecasts (six months) have a high correlation (r>0.5) for the first days of the forecast (2 weeks), but an important underestimation in the observed data from both the valley and the mountain. After applying the bias correction (APo or APb), the errors of the corrected forecasts decrease in relation to the uncorrected CFSv2 forecasts, with a noticeable improvement for the first forecasted days (being the APo errors lower than those of the APb). In the long term, and as might be expected, the errors increase: the peak precipitation is underestimated and the null rainfall is overestimated.

  13. Assessing the impact of soil moisture initialization on seasonal predictions using the NCEP AGCM

    Science.gov (United States)

    Lu, C.; Mitchell, K.

    2002-12-01

    Due to the lack of long-term consistent soil moisture analysis, numerical studies of the impact of soil moisture on medium to seasonal range forecasts are often based on extreme or idealized conditions. In this study, the atmospheric predictability at seasonal scale is investigated using soil moisture analyses that are more realistic and model consistent. This is accomplished using the Air Force Weather Agency (AFWA) Agricultural Meteorology modeling system (AGRMET), an operational global database of land surface states and energy/water fluxes, and the NCEP Global Forecast System (GFS), a state-of-the-art general circulation model. AFWA incorporated the NCEP community NOAH Land Surface Model (NOAH LSM) into AGRMET in late 1999. The soil hydrology physics are forced with analyses of shelter height temperature, relative humidity, and wind speed, short and longwave radition, and precipitation. As part of the efforts to unify land model in all NCEP global and regional models, NOAH LSM has been implemented into GFS in 2002. As AGRMET land states have spun up using same land physics that GFS executes, they provide ideal source of initial land states that are strictly self consistent with GFS land physics. Two sets of summer-time ensemble integration of atmospheric model will be performed, one using climatological soil wetness derived from the NCEP/DOE Reanalysis (R-2) and the other using AGRMET soil wetness analysis as initial conditions. The geographical variations of the predictability of soil wetness, precipitation, and near surface temperature will be examined from this dataset.

  14. Climatic variability of the mean flow and stationary planetary waves in the NCEP/NCAR reanalysis data

    Directory of Open Access Journals (Sweden)

    A. Yu. Kanukhina

    2008-05-01

    Full Text Available NCEP/NCAR (National Center for Environmental Prediction – National Center for Atmospheric Research data have been used to estimate the long-term variability of the mean flow, temperature, and Stationary Planetary Waves (SPW in the troposphere and lower stratosphere. The results obtained show noticeable climatic variabilities in the intensity and position of the tropospheric jets that are caused by temperature changes in the lower atmosphere. As a result, we can expect that this variability of the mean flow will cause the changes in the SPW propagation conditions. The simulation of the SPW with zonal wave number m=1 (SPW1, performed with a linearized model using the mean flow distributions typical for the 1960s and for the beginning of 21st century, supports this assumption and shows that during the last 40 years the amplitude of the SPW1 in the stratosphere and mesosphere increased substantially. The analysis of the SPW amplitudes extracted from the geopotential height and zonal wind NCEP/NCAR data supports the results of simulation and shows that during the last years there exists an increase in the SPW1 activity in the lower stratosphere. These changes in the amplitudes are accompanied by increased interannual variability of the SPW1, as well. Analysis of the SPW2 activity shows that changes in its amplitude have a different sign in the northern winter hemisphere and at low latitudes in the southern summer hemisphere. The value of the SPW2 variability differs latitudinally and can be explained by nonlinear interference of the primary wave propagation from below and from secondary SPW2.

  15. Extreme winds over Denmark from the NCEP/NCAR reanalysis

    DEFF Research Database (Denmark)

    Frank, H.P.

    2001-01-01

    years at the North Sea west of Denmark is 27 ms-1. It is approximately 11 % less than estimates from observations. However, values at grid points over land in Denmark cannot be compared with observations because theroughness length of these land surfaces is far to big in the model. A transformation...... to a common roughness length of 5 cm using the geostrophic drag law yields too high values. At points in northern Germany, where the surface roughness of the model isless, the transformed 50-years wind speed is 22-23 ms-1, which agrees well with estimates obtained from measurements. The analyses of the wind...... pressure indicate a weak decrease from west to east, whereas the geostrophic wind data at constant pressure levels show almost constant extreme winds across Denmark. All upper-air and and geostrophic wind data show higher extreme winds in northernGermany than in Denmark. Further investigations...

  16. National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) Atmospheric Model Intercomparison Project (AMIP)-II Reanalysis (Reanalysis-2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NCEP-DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the "50-year" (1948-present) NCEP-NCAR Reanalysis Project....

  17. The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

    Science.gov (United States)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

    2017-04-01

    We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse

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

    Directory of Open Access Journals (Sweden)

    Tao Wang

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

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

    Science.gov (United States)

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

    2015-01-01

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

  20. Towards the Development of a Global, Satellite-based, Terrestrial Snow Mission Planning Tool

    Science.gov (United States)

    Forman, Bart; Kumar, Sujay; Le Moigne, Jacqueline; Nag, Sreeja

    2017-01-01

    A global, satellite-based, terrestrial snow mission planning tool is proposed to help inform experimental mission design with relevance to snow depth and snow water equivalent (SWE). The idea leverages the capabilities of NASAs Land Information System (LIS) and the Tradespace Analysis Tool for Constellations (TAT C) to harness the information content of Earth science mission data across a suite of hypothetical sensor designs, orbital configurations, data assimilation algorithms, and optimization and uncertainty techniques, including cost estimates and risk assessments of each hypothetical orbital configuration.One objective the proposed observing system simulation experiment (OSSE) is to assess the complementary or perhaps contradictory information content derived from the simultaneous collection of passive microwave (radiometer), active microwave (radar), and LIDAR observations from space-based platforms. The integrated system will enable a true end-to-end OSSE that can help quantify the value of observations based on their utility towards both scientific research and applications as well as to better guide future mission design. Science and mission planning questions addressed as part of this concept include:1. What observational records are needed (in space and time) to maximize terrestrial snow experimental utility?2. How might observations be coordinated (in space and time) to maximize utility? 3. What is the additional utility associated with an additional observation?4. How can future mission costs being minimized while ensuring Science requirements are fulfilled?

  1. Application of Satellite-Based Spectrally-Resolved Solar Radiation Data to PV Performance Studies

    Directory of Open Access Journals (Sweden)

    Ana Maria Gracia Amillo

    2015-04-01

    Full Text Available In recent years, satellite-based solar radiation data resolved in spectral bands have become available. This has for the first time made it possible to produce maps of the geographical variation in the solar spectrum. It also makes it possible to estimate the influence of these variations on the performance of photovoltaic (PV modules. Here, we present a study showing the magnitude of the spectral influence on PV performance over Europe and Africa. The method has been validated using measurements of a CdTe module in Ispra, Italy, showing that the method predicts the spectral influence to within ±2% on a monthly basis and 0.1% over a 19-month period. Application of the method to measured spectral responses of crystalline silicon, CdTe and single-junction amorphous silicon (a-Si modules shows that the spectral effect is smallest over desert areas for all module types, higher in temperate Europe and highest in tropical Africa, where CdTe modules would be expected to yield +6% and single- junction a-Si modules up to +10% more energy due to spectral effects. In contrast, the effect for crystalline silicon modules is less than ±1% in nearly all of Africa and Southern Europe, rising to +1% or +2% in Northern Europe.

  2. A Newly Distributed Satellite-based Global Air-sea Surface Turbulent Fluxes Data Set -- GSSTF2b

    Science.gov (United States)

    Shie, C.; Nelkin, E.; Ardizzone, J.; Savtchenko, A.; Chiu, L. S.; Adler, R. F.; Lin, I.; Gao, S.

    2010-12-01

    Accurate sea surface turbulent flux measurements are crucial to understanding the global water and energy cycle changes. Remote sensing is a valuable tool for global monitoring of these flux measurements. The GSSTF (Goddard Satellite-based Surface Turbulent Fluxes) algorithm was thus developed and applied to remote sensing research and applications. The recently revived and produced daily global (1ox1o) GSSTF2b (Version-2b) dataset (July 1987-December 2008) is currently under processing for an official distribution by NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) due by the end of this month (September, 2010). Like its predecessor product GSSTF2, GSSTF2b is expected to provide the scientific community a longer-period and useful turbulent surface flux dataset for global energy and water cycle research, as well as regional and short period data analyses. We have recently been funded by the NASA/MEaSUREs Program to resume processing of the GSSTF with an objective of continually producing an up-to-date uniform and reliable dataset of sea surface turbulent fluxes, derived from improved input remote sensing data and model reanalysis, which would continue to be useful for global energy and water flux research and applications. The daily global (1ox1o) GSSTF2b dataset has lately been produced using upgraded and improved input datasets such as the Special Sensor Microwave Imager (SSM/I) Version-6 (V6) product (including brightness temperature [Tb], total precipitable water [W], and wind speed [U]) and the NCEP/DOE Reanalysis-2 (R2) product (including sea skin temperature [SKT], 2-meter air temperature [T2m], and sea level pressure [SLP]). The input datasets previously used for producing the GSSTF2 product were the SSM/I Version-4 (V4) product and the NCEP Reanalysis-1 (R1) product. The newly produced GSSTF2b was found to generally agree better with available ship measurements obtained from several field experiments in 1999 than its counterpart

  3. The Diabatic Heating and the Generation of Available Potential Energy: Results from NCEP Reanalysis

    Institute of Scientific and Technical Information of China (English)

    ZHANG Tao; WU Guoxiong; GUO Yufu

    2005-01-01

    In the existing studies on the atmospheric energy cycle, the attention to the generation of available potential energy (APE) is restricted to its global mean value. The geographical distributions of the generation of APE and its mechanism of formation are investigated by using the three-dimensional NCEP/NCAR diabatic heating reanalysis in this study. The results show that the contributions from sensible heating and net radiation to the generation of zonal and time-mean APE (Gz) are mainly located in high and middle latitudes with an opposite sign, while the latent heating shows a dominant effect on Gz mainly in the tropics and high latitudes where the contributions from the middle and upper tropospheres are also contrary to that from the low troposphere. In high latitudes, the Gz is much stronger for the Winter Hemisphere than for the Summer Hemisphere, and this is consistent with the asymmetrical feature shown by the reservoir of zonal and time-mean APE in two hemispheres, which suggests that the generation of APE plays a fundamental role in maintaining the APE in the global atmospheric energy cycle. The same contributions to the generation of stationary eddy APE (GSE) from the different regions related to the maintenance of longitudinal temperature contrast are likely arisen by different physics. Specifically, the positive contributions to GSE from the latent heating in the western tropical Pacific and from the sensible heating over land are dominated by the heating at warm regions, whereas those from the latent heating in the eastern tropical Pacific and from the sensitive heating over the oceans are dominated by the cooling at cold regions. Thus, our findings provide an observational estimate of the generation of eddy APE to identify the regional contributions in the climate simulations because it might be correct for the wrong reasons in the general circulation model (GCM). The largest positive contributions to the generation of transient eddy APE (GTE) are

  4. Improvement of NCEP Numerical Weather Prediction with Use of Satellite Land Measurements

    Science.gov (United States)

    Zheng, W.; Ek, M. B.; Wei, H.; Meng, J.; Dong, J.; Wu, Y.; Zhan, X.; Liu, J.; Jiang, Z.; Vargas, M.

    2014-12-01

    Over the past two decades, satellite measurements are being increasingly used in weather and climate prediction systems and have made a considerable progress in accurate numerical weather and climate predictions. However, it is noticed that the utilization of satellite measurements over land is far less than over ocean, because of the high land surface inhomogeneity and the high emissivity variabilities in time and space of surface characteristics. In this presentation, we will discuss the application efforts of satellite land observations in the National Centers for Environmental Prediction (NCEP) operational Global Forecast System (GFS) in order to improve the global numerical weather prediction (NWP). Our study focuses on use of satellite data sets such as vegetation type and green vegetation fraction, assimilation of satellite products such as soil moisture retrieval, and direct radiance assimilation. Global soil moisture data products could be used for initialization of soil moisture state variables in numerical weather, climate and hydrological forecast models. A global Soil Moisture Operational Product System (SMOPS) has been developed at NOAA-NESDIS to continuously provide global soil moisture data products to meet NOAA-NCEP's soil moisture data needs. The impact of the soil moisture data products on numerical weather forecast is assessed using the NCEP GFS in which the Ensemble Kalman Filter (EnKF) data assimilation algorithm has been implemented. In terms of radiance assimilation, satellite radiance measurements in various spectral channels are assimilated through the JCSDA Community Radiative Transfer Model (CRTM) on the NCEP Gridpoint Statistical Interpolation (GSI) system, which requires the CRTM to calculate model brightness temperature (Tb) with input of model atmosphere profiles and surface parameters. Particularly, for surface sensitive channels (window channels), Tb largely depends on surface parameters such as land surface skin temperature, soil

  5. Prediction skill of tropical synoptic scale transients from ECMWF and NCEP Ensemble Prediction Systems

    Energy Technology Data Exchange (ETDEWEB)

    Taraphdar, S.; Mukhopadhyay, P.; Leung, L. Ruby; Landu, Kiranmayi

    2016-01-05

    Abstract

    The prediction skill of tropical synoptic scale transients (SSTR) such as monsoon low and depression during the boreal summer of 2007–2009 are assessed using high resolution ECMWF and NCEP TIGGE forecasts data. By analyzing 246 forecasts for lead times up to 10 days, it is found that the models have good skills in forecasting the planetary scale means but the skills of SSTR remain poor, with the latter showing no skill beyond 2 days for the global tropics and Indian region. Consistent forecast skills among precipitation, velocity potential, and vorticity provide evidence that convection is the primary process responsible for precipitation. The poor skills of SSTR can be attributed to the larger random error in the models as they fail to predict the locations and timings of SSTR. Strong correlation between the random error and synoptic precipitation suggests that the former starts to develop from regions of convection. As the NCEP model has larger biases of synoptic scale precipitation, it has a tendency to generate more random error that ultimately reduces the prediction skill of synoptic systems in that model. The larger biases in NCEP may be attributed to the model moist physics and/or coarser horizontal resolution compared to ECMWF.

  6. Satellite-based monitoring of particulate matter pollution at very high resolution: the HOTBAR method

    Science.gov (United States)

    Wilson, Robin; Milton, Edward; Nield, Joanna

    2016-04-01

    Particulate matter air pollution is a major health risk, and is responsible for millions of premature deaths each year. Concentrations tend to be highest in urban areas - particularly in the mega-cities of rapidly industrialising countries, where there are limited ground monitoring networks. Satellite-based monitoring has been used for many years to assess regional-scale trends in air quality, but currently available satellite products produce data at 1-10km resolution: too coarse to discern the small-scale patterns of sources and sinks seen in urban areas. Higher-resolution satellite products are required to provide accurate assessments of particulate matter concentrations in these areas, and to allow analysis of localised air quality effects on health. The Haze Optimized Transform-based Aerosol Retrieval (HOTBAR) method is a novel method which provides estimates of PM2.5 concentrations from high-resolution (approximately 30m) satellite imagery. This method is designed to work over a wide range of land covers and performs well over the complex land-cover mosaic found in urban areas. It requires only standard visible and near-infrared data, making it applicable to a range of data from sensors such as Landsat, SPOT and Sentinel-2. The method is based upon an extension of the Haze Optimized Transform (HOT), which was originally designed for assessing areas of thick haze in satellite imagery. This was done by calculating a 'haziness' value for each pixel in an image as the distance from a 'Clear Line' in feature space, defined by the high correlation between visible bands. Here, we adapt the HOT method and use it to estimate Aerosol Optical Thickness (a measure of the column-integrated haziness of the atmosphere) instead, from which PM2.5 concentrations can then be estimated. Significant extensions to the original HOT method include Monte Carlo estimation of the 'Clear Line', object-based correction for land cover, and estimation of AOT from the haziness values

  7. Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

    Directory of Open Access Journals (Sweden)

    Yunjun Yao

    2014-01-01

    Full Text Available Satellite-based vegetation indices (VIs and Apparent Thermal Inertia (ATI derived from temperature change provide valuable information for estimating evapotranspiration (LE and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. The validation results illustrate that the daily LE can be estimated with the Root Mean Square Error (RMSE varying from 10.7 W/m2 to 87.6 W/m2, and with the square of correlation coefficient (R2 from 0.41 to 0.89 (p < 0.01. Compared with the Priestley-Taylor-based LE (PT-JPL algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02. The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.

  8. Comparison of Satellite-based Basal and Adjusted Evapotranspiration for Several California Crops

    Science.gov (United States)

    Johnson, L.; Lund, C.; Melton, F. S.

    2013-12-01

    _adj throughout each monitoring period was lower than cumulative ETb for most crops, indicating that effect of water stress tended to exceed that of soil evaporation relative to basal conditions. We present results from the analysis and discuss implications for operational use of satellite-based Kcb and ETcb estimates for agricultural water resource management.

  9. Evaluation of the Reanalysis Surface Incident Shortwave Radiation Products from NCEP, ECMWF, GSFC, and JMA Using Satellite and Surface Observations

    Directory of Open Access Journals (Sweden)

    Xiaotong Zhang

    2016-03-01

    Full Text Available Solar radiation incident at the Earth’s surface (Rs is an essential component of the total energy exchange between the atmosphere and the surface. Reanalysis data have been widely used, but a comprehensive validation using surface measurements is still highly needed. In this study, we evaluated the Rs estimates from six current representative global reanalyses (NCEP–NCAR, NCEP-DOE; CFSR; ERA-Interim; MERRA; and JRA-55 using surface measurements from different observation networks [GEBA; BSRN; GC-NET; Buoy; and CMA] (674 sites in total and the Earth’s Radiant Energy System (CERES EBAF product from 2001 to 2009. The global mean biases between the reanalysis Rs and surface measurements at all sites ranged from 11.25 W/m2 to 49.80 W/m2. Comparing with the CERES-EBAF Rs product, all the reanalyses overestimate Rs, except for ERA-Interim, with the biases ranging from −2.98 W/m2 to 21.97 W/m2 over the globe. It was also found that the biases of cloud fraction (CF in the reanalyses caused the overestimation of Rs. After removing the averaged bias of CERES-EBAF, weighted by the area of the latitudinal band, a global annual mean Rs values of 184.6 W/m2, 180.0 W/m2, and 182.9 W/m2 were obtained over land, ocean, and the globe, respectively.

  10. Satellite-based technique for nowcasting of thunderstorms over Indian region

    Indian Academy of Sciences (India)

    Suman Goyal; Ashish Kumar; M Mohapatra; L S Rathore; S K Dube; Rahul Saxena; R K Giri

    2017-08-01

    India experiences severe thunderstorms during the months, March–June. But these systems are not predicted well, mainly due to the absence of mesoscale observational network over Indian region and the expert system. As these are short lived systems, the nowcast is attempted worldwide based on satellite and radar observations. Due to inadequate radar network, satellite plays the dominant role for nowcast of these thunderstorms. In this study, a nowcast based algorithm ForTracc developed by Vila et al. (Weather Forecast 23:233–245, 2008) has been examined over the Indian region using Infrared Channel (10.8 μm) of INSAT-3D for prediction of Mesoscale Convective Systems (MCS). In this technique, the current location and intensity in terms of Cloud Top Brightness Temperature (CTBT) of the MCS are extrapolated. The purpose of this study is to validate this satellite-based nowcasting technique for Convective Cloud Clusters that helps in optimum utilization of satellite data and improve the nowcasting. The model could predict reasonably the minimum CTBT of the convective cell with average absolute error (AAE) of <7 K for different lead periods (30–180 min). However, it was underestimated for all the lead periods of forecasts. The AAE in the forecasts of size of the cluster varies from about 3×104 km2 for 30-min forecast to 7×104 km2 for 120-min forecast. The mean absolute error in prediction of size is above 31–38% of actual size for different lead periods of forecasts from 30 to 180 min. There is over estimation in prediction of size for 30 and 60 min forecasts (17% and 2.6% of actual size of the cluster, respectively) and underestimation in 90 to 180-min forecasts (–2.4% to –28%). The direct position error (DPE) based on the location of minimum CTBT ranges from 70 to 144 km for 30–180-min forecast respectively.

  11. Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

    Directory of Open Access Journals (Sweden)

    Y. Y. Liu

    2010-09-01

    Full Text Available Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved retrievals of surface soil moisture variations at global scales. Here we propose a technique to take advantage of retrieval characteristics of passive (AMSR-E and active (ASCAT microwave satellite estimates over sparse-to-moderately vegetated areas to obtain an improved soil moisture product. To do this, absolute soil moisture values from AMSR-E and relative soil moisture derived from ASCAT are rescaled against a reference land surface model date set using a cumulative distribution function (CDF matching approach. While this technique imposes the bias of the reference to the rescaled satellite products, it adjusts both satellite products to the same range and almost preserves the correlation between satellite products and in situ measurements. Comparisons with in situ data demonstrated that over the regions where the correlation coefficient between rescaled AMSR-E and ASCAT is above 0.65 (hereafter referred to as transitional regions, merging the different satellite products together increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT are respectively used in the merged product. Thus the merged product carries the advantages of better spatial coverage overall and increased number of observations particularly for the transitional regions. The combination approach developed in this study has the potential to be applied to existing microwave satellites as well as to new microwave missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

  12. Evaluation of satellite based indices for primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2008-07-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modelling within a water limited environment. Results show a strong correlation between EVI against gross primary production (GPP, demonstrating the significance of EVI for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modelling in similar semi-arid ecosystems is limited.

  13. Advanced Multipath Mitigation Techniques for Satellite-Based Positioning Applications

    Directory of Open Access Journals (Sweden)

    Mohammad Zahidul H. Bhuiyan

    2010-01-01

    Full Text Available Multipath remains a dominant source of ranging errors in Global Navigation Satellite Systems (GNSS, such as the Global Positioning System (GPS or the future European satellite navigation system Galileo. Multipath is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function used for time delay estimation. However, some wireless communications techniques exploit multipath in order to provide signal diversity though in GNSS, the major challenge is to effectively mitigate the multipath, since we are interested only in the satellite-receiver transit time offset of the Line-Of-Sight (LOS signal for the receiver's position estimate. Therefore, the multipath problem has been approached from several directions in order to mitigate the impact of multipath on navigation receivers, including the development of novel signal processing techniques. In this paper, we propose a maximum likelihood-based technique, namely, the Reduced Search Space Maximum Likelihood (RSSML delay estimator, which is capable of mitigating the multipath effects reasonably well at the expense of increased complexity. The proposed RSSML attempts to compensate the multipath error contribution by performing a nonlinear curve fit on the input correlation function, which finds a perfect match from a set of ideal reference correlation functions with certain amplitude(s, phase(s, and delay(s of the multipath signal. It also incorporates a threshold-based peak detection method, which eventually reduces the code-delay search space significantly. However, the downfall of RSSML is the memory requirement which it uses to store the reference correlation functions. The multipath performance of other delay-tracking methods previously studied for Binary Phase Shift Keying-(BPSK- and Sine Binary Offset Carrier- (SinBOC- modulated signals is also analyzed in closed loop model with the new Composite

  14. Validation of PV performance models using satellite-based irradiance measurements : a case study.

    Energy Technology Data Exchange (ETDEWEB)

    Stein, Joshua S.; Parkins, Andrew (Clean Power Research); Perez, Richard (University at Albany)

    2010-05-01

    Photovoltaic (PV) system performance models are relied upon to provide accurate predictions of energy production for proposed and existing PV systems under a wide variety of environmental conditions. Ground based meteorological measurements are only available from a relatively small number of locations. In contrast, satellite-based radiation and weather data (e.g., SUNY database) are becoming increasingly available for most locations in North America, Europe, and Asia on a 10 x 10 km grid or better. This paper presents a study of how PV performance model results are affected when satellite-based weather data is used in place of ground-based measurements.

  15. Efficient enhancing scheme for TCP performance over satellite-based internet

    Institute of Scientific and Technical Information of China (English)

    Wang Lina; Gu Xuemai

    2007-01-01

    Satellite link characteristics drastically degrade transport control protocol (TCP) performance. An efficient performance enhancing scheme is proposed. The improvement of TCP performance over satellite-based Intemet is accomplished by protocol transition gateways at each end ora satellite link. The protocol which runs over a satellite link executes the receiver-driven flow control and acknowledgements- and timeouts-based error control strategies. The validity of this TCP performance enhancing scheme is verified by a series of simulation experiments. Results show that the proposed scheme can efficiently enhance the TCP performance over satellite-based Intemet and ensure that the available bandwidth resources of the satellite link are fully utilized.

  16. Correcting satellite-based precipitation products from SMOS soil moisture data assimilation using two models of different complexity

    Science.gov (United States)

    Román-Cascón, Carlos; Pellarin, Thierry; Gibon, François

    2017-04-01

    Real-time precipitation information at the global scale is quite useful information for many applications. However, satellite-based precipitation products in real time are known to be biased from real values observed in situ. On the other hand, the information about precipitation contained in soil moisture data can be very useful to improve precipitation estimation, since the evolution of this variable is highly influenced by the amount of rainfall at a certain area after a rain event. In this context, the soil moisture data from the Soil Moisture Ocean Salinity (SMOS) satellite is used to correct the precipitation provided by real-time satellite-based products such as CMORPH, TRMM-3B42RT or PERSIANN. In this work, we test an assimilation algorithm based on the data assimilation of SMOS measurements in two models of different complexity: a simple hydrological model (Antecedent Precipitation Index (API)) and a state-of-the-art complex land-surface model (Surface Externalisée (SURFEX)). We show how the assimilation technique, based on a particle filter method, leads to the improvement of correlation and root mean squared error (RMSE) of precipitation estimates, with slightly better results for the simpler (and less expensive computationally) API model. This methodology has been evaluated for six years in ten sites around the world with different features, showing the limitations of the methodology in regions affected by mountainous terrain or by high radio-frequency interferences (RFI), which notably affect the quality of the soil moisture retrievals from brightness temperatures by SMOS. The presented results are promising for a potential near-real time application at the global scale.

  17. Fog/Low Visibility Forecasting from NCEP - Current Status and Performance

    Science.gov (United States)

    Zhou, B.; Dimego, G.; Gultepe, I.

    2010-07-01

    Low visibility(fog is very hazardous to air/land traffic and is beeing particularly emphasized at National Weather Service(NWS) of NOAA and in NextGen, a future Air Traffic Management System of Federal Aviation Administration (FAA), United States. As of now however, fog forecast is still not operational guidance from National Centers for Environment Prediction (NCEP), an official numerical weather prediction (NWP) center of NWS, due to its complexity and computational resource limitation. Instead, it is only diagnosed by local weather forecasters through either model output statistics (MOS) or other variables based upon their forecasting experience. Nevertheless, research on numerical fog prediction has been conducting at NCEP. Recently, in an effort to add it to NCEP’s operational guidance as a step to echo the requirement from NWS and the NextGen of FAA, low visibility/fog forecast was experimentally implemented and tested at NCEP. In this paper, predictions of fog and low visibility (fog from two ensemble forecast systems are also presented. One is the Short Range Ensemble Forecast System (SREF), the other is the Very Sort Range Ensemble Forecast System (VSREF). Through verifications, deterministically and probabilistically from November 2009 to March 2010 on North America, the fog and low visibility predictabilities for various models and ensembles are compared and discussed. The results show that the general performances of fog and low visibility prediction from the single model forecast systems are still low, but the application of ensemble, either in low or high resolution, has shed light on its performance improvement. Furthermore through this study, where the efforts should be focused on in the models or methods are also suggested.

  18. Global Crop Monitoring: A Satellite-Based Hierarchical Approach

    Directory of Open Access Journals (Sweden)

    Bingfang Wu

    2015-04-01

    Full Text Available Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China and “sub-countries” (for the nine largest countries. The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI, Vegetation Condition Index (VCI, Cropped Arable Land Fraction (CALF as well as Cropping Intensity (CI. Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI, cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion. Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly “CropWatch bulletin” which

  19. Unmodelled magnetic contributions in satellite-based models

    Science.gov (United States)

    Tozzi, Roberta; Mandea, Mioara; De Michelis, Paola

    2016-06-01

    A complex system of electric currents flowing in the ionosphere and magnetosphere originates from the interaction of the solar wind and the Interplanetary Magnetic Field (IMF) with the Earth's magnetic field. These electric currents generate magnetic fields contributing themselves to those measured by both ground observatories and satellites. Here, low-resolution (1 Hz) magnetic vector data recorded between 1 March 2014 and 31 May 2015 by the recently launched Swarm constellation are considered. The core and crustal magnetic fields and part of that originating in the magnetosphere are removed from Swarm measurements using CHAOS-5 model. Low- and mid-latitude residuals of the geomagnetic field representing the ionospheric and the unmodelled magnetospheric contributions are investigated, in the Solar Magnetic frame, according to the polarity of IMF B y (azimuthal) and B z (north-south) components and to different geomagnetic activity levels. The proposed approach makes it possible to investigate the features of unmodelled contributions due to the external sources of the geomagnetic field. Results show, on one side, the existence of a relation between the analysed residuals and IMF components B y and B z , possibly due to the long distance effect of high-latitude field-aligned currents. On the other side, they suggest the presence of a contribution due to the partial ring current that is activated during the main phase of geomagnetic storms. The perturbation observed on residuals is also compatible with the effect of the net field-aligned currents. Moreover, we have quantitatively estimated the effect of these current systems on computed residuals.

  20. Satellite-based empirical models linking river plume dynamics with hypoxic area andvolume

    Science.gov (United States)

    Satellite-based empirical models explaining hypoxic area and volume variation were developed for the seasonally hypoxic (O2 < 2 mg L−1) northern Gulf of Mexico adjacent to the Mississippi River. Annual variations in midsummer hypoxic area and ...

  1. The Satellite Based Hydrological Model (SHM): Routing Scheme and its Evaluation

    Science.gov (United States)

    kumari, Nikul; Paul, Pranesh Kumar; Singh, Rajendra; Panigrahy, Niranjan; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghavendra P.

    2016-04-01

    The collection of spatially extensive data by using the traditional methods of data acquisition is a challenging task for a large territory like India. To overcome such problems, the Satellite based Hydrological Model (SHM), a large scale conceptual hydrological model for the Indian Territory, is being developed under the PRACRITI-2 program of the Space Applications Centre (SAC), Ahmedabad. The model aims at preparing sustainable water management scenarios using remote sensing data from Indian satellites to handle the fresh water crisis in India. There are five modules namely, Surface Water (SW), Forest (F), Snow (S), Groundwater (GW) and Routing (ROU) in the SHM. The SW, F and S modules convert rainfall into surface runoff and generate input (infiltration and percolation) for the GW module, and GW generates baseflow using that input. In this study, a cell-to-cell routing (ROU) module has been developed for SHM. It is based on the principle of Time Variant Spatially Distributed Direct Hydrograph (SDDH) to route the generated runoff and baseflow generated by various modules upto the outlet. The entire India is divided into 5km x 5km grid cells and properties at the center of the cell are assumed to represent the property of the cell. In the routing scheme, for each cell a single downstream cell is defined in the direction of steepest descent, to create the flow network. These grid cells are classified into overland cells and channel cells based on the threshold value taken into consideration. The overland flow travel time of each overland cell is estimated by combining a steady state kinematic wave approximation with Manning's equation and the channel flow travel time of each channel cell is estimated using Manning's equation and the steady state continuity equation. The travel time for each cell is computed by dividing the travel distance through that cell with cell velocity. The cumulative travel time from each grid cell to the watershed outlet is the sum of

  2. An Effective Configuration of Ensemble Size and Horizontal Resolution for the NCEP GEFS

    Institute of Scientific and Technical Information of China (English)

    MA Juhui; Yuejian ZHU; Richard WOBUS; Panxing WANG

    2012-01-01

    Two important questions are addressed in this paper using the Global Ensemble Forecast System (GEFS)from the National Centers for Environmental Prediction (NCEP):(1) How many ensemble members are needed to better represent forecast uncertainties with limited computational resources? (2) What is the relative impact on forecast skill of increasing model resolution and ensemble size? Two-month experiments at T126L28 resolution were used to test the impact of varying the ensemble size from 5 to 80 menbers at the 500-hPa geopotential height.Results indicate that increasing the ensemble size leads to significant improvements in the performance for all forecast ranges when measured by probabilistic metrics,but these improvements are not significant beyond 20 members for long forecast ranges when measured by deterministic metrics.An ensemble of 20 to 30 members is the most effective configuration of ensemble sizes by quantifying the tradeoff between ensemble performance and the cost of computational resources.Two representative configurations of the GEFS-the T126L28 model with 70 members and the T190L28 model with 20 members,which have equivalent computing costs-were compared.Results confirm that,for the NCEP GEFS,increasing the model resolution is more (less) beneficial than increasing the ensemble size for a short (long) forecast range.

  3. Effects of the partitioning of diffuse and direct solar radiation on satellite-based modeling of crop gross primary production

    Science.gov (United States)

    Xin, Qinchuan; Gong, Peng; Suyker, Andrew E.; Si, Yali

    2016-08-01

    Modeling crop gross primary production (GPP) is critical to understanding the carbon dynamics of agro-ecosystems. Satellite-based studies have widely used production efficiency models (PEM) to estimate cropland GPP, wherein light use efficiency (LUE) is a key model parameter. One factor that has not been well considered in many PEMs is that canopy LUE could vary with illumination conditions. This study investigates how the partitioning of diffuse and direct solar radiation influences cropland GPP using both flux tower and satellite data. The field-measured hourly LUE under cloudy conditions was 1.50 and 1.70 times higher than that under near clear-sky conditions for irrigated corn and soybean, respectively. We applied a two-leaf model to simulate the canopy radiative transfer process, where modeled photosynthetically active radiation (PAR) absorbed by canopy agreed with tower measurements (R2 = 0.959 and 0.914 for corn and soybean, respectively). Derived canopy LUE became similar after accounting for the impact of light saturation on leaf photosynthetic capacity under varied illumination conditions. The impacts of solar radiation partitioning on satellite-based modeling of crop GPP was examined using vegetation indices (VI) derived from MODIS data. Consistent with the field modeling results, the relationship between daily GPP and PAR × VI under varied illumination conditions showed different patterns in terms of regression slope and intercept. We proposed a function to correct the influences of direct and diffuse radiation partitioning and the explained variance of flux tower GPP increased in all experiments. Our results suggest that the non-linear response of leaf photosynthesis to light absorption contributes to higher canopy LUE on cloudy days than on clear days. We conclude that accounting for the impacts of solar radiation partitioning is necessary for modeling crop GPP on a daily or shorter basis.

  4. Evaluation of three satellite-based latent heat flux algorithms over forest ecosystems using eddy covariance data.

    Science.gov (United States)

    Yao, Yunjun; Zhang, Yuhu; Zhao, Shaohua; Li, Xianglan; Jia, Kun

    2015-06-01

    We have evaluated the performance of three satellite-based latent heat flux (LE) algorithms over forest ecosystems using observed data from 40 flux towers distributed across the world on all continents. These are the revised remote sensing-based Penman-Monteith LE (RRS-PM) algorithm, the modified satellite-based Priestley-Taylor LE (MS-PT) algorithm, and the semi-empirical Penman LE (UMD-SEMI) algorithm. Sensitivity analysis illustrates that both energy and vegetation terms has the highest sensitivity compared with other input variables. The validation results show that three algorithms demonstrate substantial differences in algorithm performance for estimating daily LE variations among five forest ecosystem biomes. Based on the average Nash-Sutcliffe efficiency and root-mean-squared error (RMSE), the MS-PT algorithm has high performance over both deciduous broadleaf forest (DBF) (0.81, 25.4 W/m(2)) and mixed forest (MF) (0.62, 25.3 W/m(2)) sites, the RRS-PM algorithm has high performance over evergreen broadleaf forest (EBF) (0.4, 28.1 W/m(2)) sites, and the UMD-SEMI algorithm has high performance over both deciduous needleleaf forest (DNF) (0.78, 17.1 W/m(2)) and evergreen needleleaf forest (ENF) (0.51, 28.1 W/m(2)) sites. Perhaps the lower uncertainties in the required forcing data for the MS-PT algorithm, the complicated algorithm structure for the RRS-PM algorithm, and the calibrated coefficients of the UMD-SEMI algorithm based on ground-measured data may explain these differences.

  5. Assimilation of Satellite Based Soil Moisture Data in the National Weather Service's Flash Flood Guidance System

    Science.gov (United States)

    Seo, D.; Lakhankar, T.; Cosgrove, B.; Khanbilvardi, R.

    2012-12-01

    potential sources of remotely sensed soil moisture data. SMOS measures the microwave radiation emitted from the Earth's surface operating at L-band (1.20-1.41 GHz) to measure surface soil moisture directly. Microwave radiation at this wavelength offers relatively deeper penetration and has lower sensitivity to vegetation impacts. The main objective of this research is to evaluate the contribution of remote sensing technology to quantifiable improvements in flash flood applications as well as adding a remote sensing component to the NWS FFG Algorithm. The challenge of this study is employing the direct soil moisture data from SMOS to replace the model-calculated soil moisture state which is based on the soil water balance in 4 km x 4 km Hydrologic Rainfall Analysis Project (HRAP) grid cells. In order to determine the value of the satellite data to NWS operations, the streamflow generated by HL-RDHM with and without soil moisture assimilation will be compared to USGS gauge data. Furthermore, we will apply the satellite-based soil moisture data with the FFG algorithm to evaluate how many hits, misses and false alarms are generated. This study will evaluate the value of remote sensing data in constraining the state of the system for main-stem and flash flood forecasting.

  6. Comparison of Products from ERA-40, NCEP-2, and CRU with Station Data for Summer Precipitation over China

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Summer precipitation products from the 45-Year European Centre for Medium-Range Weather Forecast (ECMWF) Reanalysis (ERA-40), and NCEP-Department of Energy (DOE) Atmospheric Model Intercomparison Project (AMIP-Ⅱ) Reanalysis (NCEP-2), and Climatic Research Unit (CRU) TS 2.1dataset are compared with the corresponding observations over China in order to understand the quality and utility of the reanalysis datasets for the period 1979-2001. The results reveal that although the magnitude and location of the rainfall belts differ among the reanalysis, CRU, and station data over South and West China, the spatial distributions show good agreement over most areas of China. In comparison with the observations in most areas of China, CRU best matches the observed summer precipitation,while ERA-40 reports less precipitation and NCEP-2 reports more precipitation than the observations.With regard to the amplitude of the interannual variations, CRU is better than either of the reanalyses in representing the corresponding observations. The amplitude in NCEP-2 is stronger but that of ERA-40 is weaker than the observations in most study domains. NCEP-2 has a more obvious interannual variability than ERA-40 or CRU in most areas of East China. Through an Empirical orthogonal function (EOF)analysis, the main features of the rainfall belts produced by CRU agree better with the observations than with those produced by the reanalyses in the Yangtze-Huaihe River valley. In East of China, particularly in the Yangtze-Huaihe River valley, CRU can reveal the quasi-biennial oscillation of summer precipitation represented by the observations, but the signal of ERA-40 is comparatively weak and not very obvious,whereas that of NCEP-2 is also weak before 1990 but very strong after 1990. The results also suggest that the magnitude of the precipitation difference between ERA-40 and the observations is smaller than that between NCEP-2 and the observations, but the variations represented by NCEP-2

  7. Using R for analysing spatio-temporal datasets: a satellite-based precipitation case study

    Science.gov (United States)

    Zambrano-Bigiarini, Mauricio

    2017-04-01

    Increasing computer power and the availability of remote-sensing data measuring different environmental variables has led to unprecedented opportunities for Earth sciences in recent decades. However, dealing with hundred or thousands of files, usually in different vectorial and raster formats and measured with different temporal frequencies, impose high computation challenges to take full advantage of all the available data. R is a language and environment for statistical computing and graphics which includes several functions for data manipulation, calculation and graphical display, which are particularly well suited for Earth sciences. In this work I describe how R was used to exhaustively evaluate seven state-of-the-art satellite-based rainfall estimates (SRE) products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-adj, MSWEPv1.1 and PGFv3) over the complex topography and diverse climatic gradients of Chile. First, built-in functions were used to automatically download the satellite-images in different raster formats and spatial resolutions and to clip them into the Chilean spatial extent if necessary. Second, the raster package was used to read, plot, and conduct an exploratory data analysis in selected files of each SRE product, in order to detect unexpected problems (rotated spatial domains, order or variables in NetCDF files, etc). Third, raster was used along with the hydroTSM package to aggregate SRE files into different temporal scales (daily, monthly, seasonal, annual). Finally, the hydroTSM and hydroGOF packages were used to carry out a point-to-pixel comparison between precipitation time series measured at 366 stations and the corresponding grid cell of each SRE. The modified Kling-Gupta index of model performance was used to identify possible sources of systematic errors in each SRE, while five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities

  8. Satellite-based assessment of climate controls on US burned area

    Directory of Open Access Journals (Sweden)

    D. C. Morton

    2013-01-01

    Full Text Available Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate–fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burned area (BA, the Global Fire Emissions Database (GFED, 1997–2010 and Monitoring Trends in Burn Severity (MTBS, 1984–2009 BA products. For each US National Climate Assessment (NCA region, we analyzed the relationships between monthly BA and potential evaporation (PE derived from reanalysis climate data at 0.5° resolution. US fire activity increased over the past 25 yr, with statistically significant increases in MTBS BA for the entire US and the Southeast and Southwest NCA regions. Monthly PE was strongly correlated with US fire activity, yet the climate driver of PE varied regionally. Fire season temperature and shortwave radiation were the primary controls on PE and fire activity in Alaska, while water deficit (precipitation – PE was strongly correlated with fire activity in the Plains regions and Northwest US. BA and precipitation anomalies were negatively correlated in all regions, although fuel-limited ecosystems in the Southern Plains and Southwest exhibited positive correlations with longer lead times (6–12 months. Fire season PE increased from the 1980's–2000's, enhancing climate-driven fire risk in the southern and western US where PE–BA correlations were strongest. Spatial and temporal patterns of increasing fire season PE and BA during the 1990's–2000's highlight the potential sensitivity of US fire activity to climate change in coming decades. However, climate-fire relationships at the national scale are complex, based on the

  9. Satellite-based assessment of climate controls on US burned area

    Directory of Open Access Journals (Sweden)

    D. C. Morton

    2012-06-01

    Full Text Available Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate-fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burned area (BA, the Global Fire Emissions Database (GFED, 1997–2010 and Monitoring Trends in Burn Severity (MTBS, 1984–2009 BA products. For each US National Climate Assessment (NCA region, we analyzed the relationships between monthly BA and potential evaporation (PE derived from reanalysis climate data at 0.5° resolution. US fire activity increased over the past 25 yr, with statistically significant increases in MTBS BA for entire US and the Southeast and Southwest NCA regions. Monthly PE was strongly correlated with US fire activity, yet the climate driver of PE varied regionally. Fire season temperature and shortwave radiation were the primary controls on PE} and fire activity in the Alaska, while water deficit (precipitation – PE was strongly correlated with fire activity in the Plains regions and Northwest US. BA and precipitation anomalies were negatively correlated in all regions, although fuel-limited ecosystems in the Southern Plains and Southwest exhibited positive correlations with longer lead times (6–12 months. Fire season PE increased from the 1980s–2000s, enhancing climate-driven fire risk in the southern and western US where PE-BA correlations were strongest. Spatial and temporal patterns of increasing fire season PE and BA during the 1990s–2000s highlight the potential sensitivity of US fire activity to climate change in coming decades. However, climate-fire relationships at the national scale are complex, based on the diversity of

  10. Satellite-based assessment of climate controls on US burned area

    Science.gov (United States)

    Morton, D. C.; Collatz, G. J.; Wang, D.; Randerson, J. T.; Giglio, L.; Chen, Y.

    2013-01-01

    Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate-fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burned area (BA), the Global Fire Emissions Database (GFED, 1997-2010) and Monitoring Trends in Burn Severity (MTBS, 1984-2009) BA products. For each US National Climate Assessment (NCA) region, we analyzed the relationships between monthly BA and potential evaporation (PE) derived from reanalysis climate data at 0.5° resolution. US fire activity increased over the past 25 yr, with statistically significant increases in MTBS BA for the entire US and the Southeast and Southwest NCA regions. Monthly PE was strongly correlated with US fire activity, yet the climate driver of PE varied regionally. Fire season temperature and shortwave radiation were the primary controls on PE and fire activity in Alaska, while water deficit (precipitation - PE) was strongly correlated with fire activity in the Plains regions and Northwest US. BA and precipitation anomalies were negatively correlated in all regions, although fuel-limited ecosystems in the Southern Plains and Southwest exhibited positive correlations with longer lead times (6-12 months). Fire season PE increased from the 1980's-2000's, enhancing climate-driven fire risk in the southern and western US where PE-BA correlations were strongest. Spatial and temporal patterns of increasing fire season PE and BA during the 1990's-2000's highlight the potential sensitivity of US fire activity to climate change in coming decades. However, climate-fire relationships at the national scale are complex, based on the diversity of fire types

  11. Applying an economical scale-aware PDF-based turbulence closure model in NOAA NCEP GCMs.

    Science.gov (United States)

    Krueger, S. K.; Belochitski, A.; Moorthi, S.; Bogenschutz, P.; Pincus, R.

    2015-12-01

    A novel unified representation of sub-grid scale (SGS) turbulence, cloudiness, and shallow convection is being implemented into the NOAA NCEP Global Forecasting System (GFS) general circulation model. The approach, known as Simplified High Order Closure (SHOC), is based on predicting a joint PDF of SGS thermodynamic variables and vertical velocity and using it to diagnose turbulent diffusion coefficients, SGS fluxes, condensation and cloudiness. Unlike other similar methods, only one new prognostic variable, turbulent kinetic energy (TKE), needs to be intoduced, making the technique computationally efficient.SHOC code was adopted for a global model environment from its origins in a cloud resolving model, and incorporated into NCEP GFS. SHOC was first tested in a non-interactive mode, a configuration where SHOC receives inputs from the host model, but its outputs are not returned to the GFS. In this configuration: a) SGS TKE values produced by GFS SHOC are consistent with those produced by SHOC in a CRM, b) SGS TKE in GFS SHOC exhibits a well defined diurnal cycle, c) there's enhanced boundary layer turbulence in the subtropical stratocumulus and tropical transition-to-cumulus areas d) buoyancy flux diagnosed from the assumed PDF is consistent with independently calculated Brunt-Vaisala frequency in identifying stable and unstable regions.Next, SHOC was coupled to GFS, namely turbulent diffusion coefficients computed by SHOC are now used in place of those currently produced by the GFS boundary layer and shallow convection schemes (Han and Pan, 2011), as well as condensation and cloud fraction diagnosed from the SGS PDF replace those calculated in the current large-scale cloudines scheme (Zhao and Carr, 1997). Ongoing activities consist of debugging the fully coupled GFS/SHOC.Future work will consist of evaluating model performance and tuning the physics if necessary, by performing medium-range NWP forecasts with prescribed initial conditions, and AMIP-type climate

  12. An assessment of oceanic variability in the NCEP climate forecast system reanalysis

    Energy Technology Data Exchange (ETDEWEB)

    Xue, Yan; Hu, Zeng-Zhen; Kumar, Arun [Climate Prediction Center, NCEP/NOAA, Camp Springs, MD (United States); Huang, Boyin; Wen, Caihong [Climate Prediction Center, NCEP/NOAA, Camp Springs, MD (United States); Wyle Information System, Camp Springs, MD (United States); Behringer, David; Nadiga, Sudhir [Environmental Modeling Center, NCEP/NOAA, Camp Springs, MD (United States)

    2011-12-15

    At the National Centers for Environmental Prediction (NCEP), a reanalysis of the atmosphere, ocean, sea ice and land over the period 1979-2009, referred to as the climate forecast system reanalysis (CFSR), was recently completed. The oceanic component of CFSR includes many advances: (a) the MOM4 ocean model with an interactive sea-ice, (b) the 6 h coupled model forecast as the first guess, (c) inclusion of the mean climatological river runoff, and (d) high spatial (0.5 x 0.5 ) and temporal (hourly) model outputs. Since the CFSR will be used by many in initializing/validating ocean models and climate research, the primary motivation of the paper is to inform the user community about the saline features in the CFSR ocean component, and how the ocean reanalysis compares with in situ observations and previous reanalysis. The net ocean surface heat flux of the CFSR has smaller biases compared to the sum of the latent and sensible heat fluxes from the objectively analyzed air-sea fluxes (OAFlux) and the shortwave and longwave radiation fluxes from the International Satellite Cloud Climatology Project (ISCCP-FD) than the NCEP/NCAR reanalysis (R1) and NCEP/DOE reanalysis (R2) in both the tropics and extratropics. The ocean surface wind stress of the CFSR has smaller biases and higher correlation with the ERA40 produced by the European Centre for Medium-Range Weather Forecasts than the R1 and R2, particularly in the tropical Indian and Pacific Ocean. The CFSR also has smaller errors compared to the QuickSCAT climatology for September 1999 to October 2009 than the R1 and R2. However, the trade winds of the CFSR in the central equatorial Pacific are too strong prior to 1999, and become close to observations once the ATOVS radiance data are assimilated in late 1998. A sudden reduction of easterly wind bias is related to the sudden onset of a warm bias in the eastern equatorial Pacific temperature around 1998/1999. The sea surface height and top 300 m heat content (HC300) of

  13. Influences of tropical-extratropical interaction on the multidecadal AMOC variability in the NCEP climate forecast system

    Science.gov (United States)

    Huang, Bohua; Hu, Zeng-Zhen; Schneider, Edwin K.; Wu, Zhaohua; Xue, Yan; Klinger, Barry

    2012-08-01

    We have examined the mechanisms of a multidecadal oscillation of the Atlantic Meridional Overturning Circulation (AMOC) in a 335-year simulation of the Climate Forecast System (CFS), the climate prediction model developed at the National Centers for Environmental Prediction (NCEP). Both the mean and seasonal cycle of the AMOC in the CFS are generally consistent with observation-based estimates with a maximum northward volume transport of 16 Sv (106 m3/s) near 35°N at 1.2 km. The annual mean AMOC shows an intermittent quasi 30-year oscillation. Its dominant structure includes a deep anomalous overturning cell (referred to as the anomalous AMOC) with amplitude of 0.6 Sv near 35°N and an anomalous subtropical cell (STC) of shallow overturning spanning across the equator. The mechanism for the oscillation includes a positive feedback between the anomalous AMOC and surface wind stress anomalies in mid-latitudes and a negative feedback between the anomalous STC and AMOC. A strong AMOC is associated with warm sea surface temperature anomaly (SSTA) centered near 45°N, which generates an anticyclonic easterly surface wind anomaly. This anticyclonic wind anomaly enhances the regional downwelling and reinforces the anomalous AMOC. In the mean time, a wind-evaporation-SST (WES) feedback extends the warm SSTA to the tropics and induces a cyclonic wind stress anomaly there, which drives a tropical upwelling and weakens the STC north of the equator. The STC anomaly, in turn, drives a cold upper ocean heat content anomaly (HCA) in the northern tropical Atlantic and weakens the meridional heat transport from the tropics to the mid-latitude through an anomalous southward western boundary current. The anomalous STC transports cold HCA from the subtropics to the mid-latitudes, weakening the mid-latitude deep overturning.

  14. Influences of tropical-extratropical interaction on the multidecadal AMOC variability in the NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Bohua; Schneider, Edwin K.; Klinger, Barry [Gorge Mason University, Department of Atmospheric, Oceanic, and Earth Sciences, College of Science, Fairfax, VA (United States); Institute of Global Environment and Society, Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); Hu, Zeng-Zhen; Xue, Yan [National Centers for Environmental Prediction/NOAA, Climate Prediction Center, Camp Springs, MD (United States); Wu, Zhaohua [Florida State University, Department of Earth, Ocean, and Atmospheric Science, Center for Ocean-Atmospheric Prediction Studies, Tallahassee, FL (United States)

    2012-08-15

    We have examined the mechanisms of a multidecadal oscillation of the Atlantic Meridional Overturning Circulation (AMOC) in a 335-year simulation of the Climate Forecast System (CFS), the climate prediction model developed at the National Centers for Environmental Prediction (NCEP). Both the mean and seasonal cycle of the AMOC in the CFS are generally consistent with observation-based estimates with a maximum northward volume transport of 16 Sv (10{sup 6} m{sup 3}/s) near 35 N at 1.2 km. The annual mean AMOC shows an intermittent quasi 30-year oscillation. Its dominant structure includes a deep anomalous overturning cell (referred to as the anomalous AMOC) with amplitude of 0.6 Sv near 35 N and an anomalous subtropical cell (STC) of shallow overturning spanning across the equator. The mechanism for the oscillation includes a positive feedback between the anomalous AMOC and surface wind stress anomalies in mid-latitudes and a negative feedback between the anomalous STC and AMOC. A strong AMOC is associated with warm sea surface temperature anomaly (SSTA) centered near 45 N, which generates an anticyclonic easterly surface wind anomaly. This anticyclonic wind anomaly enhances the regional downwelling and reinforces the anomalous AMOC. In the mean time, a wind-evaporation-SST (WES) feedback extends the warm SSTA to the tropics and induces a cyclonic wind stress anomaly there, which drives a tropical upwelling and weakens the STC north of the equator. The STC anomaly, in turn, drives a cold upper ocean heat content anomaly (HCA) in the northern tropical Atlantic and weakens the meridional heat transport from the tropics to the mid-latitude through an anomalous southward western boundary current. The anomalous STC transports cold HCA from the subtropics to the mid-latitudes, weakening the mid-latitude deep overturning. (orig.)

  15. The Sensitivity of Simulated Ocean Biogeochemistry to Forcing Fields Derived from NCEP and MERRA Reanalysis Products

    Science.gov (United States)

    Gregg, Watson; Casey, Nancy

    2010-01-01

    Ocean biogeochemistry models are typically forced by atmospheric and oceanic data derived from reanalysis products. For the NASA Ocean Biogeochemistry Model (NOBM) such reanalysis forcing fields include: surface wind stress, sea surface temperature, ice distributions, shortwave radiation, surface wind speeds and surface atmospheric pressure. Additionally, proper computation of ocean irradiance requires reanalysis products of relative humidity and precipitable water (in addition to aerosol and cloud information which is derived from satellite data). The question posed here is, does the choice of reanalysis products make a difference in the representation of ocean biology and biogeochemistry? NOBM was forced by NCEP and MERRA reanalysis products for the period 2002-2009. We find that in 2009 global distributions and abundances of biological variables (total chlorophyll and nutrients) and carbon (dissolved inorganic and organic carbon and surface pCO2) were similar between the two different forcing fields. Global statistical comparisons with satellite and in situ data also showed negligible differences.

  16. Evaluating the Cloud Cover Forecast of NCEP Global Forecast System with Satellite Observation

    CERN Document Server

    Ye, Quanzhi

    2011-01-01

    To assess the quality of daily cloud cover forecast generated by the operational global numeric model, the NCEP Global Forecast System (GFS), we compose a large sample with outputs from GFS model and satellite observations from the International Satellite Cloud Climatology Project (ISCCP) in the period of July 2004 to June 2008, to conduct a quantitative and systematic assessment of the performance of a cloud model that covers a relatively long range of time, basic cloud types, and in a global view. The evaluation has revealed the goodness of the model forecast, which further illustrates our completeness on understanding cloud generation mechanism. To quantity the result, we found a remarkably high correlation between the model forecasts and the satellite observations over the entire globe, with mean forecast error less than 15% in most areas. Considering a forecast within 30% difference to the observation to be a "good" one, we find that the probability for the GFS model to make good forecasts varies between...

  17. Implementing earth observation and advanced satellite based atmospheric sounders for water resource and climate modelling

    DEFF Research Database (Denmark)

    Boegh, E.; Dellwik, Ebba; Hahmann, Andrea N.;

    This paper discusses preliminary remote sensing (MODIS) based hydrological modelling results for the Danish island Sjælland (7330 km2) in relation to project objectives and methodologies of a new research project “Implementing Earth observation and advanced satellite based atmospheric sounders...... for effective land surface representation in water resource modeling” (2009- 2012). The purpose of the new research project is to develop remote sensing based model tools capable of quantifying the relative effects of site-specific land use change and climate variability at different spatial scales....... For this purpose, a) internal catchment processes will be studied using a Distributed Temperature Sensing (DTS) system, b) Earth observations will be used to upscale from field to regional scales, and c) at the largest scale, satellite based atmospheric sounders and meso-scale climate modelling will be used...

  18. Source mass eruption rate retrieved from satellite-based data using statistical modelling

    Science.gov (United States)

    Gouhier, Mathieu; Guillin, Arnaud; Azzaoui, Nourddine; Eychenne, Julia; Valade, Sébastien

    2015-04-01

    Ash clouds emitted during volcanic eruptions have long been recognized as a major hazard likely to have dramatic consequences on aircrafts, environment and people. Thus, the International Civil Aviation Organization (ICAO) established nine Volcanic Ash Advisory Centers (VAACs) around the world, whose mission is to forecast the location and concentration of ash clouds over hours to days, using volcanic ash transport and dispersion models (VATDs). Those models use input parameters such as plume height (PH), particle size distribution (PSD), and mass eruption rate (MER), the latter being a key parameter as it directly controls the amount of ash injected into the atmosphere. The MER can be obtained rather accurately from detailed ground deposit studies, but this method does not match the operational requirements in case of a volcanic crisis. Thus, VAACs use empirical laws to determine the MER from the estimation of the plume height. In some cases, this method can be difficult to apply, either because plume height data are not available or because uncertainties related to this method are too large. We propose here an alternative method based on the utilization of satellite data to assess the MER at the source, during explosive eruptions. Satellite-based techniques allow fine ash cloud loading to be quantitatively retrieved far from the source vent. Those measurements can be carried out in a systematic and real-time fashion using geostationary satellite, in particular. We tested here the relationship likely to exist between the amount of fine ash dispersed in the atmosphere and of coarser tephra deposited on the ground. The sum of both contributions yielding an estimate of the MER. For this purpose we examined 19 eruptions (of known duration) in detail for which both (i) the amount of fine ash dispersed in the atmosphere, and (ii) the mass of tephra deposited on the ground have been estimated and published. We combined these data with contextual information that may

  19. Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data

    Science.gov (United States)

    López, Oliver; Houborg, Rasmus; McCabe, Matthew Francis

    2017-01-01

    Advances in space-based observations have provided the capacity to develop regional- to global-scale estimates of evaporation, offering insights into this key component of the hydrological cycle. However, the evaluation of large-scale evaporation retrievals is not a straightforward task. While a number of studies have intercompared a range of these evaporation products by examining the variance amongst them, or by comparison of pixel-scale retrievals against ground-based observations, there is a need to explore more appropriate techniques to comprehensively evaluate remote-sensing-based estimates. One possible approach is to establish the level of product agreement between related hydrological components: for instance, how well do evaporation patterns and response match with precipitation or water storage changes? To assess the suitability of this consistency-based approach for evaluating evaporation products, we focused our investigation on four globally distributed basins in arid and semi-arid environments, comprising the Colorado River basin, Niger River basin, Aral Sea basin, and Lake Eyre basin. In an effort to assess retrieval quality, three satellite-based global evaporation products based on different methodologies and input data, including CSIRO-PML, the MODIS Global Evapotranspiration product (MOD16), and Global Land Evaporation: the Amsterdam Methodology (GLEAM), were evaluated against rainfall data from the Global Precipitation Climatology Project (GPCP) along with Gravity Recovery and Climate Experiment (GRACE) water storage anomalies. To ensure a fair comparison, we evaluated consistency using a degree correlation approach after transforming both evaporation and precipitation data into spherical harmonics. Overall we found no persistent hydrological consistency in these dryland environments. Indeed, the degree correlation showed oscillating values between periods of low and high water storage changes, with a phase difference of about 2-3 months

  20. Long-term analysis of aerosol optical depth over Northeast Asia using a satellite-based measurement: MI Yonsei Aerosol Retrieval Algorithm (YAER)

    Science.gov (United States)

    Kim, Mijin; Kim, Jhoon; Yoon, Jongmin; Chung, Chu-Yong; Chung, Sung-Rae

    2017-04-01

    In 2010, the Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean, and Meteorological Satellite (COMS), was launched including the Meteorological Imager (MI). The MI measures atmospheric condition over Northeast Asia (NEA) using a single visible channel centered at 0.675 μm and four IR channels at 3.75, 6.75, 10.8, 12.0 μm. The visible measurement can also be utilized for the retrieval of aerosol optical properties (AOPs). Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs, we can analyze the spatiotemporal variation of the aerosol using the MI observations over NEA. Therefore, we developed an algorithm to retrieve aerosol optical depth (AOD) using the visible observation of MI, and named as MI Yonsei Aerosol Retrieval Algorithm (YAER). In this study, we investigated the accuracy of MI YAER AOD by comparing the values with the long-term products of AERONET sun-photometer. The result showed that the MI AODs were significantly overestimated than the AERONET values over bright surface in low AOD case. Because the MI visible channel centered at red color range, contribution of aerosol signal to the measured reflectance is relatively lower than the surface contribution. Therefore, the AOD error in low AOD case over bright surface can be a fundamental limitation of the algorithm. Meanwhile, an assumption of background aerosol optical depth (BAOD) could result in the retrieval uncertainty, also. To estimate the surface reflectance by considering polluted air condition over the NEA, we estimated the BAOD from the MODIS dark target (DT) aerosol products by pixel. The satellite-based AOD retrieval, however, largely depends on the accuracy of the surface reflectance estimation especially in low AOD case, and thus, the BAOD could include the uncertainty in surface reflectance estimation of the satellite-based retrieval. Therefore, we re-estimated the BAOD using the ground-based sun-photometer measurement, and

  1. NCEP全球预报系统在ARM SGP站点预报大气温度、湿度和云量的检验%Temperature, Relative Humidity, and Cloud Fraction Predicted by the NCEP Global Forecast System at the ARM SGP Site during 2001-2008:Comparison with ARM Observations

    Institute of Scientific and Technical Information of China (English)

    张寅; 罗亚丽; 管兆勇

    2012-01-01

    This study evaluates the performance of the Global Forecast System (GFS) of the U. S. National Centersfor Environmental Prediction (NCEP) against the Climate Modeling Best Estimate (CMBE) observational dataset made by the U. S. Department of Energy Atmospheric Radiation Measurement (ARM) Program at the southern Great Plains (SGP) site for the years of 2001 - 2008. The investigation focuses on the vertical distributions of air temperature (T) , relative humidity (RH), and cloud fraction. The major findings are as follows;(1) NCEP GFS was able to largely capture the seasonal variations of T and RH. However, on seasonal average, the model overestimated T at the heights of 1. 5 - 12 km, while underestimated T at 13 - 16 km in spring and winter and at 0 - 1. 5 km in autumn and winter, by less than l℃. Both the predicted and observed RH had double peaks located near the surface and around 12 km, respectively. However, the model overestimated RH in the upper and middle troposphere (4 - 12 km). Increase of model resolution from T170L42 to T254L64 significantly improved the prediction of RH at 14 - 18 km. (2) NCEP GFS generally underestimated cloud fraction at heights below 10 km and slightly overestimated cloud fraction at 11 - 13 km. Moreover, the prediction missed the daytime nonprecipitat-ing low-level clouds and underestimated precipitating cloud amounts below 8 km, indicating that activities of shallow convection and deep convection in the model were not active enough. (3) Using the observed RH and the predicted cloud water/ice mixing ratio (qe) to calculate cloud fraction with the diagnostic method in the NCEP GFS model, the result shows that cloud fraction from this calculation is more significantly underestimated compared to the NCEP GFS predicted cloud fraction, suggesting that the underestimation of cloud cover at heights below 11 km by the NCEP GFS is probably contributed by an underestimate of qe at these altitudes. (4) Improvements in the prediction of T, RH

  2. Relation between Ocean SST Dipoles and Downwind Continental Croplands Assessed for Early Management Using Satellite-based Photosynthesis Models

    Science.gov (United States)

    Kaneko, Daijiro

    2015-04-01

    Crop-monitoring systems with the unit of carbon-dioxide sequestration for environmental issues related to climate adaptation to global warming have been improved using satellite-based photosynthesis and meteorological conditions. Early management of crop status is desirable for grain production, stockbreeding, and bio-energy providing that the seasonal climate forecasting is sufficiently accurate. Incorrect seasonal forecasting of crop production can damage global social activities if the recognized conditions are unsatisfied. One cause of poor forecasting related to the atmospheric dynamics at the Earth surface, which reflect the energy budget through land surface, especially the oceans and atmosphere. Recognition of the relation between SST anomalies (e.g. ENSO, Atlantic Niño, Indian dipoles, and Ningaloo Niño) and crop production, as expressed precisely by photosynthesis or the sequestrated-carbon rate, is necessary to elucidate the mechanisms related to poor production. Solar radiation, surface air temperature, and water stress all directly affect grain vegetation photosynthesis. All affect stomata opening, which is related to the water balance or definition by the ratio of the Penman potential evaporation and actual transpiration. Regarding stomata, present data and reanalysis data give overestimated values of stomata opening because they are extended from wet models in forests rather than semi-arid regions commonly associated with wheat, maize, and soybean. This study applies a complementary model based on energy conservation for semi-arid zones instead of the conventional Penman-Monteith method. Partitioning of the integrated Net PSN enables precise estimation of crop yields by modifying the semi-closed stomata opening. Partitioning predicts production more accurately using the cropland distribution already classified using satellite data. Seasonal crop forecasting should include near-real-time monitoring using satellite-based process crop models to avoid

  3. 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

    . Collaboration with GCOM-W is not only limited to its participation to GPM constellation but also coordination in areas of algorithm development and validation in Japan. Generation of high-temporal and high-accurate global rainfall map is one of targets of the GPM mission. As a proto-type for GPM era, JAXA has developed and operates the Global Precipitation Map algorithm in near-real-time since October 2008, and hourly and 0.1-degree resolution binary data and images available at http://sharaku.eorc.jaxa.jp/GSMaP/ four hours after observation. The algorithms are based on outcomes from the Global Satellite Mapping for Precipitation (GSMaP) project, which was sponsored by the Japan Science and Technology Agency (JST) under the Core Research for Evolutional Science and Technology (CREST) framework between 2002 and 2007 (Okamoto et al., 2005; Aonashi et al., 2009; Ushio et al., 2009). Target of GSMaP project is to produce global rainfall maps that are highly accurate and in high temporal and spatial resolution through the development of rain rate retrieval algorithms based on reliable precipitation physical models by using several microwave radiometer data, and comprehensive use of precipitation radar and geostationary infrared imager data. Near-real-time GSMaP data is distributed via internet and utilized by end users. Purpose of data utilization by each user covers broad areas and in world wide; Science researches (model validation, data assimilation, typhoon study, etc.), weather forecast/service, flood warning and rain analysis over river basin, oceanographic condition forecast, agriculture, and education. Toward the GPM era, operational application should be further emphasized as well as science application. JAXA continues collaboration with hydrological communities to utilize satellite-based precipitation data as inputs to future flood prediction and warning system, as well as with meteorological agencies to proceed further data utilization in numerical weather prediction

  4. Atmospheric water vapor transport and recycling in Equatorial Central Africa through NCEP/NCAR reanalysis data

    Energy Technology Data Exchange (ETDEWEB)

    Pokam, Wilfried M.; Djiotang, Lucie A.T.; Mkankam, Francois K. [University of Yaounde 1, Laboratory for Environmental Modelling and Atmospheric Physics, Department of Physics, Faculty of Sciences, P.O. Box 812, Yaounde (Cameroon)

    2012-05-15

    The characteristics of the main components of the water cycle over Equatorial Central Africa (ECA) were analysed using the 32-year period, spanning from 1968 to 2000, of the National Centers for Environmental Prediction-National Censearch (NCEP-) reanalysis project database. A special emphasis was given to identifying the causes of annual and interannual variability of water vapor flux and precipitation recycling. The results suggest that the first maximum of moisture convergence, during the rainy season MAM, comes from upper level moisture flux, related to the north component of the African Easterly Jet (AEJ-N). The second, and greatest, maximum in SON is found to be a consequence of low level moisture advection from the Atlantic Ocean. AEJ-N also drive the seasonal spatial pattern of moisture flux. The interannual variability of moisture flux is contributed mainly by the low level moisture advected from the Atlantic Ocean, underlying its crucial role for the regional climate. Studying the recycling ratio in ECA as a whole shows a low annual cycle whereas subregional scale analysis reveals high amplitude of the seasonal variation. Seasonal variability of the spatial gradient of precipitation recycling is regulated by both moisture flux direction and strength. The annual cycles of recycling ratio in the North and the South of ECA are regulated by both moisture transport and evapotranspiration. (orig.)

  5. Reduction of NCEP Global Forecast System 2-m Temperature Forecast Errors

    Science.gov (United States)

    Zheng, W.; Ek, M. B.; Wei, H.; Meng, J.

    2015-12-01

    In this study the systematic deficiencies and cause of errors in 2-m temperature forecasts in the NCEP Global Forecast System (GFS) are identified by investigating the physics of the Noah land surface model and land-atmosphere interactions, and a practical solution is found to reduce this kind of forecast errors. This presentation focuses on further evaluation of the proposed modifications with two one-month experiments for summer and winter seasons through the verification of GFS forecasts against surface and sounding observations. It was found that the modifications can substantially avoid late afternoon rapidly dropping 2-m temperature and decoupling when a cessation of turbulent transport between the surface and the atmosphere due to high near surface atmospheric stability happens, and reduce the cold bias of 2-m temperature during nighttime. Furthermore, the surface dew point temperature, surface wind speed and scores for light and medium precipitation are also improved. In the future, new land data sets such as vegetation and soil types, near real-time green vegetation fraction and snow albedo will be updated and we expect to further reduction of 2-m temperature bias in the GFS model.

  6. The heated condensation framework as a convective trigger in the NCEP Climate Forecast System version 2

    Science.gov (United States)

    Bombardi, Rodrigo J.; Tawfik, Ahmed B.; Manganello, Julia V.; Marx, Lawrence; Shin, Chul-Su; Halder, Subhadeep; Schneider, Edwin K.; Dirmeyer, Paul A.; Kinter, James L.

    2016-09-01

    An updated version of the Heated Condensation Framework (HCF) is implemented as a convective triggering criterion into the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). The new trigger replaces the original criteria in both the deep (Simplified Arakawa-Schubert - SAS) and shallow (SAS based) convective schemes. The performance of the original and new triggering criteria is first compared against radiosonde observations. Then, a series of hindcasts are performed to evaluate the influence of the triggering criterion in the CFSv2 representation of summer precipitation, the diurnal cycle of precipitation, and hurricanes that made landfall. The observational analysis shows that the HCF trigger better captures the frequency of convection, where the original SAS trigger initiates convection too often. When implemented in CFSv2, the HCF trigger improves the seasonal forecast of the Indian summer monsoon rainfall, including the representation of the onset dates of the rainy season over India. On the other hand, the HCF trigger increases error in the seasonal forecast of precipitation over the eastern United States. The HCF trigger also improves the representation of the intensity of hurricanes. Moreover, the simulation of hurricanes provides insights on the mechanism whereby the HCF trigger impacts the representation of convection.

  7. Evaluation of NCEP TIGGE short-range forecast for Indian summer monsoon intraseasonal oscillation

    Science.gov (United States)

    Tirkey, Snehlata; Mukhopadhyay, P.

    2017-08-01

    This study focuses on the short-range prediction of Monsoon Intraseasonal Oscillations (MISOs) using the National Centers for Environmental Prediction(NCEP) Ensemble Prediction System (EPS) data from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) archive. The Indian Summer Monsoon Rainfall (ISMR), which plays an important role in the socio-economic growth of the country, is highly variable and is mostly governed by the MISOs. In addition to this, deterministic forecasts of ISMR are not very reliable. Hence, a probabilistic approach at daily scale is required. Keeping this in mind, the present analysis is done by using daily forecast data for up to 7-day lead time and compared with observations. The analysis shows that the ensemble forecast well captures the variability as compared to observations even up to 7 days. The spatial characteristics and the northward propagation of MISO are observed thoroughly in the EPS. The evolution of dynamical and thermodynamical parameters such as specific humidity, moist static energy, moisture divergence, and vorticity is also captured well but show deviation from the observation from 96 h lead time onwards. The tropospheric temperature forecast captures the observed gradient but with certain bias in magnitude whereas the wind shear is simulated quite well both in pattern and magnitude. These analyses bring out the biases in TIGGE EPS forecast and also point out the possible moist processes which needs to be improved.

  8. Simultaneous ground- and satellite-based observation of MF/HF auroral radio emissions

    Science.gov (United States)

    Sato, Yuka; Kumamoto, Atsushi; Katoh, Yuto; Shinbori, Atsuki; Kadokura, Akira; Ogawa, Yasunobu

    2016-05-01

    We report on the first simultaneous measurements of medium-high frequency (MF/HF) auroral radio emissions (above 1 MHz) by ground- and satellite-based instruments. Observational data were obtained by the ground-based passive receivers in Iceland and Svalbard, and by the Plasma Waves and Sounder experiment (PWS) mounted on the Akebono satellite. We observed two simultaneous appearance events, during which the frequencies of the auroral roar and MF bursts detected at ground level were different from those of the terrestrial hectometric radiation (THR) observed by the Akebono satellite passing over the ground-based stations. This frequency difference confirms that auroral roar and THR are generated at different altitudes across the F peak. We did not observe any simultaneous observations that indicated an identical generation region of auroral roar and THR. In most cases, MF/HF auroral radio emissions were observed only by the ground-based detector, or by the satellite-based detector, even when the satellite was passing directly over the ground-based stations. A higher detection rate was observed from space than from ground level. This can primarily be explained in terms of the idea that the Akebono satellite can detect THR emissions coming from a wider region, and because a considerable portion of auroral radio emissions generated in the bottomside F region are masked by ionospheric absorption and screening in the D/E regions associated with ionization which results from auroral electrons and solar UV radiation.

  9. Development of satellite-based drought monitoring and warning system in Asian Pacific countries

    Science.gov (United States)

    Takeuchi, W.; Oyoshi, K.; Muraki, Y.

    2013-12-01

    This research focuses on a development of satellite-based drought monitoring warning system in Asian Pacific countries. Drought condition of cropland is evaluated by using Keeth-Byram Drought Index (KBDI) computed from rainfall measurements with GSMaP product, land surface temperature by MTSAT product and vegetation phenology by MODIS NDVI product at daily basis. The derived information is disseminated as a system for an application of space based technology (SBT) in the implementation of the Core Agriculture Support Program. The benefit of this system are to develop satellite-based drought monitoring and early warning system (DMEWS) for Asian Pacific counties using freely available data, and to develop capacity of policy makers in those countries to apply the developed system in policy making. A series of training program has been carried out in 2013 to officers and researchers of ministry of agriculture and relevant agencies in Greater Mekong Subregion countries including Cambodia, China, Myanmar, Laos, Thailand and Vietnam. This system is running as fully operational and can be accessed at http://webgms.iis.u-tokyo.ac.jp/DMEWS/.

  10. nowCOAST's Map Service for NOAA NWS NCEP Real-Time Global and NASA SPoRT Sea Surface Temperature Analyses (Time Enabled)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Map Information: This nowCOAST time-enabled map service provides a map depicting the latest daily sea surface temperature analyses from both the NOAA/NWS/NCEP...

  11. How do uncertainties in NCEP R2 and CFSR surface fluxes impact tropical ocean simulations?

    Science.gov (United States)

    Wen, Caihong; Xue, Yan; Kumar, Arun; Behringer, David; Yu, Lisan

    2017-01-01

    NCEP/DOE reanalysis (R2) and Climate Forecast System Reanalysis (CFSR) surface fluxes are widely used by the research community to understand surface flux climate variability, and to drive ocean models as surface forcings. However, large discrepancies exist between these two products, including (1) stronger trade winds in CFSR than in R2 over the tropical Pacific prior 2000; (2) excessive net surface heat fluxes into ocean in CFSR than in R2 with an increase in difference after 2000. The goals of this study are to examine the sensitivity of ocean simulations to discrepancies between CFSR and R2 surface fluxes, and to assess the fidelity of the two products. A set of experiments, where an ocean model was driven by a combination of surface flux components from R2 and CFSR, were carried out. The model simulations were contrasted to identify sensitivity to different component of the surface fluxes in R2 and CFSR. The accuracy of the model simulations was validated against the tropical moorings data, altimetry SSH and SST reanalysis products. Sensitivity of ocean simulations showed that temperature bias difference in the upper 100 m is mostly sensitive to the differences in surface heat fluxes, while depth of 20 °C (D20) bias difference is mainly determined by the discrepancies in momentum fluxes. D20 simulations with CFSR winds agree with observation well in the western equatorial Pacific prior 2000, but have large negative bias similar to those with R2 winds after 2000, partly because easterly winds over the central Pacific were underestimated in both CFSR and R2. On the other hand, the observed temperature variability is well reproduced in the tropical Pacific by simulations with both R2 and CFSR fluxes. Relative to the R2 fluxes, the CFSR fluxes improve simulation of interannual variability in all three tropical oceans to a varying degree. The improvement in the tropical Atlantic is most significant and is largely attributed to differences in surface winds.

  12. Slow and fast annual cycles of the Asian summer monsoon in the NCEP CFSv2

    Science.gov (United States)

    Shin, Chul-Su; Huang, Bohua

    2016-07-01

    The climatological Asian summer monsoon (ASM) is decomposed into the slow and fast annual cycles (SAC and FAC). The FAC represents the abrupt onset and breaks phase-locked to the ASM seasonal progression. This study evaluates how well the NCEP Climate Forecast System version 2 (CFSv2) simulates the SAC and FAC over the Indian and East Asia monsoon regions (IMR and EAMR). The simulated SACs are in good agreement with observations in both regions. The FAC also represents the northward propagation in both observations and CFSv2. It is further demonstrated that the FAC is associated with a thermodynamic air-sea interaction. In particular, the different roles played by the wind-evaporation-SST (WES) feedback may account for the faster propagation in the IMR than the EAMR. However, compared with observations, the simulated FAC shows earlier monsoon onset and long-lasting stronger dry and wet phases in the IMR but delayed monsoon onset with weaker and less organized FAC in the EAMR. These reversed behaviors may originate from a warm (cold) SST bias in the IMR (EAMR) in boreal spring and enhanced by an overly sensitive surface evaporation to wind changes in the CFSv2. As a result, the warm spring SST bias in the IMR initiates a strong WES feedback and changes of solar insolation during boreal summer, which leads to a cold SST bias in early fall. On the other hand, the cold spring SST bias in the EAMR accounts for a weaker air-sea coupling, which in turn results in a warm SST bias after the withdrawal of the monsoon.

  13. Prediction of Wintertime Northern Hemisphere Blocking by the NCEP Climate Forecast System

    Institute of Scientific and Technical Information of China (English)

    JIA Xiaolong; YANG Song; SONG Wenling; HE Bin

    2014-01-01

    Daily output from the hindcasts by the NCEP Climate Forecast System version 2 (CFSv2) is analyzed to understand CFSv2’s skill in forecasting wintertime atmospheric blocking in the Northern Hemisphere. Prediction skills of sector blocking, sector-blocking episodes, and blocking onset/decay are assessed with a focus on the Euro-Atlantic sector (20◦W-45◦E) and the Pacifi c sector (160◦E-135◦W). Features of associated circulation and climate patterns are also examined. The CFSv2 well captures the observed features of longitudinal distribution of blocking activity, but underestimates blocking frequency and intensity and shows a decreasing trend in blocking frequency with increasing forecast lead time. Within 14-day lead time, the Euro-Atlantic sector blocking receives a higher skill than the Pacifi c sector blocking. Skillful forecast (taking the hit rate of 50% as a criterion) can be obtained up to 9 days in the Euro-Atlantic sector, which is slightly longer than that in the Pacifi c sector (7 days). The forecast skill of sector-blocking episodes is slightly lower than that of sector blocking in both sectors, and it is slightly higher in the Euro-Atlantic sector than in the Pacifi c sector. Compared to block onset, the skill for block decay is lower in the Euro-Atlantic sector, slightly higher in the Pacifi c sector during the early three days but lower after three days in lead time. In both the Euro-Atlantic and the Pacifi c sectors, a local dipole pattern in 500-hPa geopotential height associated with blocking is well presented in the CFSv2 prediction, but the wave-train like pattern that is far away from the blocking sector can only maintain in the forecast of relative short lead time. The CFSv2 well reproduces the observed characteristics of local temperature and precipitation anomalies associated with blocking.

  14. Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

    Science.gov (United States)

    Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

    2012-04-01

    Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture

  15. Simulation of low clouds in the Southeast Pacific by the NCEP GFS: sensitivity to vertical mixing

    Directory of Open Access Journals (Sweden)

    R. Sun

    2010-12-01

    Full Text Available The NCEP Global Forecast System (GFS model has an important systematic error shared by many other models: stratocumuli are missed over the subtropical eastern oceans. It is shown that this error can be alleviated in the GFS by introducing a consideration of the low-level inversion and making two modifications in the model's representation of vertical mixing. The modifications consist of (a the elimination of background vertical diffusion above the inversion and (b the incorporation of a stability parameter based on the cloud-top entrainment instability (CTEI criterion, which limits the strength of shallow convective mixing across the inversion. A control simulation and three experiments are performed in order to examine both the individual and combined effects of modifications on the generation of the stratocumulus clouds. Individually, both modifications result in enhanced cloudiness in the Southeast Pacific (SEP region, although the cloudiness is still low compared to the ISCCP climatology. If the modifications are applied together, however, the total cloudiness produced in the southeast Pacific has realistic values. This nonlinearity arises as the effects of both modifications reinforce each other in reducing the leakage of moisture across the inversion. Increased moisture trapped below the inversion than in the control run without modifications leads to an increase in cloud amount and cloud-top radiative cooling. Then a positive feedback due to enhanced turbulent mixing in the planetary boundary layer by cloud-top radiative cooling leads to and maintains the stratocumulus cover. Although the amount of total cloudiness obtained with both modifications has realistic values, the relative contributions of low, middle, and high layers tend to differ from the observations. These results demonstrate that it is possible to simulate realistic marine boundary clouds in large-scale models by implementing direct and physically based improvements in the

  16. Simulation of low clouds in the Southeast Pacific by the NCEP GFS: sensitivity to vertical mixing

    Directory of Open Access Journals (Sweden)

    R. Sun

    2010-08-01

    Full Text Available The NCEP Global Forecast System (GFS model has an important systematic error shared by many other models: stratocumuli are missed over the subtropical eastern oceans. It is shown that this error can be alleviated in the GFS by introducing a consideration of the low-level inversion and making two modifications in the model's representation of vertical mixing. The modifications consist of (a the elimination of background vertical diffusion above the inversion and (b the incorporation of a stability parameter based on the cloud-top entrainment instability (CTEI criterion, which limits the strength of shallow convective mixing across the inversion. A control simulation and three experiments are performed in order to examine both the individual and combined effects of modifications on the generation of the stratocumulus clouds. Individually, both modifications result in enhanced cloudiness in the Southeast Pacific (SEP region, although the cloudiness is still low compared to the ISCCP climatology. If the modifications are applied together, however, the total cloudiness produced in the southeast Pacific has realistic values. This nonlinearity arises as the effects of both modifications reinforce each other in reducing the leakage of moisture across the inversion. Increased moisture trapped below the inversion than in the control run without modifications leads to an increase in cloud amount and cloud-top radiative cooling. Then a positive feedback due to enhanced turbulent mixing in the planetary boundary layer by cloud-top radiative cooling leads to and maintains the stratocumulus cover. Although the amount of total cloudiness obtained with both modifications has realistic values, the relative contributions of low, middle, and high layers tend to differ from the observations. These results demonstrate that it is possible to simulate realistic marine boundary clouds in large-scale models by implementing direct and physically based improvements in the

  17. Simulation of low clouds in the Southeast Pacific by the NCEP GFS: sensitivity to vertical mixing

    Science.gov (United States)

    Sun, R.; Moorthi, S.; Xiao, H.; Mechoso, C. R.

    2010-12-01

    The NCEP Global Forecast System (GFS) model has an important systematic error shared by many other models: stratocumuli are missed over the subtropical eastern oceans. It is shown that this error can be alleviated in the GFS by introducing a consideration of the low-level inversion and making two modifications in the model's representation of vertical mixing. The modifications consist of (a) the elimination of background vertical diffusion above the inversion and (b) the incorporation of a stability parameter based on the cloud-top entrainment instability (CTEI) criterion, which limits the strength of shallow convective mixing across the inversion. A control simulation and three experiments are performed in order to examine both the individual and combined effects of modifications on the generation of the stratocumulus clouds. Individually, both modifications result in enhanced cloudiness in the Southeast Pacific (SEP) region, although the cloudiness is still low compared to the ISCCP climatology. If the modifications are applied together, however, the total cloudiness produced in the southeast Pacific has realistic values. This nonlinearity arises as the effects of both modifications reinforce each other in reducing the leakage of moisture across the inversion. Increased moisture trapped below the inversion than in the control run without modifications leads to an increase in cloud amount and cloud-top radiative cooling. Then a positive feedback due to enhanced turbulent mixing in the planetary boundary layer by cloud-top radiative cooling leads to and maintains the stratocumulus cover. Although the amount of total cloudiness obtained with both modifications has realistic values, the relative contributions of low, middle, and high layers tend to differ from the observations. These results demonstrate that it is possible to simulate realistic marine boundary clouds in large-scale models by implementing direct and physically based improvements in the model

  18. Sensitivity of tropical climate to low-level clouds in the NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Zeng-Zhen [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); NCEP/NWS/NOAA, Climate Prediction Center, Camp Springs, MD (United States); Huang, Bohua; Schneider, Edwin K. [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); George Mason University, Department of Atmospheric, Oceanic, and Earth Sciences, College of Science, Fairfax, VA (United States); Hou, Yu-Tai; Yang, Fanglin [NCEP/NWS/NOAA, Environmental Modeling Center, Camp Springs, MD (United States); Wang, Wanqiu [NCEP/NWS/NOAA, Climate Prediction Center, Camp Springs, MD (United States); Stan, Cristiana [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States)

    2011-05-15

    In this work, we examine the sensitivity of tropical mean climate and seasonal cycle to low clouds and cloud liquid water path (CLWP) by prescribing them in the NCEP climate forecast system (CFS). It is found that the change of low cloud cover alone has a minor influence on the amount of net shortwave radiation reaching the surface and on the warm biases in the southeastern Atlantic. In experiments where CLWP is prescribed using observations, the mean climate in the tropics is improved significantly, implying that shortwave radiation absorption by CLWP is mainly responsible for reducing the excessive surface net shortwave radiation over the southern oceans in the CFS. Corresponding to large CLWP values in the southeastern oceans, the model generates large low cloud amounts. That results in a reduction of net shortwave radiation at the ocean surface and the warm biases in the sea surface temperature in the southeastern oceans. Meanwhile, the cold tongue and associated surface wind stress in the eastern oceans become stronger and more realistic. As a consequence of the overall improvement of the tropical mean climate, the seasonal cycle in the tropical Atlantic is also improved. Based on the results from these sensitivity experiments, we propose a model bias correction approach, in which CLWP is prescribed only in the southeastern Atlantic by using observed annual mean climatology of CLWP. It is shown that the warm biases in the southeastern Atlantic are largely eliminated, and the seasonal cycle in the tropical Atlantic Ocean is significantly improved. Prescribing CLWP in the CFS is then an effective interim technique to reduce model biases and to improve the simulation of seasonal cycle in the tropics. (orig.)

  19. Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspiration products

    Directory of Open Access Journals (Sweden)

    P. López López

    2017-06-01

    Full Text Available A considerable number of river basins around the world lack sufficient ground observations of hydro-meteorological data for effective water resources assessment and management. Several approaches can be developed to increase the quality and availability of data in these poorly gauged or ungauged river basins; among them, the use of Earth observations products has recently become promising. Earth observations of various environmental variables can be used potentially to increase knowledge about the hydrological processes in the basin and to improve streamflow model estimates, via assimilation or calibration. The present study aims to calibrate the large-scale hydrological model PCRaster GLOBal Water Balance (PCR-GLOBWB using satellite-based products of evapotranspiration and soil moisture for the Moroccan Oum er Rbia River basin. Daily simulations at a spatial resolution of 5  ×  5 arcmin are performed with varying parameters values for the 32-year period 1979–2010. Five different calibration scenarios are inter-compared: (i reference scenario using the hydrological model with the standard parameterization, (ii calibration using in situ-observed discharge time series, (iii calibration using the Global Land Evaporation Amsterdam Model (GLEAM actual evapotranspiration time series, (iv calibration using ESA Climate Change Initiative (CCI surface soil moisture time series and (v step-wise calibration using GLEAM actual evapotranspiration and ESA CCI surface soil moisture time series. The impact on discharge estimates of precipitation in comparison with model parameters calibration is investigated using three global precipitation products, including ERA-Interim (EI, WATCH Forcing methodology applied to ERA-Interim reanalysis data (WFDEI and Multi-Source Weighted-Ensemble Precipitation data by merging gauge, satellite and reanalysis data (MSWEP. Results show that GLEAM evapotranspiration and ESA CCI soil moisture may be used for model

  20. Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspiration products

    Science.gov (United States)

    López López, Patricia; Sutanudjaja, Edwin H.; Schellekens, Jaap; Sterk, Geert; Bierkens, Marc F. P.

    2017-06-01

    A considerable number of river basins around the world lack sufficient ground observations of hydro-meteorological data for effective water resources assessment and management. Several approaches can be developed to increase the quality and availability of data in these poorly gauged or ungauged river basins; among them, the use of Earth observations products has recently become promising. Earth observations of various environmental variables can be used potentially to increase knowledge about the hydrological processes in the basin and to improve streamflow model estimates, via assimilation or calibration. The present study aims to calibrate the large-scale hydrological model PCRaster GLOBal Water Balance (PCR-GLOBWB) using satellite-based products of evapotranspiration and soil moisture for the Moroccan Oum er Rbia River basin. Daily simulations at a spatial resolution of 5 × 5 arcmin are performed with varying parameters values for the 32-year period 1979-2010. Five different calibration scenarios are inter-compared: (i) reference scenario using the hydrological model with the standard parameterization, (ii) calibration using in situ-observed discharge time series, (iii) calibration using the Global Land Evaporation Amsterdam Model (GLEAM) actual evapotranspiration time series, (iv) calibration using ESA Climate Change Initiative (CCI) surface soil moisture time series and (v) step-wise calibration using GLEAM actual evapotranspiration and ESA CCI surface soil moisture time series. The impact on discharge estimates of precipitation in comparison with model parameters calibration is investigated using three global precipitation products, including ERA-Interim (EI), WATCH Forcing methodology applied to ERA-Interim reanalysis data (WFDEI) and Multi-Source Weighted-Ensemble Precipitation data by merging gauge, satellite and reanalysis data (MSWEP). Results show that GLEAM evapotranspiration and ESA CCI soil moisture may be used for model calibration resulting in

  1. Using NDVI to estimate carbon fluxes from small rotationally grazed pastures

    Science.gov (United States)

    Satellite-based Normalized Difference Vegetation Index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northea...

  2. Assessing the performance of satellite-based precipitation products over the Mediterranean region

    Science.gov (United States)

    Xaver, Angelika; Dorigo, Wouter; Brocca, Luca; Ciabatta, Luca

    2017-04-01

    Detailed knowledge about the spatial and temporal patterns and quantities of precipitation is of high importance. This applies especially in the Mediterranean region, where water demand for agricultural, industrial and touristic needs is growing and climate projections foresee a decrease of precipitation amounts and an increase in variability. In this region, ground-based rain gauges are available only limited in number, particularly in northern Africa and the Middle East and lack to capture the high spatio-temporal character of precipitation over large areas. This has motivated the development of a large number of remote sensing products for monitoring rainfall. Satellite-based precipitation products are based on various observation principles and retrieval approaches, i.e. from thermal infra-red and microwaves. Although, many individual validation studies on the performance of these precipitation datasets exist, they mostly examine only one or a few of these rainfall products at the same time and are not targeted at the Mediterranean basin as a whole. Here, we present an extensive comparative study of seven different satellite-based precipitation products, namely CMORPH 30-minutes, CMORPH 3-hourly, GPCP, PERSIANN, SM2Rain CCI, TRMM TMPA 3B42, and TRMM TMPA 3B42RT, focusing on the whole Mediterranean region and on individual Mediterranean catchments. The time frame of investigation is restricted by the common availability of all precipitation products and covers the period 2000-2013. We assess the skill of the satellite products against gridded gauge-based data provided by GPCC and E-OBS. Apart from common characteristics like biases and temporal correlations we evaluate several sophisticated dataset properties that are of particular interest for Mediterranean hydrology, including the capability of the remotely sensed products to capture extreme events and trends. A clear seasonal dependency of the correlation results can be observed for the whole Mediterranean

  3. Engineering satellite-based navigation and timing global navigation satellite systems, signals, and receivers

    CERN Document Server

    Betz, J

    2016-01-01

    This book describes the design and performance analysis of satnav systems, signals, and receivers. It also provides succinct descriptions and comparisons of all the world’s satnav systems. Its comprehensive and logical structure addresses all satnav signals and systems in operation and being developed. Engineering Satellite-Based Navigation and Timing: Global Navigation Satellite Systems, Signals, and Receivers provides the technical foundation for designing and analyzing satnav signals, systems, and receivers. Its contents and structure address all satnav systems and signals: legacy, modernized, and new. It combines qualitative information with detailed techniques and analyses, providing a comprehensive set of insights and engineering tools for this complex multidisciplinary field. Part I describes system and signal engineering including orbital mechanics and constellation design, signal design principles and underlying considerations, link budgets, qua tifying receiver performance in interference, and e...

  4. DIGITAL VIDEO BROADCAST RETURN CHANNEL VIA SATELLITE (DVB-RCS HUB FOR SATELLITE BASED E-LEARNING

    Directory of Open Access Journals (Sweden)

    N.G.Vasantha Kumar

    2011-02-01

    Full Text Available This paper discusses in-house designed and developed scale-down DVB-RCS hub along with the performance of the realized hub. This development is intended to support the Satellite Based e-Learning initiative in India. The scale-down DVB-RCS HUB is implemented around a single PC with other subsystems making it very cost effective and unique of its kind. This realization will drastically reduce the total cost of Satellite based Education Networks as very low cost commercially available Satellite Interactive Terminals (SITs complying to open standard could be used at remote locations. The system is successfully tested to work with a commercial SIT using a GEO satellite EDUSAT which is especially dedicated for satellite based e-Learning. The internal detail of the DVB-RCS Forward and Return Link Organization and how it manages the Satellite Interactive Terminals access to the satellite channel using MF-TDMA approach has been described.

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

    Science.gov (United States)

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

    2017-04-01

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

  6. Validation of the Global NASA Satellite-based Flood Detection System in Bangladesh

    Science.gov (United States)

    Moffitt, C. B.

    2009-12-01

    Floods are one of the most destructive natural forces on earth, affecting millions of people annually. Nations lying in the downstream end of an international river basin often suffer the most damage during flooding and could benefit from the real-time communication of rainfall and stream flow data from countries upstream. This is less likely to happen among developing nations due to a lack of freshwater treaties (Balthrop and Hossain, Water Policy, 2009). A more viable option is for flood-prone developing nations to utilize the global satellite rainfall and modeled runoff data that is independently and freely available from the NASA Satellite-based Global Flood Detection System. Although the NASA Global Flood Detection System has been in operation in real-time since 2006, the ‘detection’ capability of flooding has only been validated against qualitative reports in news papers and other types of media. In this study, a more quantitative validation against in-situ measurements of the flood detection system over Bangladesh is presented. Using ground-measured stream flow data as well as satellite-based flood potential and rainfall data, the study looks into the relationship between rainfall and flood potential, rainfall and stream flow, and stream flow and flood potential for three very distinct river systems in Bangladesh - 1) Ganges- a snow-fed river regulated by upstream India 2) Brahmaputra - a snow-fed river that is also braided 3) Meghna - a rain-fed river. The quantitative assessment will show the effectiveness of the NASA Global Flood Detection System for a very humid and flood prone region like Bangladesh that is also faced with tremendous transboundary hurdles that can only be resolved from the vantage of space.

  7. Prediction and error growth in the daily forecast of precipitation from the NCEP CFSv2 over the subdivisions of Indian subcontinent

    Indian Academy of Sciences (India)

    Dhruva Kumar Pandey; Shailendra Rai; A K Sahai; S Abhilash; N K Shahi

    2016-02-01

    This study investigates the forecast skill and predictability of various indices of south Asian monsoon as well as the subdivisions of the Indian subcontinent during JJAS season for the time domain of 2001–2013 using NCEP CFSv2 output. It has been observed that the daily mean climatology of precipitation over the land points of India is underestimated in the model forecast as compared to observation. The monthly model bias of precipitation shows the dry bias over the land points of India and also over the Bay of Bengal, whereas the Himalayan and Arabian Sea regions show the wet bias. We have divided the Indian landmass into five subdivisions namely central India, southern India, Western Ghat, northeast and southern Bay of Bengal regions based on the spatial variation of observed mean precipitation in JJAS season. The underestimation over the land points of India during mature phase was originated from the central India, southern Bay of Bengal, southern India and Western Ghat regions. The error growth in June forecast is slower as compared to July forecast in all the regions. The predictability error also grows slowly in June forecast as compared to July forecast in most of the regions. The doubling time of predictability error was estimated to be in the range of 3–5 days for all the regions. Southern India and Western Ghats are more predictable in the July forecast as compared to June forecast, whereas IMR, northeast, central India and southern Bay of Bengal regions have the opposite nature.

  8. Prediction and error growth in the daily forecast of precipitation from the NCEP CFSv2 over the subdivisions of Indian subcontinent

    Science.gov (United States)

    Pandey, Dhruva Kumar; Rai, Shailendra; Sahai, A. K.; Abhilash, S.; Shahi, N. K.

    2016-02-01

    This study investigates the forecast skill and predictability of various indices of south Asian monsoon as well as the subdivisions of the Indian subcontinent during JJAS season for the time domain of 2001-2013 using NCEP CFSv2 output. It has been observed that the daily mean climatology of precipitation over the land points of India is underestimated in the model forecast as compared to observation. The monthly model bias of precipitation shows the dry bias over the land points of India and also over the Bay of Bengal, whereas the Himalayan and Arabian Sea regions show the wet bias. We have divided the Indian landmass into five subdivisions namely central India, southern India, Western Ghat, northeast and southern Bay of Bengal regions based on the spatial variation of observed mean precipitation in JJAS season. The underestimation over the land points of India during mature phase was originated from the central India, southern Bay of Bengal, southern India and Western Ghat regions. The error growth in June forecast is slower as compared to July forecast in all the regions. The predictability error also grows slowly in June forecast as compared to July forecast in most of the regions. The doubling time of predictability error was estimated to be in the range of 3-5 days for all the regions. Southern India and Western Ghats are more predictable in the July forecast as compared to June forecast, whereas IMR, northeast, central India and southern Bay of Bengal regions have the opposite nature.

  9. NCEP/NCAR(Ⅰ、Ⅱ)和ERA40再分析加热资料比较%Comparison of Diabatic Heating Data from NCEP/NCAR(Ⅰ,H)and ERA40

    Institute of Scientific and Technical Information of China (English)

    王同美; 吴国雄; 应明

    2011-01-01

    气候统计和诊断分析常用到NCEP-1、NCEP-2和ERA-40再分析资料.其中的加热资料为C类资料,对其使用常常存疑.对上述3类资料中的垂直积分的总加热率和地表感热通量进行比较,以分析其在亚洲地区特别是在高原和亚洲热带地区的适用性.结果表明:垂直积分的总非绝热加热在空间分布上三套资料基本一致,NCEP两套资料在大值中心的分布上相似,但量值上NCEP-2和ERA - 40比较接近,此外ERA -40在青藏高原南缘的加热估算比NCEP大;对于青藏高原区域平均的非绝热加热,无论是季节变化还是年际变率,三套资料在量级以及变化趋势上都有较好的一致性,特别是平均感热通量的年际变化,三者相关系数超过99%甚至99.9%置信度检验,因此对亚洲包括青藏高原地区使用再分析加热率资料,在一定程度上是合理可行的.%Diabatic heating data from NCEP (1 and 2) and ERA-40 are compared to analyze the applicability of these data in the Asian region, particularly in the Tibet Plateau (TP) and tropical Asia. In spite of slight difference in vertical integration of total diabatic heating rates from three data sets, the spatial distribution shows good agreement. Seasonal and interannual variability of the mean diabatic heating over TP shows agreement in the magnitude and trend. Particularly, the correlation coefficients of interannual variability of the mean sensible heat flux over TP among three data sets exceed 99% or even 99. 9% confidence level. Therefore, the reanalysis diabatic heating data over Asia, even over TP area, are feasible to a certain extent.

  10. Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets

    Directory of Open Access Journals (Sweden)

    T. Raziei

    2010-10-01

    Full Text Available Space-time variability of hydrological drought and wetness over Iran is investigated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR reanalysis and the Global Precipitation Climatology Centre (GPCC dataset for the common period 1948–2007. The aim is to complement previous studies on the detection of long-term trends in drought/wetness time series and on the applicability of reanalysis data for drought monitoring in Iran. Climate conditions of the area are assessed through the Standardized Precipitation Index (SPI on 24-month time scale, while Principal Component Analysis (PCA and Varimax rotation are used for investigating drought/wetness variability, and drought regionalization, respectively. Singular Spectrum Analysis (SSA is applied to the time series of interest to extract the leading nonlinear components and compare them with linear fittings.

    Differences in drought and wetness area coverage resulting from the two datasets are discussed also in relation to the change occurred in recent years. NCEP/NCAR and GPCC are in good agreement in identifying four sub-regions as principal spatial modes of drought variability. However, the climate variability in each area is not univocally represented by the two datasets: a good agreement is found for south-eastern and north-western regions, while noticeable discrepancies occur for central and Caspian sea regions. A comparison with NCEP Reanalysis II for the period 1979–2007, seems to exclude that the discrepancies are merely due to the introduction of satellite data into the reanalysis assimilation scheme.

  11. Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets

    Directory of Open Access Journals (Sweden)

    T. Raziei

    2010-05-01

    Full Text Available Space-time variability of hydrological drought and wetness over Iran is investigated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR reanalysis and the Global Precipitation Climatology Centre (GPCC dataset for the common period 1948–2007. The aim is to complement previous studies on the detection of long-term trends in drought/wetness time series and on the applicability of reanalysis data for drought monitoring in Iran. Climatic conditions of the area are assessed through the Standardized Precipitation Index (SPI on 24-month time scale, while Principal Component Analysis (PCA and Varimax rotation are used for investigating drought/wetness variability, and drought regionalization, respectively. Singular Spectrum Analysis (SSA is applied to the time series of interest to extract the leading nonlinear components and compare them with linear fittings.

    Differences in drought and wetness area coverage resulting from the two datasets are discussed also in relation to the change occurred in recent years. NCEP/NCAR and GPCC are in good agreement in identifying four sub-regions as principal spatial modes of drought variability. However, the climate variability in each area is not univocally represented by the two datasets: a good agreement is found for south-eastern and north-western regions, while noticeable discrepancies occur for central and Caspian sea regions. A comparison with NCEP Reanalysis II for the period 1979–2007, seems to exclude that the discrepancies are merely due to the introduction of satellite data into the reanalysis assimilation scheme.

  12. Impacts of Land Process on the Onset and Evolution of Asian Summer Monsoon in the NCEP Climate Forecast System

    Institute of Scientific and Technical Information of China (English)

    Song YANG; WEN Min; Rongqian YANG; Wayne HIGGINS; ZHANG Renhe

    2011-01-01

    Impacts of land models and initial land conditions (ICs) on the Asian summer monsoon,especially its onset,were investigated using the NCEP Climate Forecast System (CFS).Two land models,the Oregon State University (OSU) land model and the NCEP,OSU,Air Force,and Hydrologic Research Laboratory (Noah) land model,were used to get parallel experiments.The experiments also used land ICs from the NCEP/Department of Energy (DOE) Global Reanalysis 2 (GR2) and the Global Land Data Assimilation System (GLDAS).Previous studies have demonstrated that,a systematic weak bias appears in the modeled monsoon,and this bias may be related to a cold bias over the Asian land mass.Results of the current study show that replacement of the OSU land model by the Noah land model improved the model's cold bias and produced improved monsoon precipitation and circulation patterns.The CFS predicted monsoon with greater proficiency in El Ni(n)o years,compared to La Ni(n)a years,and the Noah model performed better than the OSU model in monsoon predictions for individual years.These improvements occurred not only in relation to monsoon onset in late spring but also to monsoon intensity in summer.Our analysis of the monsoon features over the India peninsula,the Indo-China peninsula,and the South Chinese Sea indicates different degrees of improvement.Furthermore,a change in the land models led to more remarkable improvement in monsoon prediction than did a change from the GR2 land ICs to the GLDAS land ICs.

  13. Active-Layer Soil Moisture Content Regional Variations in Alaska and Russia by Ground-Based and Satellite-Based Methods, 2002 Through 2014

    Science.gov (United States)

    Muskett, Reginald; Romanovsky, Vladimir; Cable, William; Kholodov, Alexander

    2016-04-01

    Soil moisture is a vital physical parameter of the active-layer in permafrost environments, and associated biological and geophysical processes operative at the microscopic to hemispheric spatial scales and at hourly to multidecadal time scales. While in-situ measurements can give the highest quality of information on a site-specific basis, the vast permafrost terrains of North America and Eurasia require space-based techniques for assessments of cause and effect and long-term changes and impacts from the changes of permafrost and the active-layer. Satellite-based 6.925 and 10.65 GHz sensor algorithmic retrievals of soil moisture by Advanced Microwave Scanning Radiometer - Earth Observation System (AMSR-E) onboard NASA-Aqua and follow-on AMSR2 onboard JAXA-Global Change Observation Mission - Water-1 are ongoing since July 2002. Accurate land-surface temperature and vegetation parameters are critical to the success of passive microwave algorithmic retrieval schemes. Strategically located soil moisture measurements are needed for spatial and temporal co-location evaluation and validation of the space-based algorithmic estimates. We compare on a daily basis ground-based (subsurface-probe) 50- and 70-MHz radio-frequency soil moisture measurements with NASA- and JAXA-algorithmic retrieval passive microwave retrievals. We find improvements in performance of the JAXA-algorithm (AMSR-E reprocessed and AMSR2 ongoing) relative to the earlier NASA-algorithm version. In the boreal forest regions accurate land-surface temperatures and vegetation parameters are still needed for algorithmic retrieval success. Over the period of AMSR-E retrievals we find evidence of at the high northern latitudes of growing terrestrial radio-frequency interference in the 10.65 GHz channel soil moisture content. This is an important error source for satellite-based active and passive microwave remote sensing soil moisture retrievals in Arctic regions that must be addressed. Ref: Muskett, R

  14. GIO-EMS and International Collaboration in Satellite based Emergency Mapping

    Science.gov (United States)

    Kucera, Jan; Lemoine, Guido; Broglia, Marco

    2013-04-01

    During the last decade, satellite based emergency mapping has developed into a mature operational stage. The European Union's GMES Initial Operations - Emergency Management Service (GIO-EMS), is operational since April 2012. It's set up differs from other mechanisms (for example from the International Charter "Space and Major Disasters"), as it extends fast satellite tasking and delivery with the value adding map production as a single service, which is available, free of charge, to the authorized users of the service. Maps and vector datasets with standard characteristics and formats ranging from post-disaster damage assessment to recovery and disaster prevention are covered by this initiative. Main users of the service are European civil protection authorities and international organizations active in humanitarian aid. All non-sensitive outputs of the service are accessible to the public. The European Commission's in-house science service Joint Research Centre (JRC) is the technical and administrative supervisor of the GIO-EMS. The EC's DG ECHO Monitoring and Information Centre acts as the service's focal point and DG ENTR is responsible for overall service governance. GIO-EMS also aims to contribute to the synergy with similar existing mechanisms at national and international level. The usage of satellite data for emergency mapping has increased during the last years and this trend is expected to continue because of easier accessibility to suitable satellite and other relevant data in the near future. Furthermore, the data and analyses coming from volunteer emergency mapping communities are expected to further enrich the content of such cartographic products. In the case of major disasters the parallel activity of more providers is likely to generate non-optimal use of resources, e.g. unnecessary duplication; whereas coordination may lead to reduced time needed to cover the disaster area. Furthermore the abundant number of geospatial products of different

  15. Providing satellite-based early warnings of fires to reduce fire flashovers on South Africa’s transmission lines

    CSIR Research Space (South Africa)

    Frost, PE

    2007-07-01

    Full Text Available The Advanced Fire Information System (AFIS) is the first near real time operational satellite-based fire monitoring system of its kind in Africa. The main aim of AFIS is to provide information regarding the prediction, detection and assessment...

  16. Multi-variable calibration of a semi-distributed hydrological model using streamflow data and satellite-based evapotranspiration

    NARCIS (Netherlands)

    Rientjes, T.H.M.; Muthuwatta, L.P.; Bos, M.G.; Booij, M.J.; Bhatti, H.A.

    2013-01-01

    In this study, streamflow (Qs) and satellite-based actual evapotranspiration (ETa) are used in a multi-variable calibration framework to reproduce the catchment water balance. The application is for the HBV rainfall–runoff model at daily time-step for the Karkheh River Basin (51,000 km2) in Iran. Mo

  17. A Satellite-Based Assessment of the Distribution and Biomass of Submerged Aquatic Vegetation in the Optically Shallow Basin of Lake Biwa

    Directory of Open Access Journals (Sweden)

    Shweta Yadav

    2017-09-01

    Full Text Available Assessing the abundance of submerged aquatic vegetation (SAV, particularly in shallow lakes, is essential for effective lake management activities. In the present study we applied satellite remote sensing (a Landsat-8 image in order to evaluate the SAV coverage area and its biomass for the peak growth period, which is mainly in September or October (2013 to 2016, in the eutrophic and shallow south basin of Lake Biwa. We developed and validated a satellite-based water transparency retrieval algorithm based on the linear regression approach (R2 = 0.77 to determine the water clarity (2013–2016, which was later used for SAV classification and biomass estimation. For SAV classification, we used Spectral Mixture Analysis (SMA, a Spectral Angle Mapper (SAM, and a binary decision tree, giving an overall classification accuracy of 86.5% and SAV classification accuracy of 76.5% (SAV kappa coefficient 0.74, based on in situ measurements. For biomass estimation, a new Spectral Decomposition Algorithm was developed. The satellite-derived biomass (R2 = 0.79 for the SAV classified area gives an overall root-mean-square error (RMSE of 0.26 kg Dry Weight (DW m-2. The mapped SAV coverage area was 20% and 40% in 2013 and 2016, respectively. Estimated SAV biomass for the mapped area shows an increase in recent years, with values of 3390 t (tons, dry weight in 2013 as compared to 4550 t in 2016. The maximum biomass density (4.89 kg DW m-2 was obtained for a year with high water transparency (September 2014. With the change in water clarity, a slow change in SAV growth was noted from 2013 to 2016. The study shows that water clarity is important for the SAV detection and biomass estimation using satellite remote sensing in shallow eutrophic lakes. The present study also demonstrates the successful application of the developed satellite-based approach for SAV biomass estimation in the shallow eutrophic lake, which can be tested in other lakes.

  18. Performance tests of a satellite-based asymmetric communication network for the 'hyper hospital'.

    Science.gov (United States)

    Yamaguchi, T

    1997-01-01

    The Hyper Hospital is a prototype networked telemedicine system which uses virtual reality. We measured the performance of a novel multimedia network based on satellite communications. The network was a hybrid system consisting of a satellite channel in one direction and a terrestrial channel in the other. Each user was equipped with a standard satellite communication receiver and a telephone connection. Requests from the users were sent by modern and telephone line and responses were received by satellite. The user requests were initiated by clicking buttons on a World Wide Web browser screen. The transmission rates of satellite and normal telephone-line communications were compared for standardized text data. Satellite communication was three to five times faster. The transmission rate was also measured for standardized graphical data (GIF format). With a file size of about 400 kByte, satellite-mediated communication was 10 times faster than telephone lines. The effect of simultaneous access on performance was also explored. For simultaneous access of nine users to a single graphics file, 78% of the transmission speed was obtained in comparison with that of a single user. The satellite-based system showed excellent high-speed communication performance, particularly for multimedia data.

  19. Characterization of absorbing aerosol types using ground and satellites based observations over an urban environment

    Science.gov (United States)

    Bibi, Samina; Alam, Khan; Chishtie, Farrukh; Bibi, Humera

    2017-02-01

    In this paper, for the first time, an effort has been made to seasonally characterize the absorbing aerosols into different types using ground and satellite based observations. For this purpose, optical properties of aerosol retrieved from AErosol RObotic NETwork (AERONET) and Ozone Monitoring Instrument (OMI) were utilized over Karachi for the period 2012 to 2014. Firstly, OMI AODabs was validated with AERONET AODabs and found to have a high degree of correlation. Then, based on this validation, characterization was conducted by analyzing aerosol Fine Mode Fraction (FMF), Angstrom Exponent (AE), Absorption Angstrom Exponent (AAE), Single Scattering Albedo (SSA) and Aerosol Index (AI) and their mutual correlation, to identify the absorbing aerosol types and also to examine the variability in seasonal distribution. The absorbing aerosols were characterized into Mostly Black Carbon (BC), Mostly Dust and Mixed BC & Dust. The results revealed that Mostly BC aerosols contributed dominantly during winter and postmonsoon whereas, Mostly Dust were dominant during summer and premonsoon. These types of absorbing aerosol were also confirmed with MODerate resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations.

  20. Hydrological Modelling using Satellite-Based Crop Coefficients: A Comparison of Methods at the Basin Scale

    Directory of Open Access Journals (Sweden)

    Johannes E. Hunink

    2017-02-01

    Full Text Available The parameterization of crop coefficients (kc is critical for determining a water balance. We used satellite-based and literature-based methods to derive kc values for a distributed hydrologic model. We evaluated the impact of different kc parametrization methods on the water balance and simulated hydrologic response at the basin and sub-basin scale. The hydrological model SPHY was calibrated and validated for a period of 15 years for the upper Segura basin (~2500 km2 in Spain, which is characterized by a wide range of terrain, soil, and ecosystem conditions. The model was then applied, using six kc parameterization methods, to determine their spatial and temporal impacts on actual evapotranspiration, streamflow, and soil moisture. The parameterization methods used include: (i Normalized Difference Vegetation Index (NDVI observations from MODIS; (ii seasonally-averaged NDVI patterns, cell-based and landuse-based; and (iii literature-based tabular values per land use type. The analysis shows that the influence of different kc parametrization methods on basin-level streamflow is relatively small and constant throughout the year, but it has a bigger effect on seasonal evapotranspiration and soil moisture. In the autumn especially, deviations can go up to about 15% of monthly streamflow. At smaller, sub-basin scale, deviations from the NDVI-based reference run can be more than 30%. Overall, the study shows that modeling of future hydrological changes can be improved by using remote sensing information for the parameterization of crop coefficients.

  1. PlumeSat: A Micro-Satellite Based Plume Imagery Collection Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Ledebuhr, A.G.; Ng, L.C.

    2002-06-30

    This paper describes a technical approach to cost-effectively collect plume imagery of boosting targets using a novel micro-satellite based platform operating in low earth orbit (LEO). The plume collection Micro-satellite or PlueSat for short, will be capable of carrying an array of multi-spectral (UV through LWIR) passive and active (Imaging LADAR) sensors and maneuvering with a lateral divert propulsion system to different observation altitudes (100 to 300 km) and different closing geometries to achieve a range of aspect angles (15 to 60 degrees) in order to simulate a variety of boost phase intercept missions. The PlumeSat will be a cost effective platform to collect boost phase plume imagery from within 1 to 10 km ranges, resulting in 0.1 to 1 meter resolution imagery of a variety of potential target missiles with a goal of demonstrating reliable plume-to-hardbody handover algorithms for future boost phase intercept missions. Once deployed on orbit, the PlumeSat would perform a series phenomenology collection experiments until expends its on-board propellants. The baseline PlumeSat concept is sized to provide from 5 to 7 separate fly by data collects of boosting targets. The total number of data collects will depend on the orbital basing altitude and the accuracy in delivering the boosting target vehicle to the nominal PlumeSat fly-by volume.

  2. An Exploitation of Satellite-based Observation for Health Information: The UFOS Project

    Energy Technology Data Exchange (ETDEWEB)

    Mangin, A.; Morel, M.; Fanton d' Andon, O

    2000-07-01

    Short, medium and long-term trends of UV intensity levels are of crucial importance for either assessing effective biological impacts on human population, or implementing adequate preventive behaviours. Better information on a large spatial scale and increased public awareness of the short-term variations in UV values will help to support health agencies' goals of educating the public on UV risks. The Ultraviolet Forecast Operational Service Project (UFAS), financed in part by the European Commission/DG Information Society (TEN-TELECOM programme), aims to exploit satellite-based observations and to supply a set of UV products directly useful to health care. The short-term objective is to demonstrate the technical and economical feasibility and benefits that could be brought by such a system. UFOS is carried out by ACRI, with the support of an Advisory Group chaired by WHO and involving representation from the sectors of Health (WHO, INTERSUN collaborating centres, ZAMBON), Environment (WMO, IASB), and Telecommunications (EURECOM, IMET). (author)

  3. Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration

    CERN Document Server

    Noureldin, Aboelmagd; Georgy, Jacques

    2013-01-01

    Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration is an introduction to the field of Integrated Navigation Systems. It serves as an excellent reference for working engineers as well as textbook for beginners and students new to the area. The book is easy to read and understand with minimum background knowledge. The authors explain the derivations in great detail. The intermediate steps are thoroughly explained so that a beginner can easily follow the material. The book shows a step-by-step implementation of navigation algorithms and provides all the necessary details. It provides detailed illustrations for an easy comprehension. The book also demonstrates real field experiments and in-vehicle road test results with professional discussions and analysis. This work is unique in discussing the different INS/GPS integration schemes in an easy to understand and straightforward way. Those schemes include loosely vs tightly coupled, open loop vs closed loop, and many more.

  4. Satellite-based Studies on Large-Scale Vegetation Changes in China

    Institute of Scientific and Technical Information of China (English)

    Xia Zhao; Daojing Zhou; Jingyun Fang

    2012-01-01

    Remotely-sensed vegetation indices,which indicate the density and photosynthetic capacity of vegetation,have been widely used to monitor vegetation dynamics over broad areas.In this paper,we reviewed satellite-based studies on vegetation cover changes,biomass and productivity variations,phenological dynamics,desertification,and grassland degradation in China that occurred over the past 2-3 decades.Our review shows that the satellite-derived index (Normalized Difference Vegetation Index,NDVI) during growing season and the vegetation net primary productivity in major terrestrial ecosystems (for example forests,grasslands,shrubs,and croplands) have significantly increased,while the number of fresh lakes and vegetation coverage in urban regions have experienced a substantial decline.The start of the growing season continually advanced in China's temperate regions until the 1990s,with a large spatial heterogeneity.We also found that the coverage of sparsely-vegetated areas declined,and the NDVI per unit in vegetated areas increased in arid and semi-arid regions because of increased vegetation activity in grassland and oasis areas.However,these results depend strongly not only on the periods chosen for investigation,but also on factors such as data sources,changes in detection methods,and geospatial heterogeneity.Therefore,we should be cautious when applying remote sensing techniques to monitor vegetation structures,functions,and changes.

  5. Heavy rainfall prediction applying satellite-based cloud data assimilation over land

    Science.gov (United States)

    Seto, Rie; Koike, Toshio; Rasmy, Mohamed

    2016-08-01

    To optimize flood management, it is crucial to determine whether rain will fall within a river basin. This requires very fine precision in prediction of rainfall areas. Cloud data assimilation has great potential to improve the prediction of precipitation area because it can directly obtain information on locations of rain systems. Clouds can be observed globally by satellite-based microwave remote sensing. Microwave observation also includes information of latent heat and water vapor associated with cloud amount, which enables the assimilation of not only cloud itself but also the cloud-affected atmosphere. However, it is difficult to observe clouds over land using satellite microwave remote sensing, because their emissivity is much lower than that of the land surface. To overcome this challenge, we need appropriate representation of heterogeneous land emissivity. We developed a coupled atmosphere and land data assimilation system with the Weather Research and Forecasting Model (CALDAS-WRF), which can assimilate soil moisture, vertically integrated cloud water content over land, and heat and moisture within clouds simultaneously. We applied this system to heavy rain events in Japan. Results show that the system effectively assimilated cloud signals and produced very accurate cloud and precipitation distributions. The system also accurately formed a consistent atmospheric field around the cloud. Precipitation intensity was also substantially improved by appropriately representing the local atmospheric field. Furthermore, combination of the method and operationally analyzed dynamical and moisture fields improved prediction of precipitation duration. The results demonstrate the method's promise in dramatically improving predictions of heavy rain and consequent flooding.

  6. The satellite based augmentation system – EGNOS for non-precision approach global navigation satellite system

    Directory of Open Access Journals (Sweden)

    Andrzej FELLNER

    2012-01-01

    Full Text Available First in the Poland tests of the EGNOS SIS (Signal in Space were conducted on 5th October 2007 on the flight inspection with SPAN (The Synchronized Position Attitude Navigation technology at the Mielec airfield. This was an introduction to a test campaign of the EGNOS-based satellite navigation system for air traffic. The advanced studies will be performed within the framework of the EGNOS-APV project in 2011. The implementation of the EGNOS system to APV-I precision approach operations, is conducted according to ICAO requirements in Annex 10. Definition of usefulness and certification of EGNOS as SBAS (Satellite Based Augmentation System in aviation requires thorough analyses of accuracy, integrity, continuity and availability of SIS. Also, the project will try to exploit the excellent accuracy performance of EGNOS to analyze the implementation of GLS (GNSS Landing System approaches (Cat I-like approached using SBAS, with a decision height of 200 ft. Location of the EGNOS monitoring station Rzeszów, located near Polish-Ukrainian border, being also at the east border of planned EGNOS coverage for ECAC states is very useful for SIS tests in this area. According to current EGNOS programmed schedule, the project activities will be carried out with EGNOS system v2.2, which is the version released for civil aviation certification. Therefore, the project will allow demonstrating the feasibility of the EGNOS certifiable version for civil applications.

  7. Evaluation of satellite based indices for gross primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2009-01-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate NDVI, EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modeling within a water limited environment. Results show a strong correlation between vegetation indices and gross primary production (GPP, demonstrating the significance of vegetation indices for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modeling in similar semi-arid ecosystems is limited.

  8. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  9. Global Estimates of Average Ground-Level Fine Particulate Matter Concentrations from Satellite-Based Aerosol Optical Depth

    Science.gov (United States)

    Van Donkelaar, A.; Martin, R. V.; Brauer, M.; Kahn, R.; Levy, R.; Verduzco, C.; Villeneuve, P.

    2010-01-01

    Exposure to airborne particles can cause acute or chronic respiratory disease and can exacerbate heart disease, some cancers, and other conditions in susceptible populations. Ground stations that monitor fine particulate matter in the air (smaller than 2.5 microns, called PM2.5) are positioned primarily to observe severe pollution events in areas of high population density; coverage is very limited, even in developed countries, and is not well designed to capture long-term, lower-level exposure that is increasingly linked to chronic health effects. In many parts of the developing world, air quality observation is absent entirely. Instruments aboard NASA Earth Observing System satellites, such as the MODerate resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR), monitor aerosols from space, providing once daily and about once-weekly coverage, respectively. However, these data are only rarely used for health applications, in part because the can retrieve the amount of aerosols only summed over the entire atmospheric column, rather than focusing just on the near-surface component, in the airspace humans actually breathe. In addition, air quality monitoring often includes detailed analysis of particle chemical composition, impossible from space. In this paper, near-surface aerosol concentrations are derived globally from the total-column aerosol amounts retrieved by MODIS and MISR. Here a computer aerosol simulation is used to determine how much of the satellite-retrieved total column aerosol amount is near the surface. The five-year average (2001-2006) global near-surface aerosol concentration shows that World Health Organization Air Quality standards are exceeded over parts of central and eastern Asia for nearly half the year.

  10. The development of pan-African food forecasting and the exploration of satellite-based precipitation estimates

    NARCIS (Netherlands)

    Thiemig, Vera

    2014-01-01

    The main objective of this PhD is to contribute to the development of a pan-African flood forecasting system in order to enhance flood forecasting for the whole of Africa. In view of the dimension and complexity of this goal, this research focused on particular aspects of flood forecasting,

  11. Association Between Satellite-based Estimates of Long-term PM2.5 Exposure and Coronary Artery Disease

    Science.gov (United States)

    Background: Epidemiological studies have identified associations between long-term PM2.5 exposure and cardiovascular events, though most have relied on concentrations from central-site air quality monitors. Methods: We utilized a cohort of 5679 patients who had undergone cardiac ...

  12. Association Between Satellite-based Estimates of Long-term PM2.5 Exposure and Coronary Artery Disease

    Science.gov (United States)

    Background: Epidemiological studies have identified associations between long-term PM2.5 exposure and cardiovascular events, though most have relied on concentrations from central-site air quality monitors. Methods: We utilized a cohort of 5679 patients who had undergone cardiac ...

  13. NCEP/DOE Reanalysis II in HDF-EOS5, for GSSTF2c, 1x1 deg Daily grid V2c

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-2c (GSSTF2c) Dataset recently produced through a MEaSURES funded project led by Dr....

  14. Categorizing natural disaster damage assessment using satellite-based geospatial techniques

    Directory of Open Access Journals (Sweden)

    S. W. Myint

    2008-07-01

    Full Text Available Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services and hazards (e.g., downed power lines, gas lines, etc., the need for rapid mobilization (particularly for remote locations, and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale. Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.

  15. Categorizing natural disaster damage assessment using satellite-based geospatial techniques

    Science.gov (United States)

    Myint, S. W.; Yuan, M.; Cerveny, R. S.; Giri, C.

    2008-07-01

    Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.

  16. Magnetic resonance imaging research in sub-Saharan Africa: challenges and satellite-based networking implementation.

    Science.gov (United States)

    Latourette, Matthew T; Siebert, James E; Barto, Robert J; Marable, Kenneth L; Muyepa, Anthony; Hammond, Colleen A; Potchen, Michael J; Kampondeni, Samuel D; Taylor, Terrie E

    2011-08-01

    As part of an NIH-funded study of malaria pathogenesis, a magnetic resonance (MR) imaging research facility was established in Blantyre, Malaŵi to enhance the clinical characterization of pediatric patients with cerebral malaria through application of neurological MR methods. The research program requires daily transmission of MR studies to Michigan State University (MSU) for clinical research interpretation and quantitative post-processing. An intercontinental satellite-based network was implemented for transmission of MR image data in Digital Imaging and Communications in Medicine (DICOM) format, research data collection, project communications, and remote systems administration. Satellite Internet service costs limited the bandwidth to symmetrical 384 kbit/s. DICOM routers deployed at both the Malaŵi MRI facility and MSU manage the end-to-end encrypted compressed data transmission. Network performance between DICOM routers was measured while transmitting both mixed clinical MR studies and synthetic studies. Effective network latency averaged 715 ms. Within a mix of clinical MR studies, the average transmission time for a 256 × 256 image was ~2.25 and ~6.25 s for a 512 × 512 image. Using synthetic studies of 1,000 duplicate images, the interquartile range for 256 × 256 images was [2.30, 2.36] s and [5.94, 6.05] s for 512 × 512 images. Transmission of clinical MRI studies between the DICOM routers averaged 9.35 images per minute, representing an effective channel utilization of ~137% of the 384-kbit/s satellite service as computed using uncompressed image file sizes (including the effects of image compression, protocol overhead, channel latency, etc.). Power unreliability was the primary cause of interrupted operations in the first year, including an outage exceeding 10 days.

  17. On the value of satellite-based river discharge and river flood data

    Science.gov (United States)

    Kettner, A. J.; Brakenridge, R.; van Praag, E.; Borrero, S.; Slayback, D. A.; Young, C.; Cohen, S.; Prades, L.; de Groeve, T.

    2015-12-01

    Flooding is the most common natural hazard worldwide. According to the World Resources Institute, floods impact 21 million people every year and affect the global GDP by $96 billion. Providing accurate flood maps in near-real time (NRT) is critical to their utility to first responders. Also, in times of flooding, river gauging stations on location, if any, are of less use to monitor stage height as an approximation for water surface area, as often the stations themselves get washed out or peak water levels reach much beyond their design measuring capacity. In a joint effort with NASA Goddard Space Flight Center, the European Commission Joint Research Centre and the University of Alabama, the Dartmouth Flood Observatory (DFO) measures NRT: 1) river discharges, and 2) water inundation extents, both with a global coverage on a daily basis. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations'. Once calibrated, daily discharge time series span from 1998 to the present. Also, the two MODIS instruments aboard the NASA Terra and Aqua satellites provide daily floodplain inundation extent with global coverage at a spatial resolution of 250m. DFO's mission is to provide easy access to NRT river and flood data products. Apart from the DFO web portal, several water extent products can be ingested by utilizing a Web Map Service (WMS), such as is established with for Latin America and the Caribbean (LAC) region through the GeoSUR program portal. This effort includes implementing over 100 satellite discharge stations showing in NRT if a river is flooding, normal, or in low flow. New collaborative efforts have resulted in flood hazard maps which display flood extent as well as exceedance probabilities. The record length of our sensors allows mapping the 1.5 year, 5 year and 25 year flood extent. These can provide key information to water management and disaster response entities.

  18. Adjusting thresholds of satellite-based convective initiation interest fields based on the cloud environment

    Science.gov (United States)

    Jewett, Christopher P.; Mecikalski, John R.

    2013-11-01

    The Time-Space Exchangeability (TSE) concept states that similar characteristics of a given property are closely related statistically for objects or features within close proximity. In this exercise, the objects considered are growing cumulus clouds, and the data sets to be considered in a statistical sense are geostationary satellite infrared (IR) fields that help describe cloud growth rates, cloud top heights, and whether cloud tops contain significant amounts of frozen hydrometeors. In this exercise, the TSE concept is applied to alter otherwise static thresholds of IR fields of interest used within a satellite-based convective initiation (CI) nowcasting algorithm. The convective environment in which the clouds develop dictate growth rate and precipitation processes, and cumuli growing within similar mesoscale environments should have similar growth characteristics. Using environmental information provided by regional statistics of the interest fields, the thresholds are examined for adjustment toward improving the accuracy of 0-1 h CI nowcasts. Growing cumulus clouds are observed within a CI algorithm through IR fields for many 1000 s of cumulus cloud objects, from which statistics are generated on mesoscales. Initial results show a reduction in the number of false alarms of ~50%, yet at the cost of eliminating approximately ~20% of the correct CI forecasts. For comparison, static thresholds (i.e., with the same threshold values applied across the entire satellite domain) within the CI algorithm often produce a relatively high probability of detection, with false alarms being a significant problem. In addition to increased algorithm performance, a benefit of using a method like TSE is that a variety of unknown variables that influence cumulus cloud growth can be accounted for without need for explicit near-cloud observations that can be difficult to obtain.

  19. A Comparison of Different Regression Algorithms for Downscaling Monthly Satellite-Based Precipitation over North China

    Directory of Open Access Journals (Sweden)

    Wenlong Jing

    2016-10-01

    Full Text Available Environmental monitoring of Earth from space has provided invaluable information for understanding land–atmosphere water and energy exchanges. However, the use of satellite-based precipitation observations in hydrologic and environmental applications is often limited by their coarse spatial resolutions. In this study, we propose a downscaling approach based on precipitation–land surface characteristics. Daytime land surface temperature, nighttime land surface temperature, and day–night land surface temperature differences were introduced as variables in addition to the Normalized Difference Vegetation Index (NDVI, the Digital Elevation Model (DEM, and geolocation (longitude, latitude. Four machine learning regression algorithms, the classification and regression tree (CART, the k-nearest neighbors (k-NN, the support vector machine (SVM, and random forests (RF, were implemented to downscale monthly TRMM 3B43 V7 precipitation data from 25 km to 1 km over North China for the purpose of comparison of algorithm performance. The downscaled results were validated based on observations from meteorological stations and were also compared to a previous downscaling algorithm. According to the validation results, the RF-based model produced the results with the highest accuracy. It was followed by SVM, CART, and k-NN, but the accuracy of the downscaled results using SVM relied greatly on residual correction. The downscaled results were well correlated with the observations during the year, but the accuracies were relatively lower in July to September. Downscaling errors increase as monthly total precipitation increases, but the RF model was less affected by this proportional effect between errors and observation compared with the other algorithms. The variable importances of the land surface temperature (LST feature variables were higher than those of NDVI, which indicates the significance of considering the precipitation–land surface temperature

  20. Long-term change analysis of satellite-based evapotranspiration over Indian vegetated surface

    Science.gov (United States)

    Gupta, Shweta; Bhattacharya, Bimal K.; Krishna, Akhouri P.

    2016-05-01

    In the present study, trend of satellite based annual evapotranspiration (ET) and natural forcing factors responsible for this were analyzed. Thirty years (1981-2010) of ET data at 0.08° grid resolution, generated over Indian region from opticalthermal observations from NOAA PAL and MODIS AQUA satellites, were used. Long-term data on gridded (0.5° x 0.5°) annual rainfall (RF), annual mean surface soil moisture (SSM) ERS scatterometer at 25 km resolution and annual mean incoming shortwave radiation from MERRA-2D reanalysis were also analyzed. Mann-Kendall tests were performed with time series data for trend analysis. Mean annual ET loss from Indian ago-ecosystem was found to be almost double (1100 Cubic Km) than Indian forest ecosystem (550 Cubic Km). Rainfed vegetation systems such as forest, rainfed cropland, grassland showed declining ET trend @ - 4.8, -0.6 &-0.4 Cubic Kmyr-1, respectively during 30 years. Irrigated cropland initially showed ET decline upto 1995 @ -0.8 cubic Kmyr-1 which could possibly be due to solar dimming followed by increasing ET @ 0.9 cubic Kmyr-1 after 1995. A cross-over point was detected between forest ET decline and ET increase in irrigated cropland during 2008. During 2001-2010, the four agriculturally important Indian states eastern, central, western and southern showed significantly increasing ET trend with S-score of 15-25 and Z-score of 1.09-2.9. Increasing ET in western and southern states was found to be coupled with increase in annual rainfall and SSM. But in eastern and central states no significant trend in rainfall was observed though significant increase in ET was noticed. The study recommended to investigate the influence of anthropogenic factors such as increase in area under irrigation, increased use of water for irrigation through ground water pumping, change in cropping pattern and cultivars on increasing ET.

  1. Satellite Based Analysis of Carbon Monoxide Levels Over Alberta Oil Sand

    Science.gov (United States)

    Marey, H. S.; Hashisho, Z.; Fu, L.; Gille, J. C.

    2014-12-01

    The rapid expansion of oil sands activities and massive energy requirements to extract and upgrade the bitumen require a comprehensive understanding of their potential environmental impacts, particularly on air quality. In this study, satellite-based analysis of carbon monoxide (CO) levels was used to assess the magnitude and distribution of this pollutant throughout Alberta oil sands region. Measurements of Pollution in the Troposphere (MOPITT) V5 multispectral product that uses both near-infrared and the thermal-infrared radiances for CO retrieval were used. MOPITT-based climatology and inter-annual variations were examined for 12 years (2002-2013) on spatial and temporal scales. Seasonal climatological maps for CO total columns indicated conspicuous spatial variations in all seasons except in winter where the CO spatial variations are less prominent. High CO loadings are observed to extend from the North East to North West regions of Alberta, with highest values in spring. The CO mixing ratios at the surface level in winter and spring seasons exhibited dissimilar spatial distribution pattern where the enhancements are detected in south eastern rather than northern Alberta. Analyzing spatial distributions of Omega at 850 mb pressure level for four seasons implied that, conditions in northeastern Alberta are more favorable for up lofting while in southern Alberta, subsidence of CO emissions are more likely. Time altitude CO profile climatology as well as the inter-annual variability were investigated for the oil sands and main urban regions in Alberta to assess the impact of various sources on CO loading. Monthly variations over urban regions are consistent with the general seasonal cycle of CO in Northern Hemisphere which exhibits significant enhancement in winter and spring, and minimum mixing ratios in summer. The typical seasonal CO variations over the oil sands region are less prominent. This study has demonstrated the potential use of multispectral CO

  2. Categorizing natural disaster damage assessment using satellite-based geospatial techniques

    Science.gov (United States)

    Myint, S.W.; Yuan, M.; Cerveny, R.S.; Giri, C.

    2008-01-01

    Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.

  3. A method to develop mission critical data processing systems for satellite based instruments. The spinning mode case

    CERN Document Server

    Lazzarotto, Francesco; Costa, Enrico; Del Monte, Ettore; Di Persio, Giuseppe; Donnarumma, Immacolata; Evangelista, Yuri; Feroci, Marco; Pacciani, Luigi; Rubini, Alda; Soffitta, Paolo

    2011-01-01

    Modern satellite based experiments are often very complex real-time systems, composed by flight and ground segments, that have challenging resource related constraints, in terms of size, weight, power, requirements for real-time response, fault tolerance, and specialized input/output hardware-software, and they must be certified to high levels of assurance. Hardware-software data processing systems have to be responsive to system degradation and to changes in the data acquisition modes, and actions have to be taken to change the organization of the mission operations. A big research & develop effort in a team composed by scientists and technologists can lead to produce software systems able to optimize the hardware to reach very high levels of performance or to pull degraded hardware to maintain satisfactory features. We'll show real-life examples describing a system, processing the data of a X-Ray detector on satellite-based mission in spinning mode.

  4. Discrepancies in Southern Hemisphere Mid-latitude Atmospheric Variability of the NCEP-NCAR and ECMWF Reanalyses

    CERN Document Server

    Dell'Aquila, A; Calmanti, S; Lucarini, V

    2005-01-01

    In this paper we compare the representation of the southern hemisphere midlatitude winter variability in the NCEP-NCAR and ECMWF reanalyses. We use the classical Hayashi spectral technique, recently applied to compare the description of the atmospheric variability in the northern hemisphere on different spectral sub-domains as provided by the two reanalyses. We find relevant discrepancies in the description of the variability at different spatial and temporal scales. ERA40 is generally characterised by a larger variance, especially in the high frequency spectral region. In the southern hemisphere, also in the satellite period, the assimilated data are relatively scarce, predominately over the oceans, and they provide a weaker constraint to the model dynamics. In the pre-satellite period the discrepancies between the two reanalyses are large and randomly distributed while after the 1979 the discrepancies are smaller but systematic. Moreover, a sudden jump in the VTPR period (1973-1978) is observed, mostly in t...

  5. Validation of satellite-based noontime UVI with NDACC ground-based instruments: influence of topography, environment and satellite overpass time

    Science.gov (United States)

    Brogniez, Colette; Auriol, Frédérique; Deroo, Christine; Arola, Antti; Kujanpää, Jukka; Sauvage, Béatrice; Kalakoski, Niilo; Riku Aleksi Pitkänen, Mikko; Catalfamo, Maxime; Metzger, Jean-Marc; Tournois, Guy; Da Conceicao, Pierre

    2016-12-01

    Spectral solar UV radiation measurements are performed in France using three spectroradiometers located at very different sites. One is installed in Villeneuve d'Ascq, in the north of France (VDA). It is an urban site in a topographically flat region. Another instrument is installed in Observatoire de Haute-Provence, located in the southern French Alps (OHP). It is a rural mountainous site. The third instrument is installed in Saint-Denis, Réunion Island (SDR). It is a coastal urban site on a small mountainous island in the southern tropics. The three instruments are affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC) and carry out routine measurements to monitor the spectral solar UV radiation and enable derivation of UV index (UVI). The ground-based UVI values observed at solar noon are compared to similar quantities derived from the Ozone Monitoring Instrument (OMI, onboard the Aura satellite) and the second Global Ozone Monitoring Experiment (GOME-2, onboard the Metop-A satellite) measurements for validation of these satellite-based products. The present study concerns the period 2009-September 2012, date of the implementation of a new OMI processing tool. The new version (v1.3) introduces a correction for absorbing aerosols that were not considered in the old version (v1.2). Both versions of the OMI UVI products were available before September 2012 and are used to assess the improvement of the new processing tool. On average, estimates from satellite instruments always overestimate surface UVI at solar noon. Under cloudless conditions, the satellite-derived estimates of UVI compare satisfactorily with ground-based data: the median relative bias is less than 8 % at VDA and 4 % at SDR for both OMI v1.3 and GOME-2, and about 6 % for OMI v1.3 and 2 % for GOME-2 at OHP. The correlation between satellite-based and ground-based data is better at VDA and OHP (about 0.99) than at SDR (0.96) for both space-borne instruments. For all

  6. Effects of in-situ and reanalysis climate data on estimation of cropland gross primary production using the Vegetation Photosynthesis Model

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Cui; Xiao, Xiangming; Wagle, Pradeep; Griffis, Timothy; Dong, Jinwei; Wu, Chaoyang; Qin, Yuanwei; Cook, David R.

    2015-11-01

    Satellite-based Production Efficiency Models (PEMs) often require meteorological reanalysis data such as the North America Regional Reanalysis (NARR) by the National Centers for Environmental Prediction (NCEP) as model inputs to simulate Gross Primary Production (GPP) at regional and global scales. This study first evaluated the accuracies of air temperature (TNARR) and downward shortwave radiation (RNARR) of the NARR by comparing with in-situ meteorological measurements at 37 AmeriFlux non-crop eddy flux sites, then used one PEM – the Vegetation Photosynthesis Model (VPM) to simulate 8-day mean GPP (GPPVPM) at seven AmeriFlux crop sites, and investigated the uncertainties in GPPVPM from climate inputs as compared with eddy covariance-based GPP (GPPEC). Results showed that TNARR agreed well with in-situ measurements; RNARR, however, was positively biased. An empirical linear correction was applied to RNARR, and significantly reduced the relative error of RNARR by ~25% for crop site-years. Overall, GPPVPM calculated from the in-situ (GPPVPM(EC)), original (GPPVPM(NARR)) and adjusted NARR (GPPVPM(adjNARR)) climate data tracked the seasonality of GPPEC well, albeit with different degrees of biases. GPPVPM(EC) showed a good match with GPPEC for maize (Zea mays L.), but was slightly underestimated for soybean (Glycine max L.). Replacing the in-situ climate data with the NARR resulted in a significant overestimation of GPPVPM(NARR) (18.4/29.6% for irrigated/rainfed maize and 12.7/12.5% for irrigated/rainfed soybean). GPPVPM(adjNARR) showed a good agreement with GPPVPM(EC) for both crops due to the reduction in the bias of RNARR. The results imply that the bias of RNARR introduced significant uncertainties into the PEM-based GPP estimates, suggesting that more accurate surface radiation datasets are needed to estimate primary production of terrestrial ecosystems at regional and global scales.

  7. Utility and Value of Satellite-Based Frost Forecasting for Kenya's Tea Farming Sector

    Science.gov (United States)

    Morrison, I.

    2016-12-01

    Frost damage regularly inflicts millions of dollars of crop losses in the tea-growing highlands of western Kenya, a problem that the USAID/NASA Regional Visualization and Monitoring System (SERVIR) program is working to mitigate through a frost monitoring and forecasting product that uses satellite-based temperature and soil moisture data to generate up to three days of advanced warning before frost events. This paper presents the findings of a value of information (VOI) study assessing the value of this product based on Kenyan tea farmers' experiences with frost and frost-damage mitigation. Value was calculated based on historic trends of frost frequency, severity, and extent; likelihood of warning receipt and response; and subsequent frost-related crop-loss aversion. Quantification of these factors was derived through inferential analysis of survey data from 400 tea-farming households across the tea-growing regions of Kericho and Nandi, supplemented with key informant interviews with decision-makers at large estate tea plantations, historical frost incident and crop-loss data from estate tea plantations and agricultural insurance companies, and publicly available demographic and economic data. At this time, the product provides a forecasting window of up to three days, and no other frost-prediction methods are used by the large or small-scale farmers of Kenya's tea sector. This represents a significant opportunity for preemptive loss-reduction via Earth observation data. However, the tea-growing community has only two realistic options for frost-damage mitigation: preemptive harvest of available tea leaves to minimize losses, or skiving (light pruning) to facilitate fast recovery from frost damage. Both options are labor-intensive and require a minimum of three days of warning to be viable. As a result, the frost forecasting system has a very narrow margin of usefulness, making its value highly dependent on rapid access to the warning messages and flexible access

  8. The development of potassium tantalate niobate thin films for satellite-based pyroelectric detectors

    Energy Technology Data Exchange (ETDEWEB)

    Cherry, Hilary B.B. [Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Mineral Engineering

    1997-05-01

    Potassium tantalate niobate (KTN) pyroelectric detectors are expected to provide detectivities, of 3.7 x 1011 cmHz 1/2W-1 for satellite-based infrared detection at 90 K. The background limited detectivity for a room-temperature thermal detector is 1.8 x 1010 cmHz1/2W-1 . KTN is a unique ferroelectric for this application because of the ability to tailor the temperature of its pyroelectric response by adjusting its ratio of tantalum to niobium. The ability to fabricate high quality KTN thin films on Si-based substrates is crucial to the development of KTN pyroelectric detectors. SixNymembranes created on the Si substrate will provide the weak thermal link necessary to reach background limited detectivities. The device dimensions obtainable by thin film processing are expected to increase the ferroelectric response by 20 times over bulk fabricated KTN detectors. In addition, microfabrication techniques allow for easier array development. This is the first reported attempt at growth of KTN films on Si-based substrates. Pure phase perovskite films were grown by pulsed laser deposition on SrRuO3/Pt/Ti/SixNy/Si and SrRuO3/SixNy/Si structures; room temperature dielectric permittivities for the KTN films were 290 and 2.5, respectively. The dielectric permittivity for bulk grown, single crystal KTN is ~380. In addition to depressed dielectric permittivities, no ferroelectric hysteresis was found between 80 and 300 K for either structure. RBS, AES, TEM and multi-frequency dielectric measurements were used to investigate the origin of this apparent lack of ferroelectricity. Other issues addressed by this dissertation include: the role of oxygen and target density during pulsed laser deposition of KTN thin films; the use of YBCO, LSC and Pt as direct contact bottom electrodes to the KTN films, and the adhesion of the bottom

  9. Assessment of Satellite-based Precipitation Products (TRMM) in Hydrologic Modeling: Case Studies from Northern Morocco

    Science.gov (United States)

    EL kadiri, R.; Milewski, A.; Durham, M.

    2012-12-01

    Precipitation is the most important forcing parameter in hydrological modeling, yet it is largely unknown in the arid Middle East. We assessed the magnitude, probability of detection, and false alarm rates of various rainfall satellite products (e.g., TRMM, RFE2.0) compared to in situ gauge data (~79 stations) across the Our Er Rbia, Sebou, and Melouya Watersheds in Northern Morocco. Precipitation over the area is relatively high with an average of ~400mm/year according to TRMM (1998-2008). The existing gauges indicate that the average annual precipitation across the Tadla and Coastal Plains region is 260mm/year and 390mm/year across the Atlas Mountains. Following the assessment of satellite products against in situ gauge data, we evaluated the effects (e.g., runoff and recharge amounts) of using satellite driven hydrologic models using SWAT. Specifically, we performed a four-fold exercise: (1) The first stage focused on the analysis of the rainfall products; (2) the second stage involved the construction of a rainfall-runoff model using gauge data; (3) the third stage entailed the calibration of the model against flow gauges and/or dams storage variability, and (4) model simulation using satellite based rainfall products using the calibrated parameters from the initial simulation. Results suggest the TRMM V7 has a much better correlation with the field data over the Oum Er Rbia watershed. The Correlation E (Nash-Suncliffe coefficient) has a positive value of 0.5, while the correlation coefficient of TRMM V6 vs. gauges data is a negative value of -0.25. This first order evaluation of the TRMM V7 shows the new algorithm has partially overcame the underestimation effect in the semi-arid environments. However, more research needs to be done to increase the usability of TRMM V7 in hydrologic models. Low correlations are most likely a result of the following: (1) snow at the high elevations in the Oum Er Rbia watershed, (2) the ocean effect on TRMM measurements along

  10. Advanced Oil Spill Detection Algorithms For Satellite Based Maritime Environment Monitoring

    Science.gov (United States)

    Radius, Andrea; Azevedo, Rui; Sapage, Tania; Carmo, Paulo

    2013-12-01

    During the last years, the increasing pollution occurrence and the alarming deterioration of the environmental health conditions of the sea, lead to the need of global monitoring capabilities, namely for marine environment management in terms of oil spill detection and indication of the suspected polluter. The sensitivity of Synthetic Aperture Radar (SAR) to the different phenomena on the sea, especially for oil spill and vessel detection, makes it a key instrument for global pollution monitoring. The SAR performances in maritime pollution monitoring are being operationally explored by a set of service providers on behalf of the European Maritime Safety Agency (EMSA), which has launched in 2007 the CleanSeaNet (CSN) project - a pan-European satellite based oil monitoring service. EDISOFT, which is from the beginning a service provider for CSN, is continuously investing in R&D activities that will ultimately lead to better algorithms and better performance on oil spill detection from SAR imagery. This strategy is being pursued through EDISOFT participation in the FP7 EC Sea-U project and in the Automatic Oil Spill Detection (AOSD) ESA project. The Sea-U project has the aim to improve the current state of oil spill detection algorithms, through the informative content maximization obtained with data fusion, the exploitation of different type of data/ sensors and the development of advanced image processing, segmentation and classification techniques. The AOSD project is closely related to the operational segment, because it is focused on the automation of the oil spill detection processing chain, integrating auxiliary data, like wind information, together with image and geometry analysis techniques. The synergy between these different objectives (R&D versus operational) allowed EDISOFT to develop oil spill detection software, that combines the operational automatic aspect, obtained through dedicated integration of the processing chain in the existing open source NEST

  11. The development of potassium tantalate niobate thin films for satellite-based pyroelectric detectors

    Energy Technology Data Exchange (ETDEWEB)

    Cherry, H B.B. [Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Mineral Engineering

    1997-05-01

    Potassium tantalate niobate (KTN) pyroelectric detectors are expected to provide detectivities, of 3.7 x 10{sup 11} cmHz {sup {1/2}}W{sup {minus}1} for satellite-based infrared detection at 90 K. The background limited detectivity for a room-temperature thermal detector is 1.8 x 10{sup 10} cmHz{sup {1/2}}W{sup {minus}1}. KTN is a unique ferroelectric for this application because of the ability to tailor the temperature of its pyroelectric response by adjusting its ratio of tantalum to niobium. The ability to fabricate high quality KTN thin films on Si-based substrates is crucial to the development of KTN pyroelectric detectors. Si{sub x}N{sub y} membranes created on the Si substrate will provide the weak thermal link necessary to reach background limited detectivities. The device dimensions obtainable by thin film processing are expected to increase the ferroelectric response by 20 times over bulk fabricated KTN detectors. In addition, microfabrication techniques allow for easier array development. This is the first reported attempt at growth of KTN films on Si-based substrates. Pure phase perovskite films were grown by pulsed laser deposition on SrRuO{sub 3}/Pt/Ti/Si{sub x}N{sub y}/Si and SrRuO{sub 3}/Si{sub x}N{sub y}/Si structures; room temperature dielectric permittivities for the KTN films were 290 and 2.5, respectively. The dielectric permittivity for bulk grown, single crystal KTN is {approximately}380. In addition to depressed dielectric permittivities, no ferroelectric hysteresis was found between 80 and 300 K for either structure. RBS, AES, TEM and multi-frequency dielectric measurements were used to investigate the origin of this apparent lack of ferroelectricity. Other issues addressed by this dissertation include: the role of oxygen and target density during pulsed laser deposition of KTN thin films; the use of YBCO, LSC and Pt as direct contact bottom electrodes to the KTN films, and the adhesion of the bottom electrode layers to Si{sub x}N{sub y}/Si.

  12. Towards a protocol for validating satellite-based Land Surface Temperature: Theoretical considerations

    Science.gov (United States)

    Schneider, Philipp; Ghent, Darren J.; Corlett, Gary C.; Prata, Fred; Remedios, John J.

    2013-04-01

    Land Surface Temperature (LST) and emissivity are important parameters for environmental monitoring and earth system modelling. LST has been observed from space for several decades using a wide variety of satellite instruments with different characteristics, including both platforms in low-earth orbit and in geostationary orbit. This includes for example the series of Advanced Very High Resolution Radiometers (AVHRR) delivering a continuous thermal infrared (TIR) data stream since the early 1980s, the series of Along-Track Scanning Radiometers (ATSR) providing TIR data since 1991, and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard NASA's Terra and Aqua platforms, providing data since the year 2000. In addition, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard of the geostationary Meteosat satellites is now providing LST at unprecedented sub-hour frequency. The data record provided by such instruments is extremely valuable for a wide variety of applications, including climate change, land/atmosphere feedbacks, fire monitoring, modelling, land cover change, geology, crop- and water management. All of these applications, however, require a rigorous validation of the data in order to assess the product quality and the associated uncertainty. Here we report on recent work towards developing a protocol for validation of satellite-based Land Surface Temperature products. Four main validation categories are distinguished within the protocol: A) Comparison with in situ observations, B) Radiance-based validation, C) Inter-comparison with similar LST products, and D) Time-series analysis. Each category is further subdivided into several quality classes, which approximately reflect the validation accuracy that can be achieved by the different approaches, as well as the complexity involved with each method. Advice on best practices is given for methodology common to all categories. For each validation category, recommendations

  13. Simulation of large-scale soil water systems using groundwater data and satellite based soil moisture

    Science.gov (United States)

    Kreye, Phillip; Meon, Günter

    2016-04-01

    Complex concepts for the physically correct depiction of dominant processes in the hydrosphere are increasingly at the forefront of hydrological modelling. Many scientific issues in hydrological modelling demand for additional system variables besides a simulation of runoff only, such as groundwater recharge or soil moisture conditions. Models that include soil water simulations are either very simplified or require a high number of parameters. Against this backdrop there is a heightened demand of observations to be used to calibrate the model. A reasonable integration of groundwater data or remote sensing data in calibration procedures as well as the identifiability of physically plausible sets of parameters is subject to research in the field of hydrology. Since this data is often combined with conceptual models, the given interfaces are not suitable for such demands. Furthermore, the application of automated optimisation procedures is generally associated with conceptual models, whose (fast) computing times allow many iterations of the optimisation in an acceptable time frame. One of the main aims of this study is to reduce the discrepancy between scientific and practical applications in the field of hydrological modelling. Therefore, the soil model DYVESOM (DYnamic VEgetation SOil Model) was developed as one of the primary components of the hydrological modelling system PANTA RHEI. DYVESOMs structure provides the required interfaces for the calibrations made at runoff, satellite based soil moisture and groundwater level. The model considers spatial and temporal differentiated feedback of the development of the vegetation on the soil system. In addition, small scale heterogeneities of soil properties (subgrid-variability) are parameterized by variation of van Genuchten parameters depending on distribution functions. Different sets of parameters are operated simultaneously while interacting with each other. The developed soil model is innovative regarding concept

  14. A robust TEC depletion detector algorithm for satellite based navigation in Indian zone and depletion analysis for GAGAN

    Science.gov (United States)

    Dashora, Nirvikar

    2012-07-01

    Equatorial plasma bubble (EPB) and associated plasma irregularities are known to cause severe scintillation for the satellite signals and produce range errors, which eventually result either in loss of lock of the signal or in random fluctuation in TEC, respectively, affecting precise positioning and navigation solutions. The EPBs manifest as sudden reduction in line of sight TEC, which are more often called TEC depletions, and are spread over thousands of km in meridional direction and a few hundred km in zonal direction. They change shape and size while drifting from one longitude to another in nighttime ionosphere. For a satellite based navigation system, like GAGAN in India that depends upon (i) multiple satellites (i.e. GPS) (ii) multiple ground reference stations and (iii) a near real time data processing, such EPBs are of grave concern. A TEC model generally provides a near real-time grid based ionospheric vertical errors (GIVEs) over hypothetically spread 5x5 degree latitude-longitude grid points. But, on night when a TEC depletion occurs in a given longitude sector, it is almost impossible for any system to give a forecast of GIVEs. If loss-of-lock events occur due to scintillation, there is no way to improve the situation. But, when large and random depletions in TEC occur with scintillations and without loss-of-lock, it affects low latitude TEC in two ways. (a) Multiple satellites show depleted TEC which may be very different from model-TEC values and hence the GIVE would be incorrect over various grid points (ii) the user may be affected by depletions which are not sampled by reference stations and hence interpolated GIVE within one square would be grossly erroneous. The most general solution (and the far most difficult as well) is having advance knowledge of spatio-temporal occurrence and precise magnitude of such depletions. While forecasting TEC depletions in spatio-temporal domain are a scientific challenge (as we show below), operational systems

  15. Role of physical forcings and nutrient availability on the control of satellite-based chlorophyll a concentration in the coastal upwelling area of the Sicilian Channel

    Directory of Open Access Journals (Sweden)

    Bernardo Patti

    2010-08-01

    Full Text Available The northern sector of the Sicilian Channel is an area of favourable upwelling winds, which ought to support primary production. However, the values for primary production are low when compared with other Mediterranean areas and very low compared with the most biologically productive regions of the world’s oceans: California, the Canary Islands, Humboldt and Benguela. The aim of this study was to identify the main factors that limit phytoplankton biomass in the Sicilian Channel and modulate its monthly changes. We compared satellite-based estimates of chlorophyll a concentration in the Strait of Sicily with those observed in the four Eastern Boundary Upwelling Systems mentioned above and in other Mediterranean wind-induced coastal upwelling systems (the Alboran Sea, the Gulf of Lions and the Aegean Sea. Our results show that this low level of chlorophyll is mainly due to the low nutrient level in surface and sub-surface waters, independently of wind-induced upwelling intensity. Further, monthly changes in chlorophyll are mainly driven by the mixing of water column and wind-induced and/or circulation-related upwelling processes. Finally, primary production limitation due to the enhanced stratification processes resulting from the general warming trend of Mediterranean waters is not active over most of the coastal upwelling area off the southern Sicilian coast.

  16. Lack of chart reminder effectiveness on family medicine resident JNC-VI and NCEP III guideline knowledge and attitudes

    Directory of Open Access Journals (Sweden)

    Upshur Ross EG

    2004-07-01

    Full Text Available Abstract Background The literature demonstrates that medical residents and practicing physicians have an attitudinal-behavioral discordance concerning their positive attitudes towards clinical practice guidelines (CPG, and the implementation of these guidelines into clinical practice patterns. Methods A pilot study was performed to determine if change in a previously identified CPG compliance factor (accessibility would produce a significant increase in family medicine resident knowledge and attitude toward the guidelines. The primary study intervention involved placing a summary of the Sixth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC VI and the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (NCEP III CPGs in all patient (>18 yr. charts for a period of three months. The JNC VI and NCEP III CPGs were also distributed to each Wayne State family medicine resident, and a copy of each CPG was placed in the preceptor's area of the involved clinics. Identical pre- and post- intervention questionnaires were administered to all residents concerning CPG knowledge and attitude. Results Post-intervention analysis failed to demonstrate a significant difference in CPG knowledge. A stastically significant post-intervention difference was found in only on attitude question. The barriers to CPG compliance were identified as 1 lack of CPG instruction; 2 lack of critical appraisal ability; 3 insufficient time; 4 lack of CPG accessibility; and 5 lack of faculty modeling. Conclusion This study demonstrated no significant post intervention changes in CPG knowledge, and only one question that reflected attitude change. Wider resident access to dedicated clinic time, increased faculty modeling, and the implementation of an electronic record/reminder system that uses a team-based approach are compliance factors that

  17. 4D Hybrid Ensemble-Variational Data Assimilation for the NCEP GFS: Outer Loops and Variable Transforms

    Science.gov (United States)

    Kleist, D. T.; Ide, K.; Mahajan, R.; Thomas, C.

    2014-12-01

    The use of hybrid error covariance models has become quite popular for numerical weather prediction (NWP). One such method for incorporating localized covariances from an ensemble within the variational framework utilizes an augmented control variable (EnVar), and has been implemented in the operational NCEP data assimilation system (GSI). By taking the existing 3D EnVar algorithm in GSI and allowing for four-dimensional ensemble perturbations, coupled with the 4DVAR infrastructure already in place, a 4D EnVar capability has been developed. The 4D EnVar algorithm has a few attractive qualities relative to 4DVAR, including the lack of need for tangent-linear and adjoint model as well as reduced computational cost. Preliminary results using real observations have been encouraging, showing forecast improvements nearly as large as were found in moving from 3DVAR to hybrid 3D EnVar. 4D EnVar is the method of choice for the next generation assimilation system for use with the operational NCEP global model, the global forecast system (GFS). The use of an outer-loop has long been the method of choice for 4DVar data assimilation to help address nonlinearity. An outer loop involves the re-running of the (deterministic) background forecast from the updated initial condition at the beginning of the assimilation window, and proceeding with another inner loop minimization. Within 4D EnVar, a similar procedure can be adopted since the solver evaluates a 4D analysis increment throughout the window, consistent with the valid times of the 4D ensemble perturbations. In this procedure, the ensemble perturbations are kept fixed and centered about the updated background state. This is analogous to the quasi-outer loop idea developed for the EnKF. Here, we present results for both toy model and real NWP systems demonstrating the impact from incorporating outer loops to address nonlinearity within the 4D EnVar context. The appropriate amplitudes for observation and background error

  18. Comparative Evaluation of Performances of Two Versions of NCEP Climate Forecast System in Predicting Winter Precipitation over India

    Science.gov (United States)

    Nageswararao, M. M.; Mohanty, U. C.; Nair, Archana; Ramakrishna, S. S. V. S.

    2016-06-01

    The precipitation during winter (December through February) over India is highly variable in terms of time and space. Maximum precipitation occurs over the Himalaya region, which is important for water resources and agriculture sectors over the region and also for the economy of the country. Therefore, in the present global warming era, the realistic prediction of winter precipitation over India is important for planning and implementing agriculture and water management strategies. The National Centers for Environmental Prediction (NCEP) issued the operational prediction of climatic variables in monthly to seasonal scale since 2004 using their first version of fully coupled global climate model known as Climate Forecast System (CFSv1). In 2011, a new version of CFS (CFSv2) was introduced with the incorporation of significant changes in older version of CFS (CFSv1). The new version of CFS is required to compare in detail with the older version in the context of simulating the winter precipitation over India. Therefore, the current study presents a detailed analysis on the performance of CFSv2 as compared to CFSv1 for the winter precipitation over India. The hindcast runs of both CFS versions from 1982 to 2008 with November initial conditions are used and the model's precipitation is evaluated with that of India Meteorological Department (IMD). The models simulated wind and geopotential height against the National Center for Atmospheric Research (NCEP-NCAR) reanalysis-2 (NNRP2) and remote response patterns of SST against Extended Reconstructed Sea Surface Temperatures version 3b (ERSSTv3b) are examined for the same period. The analyses of winter precipitation revealed that both the models are able to replicate the patterns of observed climatology; interannual variability and coefficient of variation. However, the magnitude is lesser than IMD observation that can be attributed to the model's inability to simulate the observed remote response of sea surface

  19. Advancing satellite-based solar power forecasting through integration of infrared channels for automatic detection of coastal marine inversion layer

    Energy Technology Data Exchange (ETDEWEB)

    Kostylev, Vladimir; Kostylev, Andrey; Carter, Chris; Mahoney, Chad; Pavlovski, Alexandre; Daye, Tony [Green Power Labs Inc., Dartmouth, NS (Canada); Cormier, Dallas Eugene; Fotland, Lena [San Diego Gas and Electric Co., San Diego, CA (United States)

    2012-07-01

    The marine atmospheric boundary layer is a layer or cool, moist maritime air with the thickness of a few thousand feet immediately below a temperature inversion. In coastal areas as moist air rises from the ocean surface, it becomes trapped and is often compressed into fog above which a layer of stratus clouds often forms. This phenomenon is common for satellite-based solar radiation monitoring and forecasting. Hour ahead satellite-based solar radiation forecasts are commonly using visible spectrum satellite images, from which it is difficult to automatically differentiate low stratus clouds and fog from high altitude clouds. This provides a challenge for cloud motion tyracking and cloud cover forecasting. San Diego Gas and Electric {sup registered} (SDG and E {sup registered}) Marine Layer Project was undertaken to obtain information for integration with PV forecasts, and to develop a detailed understanding of long-term benefits from forecasting Marine Layer (ML) events and their effects on PV production. In order to establish climatological ML patterns, spatial extent and distribution of marine layer, we analyzed visible and IR spectrum satellite images (GOES WEST) archive for the period of eleven years (2000 - 2010). Historical boundaries of marine layers impact were established based on the cross-classification of visible spectrum (VIS) and infrared (IR) images. This approach is successfully used by us and elsewhere for evaluating cloud albedo in common satellite-based techniques for solar radiation monitoring and forecasting. The approach allows differentiation of cloud cover and helps distinguish low laying fog which is the main consequence of marine layer formation. ML occurrence probability and maximum extent inland was established for each hour and day of the analyzed period and seasonal/patterns were described. SDG and E service area is the most affected region by ML events with highest extent and probability of ML occurrence. Influence of ML was the

  20. Use of satellite-based aerosol optical depth and spatial clustering to predict ambient PM2.5 concentrations

    OpenAIRE

    2012-01-01

    Satellite-based PM2.5 monitoring has the potential to complement ground PM2.5 monitoring networks, especially for regions with sparsely distributed monitors. Satellite remote sensing provides data on aerosol optical depth (AOD), which reflects particle abundance in the atmospheric column. Thus AOD has been used in statistical models to predict ground-level PM2.5 concentrations. However, previous studies have shown that AOD may not be a strong predictor of PM2.5 ground levels. Another shortcom...

  1. Influence of upper ocean on Indian summer monsoon rainfall: studies by observation and NCEP climate forecast system (CFSv2)

    Science.gov (United States)

    Chaudhari, Hemantkumar S.; Pokhrel, Samir; Rahman, H.; Dhakate, A.; Saha, Subodh K.; Pentakota, S.; Gairola, R. M.

    2016-08-01

    This study explores the role played by ocean processes in influencing Indian summer monsoon rainfall (ISMR) and compares the observed findings with National Centers for Environmental Prediction (NCEP)-coupled model Climate Forecast System, version 2 (CFSv2). The excess and deficit ISMR clearly brings out the distinct signatures in sea surface height (SSH) anomaly, thermocline and mixed layer depth over north Indian Ocean. CFSv2 is successful in simulating SSH anomalies, especially over Arabian Sea and Bay of Bengal region. CFSv2 captures observed findings of SSH anomalies during flood and drought (e.g., Rossby wave propagation which reaches western Bay of Bengal (BoB) during flood years, Rossby wave propagation which did not reach western BoB during drought). It highlights the ability of CFSv2 to simulate the basic ocean processes which governs the SSH variability. These differences are basically generated by upwelling and downwelling caused by the equatorial and coastal Kelvin and Rossby waves, thereby causing difference in SSH anomaly and thermocline, and subsequently modifying the convection centers, which dictates precipitation over the Indian subcontinent region. Since the observed SSH anomaly and thermal structure show distinct characteristic features with respect to strong and weak ISMR variability, the assimilation of real ocean data in terms of satellite products (like SSHA from AVISO/SARAL) bestow great promise for the future improvement.

  2. Evaluation of cloud properties in the NCEP CFSv2 model and its linkage with Indian summer monsoon

    Science.gov (United States)

    Hazra, Anupam; Chaudhari, Hemantkumar S.; Dhakate, Ashish

    2016-04-01

    Cloud fraction, which varies greatly among general circulation models, plays a crucial role in simulation of Indian summer monsoon rainfall (ISMR). The NCEP Climate Forecast System version 2 (CFSv2) model is evaluated in terms of its simulation of cloud fraction, cloud condensate, outgoing longwave radiation (OLR), and tropospheric temperature (TT). Biases in these simulated quantities are computed using observations from CALIPSO and reanalysis data from MERRA. It is shown that CFSv2 underestimates (overestimates) high- (mid-) level clouds. The cloud condensate is also examined to see its impact on different types of clouds. The upper-level cloud condensate is underestimated, particularly during the summer monsoon period, which leads to a cold TT and a dry precipitation bias. The unrealistically weak TT gradient between ocean and land is responsible for the underestimation of ISMR. The model-simulated OLR is overestimated which depicts the weaker convective activity. A large underestimate of precipitable water is also seen along the cross-equatorial flow and particularly over the Indian land region collocated with a dry precipitation bias. The linkages among cloud microphysical, thermodynamical, and dynamical processes are identified here. Thus, this study highlights the importance of cloud properties, a major cause of uncertainty in CFSv2, and also proposes a pathway for improvements in its simulation of the Indian summer monsoon.

  3. Hayashi Spectra of the Northern Hemisphere Mid-latitude Atmospheric Variability in the NCEP and ERA 40 Reanalyses

    CERN Document Server

    Dell'Aquila, A; Ruti, P; Calmanti, S; Aquila, Alessandro Dell'; Lucarini, Valerio; Ruti, Paolo; Calmanti, Sandro

    2004-01-01

    We compare 45 years of the reanalyses of NCEP-NCAR and ECMWF in terms of their representation of the mid-latitude winter atmospheric variability for the overlapping time frame 1957-2002. We adopt the classical approach of computing the Hayashi spectra of the 500 hPa geopotential height fields. Discrepancies are found especially in the first 15 years of the records in the high-frequency-high wavenumber propagating waves and secondly on low frequency-low wavenumber standing waves. This implies that in the first period the two datasets have a different representation of the baroclinic available energy conversion processes. In the period starting from 1973 a positive impact of the aircraft data on the Euro-Atlantic synoptic waves has been highlighted. Since in the first period the assimilated data are scarcer and of lower quality than later on, they provide a weaker constraint to the model dynamics. Therefore, the resulting discrepancies in the reanalysis products may be mainly attributed to differences in the mo...

  4. Sensitivity of a Floodplain Hydrodynamic Model to Satellite-Based DEM Scale and Accuracy: Case Study—The Atchafalaya Basin

    Directory of Open Access Journals (Sweden)

    Hahn Chul Jung

    2015-06-01

    Full Text Available The hydrodynamics of low-lying riverine floodplains and wetlands play a critical role in hydrology and ecosystem processes. Because small topographic features affect floodplain storage and flow velocity, a hydrodynamic model setup of these regions imposes more stringent requirements on the input Digital Elevation Model (DEM compared to upland regions with comparatively high slopes. This current study provides a systematic approach to evaluate the required relative vertical accuracy and spatial resolution of current and future satellite-based altimeters within the context of DEM requirements for 2-D floodplain hydrodynamic models. A case study is presented for the Atchafalaya Basin with a model domain of 1190 km2. The approach analyzes the sensitivity of modeled floodplain water elevation and velocity to typical satellite-based DEM grid-box scale and vertical error, using a previously calibrated version of the physically-based flood inundation model (LISFLOOD-ACC. Results indicate a trade-off relationship between DEM relative vertical error and grid-box size. Higher resolution models are the most sensitive to vertical accuracy, but the impact diminishes at coarser resolutions because of spatial averaging. The results provide guidance to engineers and scientists when defining the observation scales of future altimetry missions such as the   Surface Water and Ocean Topography (SWOT mission from the perspective of numerical modeling requirements for large floodplains of O[103] km2 and greater.

  5. 基于GPS和NCEP FNL数据改正InSAR大气延迟的可行性分析%Feasibility analysis of InSAR atmospheric delay correction based on GPS observations and NCEP FNL data

    Institute of Scientific and Technical Information of China (English)

    张书毕; 傅拓

    2012-01-01

    Over last two decades, Interferometric Synthetic Aperture Radar (InSAR) has been widely used to monitor geological hazards due to its high precision, wide area coverage and low cost. However, InSAR suffers from the phase delay in radio signal propagation through the atmosphere, and it becomes worse during the geological hazards which always occur in complex geological hilly areas with heavy rainfall. Based on a detailed review of some main application studies so far in the world, the advantages and difficulties concerning the application of these skills to landslide monitoring are concluded. By using some new developments of monitoring technique, possible solutions for the existing problems to practical application of InSAR atmospheric delay correction based on GPS observations and NCEP FNL data are proposed. This paper introduces the principles and data processing method of this technique, associates with some examples proving the advantages of reducing the residual of InSAR atmospheric delay phase, so as to improve monitoring accuracy.%InSAR技术是近二十几年来迅速发展的极具应用价值的空间对地观测新技术,它具有监测精度高、范围大、成本低、空间连续覆盖等优点,为滑坡、泥石流等地质灾害监测提供了一种新型的监测方法。但由于地质灾害多发生在暴雨频发、地质地貌复杂的区域,特殊的地理位置与气候使得InSAR技术应用中受大气延迟的影响非常严重,导致InSAR图像错误解释。本文在全面回顾当前主流的几种改正InSAR大气延迟的方法在国内外滑坡监测中的应用现状和实例的基础上,分析这几种技术的优势及问题点,并结合最新技术进展提出了一种基于GPS和NCEP FNL数据改正InSAR大气延迟的新方法,详细推导了该方法处理的流程,结合实例进行了分析比较,证明了其可有效削弱InSAR干涉图中的残余大气延迟相位,进而提高InSAR监测精度的优点。

  6. Avaliação do modelo regional eta utilizando as análises do CPTEC e NCEP Evaluation of the eta regional model using the analysis of CPTEC and NCEP

    Directory of Open Access Journals (Sweden)

    Rildo Gonçalves de Moura

    2010-03-01

    Full Text Available Os modelos numéricos de tempo são ferramentas essenciais para a previsão de curto e longo prazo, permitindo realizar a previsão com vários dias de antecedência. O conhecimento do desempenho dos modelos e dos erros sistemáticos a eles associados, é de suma importância, pois permite avaliar a capacidade dos mesmos em captar os processos físicos da atmosfera. Com intuito de melhorar a qualidade da previsão de tempo na América do Sul, disponibilizada no Centro de Previsão de Tempo e Estudos Climáticos (CPTEC, este trabalho avaliou as previsões de precipitação e pressão ao nível médio do mar para o prazo de até 120 horas, utilizando o erro médio (EM e a raiz do erro médio quadrático (REMQ no período de dezembro de 2007 a fevereiro de 2008. O modelo utilizado foi o ETA (40 km, com duas entradas distintas de dados, as análises do Physical-space Statistical Analysis System (PSAS (ETA-I e do National Centers for Environmental Predictions (NCEP (ETA-II. Os resultados mostraram, para ambas as análises, uma tendência de superestimativa (valores positivos do erro médio da precipitação sobre a Região Norte do Brasil, principalmente para 24 horas de previsão. Em relação à pressão ao nível médio do mar (PNMM foi possível verificar claramente que o ETA-I apresenta melhores resultados em comparação com o ETA-II, cujos valores de pressão se aproximaram bastante do observado, principalmente nas primeiras horas de integração.The numerical weather models are essential tools for predicting short and long term, allowing the prediction of weather conditions several days in advance. The knowledge of models performance and the systematic errors associated with them is extremely important because it allows to evaluate the ability to capture the physical processes of the atmosphere. In order to improve the quality of weather forecast in South America, available at Center for Weather Forecast and Climate Studies (CPTEC, this study

  7. El príncep, Niccolò Machiavelli: elogi del passat, crítica del present, projecte del futur

    Directory of Open Access Journals (Sweden)

    Àngels B. Miró

    2002-04-01

    Full Text Available El príncep és una obra fonamental dins la història de la filosofia política. Però no podem entendre l'obra cabdal de Maquiavel sense detenir-nos en la trajectòria personal i literària de l'autor i en l'entorn en què va viure.

  8. Benchmarking LSM root-zone soil mositure predictions using satellite-based vegetation indices

    Science.gov (United States)

    The application of modern land surface models (LSMs) to agricultural drought monitoring is based on the premise that anomalies in LSM root-zone soil moisture estimates can accurately anticipate the subsequent impact of drought on vegetation productivity and health. In addition, the water and energy ...

  9. A Preliminary Study on the Use of NCEP Temperature Images and Additive Tectonic Stress from Astro-Tidal-Triggering to Forecast Short-Impending Earthquakes

    Institute of Scientific and Technical Information of China (English)

    Ma Weiyu; Zhang Xingcai; Dai Xiaofang; Xie Fang

    2007-01-01

    Taking the three earthquakes which occurred in Tibet,China during the period of July 12 to August 25,2004 as an example,the paper analyses the Ms≥6.0 earthquakes that occurred in China and Ms≥7.0 earthquakes that occurred overseas since May of 2003 by combining the jmage data from the National Center for Environmental Prediction of America (NCEP) with the additive tectonic stress from astro-tidal-triggering (ATSA) and makes the following conclusions:The abnormal temperature image data of NCEP can better reflect the spatial-temporal evolution process of tectonic earthquake activity;The ATSA has an evident triggering effect on the activity of a fault when the terra stress is in critical status; using the NCEP images and the ATSA to forecast short-impending earthquake is a new concept:The three earthquakes occurred during the same phase of the respective ATSA cycle,i.e.that occurred at the time when the ATSA reached the relatively steady end of a peak,rather than at the time when the variation rate was maximal.In addition, the author discovered that the occurrence time of other earthquake cases during 2003~2004 in Tibet was also in the same phase of the above-mentioned cycles,and therefore,further study of this feature is needed with more earthquake eases in other areas over longer periods of time.

  10. Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

    Science.gov (United States)

    Chen, H.; Chandrasekar, V.; Biswas, S.

    2015-12-01

    Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X

  11. Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

    Science.gov (United States)

    Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

    2011-01-01

    A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

  12. Assessing Satellite-Based Fire Data for use in the National Emissions Inventory

    Science.gov (United States)

    Soja, Amber J.; Al-Saadi, Jassim; Giglio, Louis; Randall, Dave; Kittaka, Chieko; Pouliot, George; Kordzi, Joseph J.; Raffuse, Sean; Pace, Thompson G.; Pierce, Thomas E.; Moore, Tom; Biswadev, Roy; Pierce, R. Bradley; Szykman, James J.

    2009-01-01

    Biomass burning is significant to emission estimates because: (1) it can be a major contributor of particulate matter and other pollutants; (2) it is one of the most poorly documented of all sources; (3) it can adversely affect human health; and (4) it has been identified as a significant contributor to climate change through feedbacks with the radiation budget. Additionally, biomass burning can be a significant contributor to a regions inability to achieve the National Ambient Air Quality Standards for PM 2.5 and ozone, particularly on the top 20% worst air quality days. The United States does not have a standard methodology to track fire occurrence or area burned, which are essential components to estimating fire emissions. Satellite imagery is available almost instantaneously and has great potential to enhance emission estimates and their timeliness. This investigation compares satellite-derived fire data to ground-based data to assign statistical error and helps provide confidence in these data. The largest fires are identified by all satellites and their spatial domain is accurately sensed. MODIS provides enhanced spatial and temporal information, and GOES ABBA data are able to capture more small agricultural fires. A methodology is presented that combines these satellite data in Near-Real-Time to produce a product that captures 81 to 92% of the total area burned by wildfire, prescribed, agricultural and rangeland burning. Each satellite possesses distinct temporal and spatial capabilities that permit the detection of unique fires that could be omitted if using data from only one satellite.

  13. Code Tracking Algorithms for Mitigating Multipath Effects in Fading Channels for Satellite-Based Positioning

    Directory of Open Access Journals (Sweden)

    Markku Renfors

    2007-12-01

    Full Text Available The ever-increasing public interest in location and positioning services has originated a demand for higher performance global navigation satellite systems (GNSSs. In order to achieve this incremental performance, the estimation of line-of-sight (LOS delay with high accuracy is a prerequisite for all GNSSs. The delay lock loops (DLLs and their enhanced variants (i.e., feedback code tracking loops are the structures of choice for the commercial GNSS receivers, but their performance in severe multipath scenarios is still rather limited. In addition, the new satellite positioning system proposals specify the use of a new modulation, the binary offset carrier (BOC modulation, which triggers a new challenge in the code tracking stage. Therefore, in order to meet this emerging challenge and to improve the accuracy of the delay estimation in severe multipath scenarios, this paper analyzes feedback as well as feedforward code tracking algorithms and proposes the peak tracking (PT methods, which are combinations of both feedback and feedforward structures and utilize the inherent advantages of both structures. We propose and analyze here two variants of PT algorithm: PT with second-order differentiation (Diff2, and PT with Teager Kaiser (TK operator, which will be denoted herein as PT(Diff2 and PT(TK, respectively. In addition to the proposal of the PT methods, the authors propose also an improved early-late-slope (IELS multipath elimination technique which is shown to provide very good mean-time-to-lose-lock (MTLL performance. An implementation of a noncoherent multipath estimating delay locked loop (MEDLL structure is also presented. We also incorporate here an extensive review of the existing feedback and feedforward delay estimation algorithms for direct sequence code division multiple access (DS-CDMA signals in satellite fading channels, by taking into account the impact of binary phase shift keying (BPSK as well as the newly proposed BOC modulation

  14. Evaluation of Mid-Depth Currents of NCEP Reanalysis Data in the Tropical Pacific Using ARGO Float Position Information

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The global project of the Array for Real-time Geostrophic Oceanography (ARGO) provides a unique opportunity to observe the absolute velocity in mid-depths of the world oceans. A total of 1597 velocity vectors at 1000 (2000) db in the tropical Pacific derived from the ARGO float position information during the period November 2001 to October 2004 are used to evaluate the intermediate currents of the National Centers for Environmental Prediction reanalysis. To derive reliable velocity information from ARGO float trajectory points, a rigorous quality control scheme is applied, and by virtue of a correction method for reducing the drift error on the surface in obtaining the velocity vectors, their relative errors are less than 25%. Based on the comparisons from the quantitative velocity vectors and from the space-time average currents, some substantial discrepancies are revealed. The first is that the velocities of the reanalysis at mid-depths except near the equator are underestimated relative to the observed velocities by the floats.The average speed difference between NCEP and ARGO values ranges from about -2.3 cms-1 to -1.8cms-1. The second is that the velocity difference between the ocean model and the observations at 2000dB seems smaller than that at 1000 dB. The third is that the zonal flow in the reanalysis is too dominant so that some eddies could not be simulated, such as the cyclonic eddy to the east of 160°E between 20°N and 30°N at 2000 dB. In addition, it is noticeable that many floats parking at 1000 dB cannot acquire credible mid-depth velocities due to the time information of their end of ascent (start of descent) on the surface in the trajectory files. Thus, relying on default times of parking, descent and ascent in the metadata files gravely confines their application to measuring mid-depth currents.

  15. Satellites Based Annual Carbon Dynamics of Africa Tropical Vegetation During the 2003-2014 Period

    Science.gov (United States)

    Baccini, A.

    2015-12-01

    Tracking terrestrial carbon fluxes and predicting how tropical forests will respond to continuous global change requires accurate estimates of annual changes in the density and distribution of carbon stocks at local to global scales. Existing evidence for tropical forests as a carbon sink is based on a limited number of repeated field measurements (Phillips et al. 1998,Lewis et al. 2009, Brienen et al. 2015), while spatially explicit estimates over large areas are limited to emissions derived from deforestation without being able to account for degradation and gain (Harris et al. 2012, Hansen et al. 2013). Here we use 12 years (2003-2014) of satellite data to quantify wall-to-wall annual net changes in aboveground carbon density, showing that Africa tropical forests are a net carbon source on the order of 72.1 ± 32.9 Tg C yr-1. This net release of carbon consists of losses of 205.0 ± 24.7 Tg C yr1 and gains of -132.9 ± 19.3 Tg C yr1. The net gains result from forest growth; net losses result from both reductions in forest area due to deforestation and in biomass density within forests due to degradation; this last accounting overall for 68.9 % of the losses. We anticipate several advantages over the traditional estimates. It measures carbon lost from forest degradation as well as from deforestation. It measures the gains of carbon in forest growth. Data are available to determine annual changes with associated uncertainty. The approach focuses directly on changes in carbon. While global emissions from fossil fuel stabilized in 2014 for the first time in the past 40 years, results from this study indicate that the annual rate of emissions from tropical forests has tended upward over the latest years of the 2003-2014 period.

  16. Satellite Based Soil Moisture Product Validation Using NOAA-CREST Ground and L-Band Observations

    Science.gov (United States)

    Norouzi, H.; Campo, C.; Temimi, M.; Lakhankar, T.; Khanbilvardi, R.

    2015-12-01

    Soil moisture content is among most important physical parameters in hydrology, climate, and environmental studies. Many microwave-based satellite observations have been utilized to estimate this parameter. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is one of many remotely sensors that collects daily information of land surface soil moisture. However, many factors such as ancillary data and vegetation scattering can affect the signal and the estimation. Therefore, this information needs to be validated against some "ground-truth" observations. NOAA - Cooperative Remote Sensing and Technology (CREST) center at the City University of New York has a site located at Millbrook, NY with several insitu soil moisture probes and an L-Band radiometer similar to Soil Moisture Passive and Active (SMAP) one. This site is among SMAP Cal/Val sites. Soil moisture information was measured at seven different locations from 2012 to 2015. Hydra probes are used to measure six of these locations. This study utilizes the observations from insitu data and the L-Band radiometer close to ground (at 3 meters height) to validate and to compare soil moisture estimates from AMSR2. Analysis of the measurements and AMSR2 indicated a weak correlation with the hydra probes and a moderate correlation with Cosmic-ray Soil Moisture Observing System (COSMOS probes). Several differences including the differences between pixel size and point measurements can cause these discrepancies. Some interpolation techniques are used to expand point measurements from 6 locations to AMSR2 footprint. Finally, the effect of penetration depth in microwave signal and inconsistencies with other ancillary data such as skin temperature is investigated to provide a better understanding in the analysis. The results show that the retrieval algorithm of AMSR2 is appropriate under certain circumstances. This validation algorithm and similar study will be conducted for SMAP mission. Keywords: Remote Sensing, Soil

  17. Using NASA's Giovanni Web Portal to Access and Visualize Satellite-based Earth Science Data in the Classroom

    Science.gov (United States)

    Lloyd, Steven; Acker, James G.; Prados, Ana I.; Leptoukh, Gregory G.

    2008-01-01

    One of the biggest obstacles for the average Earth science student today is locating and obtaining satellite-based remote sensing data sets in a format that is accessible and optimal for their data analysis needs. At the Goddard Earth Sciences Data and Information Services Center (GES-DISC) alone, on the order of hundreds of Terabytes of data are available for distribution to scientists, students and the general public. The single biggest and time-consuming hurdle for most students when they begin their study of the various datasets is how to slog through this mountain of data to arrive at a properly sub-setted and manageable data set to answer their science question(s). The GES DISC provides a number of tools for data access and visualization, including the Google-like Mirador search engine and the powerful GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) web interface.

  18. Experimental free-space distribution of entangled photon pairs over 13 km: towards satellite-based global quantum communication.

    Science.gov (United States)

    Peng, Cheng-Zhi; Yang, Tao; Bao, Xiao-Hui; Zhang, Jun; Jin, Xian-Min; Feng, Fa-Yong; Yang, Bin; Yang, Jian; Yin, Juan; Zhang, Qiang; Li, Nan; Tian, Bao-Li; Pan, Jian-Wei

    2005-04-22

    We report free-space distribution of entangled photon pairs over a noisy ground atmosphere of 13 km. It is shown that the desired entanglement can still survive after both entangled photons have passed through the noisy ground atmosphere with a distance beyond the effective thickness of the aerosphere. This is confirmed by observing a spacelike separated violation of Bell inequality of 2.45+/-0.09. On this basis, we exploit the distributed entangled photon source to demonstrate the Bennett-Brassard 1984 quantum cryptography scheme. The distribution distance of entangled photon pairs achieved in the experiment is for the first time well beyond the effective thickness of the aerosphere, hence presenting a significant step towards satellite-based global quantum communication.

  19. Satellite-based measurements of surface deformation reveal fluid flow associated with the geological storage of carbon dioxide

    Energy Technology Data Exchange (ETDEWEB)

    Vasco, D.W.; Rucci, A.; Ferretti, A.; Novali, F.; Bissell, R.; Ringrose, P.; Mathieson, A.; Wright, I.

    2009-10-15

    Interferometric Synthetic Aperture Radar (InSAR), gathered over the In Salah CO{sub 2} storage project in Algeria, provides an early indication that satellite-based geodetic methods can be effective in monitoring the geological storage of carbon dioxide. An injected volume of 3 million tons of carbon dioxide, from one of the first large-scale carbon sequestration efforts, produces a measurable surface displacement of approximately 5 mm/year. Using geophysical inverse techniques we are able to infer flow within the reservoir layer and within a seismically detected fracture/ fault zone intersecting the reservoir. We find that, if we use the best available elastic Earth model, the fluid flow need only occur in the vicinity of the reservoir layer. However, flow associated with the injection of the carbon dioxide does appear to extend several kilometers laterally within the reservoir, following the fracture/fault zone.

  20. Validation and in vivo assessment of an innovative satellite-based solar UV dosimeter for a mobile app dedicated to skin health.

    Science.gov (United States)

    Morelli, M; Masini, A; Simeone, E; Khazova, M

    2016-09-31

    We present an innovative satellite-based solar UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in vivo assessment of the erythemal effects on some volunteers having controlled exposure to solar radiation. The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. Both validations showed that the system has a good accuracy and reliability needed for health-related applications. This app will be launched on the market by siHealth Ltd in May 2016 under the name of "HappySun" and is available for both Android and iOS devices (more info on ). Extensive R&D activities are on-going for the further improvement of the satellite-based UV dosimeter's accuracy.

  1. On the ability of RegCM4 to simulate surface solar radiation patterns over Europe: An assessment using satellite-based observations

    Science.gov (United States)

    Alexandri, Georgia; Georgoulias, Aristeidis K.; Zanis, Prodromos; Tsikerdekis, Athanasios; Katragkou, Eleni; Kourtidis, Konstantinos; Meleti, Charikleia

    2015-04-01

    We assess here the ability of RegCM4 to simulate the surface solar radiation (SSR) patterns over the European domain. For the needs of this work, a decadal (1999-2009) simulation was implemented at a horizontal resolution of 50km using the first year as a spin-up. The model is driven by emissions from CMIP5 while ERA-interim data were used as lateral boundary conditions. The RegCM4 SSR fields were validated against satellite-based SSR observations from Meteosat First Generation (MFG) and Meteosat Second Generation (MSG) sensors (CM SAF SIS product). The RegCM4 simulations slightly overestimate SSR compared to CM SAF over Europe with the bias being +1.54% in case of MFG (2000-2005) and +3.34% in case of MSG (2006-2009). SSR from RegCM4 is much closer to SSR from CM SAF over land (bias of -1.59% for MFG and +0.66% for MSG) than over ocean (bias of +7.20% for MFG and 8.07% for MSG). In order to understand the reasons of this bias, we proceeded to a detailed assessment of various parameters that define the SSR levels (cloud fractional cover - CFC, cloud optical thickness - COT, cloud droplet effective radius - Re, aerosol optical thickness - AOD, asymmetry factor - ASY, single scattering albedo - SSA, water vapor - WV and surface albedo - ALB). We validated the simulated CFC, COT and Re from RegCM4 against satellite-based observations from MSG and we found that RegCM4 significantly underestimates CFC and Re, and overestimates COT over Europe. The aerosol-related parameters from RegCM4 were compared with values from the aerosol climatology taken into account within CM SAF SSR estimates. AOD is significantly underestimated in our simulations which leads to a positive SSR bias. The RegCM4 WV and ALB were compared with WV values from ERA-interim and ALB climatological observations from CERES which are also taken into account within CM SAF SSR estimates. Finally, with the use of a radiative transfer model (SBDART) we manage to quantify the relative contribution of each of

  2. Satellite Based Assessment of Hydroclimatic Conditions Related to Cholera in Zimbabwe.

    Directory of Open Access Journals (Sweden)

    Antarpreet Jutla

    Full Text Available Cholera, an infectious diarrheal disease, has been shown to be associated with large scale hydroclimatic processes. The sudden and sporadic occurrence of epidemic cholera is linked with high mortality rates, in part, due to uncertainty in timing and location of outbreaks. Improved understanding of the relationship between pathogenic abundance and climatic processes allows prediction of disease outbreak to be an achievable goal. In this study, we show association of large scale hydroclimatic processes with the cholera epidemic in Zimbabwe reported to have begun in Chitungwiza, a city in Mashonaland East province, in August, 2008.Climatic factors in the region were found to be associated with triggering cholera outbreak and are shown to be related to anomalies of temperature and precipitation, validating the hypothesis that poor conditions of sanitation, coupled with elevated temperatures, and followed by heavy rainfall can initiate outbreaks of cholera. Spatial estimation by satellite of precipitation and global gridded air temperature captured sensitivities in hydroclimatic conditions that permitted identification of the location in the region where the disease outbreak began.Satellite derived hydroclimatic processes can be used to capture environmental conditions related to epidemic cholera, as occurred in Zimbabwe, thereby providing an early warning system. Since cholera cannot be eradicated because the causative agent, Vibrio cholerae, is autochthonous to the aquatic environment, prediction of conditions favorable for its growth and estimation of risks of triggering the disease in a given population can be used to alert responders, potentially decreasing infection and saving lives.

  3. Satellite Based Assessment of Hydroclimatic Conditions Related to Cholera in Zimbabwe.

    Science.gov (United States)

    Jutla, Antarpreet; Aldaach, Haidar; Billian, Hannah; Akanda, Ali; Huq, Anwar; Colwell, Rita

    2015-01-01

    Cholera, an infectious diarrheal disease, has been shown to be associated with large scale hydroclimatic processes. The sudden and sporadic occurrence of epidemic cholera is linked with high mortality rates, in part, due to uncertainty in timing and location of outbreaks. Improved understanding of the relationship between pathogenic abundance and climatic processes allows prediction of disease outbreak to be an achievable goal. In this study, we show association of large scale hydroclimatic processes with the cholera epidemic in Zimbabwe reported to have begun in Chitungwiza, a city in Mashonaland East province, in August, 2008. Climatic factors in the region were found to be associated with triggering cholera outbreak and are shown to be related to anomalies of temperature and precipitation, validating the hypothesis that poor conditions of sanitation, coupled with elevated temperatures, and followed by heavy rainfall can initiate outbreaks of cholera. Spatial estimation by satellite of precipitation and global gridded air temperature captured sensitivities in hydroclimatic conditions that permitted identification of the location in the region where the disease outbreak began. Satellite derived hydroclimatic processes can be used to capture environmental conditions related to epidemic cholera, as occurred in Zimbabwe, thereby providing an early warning system. Since cholera cannot be eradicated because the causative agent, Vibrio cholerae, is autochthonous to the aquatic environment, prediction of conditions favorable for its growth and estimation of risks of triggering the disease in a given population can be used to alert responders, potentially decreasing infection and saving lives.

  4. Satellite Based Assessment of Hydroclimatic Conditions Related to Cholera in Zimbabwe

    Science.gov (United States)

    Jutla, Antarpreet; Aldaach, Haidar; Billian, Hannah; Akanda, Ali; Huq, Anwar; Colwell, Rita

    2015-01-01

    Introduction Cholera, an infectious diarrheal disease, has been shown to be associated with large scale hydroclimatic processes. The sudden and sporadic occurrence of epidemic cholera is linked with high mortality rates, in part, due to uncertainty in timing and location of outbreaks. Improved understanding of the relationship between pathogenic abundance and climatic processes allows prediction of disease outbreak to be an achievable goal. In this study, we show association of large scale hydroclimatic processes with the cholera epidemic in Zimbabwe reported to have begun in Chitungwiza, a city in Mashonaland East province, in August, 2008. Principal Findings Climatic factors in the region were found to be associated with triggering cholera outbreak and are shown to be related to anomalies of temperature and precipitation, validating the hypothesis that poor conditions of sanitation, coupled with elevated temperatures, and followed by heavy rainfall can initiate outbreaks of cholera. Spatial estimation by satellite of precipitation and global gridded air temperature captured sensitivities in hydroclimatic conditions that permitted identification of the location in the region where the disease outbreak began. Discussion Satellite derived hydroclimatic processes can be used to capture environmental conditions related to epidemic cholera, as occurred in Zimbabwe, thereby providing an early warning system. Since cholera cannot be eradicated because the causative agent, Vibrio cholerae, is autochthonous to the aquatic environment, prediction of conditions favorable for its growth and estimation of risks of triggering the disease in a given population can be used to alert responders, potentially decreasing infection and saving lives. PMID:26417994

  5. Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

    Directory of Open Access Journals (Sweden)

    Wenwen Cai

    2014-09-01

    Full Text Available Terrestrial gross primary production (GPP is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000–2010 varied from 95.10 to 139.71 Pg C∙yr−1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.

  6. Using long-term daily satellite based rainfall data (1983-2015) to analyze spatio-temporal changes in the sahelian rainfall regime

    Science.gov (United States)

    Zhang, Wenmin; Brandt, Martin; Guichard, Francoise; Tian, Qingjiu; Fensholt, Rasmus

    2017-07-01

    The sahelian rainfall regime is characterized by a strong spatial as well as intra- and inter-annual variability. The satellite based African Rainfall Climatology Version 2 (ARC2) daily gridded rainfall estimates with a 0.1° × 0.1° spatial resolution provides the possibility for in-depth studies of seasonal changes over a 33-year period (1983-2015). Here we analyze rainfall regime variables that require daily observations: onset, cessation, and length of the wet season; seasonal rainfall amount; number of rainy days; intensity and frequency of rainfall events; number, length, and cumulative duration of dry spells. Rain gauge stations and MSWEP (Multi-Source Weighted-Ensemble Precipitation) data were used to evaluate the agreement of rainfall variables in both space and time, and trends were analyzed. Overall, ARC2 rainfall variables reliably show the spatio-temporal dynamics of seasonal rainfall over 33 years when compared to gauge and MSWEP data. However, a higher frequency of low rainfall events (spell characteristics). Most rainfall variables (both ARC2 and gauge data) show negative anomalies (except for onset of rainy season) from 1983 until the end of the 1990s, from which anomalies become mostly positive and inter-annual variability is higher. ARC2 data show a strong increase in seasonal rainfall, wet season length (caused by both earlier onset and a late end), number of rainy days, and high rainfall events (>20 mm day-1) for the western/central Sahel over the period of analysis, whereas the opposite trend characterizes the eastern part of the Sahel.

  7. Towards a satellite based system for monitoring agricultural water use: A case study for Saudi Arabia

    KAUST Repository

    McCabe, Matthew

    2015-11-12

    Over the last few decades, the Kingdom of Saudi Arabia (KSA) has witnessed a dramatic expansion of its agricultural sector. In common with many other developing countries, this has been driven by a combination of population increases and the related effects on consumption as well as a demand for increased food security. Inevitably, the sector growth has come at the expense of a parallel increase in water consumption. Indeed, it is estimated that more than 80% of all of the water used in the Kingdom relates to agricultural production. More concerning is that the vast majority of this water is derived from non-renewable fossil groundwater extraction. To exacerbate the problem, groundwater extraction is largely unmonitored, meaning that there is very little accounting of water use on a routine basis. In the absence of techniques to directly quantify abstractions related to agriculture at large spatial scales, a mechanism for inferring crop water use as an indirect surrogate is required.

  8. Satellite-based retrieval of particulate matter concentrations over the United Arab Emirates (UAE)

    Science.gov (United States)

    Zhao, Jun; Temimi, Marouane; Hareb, Fahad; Eibedingil, Iyasu

    2016-04-01

    In this study, an empirical algorithm was established to retrieve particulate matter (PM) concentrations (PM2.5 and PM10) using satellite-derived aerosol optical depth (AOD) over the United Arab Emirates (UAE). Validation of the proposed algorithm using ground truth data demonstrates its good accuracy. Time series of in situ measured PM concentrations between 2014 and 2015 showed high values in summer and low values in winter. Estimated and in situ measured PM concentrations were higher in 2015 than 2014. Remote sensing is an essential tool to reveal and back track the seasonality and inter-annual variations of PM concentrations and provide valuable information on the protection of human health and the response of air quality to anthropogenic activities and climate change.

  9. Multiple-Symbol combined differential detection for satellite-based AIS Signals

    Science.gov (United States)

    Hao, Jingsong; Ma, Shexiang; Wang, Junfeng; Meng, Xin

    2015-12-01

    In this paper, a multiple-symbol combined differential Viterbi decoding algorithm which is insensitive to frequency offset is proposed. According to the theories of multiple-symbol differential detection and maximum-likelihood detection, we combine the multiple-order differential information with the Viterbi algorithm. The phase shift caused by the frequency offset is estimated and compensated from the above information in the process of decoding. The simulation results show that the bit error rate (BER) of 2 bits combined differential Viterbi algorithm is below 10-3 when the normalized signal-to-noise ratio (NSNR) is 11 dB, and the decoding performances approach those of the coherent detection as the length of the combined differential symbols increases. The proposed method is simple and its performance remains stable under different frequency offsets.

  10. Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

    Science.gov (United States)

    Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

    2014-12-01

    The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are

  11. Satellite Based Probabilistic Snow Cover Extent Mapping (SCE) at Hydro-Québec

    Science.gov (United States)

    Teasdale, Mylène; De Sève, Danielle; Angers, Jean-François; Perreault, Luc

    2016-04-01

    Over 40% of Canada's water resources are in Quebec and Hydro-Quebec has developed potential to become one of the largest producers of hydroelectricity in the world, with a total installed capacity of 36,643 MW. The Hydro-Québec fleet park includes 27 large reservoirs with a combined storage capacity of 176 TWh, and 668 dams and 98 controls. Thus, over 98% of all electricity used to supply the domestic market comes from water resources and the excess output is sold on the wholesale markets. In this perspective the efficient management of water resources is needed and it is based primarily on a good river flow estimation including appropriate hydrological data. Snow on ground is one of the significant variables representing 30% to 40% of its annual energy reserve. More specifically, information on snow cover extent (SCE) and snow water equivalent (SWE) is crucial for hydrological forecasting, particularly in northern regions since the snowmelt provides the water that fills the reservoirs and is subsequently used for hydropower generation. For several years Hydro Quebec's research institute ( IREQ) developed several algorithms to map SCE and SWE. So far all the methods were deterministic. However, given the need to maximize the efficient use of all resources while ensuring reliability, the electrical systems must now be managed taking into account all risks. Since snow cover estimation is based on limited spatial information, it is important to quantify and handle its uncertainty in the hydrological forecasting system. This paper presents the first results of a probabilistic algorithm for mapping SCE by combining Bayesian mixture of probability distributions and multiple logistic regression models applied to passive microwave data. This approach allows assigning for each grid point, probabilities to the set of the mutually exclusive discrete outcomes: "snow" and "no snow". Its performance was evaluated using the Brier score since it is particularly appropriate to

  12. Evaluation of the hydrological cycle of MATCH driven by NCEP reanalysis data: comparison with GOME water vapor measurements

    Directory of Open Access Journals (Sweden)

    R. Lang

    2005-01-01

    Full Text Available This study examines two key parameters of the hydrological cycle, water vapor (WV and precipitation rates (PR, as modelled by the chemistry transport model MATCH (Model of Atmospheric Transport and Chemistry driven by National Centers for Environmental Prediction (NCEP reanalysis data (NRA. For model output evaluation we primarily employ WV total column data from the Global Ozone Monitoring Experiment (GOME on ERS-2, which is the only instrument capable measuring WV on a global scale and over all surface types with a substantial data record from 1995 to the present. We find that MATCH and NRA WV and PR distributions are closely related, but that significant regional differences in both parameters exist in magnitude and distribution patterns when compared to the observations. We also find that WV residual patterns between model and observations show remarkable similarities to residuals observed in the PR when comparing MATCH and NRA output to observations comprised by the Global Precipitation Climatology Project (GPCP. We conclude that deficiencies in model parameters shared by MATCH and NRA, like in the surface evaporation rates and regional transport patterns, are likely to lead to the observed differences. Monthly average regional differences between MATCH modelled WV columns and the observations can be as large as 2 cm, based on the analysis of three years. Differences in the global mean WV values are, however, below 0.1 cm. Regional differences in the PR between MATCH and GPCP can be above 0.5 cm per day and MATCH computes on average a higher PR than what has been observed. The lower water vapor content of MATCH is related to shorter model WV residence times by up to 1 day as compared to the observations. We find that MATCH has problems in modelling the WV content in regions of strong upward convection like, for example, along the Inter Tropical Convergence Zone, where it appears to be generally too dry as compared to the observations. We

  13. Systematic Evaluation of Satellite-Based Rainfall Products over the Brahmaputra Basin for Hydrological Applications

    Directory of Open Access Journals (Sweden)

    Sagar Ratna Bajracharya

    2015-01-01

    Full Text Available Estimation of the flow generated in the Brahmaputra river basin is important for establishing an effective flood prediction and warning services as well as for water resources assessment and management. But this is a data scarce region with few and unevenly distributed hydrometeorological stations. Five high-resolution satellite rainfall products (CPC RFE2.0, RFE2.0-Modified, CMORPH, GSMaP, and TRMM 3B42 were evaluated at different spatial and temporal resolutions (daily, dekadal, monthly, and seasonal with observed rain gauge data from 2004 to 2006 to determine their ability to fill the data gap and suitability for use in hydrological and water resources management applications. Grid-to-grid (G-G and catchment-to-catchment (C-C comparisons were performed using the verification methods developed by the International Precipitation Working Group (IPWG. Comparing different products, RFE2.0-Modified, TRMM 3B42, and CMORPH performed best; they all detected heavy, moderate, and low rainfall but still significantly underestimated magnitude of rainfall, particularly in orographically influenced areas. Overall, RFE2.0-Modified performed best showing a high correlation coefficient with observed data and low mean absolute error, root mean square error, and multiple bias and is reasonably good at detecting the occurrence of rainfall. TRMM 3B42 showed the second best performance. The study demonstrates that there is a potential use of satellite rainfall in a data scarce region.

  14. NOAA NESDIS global automated satellite-based snow mapping system and products

    Science.gov (United States)

    Romanov, Peter

    2016-05-01

    Accurate, timely and spatially detailed information on the snow cover distribution and on the snow pack properties is needed in various research and practical applications including numerical weather prediction, climate modeling, river runoff estimates and flood forecasts. Owing to the wide area coverage, high spatial resolution and short repeat cycle of observations satellites present one of the key components of the global snow and ice cover monitoring system. The Global Multisensor Automated Snow and Ice Mapping System (GMASI) has been developed at the request of NOAA National Weather Service (NWS) and NOAA National Ice Center (NIC) to facilitate NOAA operational monitoring of snow and ice cover and to provide information on snow and ice for use in NWP models. Since 2006 the system has been routinely generating daily snow and ice cover maps using combined observations in the visible/infrared and in the microwave from operational meteorological satellites. The output product provides continuous (gap free) characterization of the global snow and ice cover distribution at 4 km spatial resolution. The paper presents a basic description of the snow and ice mapping algorithms incorporated in the system as well as of the product generated with GMASI. It explains the approach used to validate the derived snow and ice maps and provides the results of their accuracy assessment.

  15. Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Singaiah Chintalapudi

    2014-05-01

    Full Text Available In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.

  16. GNSS Carrier Phase-based Attitude Determination: Estimation and Applications

    NARCIS (Netherlands)

    Giorgi, G.

    2011-01-01

    Attitude determination through the use of Global Navigation Satellite System (GNSS) signals is one of the many applications of satellite-based navigation. Multiple GNSS antennas installed on a given platform are used to provide orientation estimates, thus adding attitude information to the standard

  17. GNSS Carrier Phase-based Attitude Determination: Estimation and Applications

    NARCIS (Netherlands)

    Giorgi, G.

    2011-01-01

    Attitude determination through the use of Global Navigation Satellite System (GNSS) signals is one of the many applications of satellite-based navigation. Multiple GNSS antennas installed on a given platform are used to provide orientation estimates, thus adding attitude information to the standard

  18. Satellite-based monitoring of grassland: assessment of harvest dates and frequency using SAR

    Science.gov (United States)

    Siegmund, R.; Grant, K.; Wagner, M.; Hartmann, S.

    2016-10-01

    Grasslands are among the largest ecosystems worldwide and according to the FAO they contribute to the livelihoods of more than 800 million people. Harvest dates and frequency can be utilised for an improved estimation of grassland yields. In the presented project a highly automatised methodology for detecting harvest dates and frequency using SARamplitude data was developed based on an amplitude change detection techniques. This was achieved by evaluating spatial statistics over field boundaries provided by the European Integrated Administration and Control System (IACS) to identify changes between pre- and post-harvest acquisitions. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. In our contribution we will focus on SAR-remote sensing for monitoring harvest frequencies, discuss the requirements concerning the acquisition system, present the technical approach and analyse the verified results. In terms of the acquisition system a high temporal acquisition rate is required, which is generally met by using SARsatellite constellations providing a revisit time of few days. COSMO-SkyMed data were utilised for the pilot study for developing and prototyping a monitoring system. Subsequently the approach was adapted to the use of the C-Band system Sentinel-1A becoming fully operational with the availability of Sentinal-1B. The study area is situated northeast of Munich, Germany, extending to an area of approx. 40km to 40km and covering major verification sites and in-situ data provided by research farms or continuously surveyed in-situ campaigns. An extended time series of SAR data was collected during the cultivation and vegetation cycles between March 2014 and March 2016. All data were processed and harmonised in a GIS database to be analysed and verified according to corresponding in-situ data.

  19. Satellite-based Dust Source Identification over North Africa: Diurnal Cycle, Meteorological Controls, and Interannual Variability

    Science.gov (United States)

    Schepanski, Kerstin; Tegen, Ina; Macke, Andreas

    2010-05-01

    Mineral dust aerosol emitted from arid and semi-arid areas impacts on the weather and climate system by affecting e.g. radiation fluxes and nutrient cycles. To estimate the effect of dust aerosol, detailed knowledge on the spatio-temporal distribution of active dust sources is necessary. For a better representation of dust-related processes in numerical models and climate change projections the knowledge on the natural variability of dust source activity has to be improved. As dust sources are mostly located over remote areas satellite observations are suitable for identifying active dust sources. The accuracy of dust source identification using such an indirect method is limited by the temporal resolution and the ambiguities of the retrieval. Here, a data set on the spatial (1°x1°) and temporal (3-hourly) distribution of dust source activations (DSA) over North Africa is compiled by analyzing 15-minute Meteosat Second Generation (MSG) infra-red (IR) dust index images since March 2006. The index is designed using radiances measured by the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board MSG at 8.7 µm, 10.8 µm and 12.0 µm which are converted to brightness temperatures (BTs). To strengthen the dust signal, differences of BTs are used to compute RGB-composite images. This newly data set providing information on the diurnal cycle of dust emission has been used (1) to identify most active dust source areas, and (2) to investigate on the temporal distribution of DSAs. Over the Sahara Desert 65% of dust sources become active during 06-09 UTC pointing towards an important role of the break-down of the nocturnal low-level jet (LLJ) for dust mobilization besides other meteorological features like density currents, haboobs, and cyclones. Furthermore the role of the nocturnal LLJs for dust mobilization over the Sahara is investigated by weather observations and a regional modeling study. Four years of DSA observations indicate an interannual variability in

  20. Using NASA's Giovanni Web Portal to Access and Visualize Satellite-Based Earth Science Data in the Classroom

    Science.gov (United States)

    Lloyd, S. A.; Acker, J. G.; Prados, A. I.; Leptoukh, G. G.

    2008-12-01

    One of the biggest obstacles for the average Earth science student today is locating and obtaining satellite- based remote sensing datasets in a format that is accessible and optimal for their data analysis needs. At the Goddard Earth Sciences Data and Information Services Center (GES-DISC) alone, on the order of hundreds of Terabytes of data are available for distribution to scientists, students and the general public. The single biggest and time-consuming hurdle for most students when they begin their study of the various datasets is how to slog through this mountain of data to arrive at a properly sub-setted and manageable dataset to answer their science question(s). The GES DISC provides a number of tools for data access and visualization, including the Google-like Mirador search engine and the powerful GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) web interface. Giovanni provides a simple way to visualize, analyze and access vast amounts of satellite-based Earth science data. Giovanni's features and practical examples of its use will be demonstrated, with an emphasis on how satellite remote sensing can help students understand recent events in the atmosphere and biosphere. Giovanni is actually a series of sixteen similar web-based data interfaces, each of which covers a single satellite dataset (such as TRMM, TOMS, OMI, AIRS, MLS, HALOE, etc.) or a group of related datasets (such as MODIS and MISR for aerosols, SeaWIFS and MODIS for ocean color, and the suite of A-Train observations co-located along the CloudSat orbital path). Recently, ground-based datasets have been included in Giovanni, including the Northern Eurasian Earth Science Partnership Initiative (NEESPI), and EPA fine particulate matter (PM2.5) for air quality. Model data such as the Goddard GOCART model and MERRA meteorological reanalyses (in process) are being increasingly incorporated into Giovanni to facilitate model- data intercomparison. A full suite of data

  1. Sensitivity of Simulated Global Ocean Carbon Flux Estimates to Forcing by Reanalysis Products

    Science.gov (United States)

    Gregg, Watson W.; Casey, Nancy W.; Rousseaux, Cecile S.

    2015-01-01

    Reanalysis products from MERRA, NCEP2, NCEP1, and ECMWF were used to force an established ocean biogeochemical model to estimate air-sea carbon fluxes (FCO2) and partial pressure of carbon dioxide (pCO2) in the global oceans. Global air-sea carbon fluxes and pCO2 were relatively insensitive to the choice of forcing reanalysis. All global FCO2 estimates from the model forced by the four different reanalyses were within 20% of in situ estimates (MERRA and NCEP1 were within 7%), and all models exhibited statistically significant positive correlations with in situ estimates across the 12 major oceanographic basins. Global pCO2 estimates were within 1% of in situ estimates with ECMWF being the outlier at 0.6%. Basin correlations were similar to FCO2. There were, however, substantial departures among basin estimates from the different reanalysis forcings. The high latitudes and tropics had the largest ranges in estimated fluxes among the reanalyses. Regional pCO2 differences among the reanalysis forcings were muted relative to the FCO2 results. No individual reanalysis was uniformly better or worse in the major oceanographic basins. The results provide information on the characterization of uncertainty in ocean carbon models due to choice of reanalysis forcing.

  2. The Correlation Between Atmospheric Dust Deposition to the Surface Ocean and SeaWiFS Ocean Color: A Global Satellite-Based Analysis

    Science.gov (United States)

    Erickson, D. J., III; Hernandez, J.; Ginoux, P.; Gregg, W.; Kawa, R.; Behrenfeld, M.; Esaias, W.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    Since the atmospheric deposition of iron has been linked to primary productivity in various oceanic regions, we have conducted an objective study of the correlation of dust deposition and satellite remotely sensed surface ocean chlorophyll concentrations. We present a global analysis of the correlation between atmospheric dust deposition derived from a satellite-based 3-D atmospheric transport model and SeaWiFs estimates of ocean color. We use the monthly mean dust deposition fields of Ginoux et al. which are based on a global model of dust generation and transport. This model is driven by atmospheric circulation from the Data Assimilation Office (DAO) for the period 1995-1998. This global dust model is constrained by several satellite estimates of standard circulation characteristics. We then perform an analysis of the correlation between the dust deposition and the 1998 SeaWIFS ocean color data for each 2.0 deg x 2.5 deg lat/long grid point, for each month of the year. The results are surprisingly robust. The region between 40 S and 60 S has correlation coefficients from 0.6 to 0.95, statistically significant at the 0.05 level. There are swaths of high correlation at the edges of some major ocean current systems. We interpret these correlations as reflecting areas that have shear related turbulence bringing nitrogen and phosphorus from depth into the surface ocean, and the atmospheric supply of iron provides the limiting nutrient and the correlation between iron deposition and surface ocean chlorophyll is high. There is a region in the western North Pacific with high correlation, reflecting the input of Asian dust to that region. The southern hemisphere has an average correlation coefficient of 0.72 compared that in the northern hemisphere of 0.42 consistent with present conceptual models of where atmospheric iron deposition may play a role in surface ocean biogeochemical cycles. The spatial structure of the correlation fields will be discussed within the context

  3. Land-use regression with long-term satellite-based greenness index and culture-specific sources to model PM2.5 spatial-temporal variability.

    Science.gov (United States)

    Wu, Chih-Da; Chen, Yu-Cheng; Pan, Wen-Chi; Zeng, Yu-Ting; Chen, Mu-Jean; Guo, Yue Leon; Lung, Shih-Chun Candice

    2017-05-01

    This study utilized a long-term satellite-based vegetation index, and considered culture-specific emission sources (temples and Chinese restaurants) with Land-use Regression (LUR) modelling to estimate the spatial-temporal variability of PM2.5 using data from Taipei metropolis, which exhibits typical Asian city characteristics. Annual average PM2.5 concentrations from 2006 to 2012 of 17 air quality monitoring stations established by Environmental Protection Administration of Taiwan were used for model development. PM2.5 measurements from 2013 were used for external data verification. Monthly Normalized Difference Vegetation Index (NDVI) images coupled with buffer analysis were used to assess the spatial-temporal variations of greenness surrounding the monitoring sites. The distribution of temples and Chinese restaurants were included to represent the emission contributions from incense and joss money burning, and gas cooking, respectively. Spearman correlation coefficient and stepwise regression were used for LUR model development, and 10-fold cross-validation and external data verification were applied to verify the model reliability. The results showed a strongly negative correlation (r: -0.71 to -0.77) between NDVI and PM2.5 while temples (r: 0.52 to 0.66) and Chinese restaurants (r: 0.31 to 0.44) were positively correlated to PM2.5 concentrations. With the adjusted model R(2) of 0.89, a cross-validated adj-R(2) of 0.90, and external validated R(2) of 0.83, the high explanatory power of the resultant model was confirmed. Moreover, the averaged NDVI within a 1750 m circular buffer (p < 0.01), the number of Chinese restaurants within a 1750 m buffer (p < 0.01), and the number of temples within a 750 m buffer (p = 0.06) were selected as important predictors during the stepwise selection procedures. According to the partial R(2), NDVI explained 66% of PM2.5 variation and was the dominant variable in the developed model. We suggest future studies consider

  4. On the balance of precipitation and evaporation over global oceans in satellite based and reanalysis data sets

    Science.gov (United States)

    Bakan, S.; Andersson, A.; Fennig, K.; Klepp, C.; Klocke, D.; Schulz, J.

    2009-04-01

    Over the global oceans, precipitation should be smaller than evaporation and the balance should be compensated by the global runoff from land surfaces. But to which extent do satellite climatologies and reanalysis products reproduce this basic feature of the global water cycle? The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data set, HOAPS-3 (www.hoaps.org), contains fields of precipitation and evaporation over the global ocean and all basic state variables needed for the derivation of the fluxes. Except for the NOAA Pathfinder SST data set, all variables are derived from SSM/I satellite data over the ice free global ocean between 1987 and 2005. Special emphasis has been put into quality control and inter-satellite calibration in order to derive the data fields as homogeneous as possible. One of the major design goals of HOAPS was to provide a data set that is based exclusively on retrieval procedures which avoid any additional model or reanalysis input. On a global scale, the average evaporation since 1987 exceeds precipitation rate over the oceans in HOAPS-3 systematically, with almost negligible yearly cycle and small monthly variations. While the globally averaged precipitation time series does not exhibit any significant trend over the study period, evaporation shows a continuous increase during this time. Regionally, this increase concentrates in the subtropics and is, together with some reduction in precipitation, consistent with a strengthening of the Hadley circulation during the observation period. These results are compared with similar data fields of the same period from various satellite climatologies to insure the consistency of our results and to the NCEP and ERA40 as well as ERAInterim reanalysis products. Remarkable similarities and differences between the different information sources have been found and will be discussed in the presentation.

  5. NCEP/NCAR 再分析资料在喜马拉雅山-青藏高原气象研究中的可行性分析%Reliability of NCEP/NCAR reanalysis data in the Himalayas/Tibetan Plateau

    Institute of Scientific and Technical Information of China (English)

    谢爱红; 任贾文; 秦翔; 康世昌

    2007-01-01

    Due to the difficult logistics in the extreme high elevation regions over the Himalayas and Tibetan Plateau, the observational meteorological data are very few. In 2003, an automatic weather station was deployed at the northeastern saddle of Mt. Nyainqentanglha (NQ) (30°24′44.3″ N, 90°34′13.1″ E, 5850 m a.s.l.), the southern Tibetan Plateau. In 2005, another station was operated at the East Rongbuk Glacier Col (28°01′0.95″ N, 86°57′48.4″ E, 6523 m a.s.l.) of Mt. Qomolangma. Observational data from the two sites have been compared with the reanalysis data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), reliability of NCEP/NCAR reanalysis data has been investigated in the Himalayas/Tibetan Plateau region. The reanalysis data can capture much of the synoptic-scale variability in temperature and pressure, although the reanalysis values are systematically lower than the observation. Furthermore, most of the variability magnitude is, to some degree, underestimated. In addition, the weather event extracted from the NCEP/NCAR reanalyzed pressure and temperature prominently appears one day ahead of the observational data on Mt. Qomolangma, while on Mt. NQ it occurs basically in the same day.

  6. Constraints from atmospheric CO2 and satellite-based vegetation activity observations on current land carbon cycle trends

    Directory of Open Access Journals (Sweden)

    S. Zaehle

    2012-11-01

    Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to achieve a better understanding of the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely-sensed vegetation activity to provide a firm set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits specifically considers the robustness of information given the uncertainties in both data and evaluation analysis. In addition, we provide a baseline benchmark, a minimum test that the model under consideration has to pass, to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI-Earth system model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite based vegetation activity data allows to pinpoint specific model failures that would not be possible by the sole use of atmospheric CO2 observations.

  7. The Evolution of Operational Satellite Based Remote Sensing in Support of Weather Analysis, Nowcasting, and Hazard Mitigation

    Science.gov (United States)

    Hughes, B. K.

    2010-12-01

    The mission of the National Oceanic and Atmospheric Administration (NOAA) National Environmental Data Information Service (NESDIS) is to provide timely access to global environmental data from satellites and other sources to promote, protect, and enhance America’s economy, security, environment, and quality of life. To fulfill its responsibilities, NESDIS acquires and manages America’s operational environmental satellites, operates the NOAA National Data Centers, provides data and information services including Earth system monitoring, performs official assessments of the environment, and conducts related research. The Nation’s fleet of operational environmental satellites has proven to be very critical in the detection, analysis, and forecast of natural or man-made phenomena. These assets have provided for the protection of people and property while safeguarding the Nation’s commerce and enabling safe and effective military operations. This presentation will take the audience through the evolution of operational satellite based remote sensing in support of weather forecasting, nowcasting, warning operations, hazard detection and mitigation. From the very first experiments involving radiation budget to today’s fleet of Geostationary and Polar Orbiting satellites to tomorrow’s constellation of high resolution imagers and hyperspectral sounders, environmental satellites sustain key observations for current and future generations.

  8. Assessment of the aerosol optical depths measured by satellite-based passive remote sensors in the Alberta oil sands region

    Science.gov (United States)

    Sioris, Christopher E.; McLinden, Chris A.; Shephard, Mark W.; Fioletov, Vitali E.; Abboud, Ihab

    2017-02-01

    Several satellite aerosol optical depth (AOD) products are assessed in terms of their data quality in the Alberta oil sands region. The instruments consist of MODIS (Moderate Resolution Imaging Spectroradiometer), POLDER (Polarization and Directionality of Earth Reflectances), MISR (Multi-angle Imaging SpectroRadiometer), and AATSR (Advanced Along-Track Scanning Radiometer). The AOD data products are examined in terms of multiplicative and additive biases determined using local Aerosol Robotic Network (AERONET) (AEROCAN) stations. Correlation with ground-based data is used to assess whether the satellite-based AODs capture day-to-day, month-to-month, and spatial variability. The ability of the satellite AOD products to capture interannual variability is assessed at Albian mine and Shell Muskeg River, two neighbouring sites in the northern mining region where a statistically significant positive trend (2002-2015) in PM2.5 mass density exists. An increasing trend of similar amplitude (˜ 5 % year-1) is observed in this northern mining region using some of the satellite AOD products.

  9. Evaporation-precipitation variability over Indian Ocean and its assessment in NCEP Climate Forecast System (CFSv2)

    Energy Technology Data Exchange (ETDEWEB)

    Pokhrel, Samir; Parekh, Anant; Saha, Subodh Kumar; Dhakate, Ashish; Chaudhari, Hemantkumar S. [Indian Institute of Tropical Meteorology, Pune (India); Rahaman, Hasibur [Indian National Centre for Ocean Information Services, Hyderabad (India); Gairola, Rakesh Mohan [Space Applications Centre, ISRO, Ahmedabad (India)

    2012-11-15

    An attempt has been made to explore all the facets of Evaporation-Precipitation (E-P) distribution and variability over the Indian Ocean (IO) basin using Objectively Analyzed air-sea Fluxes (OAFlux) data and subsequently a thorough assessment of the latest version of National Centers for Environment Prediction (NCEP) Climate Forecast System (CFS) version-2 is done. This study primarily focuses on two fundamental issues, first, the core issue of pervasive cold SST bias in the CFS simulation in the context of moisture flux exchange between the atmosphere and the ocean and second, the fidelity of the model in simulating mean and variability of E-P and its elemental components associated with the climatic anomalies occurring over the Indian and the Pacific ocean basin. Valuation of evaporation and precipitation, the two integral component of E-P, along with the similar details of wind speed, air-sea humidity difference ({Delta}Q) and Sea Surface Temperature (SST) are performed. CFS simulation is vitiated by the presence of basin wide systematic positive bias in evaporation, {Delta}Q and similar negative bias in wind speed and SST. Bifurcation of the evaporation bias into its components reveals that bias in air humidity (Q{sub a}) is basically responsible for the presence of pervasive positive evaporation bias. The regions where CFS does not adhere to the observed wind-evaporation and Q{sub a} -evaporation relation was found to lie over the northern Arabian Sea (AS), the western Bay of Bengal (BoB) and the western Equatorial IO. Evaporation bias is found to control a significant quantum of cold SST bias over most of the basin owing to its intimate association with SST in a coupled feedback system. This area is stretched over the almost entire north IO, north of 15 {sup circle} S excluding a small equatorial strip, where the evaporation bias may essentially explain 20-100 % of cold SST bias. This percentage is maximum over the western IO, central AS and BoB. The CFS

  10. Sub-Seasonal Prediction of the Maritime Continent Rainfall of Wet-Dry Transitional Seasons in the NCEP Climate Forecast Version 2

    Directory of Open Access Journals (Sweden)

    Tuantuan Zhang

    2016-02-01

    Full Text Available This study investigates the characteristics and prediction of the Maritime Continent (MC rainfall for the transitional periods between wet and dry seasons. Several observational data sets and the output from the 45-day hindcast by the U.S. National Centers for Environmental Prediction (NCEP Climate Forecast System version 2 (CFSv2 are used. Results show that the MC experiences a sudden transition from wet season to dry season (WTD around the 27th pentad, and a gradual transition from dry season to wet season (DTW around the 59th pentad. Correspondingly, the westerlies over the equatorial Indian Ocean, the easterlies over the equatorial Pacific Ocean, and the Australia High become weaker, contributing to weakening of the convergence over the MC. The subtropical western Pacific high intensifies and extends northeastward during the WTD. The Mascarene High becomes weaker, an anomalous anticyclonic circulation forms over the northeast of the Philippines, and an anomalous low-level convergence occurs over the western MC during the DTW. The NCEP CFSv2 captures the major features of rainfall and related atmospheric circulation when forecast lead time is less than three weeks for WTD and two weeks for DTW. The model predicts a weaker amplitude of the changes in rainfall and related atmospheric circulation for both WTD and DTW as lead time increases.

  11. Sensitivity of Satellite-Based Skin Temperature to Different Surface Emissivity and NWP Reanalysis Sources Demonstrated Using a Single-Channel, Viewing-Angle-Corrected Retrieval Algorithm

    Science.gov (United States)

    Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.

    2015-12-01

    station, and NOAA ESRL high-resolution Optimum Interpolation SST (OISST). Precise understanding of the influence these auxiliary inputs have on final satellite-based Ts retrievals may help guide refinement in ɛs characterization and NWP development, e.g., future Goddard Earth Observing System Data Assimilation System versions.

  12. The Multi-Angle Imager for Aerosols (MAIA) Instrument, the Satellite-Based Element of an Investigation to Benefit Public Health

    Science.gov (United States)

    Diner, D. J.

    2016-12-01

    Maps of airborne particulate matter (PM) derived from satellite instruments, including MISR and MODIS, have provided key contributions to many health-related investigations. Although it is well established that PM exposure increases the risks of cardiovascular and respiratory disease, adverse birth outcomes, and premature deaths, our understanding of the relative toxicity of specific PM types—mixtures having different size distributions and compositions—is relatively poor. To address this, the Multi-Angle Imager for Aerosols (MAIA) investigation was proposed to NASA's third Earth Venture Instrument (EVI-3) solicitation. MAIA was selected for funding in March 2016. The satellite-based MAIA instrument is one element of the scientific investigation, which will combine WRF-Chem transport model estimates of the abundances of different aerosol types with the data acquired from Earth orbit. Geostatistical models derived from collocated surface and MAIA retrievals will be used to relate retrieved fractional column aerosol optical depths to near-surface concentrations of major PM constituents. Epidemiological analyses of geocoded birth, death, and hospital records will be used to associate exposure to PM types with adverse health outcomes. The MAIA instrument obtains its sensitivity to particle type by building upon the legacies of many satellite sensors; observing in the UV, visible, near-IR, and shortwave-IR regions of the electromagnetic spectrum; acquiring images at multiple angles of view; determining the degree to which the scattered light is polarized; and integrating these capabilities at moderately high spatial resolution. The instrument concept is based on the first and second generation Airborne Multiangle SpectroPolarimetric Imagers, AirMSPI and AirMSPI-2. MAIA incorporates a pair of pushbroom cameras on a two-axis gimbal to provide regional multiangle observations of selected, globally distributed target areas. A set of Primary Target Areas (PTAs) on five

  13. An Evaluation of Satellite-Based and Re-Analysis Radiation Budget Datasets Using CERES EBAF Products

    Science.gov (United States)

    Gupta, Shashi; Stackhouse, Paul; Wong, Takmeng; Mikovitz, Colleen; Cox, Stephen; Zhang, Taiping

    2016-04-01

    Top-of-atmosphere (TOA) and surface radiative fluxes from CERES Energy Balanced and Filled (EBAF; Loeb et al., 2009; Kato et al. 2013) products are used to evaluate the performance of several widely used long-term radiation budget datasets. Two of those are derived from satellite observations and five more are from re-analysis products. Satellite-derived datasets are the NASA/GEWEX Surface and TOA Radiation Budget Dataset Release-3 and the ISCCP-FD Dataset. The re-analysis datasets are taken from NCEP-CFSR, ERA-Interim, Japanese Re-Analysis (JRA-55), MERRA and the newly released MERRA2 products. Close examination is made of the differences between MERRA and MERRA2 products for the purpose of identifying improvements achieved for MERRA2. Many of these datasets have undergone quality assessment under the GEWEX Radiative Flux Assessment (RFA) project. For the purposes of the present study, EBAF datasets are treated as reference and other datasets are compared with it. All-sky and clear-sky, SW and LW, TOA and surface fluxes are included in this study. A 7-year period (2001-2007) common to all datasets is chosen for comparisons of global and zonal averages, monthly and annual average timeseries, and their anomalies. These comparisons show significant differences between EBAF and the other datasets. Certain anomalies and trends observed in the satellite-derived datasets are attributable to corresponding features in satellite datasets used as input, especially ISCCP cloud properties. Comparisons of zonal averages showed significant differences especially over higher latitudes even when those differences are not obvious in the global averages. Special emphasis is placed on the analysis of the correspondence between spatial patterns of geographical distribution of the above fluxes on a 7-year average as well as on a month-by-month basis using the Taylor (2001) methodology. Results showed that for 7-year average fields correlation coefficients between spatial patterns

  14. Satellite-Based Surface Heat Budgets and Sea Surface Temperature Tendency in the Tropical Eastern Indian and Western Pacific Oceans for the 1997/98 El Nino and 1998/99 La Nina

    Science.gov (United States)

    Chou, Shu-Hsien; Chou, Ming-Dah; Chan, Pui-King; Lin, Po-Hsiung

    2002-01-01

    The 1997/98 is a strong El Nino warm event, while the 1998/99 is a moderate La Nina cold event. We have investigated surface heat budgets and sea surface temperature (SST) tendency for these two events in the tropical western Pacific and eastern Indian Oceans using satellite-retrieved surface radiative and turbulent fluxes. The radiative fluxes are taken from the Goddard Satellite-retrieved Surface Radiation Budget (GSSRB), derived from radiance measurements of the Japanese Geostationary Meteorological Satellite 5. The GSSRB covers the domain 40 deg S - 4 deg N, 90 deg E-17 deg W and a period from October 1997 to December 2000. The spatial resolution is 0.5 deg x 0.5 deg lat-long and the temporal resolution is 1 day. The turbulent fluxes are taken from Version 2 of the Goddard Satellite-based Surface Turbulent Fluxes (GSSTF-2). The GSSTF-2 has a spatial resolution of 1 deg x 1 deg lat-long over global Oceans and a temporal resolution of 1 day covering the period July 1987-December 2000. Daily turbulent fluxes are derived from the S S M (Special Sensor Microwave/Imager) surface wind and surface air humidity, and the SST and 2-m air temperature of the NCEP/NCAR reanalysis, using a stability-dependent bulk flux algorithm. The changes of surface heat budgets, SST and tendency, cloudiness, wind speed, and zonal wind stress of the 1997/98 El Nino relative to the1998/99 La Nina for the northern winter and spring seasons are analyzed. The relative changes of surface heat budgets and SST tendency of the two events are quite different between the tropical eastern Indian and western Pacific Oceans. For the tropical western Pacific, reduced solar heating (more clouds) is generally associated with decreased evaporative cooling (weaker winds), and vise versa. The changes in evaporative cooling over-compensate that of solar heating and dominate the spatial variability of the changes in net surface heating. Both solar heating and evaporative cooling offset each other to reduce

  15. Severe thunderstorm activity over Bihar on 21st April, 2015: a simulation study by satellite based Nowcasting technique

    Science.gov (United States)

    Goyal, Suman; Kumar, Ashish; Sangar, Ghansham; Mohapatra, M.

    2016-05-01

    Satellite based Nowcasting technique is customized version of Forecast and Tracking the Evolution of Cloud Clusters (ForTraCC), it uses the extrapolation technique that allows for the tracking of Mesoscale convective systems (MCS) radiative and morphological properties and forecasts the evolution of these properties (based on cloud-top brightness temperature and area of the cloud cluster) up to 360 minutes, using infrared satellite imagery. The Thermal Infrared (TIR) channel of the weather satellite has been broadly used to study the behaviour of the cloud systems associated with deep convection. The main advantage of this approach is that for most of the globe the best statistics can only be obtained from satellite observations. Such a satellite survey would provide the statistics of MCSs covering the range of meteorological conditions needed to generalize the result and on the other hand only satellite observations can cover the very large range of space and time scale. The algorithm script is taken from Brazilian Scientist Dr. Danial Vila and implemented it into the Indian environment and made compatible with INSAT-3D hdf5 data format. For Indian region it utilizes the INSAT-3D satellite data of TIR1 (10.8 μm) channel and creates nowcast. The output is made compatible with GUI based software MIAS by generating the output in hdf5 format for better understanding and analysis of forecast. The main features of this algorithm are detection of Cloud Cluster based on Cloud Top Brightness Temperature (CTBT) and area i.e. ≤235 ºK and ≥2400 km2 respectively. The tracking technique based on MCS overlapping areas in successive images. The script has been automized in Auxiliary Data Processing System (ADPS) and generating the forecast file in every half an hour and convert the output file in geotiff format. The geotiff file is easily converted into KMZ file format using ArcGIS software to overlay it on google map and hosted on the web server.

  16. Dynamics of large-scale atmospheric circulation over Siberia using NCEP/DOE AMIP-II reanalysis data and synoptic maps

    Science.gov (United States)

    Podnebesnykh, Nataliya

    2014-05-01

    Dynamics of large-scale atmospheric circulation over Siberia using NCEP/DOE AMIP-II reanalysis data and synoptic maps Podnebesnykh N.V., Ippolitov I.I. Institute of Monitoring of Climatic and Ecological Systems SB RAS 634055, Tomsk, 10/3 Academichesky Ave. In this paper a comparative analysis of cyclones and anticyclones characteristics, which defined circulation conditions over Siberia (50-70°W, 60-110°N) in the period of 1976-2011 was carried out using synoptic maps and NCEP/DOE AMIP II reanalysis data. The analysis has shown the ambiguous relationships in the results of the comparison. The number of cyclones and anticyclones, obtained from synoptic maps exceeds on an average by 1.2 times the number of pressure formations, determined from reanalysis data. This tendency is, probably, due to the fact that in general NCEP/DOE AMIP-II reanalysis data, like other reanalysis datasets, represents large pressure systems better than small systems. Such result is in a good agreement with studies of other authors. The pressure in the cyclonic centers varies from 996.7 to 1006.0 hPa using synoptic maps and from 992.4 to 1000.3 hPa using reanalysis data. As for anticyclones the pressure in the centers varies from 1026.3 to 1034.2 hPa and 1022.9-1028.1 hPa according to synoptic maps and reanalysis data, respectively. The average pressure in the cyclonic centers for the period of 1976-2006 was 1000.9 hPa (σ = 2.0 hPa) according to synoptic maps, and 996.6 hPa (σ = 1.9 hPa) according to reanalysis data. The average pressure in the anticyclonic centers was 1029.9 hPa (σ = 1.8 hPa) and 1026.0 hPa (σ = 1.4 hPa), respectively. Therefore, cyclones, obtained by synoptic maps, are not deep and anticyclones are more intensive in comparison with pressure formations from reanalysis data. The average annual number of days with cyclones over the territory of under study is less than that with anticyclones, i.e. during the period of 1976-2006 anticyclonic weather conditions dominated

  17. Diurnal variability of water vapour in the Baltic Sea region according to NCEP-CFSR and BaltAn65+ reanalyses

    Directory of Open Access Journals (Sweden)

    Erko Jakobson

    2014-03-01

    Full Text Available Diurnal variations in water vapour in the Baltic Sea region are examined using BaltAn65+ and NCEP-CFSR reanalyses of summer (JJA data for the period 1979-2005. A systematic difference between precipitable water (PW diurnal variability above the land and the water is revealed. Above the land, PW diurnal variability has minimal values at 00 and 06 UTC, as in previous studies, whereas above the water, the minima are at 12 and 18 UTC. Diurnal variability in the vertical humidity profile is controlled by turbulent mixing and the diurnal behaviour of sea breezes. The impacts and proportions of diurnal variability of humidity are evaluated at different vertical levels.

  18. Prevalence and control of hypercholesterolaemia as defined by NCEP-ATPIII guidelines and predictors of LDL-C goal attainment in a multi-ethnic Asian population.

    Science.gov (United States)

    Khoo, Chin Meng; Tan, Maudrene L S; Wu, Yi; Wai, Daniel C H; Subramaniam, Tavintharan; Tai, E Shyong; Lee, Jeannette

    2013-08-01

    Few studies in Asia have assessed the burden of hypercholesterolaemia based on the global cardiovascular risk assessment. This study determines the burden of hypercholesterolaemia in an Asian population based on the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATPIII) guidelines, and examines predictors of low-density lipoprotein cholesterol (LDL-C) goal attainment. Five thousand and eighty-three Chinese, Malays and Asian-Indians living in Singapore were assigned to coronary heart disease (CHD)-risk category based on the NCEP-ATPIII guidelines. Awareness, treatment and control of hypercholesterolaemia based on risk- specific LDL-C goal were determined, including the use of lipid-lowering therapy (LLT). Cox-regression models were used to identify predictors of LDL-C above goal among those who were aware and unaware of hypercholesterolaemia. One thousand five hundred and sixty-eight (30.8%) participants were aware of hypercholesterolaemia and 877 (17.3%) were newly diagnosed (unaware). For those who were aware, 39.3% participants received LLT. Among those with 2 risk factors, only 59.7% attained LDL-C goal. The majority of them were taking statin monotherapy, and the median dose of statins was similar across all CHD risk categories. Among participants with 2 risk factors and not receiving LLT, 34.1% would require LLT. Malays or Asian-Indians, higher CHD risk category, increasing body mass index (BMI), current smoking and lower education status were associated with higher risk of LDL-C above goal. Being on LLT reduced the risk of having LDL-C above goal. The burden of hypercholesterolaemia is high in this multi-ethnic population especially those in the higher CHD risk categories, and might be partly contributed by inadequate titration of statins therapy. Raising awareness of hypercholesterolaemia, appropriate LLT initiation and titration, weight management and smoking cessation may improve LDL-C goal attainment in this population.

  19. ¿Son aplicables las funciones SCORE y NCEP para el cálculo del riesgo cardiovascular en prevención primaria en la población argentina?

    Directory of Open Access Journals (Sweden)

    Silvia F. Benozzi

    2010-01-01

    Full Text Available RESUMENIntroducciónLa estimación del riesgo cardiovascular en prevención primaria mediante ecuaciones elaboradaspara tal fin permite optimizar la utilización de recursos disponibles en salud pública.ObjetivosEvaluar el riesgo cardiovascular mediante la aplicación de las funciones SCORE y NCEP yanalizar la concordancia entre ambas tablas en una población argentina.Material y métodosSe obtuvieron datos clínicos y bioquímicos de 234 personas adultas, de ambos sexos, queconcurrieron al Servicio de Medicina Preventiva del Hospital Municipal de Bahía Blanca. Sedefinió el síndrome metabólico según criterios de la AHA y se determinó riesgo cardiovascularbajo según NCEP III < 20% y según SCORE < 5%.ResultadosLas funciones SCORE y NCEP clasificaron con una precisión del 93,16% a los individuoscon riesgo cardiovascular bajo y la concordancia fue moderada (kappa: 0,452.ConclusiónLa aplicación de las tablas SCORE y NCEP en prevención primaria puede ser una herramientaútil y costo-eficiente en la práctica clínica diaria.REV ARGENT CARDIOL 2010;78:346-349.

  20. Spatio-Temporal Analysis of Model and Satellite Based Soil Moisture Estimations for Assessing Coupling Hot Spots in the Southern La Plata Basin

    Science.gov (United States)

    Bruscantini, C. A.; Karszenbaum, H.; Ruscica, R. C.; Spennemann, P.; Salvia, M.; Sorensson, A. A.; Grings, F. M.; Saulo, C.

    2015-12-01

    The southern La Plata Basin, located in southeastern South America (SESA), a region of great importance because of its hydrological characteristics, the fact that it has the largest population density and is one of the most productive regions in terms of agriculture, cattle raising and industry of the continent, has been identified as a strong hotspot between soil moisture (SM) and the atmosphere by different regional studies. Among them, Ruscica et al. (2014, Atmos. Sci. Let, Int. J. Climatol.), and Spennemann et al. (2015, Int. J. Climatol.) show, through different modeling approaches, the presence of strong soil moisture-precipitation and evapotranspiration interactions during austral summer in SESA, revealing similar hotspots. Nevertheless these studies have diverse limitations related to model assumptions and to vegetation parameterizations, as well as the lack of observational data for the evaluation of models performance (Ferguson and Wood, 2011, J. of Hydrometeorology). On the other hand, in the last decade several instruments on board satellites are providing soil moisture products globally and in a continuous way. A recent work by Grings et al. (2015, IEEE JSTARS, in press), done over the Pampas Plains in SESA showed characteristic soil moisture patterns that follow the Standardized Precipitation Index (SPI) under extreme wet and dry conditions In order to deepen and overcome some of the mentioned model limitations, this work adds satellite soil moisture and vegetation products in the spatio-temporal analysis of the regions of strong soil moisture-atmosphere interactions. The main objectives and related outcomes are: the verification of already identified regions where soil moisture anomalies may have an influence on subsequent precipitation, evapotranspiration and temperature anomalies, and the study of their seasonal characteristics and land cover influences.

  1. SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

    CSIR Research Space (South Africa)

    Snider, G

    2015-01-01

    Full Text Available reflectometer (SSR), which acts as a surrogate for black carbon (Quincey et al., 2009). The SSR measurements are calibrated to thermal optical reflectance elemental carbon measurements on pre- fired quartz filters collected with a collocated Harvard Im- pactor...

  2. Satellite-based technology, systems testing of fishing vessels: Newfoundland Region (1997) = Essais de systèmes de satellites pour les bateaux de pêche : règion de Terre-Neuve (1997)

    National Research Council Canada - National Science Library

    1998-01-01

    The application of satellite-based technology for monitoring fishing vessels and fishing activity is an effective management tool, permitting two-way communication and electronic tracking and reporting...

  3. A closer look at the climatological discontinuities present in the NCEP/NCAR reanalysis temperature due to the introduction of satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Sturaro, G. [Institute of Atmospheric Sciences and Climate, CNR-ISAC, Unita Operativa Clima e Microclima, Corso Stati Uniti, 4 I-35127 Padova (Italy)

    2003-09-01

    Principal component analysis was applied to NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalyses data for monthly temperature at given pressure levels between 1948-2000. The series composed with the time coefficients of the main components were tested for possible discontinuities. The study proved useful in gaining a better understanding of the impact of satellite observations in the reanalyses. The period 1975-1979 proved to be the most affected by inhomogeneities, in particular in August-September 1976 and December 1978-January 1979. The latter time corresponds with the introduction of satellite infrared and microwave retrievals, which gave global coverage to the observing network. Inhomogeneities due to satellite data especially affect patterns in the tropics for levels between 700 and 50 hPa and over the Southern Ocean in the layer 500 to 250 hPa, i.e. the affected regions are larger than previously determined with other methods. Greatest shifts were observed in the tropics at 100 and 150 hPa, where the discontinuity is equal to 1.6-2.0 standard deviations. (orig.)

  4. Non Linear Optimization Applied to Angle-Of Satellite Based Geo-Localization for Biased and Time-Drifting Sensors

    Science.gov (United States)

    Levy, Daniel; Roos, Jason; Robinson, Jace; Carpenter, William; Martin, Richard; Taylor, Clark; Sugrue, Joseph; Terzuoli, Andrew

    2016-06-01

    Multiple sensors are used in a variety of geolocation systems. Many use Time Difference of Arrival (TDOA) or Received Signal Strength (RSS) measurements to estimate the most likely location of a signal. When an object does not emit an RF signal, Angle of Arrival (AOA) measurements using optical or infrared frequencies become more feasible than TDOA or RSS measurements. AOA measurements can be created from any sensor platform with any sort of optical sensor, location and attitude knowledge to track passive objects. Previous work has created a non-linear optimization (NLO) method for calculating the most likely estimate from AOA measurements. Two new modifications to the NLO algorithm are created and shown to correct AOA measurement errors by estimating the inherent bias and time-drift in the Inertial Measurement Unit (IMU) of the AOA sensing platform. One method corrects the sensor bias in post processing while treating the NLO method as a module. The other method directly corrects the sensor bias within the NLO algorithm by incorporating the bias parameters as a state vector in the estimation process. These two methods are analyzed using various Monte-Carlo simulations to check the general performance of the two modifications in comparison to the original NLO algorithm.

  5. Estimate of Global Sea-Air CO2 Flux with Sea-State-Dependent Parameterization

    Institute of Scientific and Technical Information of China (English)

    HU Wei; GUAN Changlong

    2008-01-01

    Although the annual global sea-air CO2 flux has been estimated extensively with various wind-dependent-k parameteri- zations, uncertainty still exists in the estimates. The sea-state-dependent-k parameterization is expected to improve the uncertainty existing in these estimates. In the present study, the annual global sea-air CO2 flux is estimated with the sea-state-dependent-k parameterization proposed by Woolf (2005), using NOAA/NCEP reanalysis wind speed and hindcast wave data from 1998 to 2006, and a new estimate, -2.18 Gt C year-1, is obtained, which is comparable with previous estimates with biochemical methods. It is in- teresting to note that the averaged value of previous estimates with various wind-dependent-k parameterizations is almost identical to that of previous estimates with biochemical methods by various authors, and that the new estimate is quite consistent with these av- eraged estimates.

  6. Assessing regional crop water demand using a satellite-based combination equation with a land surface temperature componen

    DEFF Research Database (Denmark)

    Moyano, Carmen; Garcia, Monica; Tornos, Lucia

    2015-01-01

    consumption trends in the area. The results showed that the thermal-PT-JPL model is a suitable and simple tool requiring only air temperature and incoming solar radiation apart from standard satellites-products freely available. Our results show that in comparison with the hydrological model conceptual...... to estimate soil surface conductance based on an apparent thermal inertia index. A process-based model was applied to estimate surface energy fluxes including daily ET based on a modified version of the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model at 1km pixel resolution during a chrono......-sequence spanning for more than a decade (2002-2013). The thermal-PT-JPL model was forced with vegetation, albedo, reflectance and temperature products from the Moderate-resolution Imaging Spectroradiometer (MODIS) from both Aqua and Terra satellites. The study region, B-XII Irrigation District of the Lower...

  7. A wavelet-based non-linear autoregressive with exogenous inputs (WNARX) dynamic neural network model for real-time flood forecasting using satellite-based rainfall products

    Science.gov (United States)

    Nanda, Trushnamayee; Sahoo, Bhabagrahi; Beria, Harsh; Chatterjee, Chandranath

    2016-08-01

    Although flood forecasting and warning system is a very important non-structural measure in flood-prone river basins, poor raingauge network as well as unavailability of rainfall data in real-time could hinder its accuracy at different lead times. Conversely, since the real-time satellite-based rainfall products are now becoming available for the data-scarce regions, their integration with the data-driven models could be effectively used for real-time flood forecasting. To address these issues in operational streamflow forecasting, a new data-driven model, namely, the wavelet-based non-linear autoregressive with exogenous inputs (WNARX) is proposed and evaluated in comparison with four other data-driven models, viz., the linear autoregressive moving average with exogenous inputs (ARMAX), static artificial neural network (ANN), wavelet-based ANN (WANN), and dynamic nonlinear autoregressive with exogenous inputs (NARX) models. First, the quality of input rainfall products of Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA), viz., TRMM and TRMM-real-time (RT) rainfall products is assessed through statistical evaluation. The results reveal that the satellite rainfall products moderately correlate with the observed rainfall, with the gauge-adjusted TRMM product outperforming the real-time TRMM-RT product. The TRMM rainfall product better captures the ground observations up to 95 percentile range (30.11 mm/day), although the hit rate decreases for high rainfall intensity. The effect of antecedent rainfall (AR) and climate forecast system reanalysis (CFSR) temperature product on the catchment response is tested in all the developed models. The results reveal that, during real-time flow simulation, the satellite-based rainfall products generally perform worse than the gauge-based rainfall. Moreover, as compared to the existing models, the flow forecasting by the WNARX model is way better than the other four models studied herein with the

  8. Evaluation of Crop-Water Consumption Simulation to Support Agricultural Water Resource Management using Satellite-based Water Cycle Observations

    Science.gov (United States)

    Gupta, M.; Bolten, J. D.; Lakshmi, V.

    2016-12-01

    Water scarcity is one of the main factors limiting agricultural development. Numerical models integrated with remote sensing datasets are increasingly being used operationally as inputs for crop water balance models and agricultural forecasting due to increasing availability of high temporal and spatial resolution datasets. However, the model accuracy in simulating soil water content is affected by the accuracy of the soil hydraulic parameters used in the model, which are used in the governing equations. However, soil databases are known to have a high uncertainty across scales. Also, for agricultural sites, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally. The present study utilizes effective soil hydraulic parameters obtained using a 1-km downscaled microwave remote sensing soil moisture product based on the NASA Advanced Microwave Scanning Radiometer (AMSR-E) using the genetic algorithm inverse method within the Catchment Land Surface Model (CLSM). Secondly, to provide realistic irrigation estimates for agricultural sites, an irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches the threshold, 50% with respect to the maximum available water capacity obtained from the effective soil hydraulic parameters. An additional important criterion utilized is the estimation of crop water consumption based on dynamic root growth and uptake in root zone layer. Model performance is evaluated using MODIS land surface temperature (LST) product. The soil moisture estimates for the root zone are also validated with the in situ field data, for three sites (2- irrigated and 1- rainfed) located at the University of Nebraska Agricultural Research and Development Center near Mead, NE and monitored

  9. Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Directory of Open Access Journals (Sweden)

    R. Zubieta

    2017-07-01

    Full Text Available In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG (product/final run as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015 when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively. In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %. Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin. GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins, probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  10. Hydrological modeling of the Peruvian-Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Science.gov (United States)

    Zubieta, Ricardo; Getirana, Augusto; Carlo Espinoza, Jhan; Lavado-Casimiro, Waldo; Aragon, Luis

    2017-07-01

    In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM) have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM) mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG) (product/final run) as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015) when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets) and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively). In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ˜ 20 %). Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin). GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins), probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  11. A Comparison of Satellite Based, Modeled Derived Daily Solar Radiation Data with Observed Data for the Continental US

    Science.gov (United States)

    White, Jeffrey W.; Hoogenboom, Gerrit; Wilkens, Paul W.; Stackhouse, Paul W., Jr.; Hoell, James M.

    2010-01-01

    Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these tools. Daily solar radiation (SRAD) data are especially problematic because the instruments require electronic integrators, accurate sensors are expensive, and calibration standards are seldom available. The Prediction Of Worldwide Energy Resources (NASA/POWER; power.larc.nasa.gov) project at the NASA Langley Research Center estimates daily solar radiation based on data that are derived from satellite observations of outgoing visible radiances and atmospheric parameters based upon satellite observations and assimilation models. The solar data are available for a global 1 degree x 1 degree coordinate grid. SRAD can also be estimated based on attenuation of extraterrestrial radiation (Q0) using daily temperature and rainfall data to estimate the optical thickness of the atmosphere. This study compares daily solar radiation data from NASA/POWER (SRADNP) with instrument readings from 295 stations (SRADOB), as well as with values that were estimated with the WGENR solar generator. WGENR was used both with daily temperature and precipitation records from the stations reporting solar data and records from the NOAA Cooperative Observer Program (COOP), thus providing two additional sources of solar data, SRADWG and SRADCO. Values of SRADNP for different grid cells consistently showed higher correlations (typically 0.85 to 0.95) with SRADOB data than did SRADWG or SRADCO for sites within the corresponding cells. Mean values of SRADOB, SRADWG and SRADNP for sites within a grid cell usually were within 1 MJm-2d-1 of each other, but NASA/POWER values averaged 1.1 MJm-2d-1 lower than SRADOB. The magnitude of this bias was greater at lower latitudes and during summer months and may be at

  12. Satellite-based detection of 16.76 MeV γ-ray from H-bomb D-T fusion

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Based on the high energy γ-ray yield from the H-bomb D-T fusion reaction,it brings forward the idea applying the 16.76 MeV γ-ray to judge whether the H-bomb happens or not,and to deduce the explosion TNT equivalent accurately.The Monte Carlo N-Particle was applied to simulate the high energy γ-ray radiation characteristics reaching the geosynchronous orbit satellite,and the CVD diamond detector suit for the requirements was researched.A series of experiments were carried out to testify the capabilities of the diamond detector.It provides a brand-new approach to satellite-based nuclear explosion detection.

  13. A satellite-based analysis of the Val d'Agri (South of Italy Oil Center gas flaring emissions

    Directory of Open Access Journals (Sweden)

    M. Faruolo

    2014-06-01

    Full Text Available In this paper the Robust Satellite Techniques (RST, a multi-temporal scheme of satellite data analysis, was implemented to analyze the flaring activity of the largest Italian gas and oil pre-treatment plant (i.e. the Ente Nazionale Idrocarburi – ENI – Val d'Agri Oil Center – COVA. For this site, located in an anthropized area characterized by a~large environmental complexity, flaring emissions are mainly related to emergency conditions (i.e. waste flaring, being the industrial process regulated by strict regional laws. With reference to the peculiar characteristics of COVA flaring, the main aim of this work was to assess the performances of RST in terms of sensitivity and reliability in providing independent estimations of gas flaring volumes in such conditions. In detail, RST was implemented on thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS medium and thermal infrared data in order to identify the highly radiant records associated to the COVA flare emergency discharges. Then, exploiting data provided by ENI about gas flaring volumes in the period 2003–2009, a MODIS-based regression model was developed and tested. Achieved results indicate that such a model is able to estimate, with a good level of accuracy (R2 of 0.83, emitted gas flaring volumes at COVA.

  14. Assessment of ionospheric Joule heating by GUMICS-4 MHD simulation, AMIE, and satellite-based statistics: towards a synthesis

    Directory of Open Access Journals (Sweden)

    M. Palmroth

    2005-09-01

    Full Text Available We investigate the Northern Hemisphere Joule heating from several observational and computational sources with the purpose of calibrating a previously identified functional dependence between solar wind parameters and ionospheric total energy consumption computed from a global magnetohydrodynamic (MHD simulation (Grand Unified Magnetosphere Ionosphere Coupling Simulation, GUMICS-4. In this paper, the calibration focuses on determining the amount and temporal characteristics of Northern Hemisphere Joule heating. Joule heating during a substorm is estimated from global observations, including electric fields provided by Super Dual Auroral Network (SuperDARN and Pedersen conductances given by the ultraviolet (UV and X-ray imagers on board the Polar satellite. Furthermore, Joule heating is assessed from several activity index proxies, large statistical surveys, assimilative data methods (AMIE, and the global MHD simulation GUMICS-4. We show that the temporal and spatial variation of the Joule heating computed from the GUMICS-4 simulation is consistent with observational and statistical methods. However, the different observational methods do not give a consistent estimate for the magnitude of the global Joule heating. We suggest that multiplying the GUMICS-4 total Joule heating by a factor of 10 approximates the observed Joule heating reasonably well. The lesser amount of Joule heating in GUMICS-4 is essentially caused by weaker Region 2 currents and polar cap potentials. We also show by theoretical arguments that multiplying independent measurements of averaged electric fields and Pedersen conductances yields an overestimation of Joule heating.

    Keywords. Ionosphere (Auroral ionosphere; Modeling and forecasting; Electric fields and currents

  15. Evaluation of Satellite-based Global Hydrologic Simulation using the Distributed CREST Model and Global Runoff Data Centre Archives

    Science.gov (United States)

    Xue, X.; Hong, Y.; Gourley, J. J.; Wang, X.

    2011-12-01

    Flooding is one of the most deadly natural hazards around the world. Distributed hydrologic models can provide the spatial and temporal distribution of precipitation, soil moisture, evapotranspiration and runoff. Implementation of a flood prediction and/or forecast system using a distributed hydrologic model can potentially help mitigate flood-induced hazards. In this study, we propose the use of the Coupled Routing and Excess STorage (CREST) distributed hydrological model driven by real-time rainfall forcing from TRMM-based multi-satellite products and/or precipitation forecast data from the Global Forecast System model (GFS), combined with automatic parameter optimization methods, to estimate hydrological fluxes, storages and inundated areas. Evaluations show that: 1) the capability of real-time streamflow prediction and/or forecast at drainage outlets and identification of inundated areas upstream is an achievable goal even for ungauged basins; 2) a-priori, physically-based parameter estimates with CREST reduce the dependence on rainfall-runoff data often required to calibrate distributed hydrologic models; and 3) the validation of CREST simulations of basin discharge are skillful in several basins throughout the world.

  16. A satellite-based analysis of the Val d'Agri (South of Italy) Oil Center gas flaring emissions

    Science.gov (United States)

    Faruolo, M.; Coviello, I.; Filizzola, C.; Lacava, T.; Pergola, N.; Tramutoli, V.

    2014-06-01

    In this paper the Robust Satellite Techniques (RST), a multi-temporal scheme of satellite data analysis, was implemented to analyze the flaring activity of the largest Italian gas and oil pre-treatment plant (i.e. the Ente Nazionale Idrocarburi - ENI - Val d'Agri Oil Center - COVA). For this site, located in an anthropized area characterized by a~large environmental complexity, flaring emissions are mainly related to emergency conditions (i.e. waste flaring), being the industrial process regulated by strict regional laws. With reference to the peculiar characteristics of COVA flaring, the main aim of this work was to assess the performances of RST in terms of sensitivity and reliability in providing independent estimations of gas flaring volumes in such conditions. In detail, RST was implemented on thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) medium and thermal infrared data in order to identify the highly radiant records associated to the COVA flare emergency discharges. Then, exploiting data provided by ENI about gas flaring volumes in the period 2003-2009, a MODIS-based regression model was developed and tested. Achieved results indicate that such a model is able to estimate, with a good level of accuracy (R2 of 0.83), emitted gas flaring volumes at COVA.

  17. A satellite-based analysis of the Val d'Agri Oil Center (southern Italy) gas flaring emissions

    Science.gov (United States)

    Faruolo, M.; Coviello, I.; Filizzola, C.; Lacava, T.; Pergola, N.; Tramutoli, V.

    2014-10-01

    In this paper, the robust satellite techniques (RST), a multi-temporal scheme of satellite data analysis, was implemented to analyze the flaring activity of the Val d'Agri Oil Center (COVA), the largest Italian gas and oil pre-treatment plant, owned by Ente Nazionale Idrocarburi (ENI). For this site, located in an anthropized area characterized by a large environmental complexity, flaring emissions are mainly related to emergency conditions (i.e., waste flaring), as industrial processes are regulated by strict regional laws. While regarding the peculiar characteristics of COVA flaring, the main aim of this work was to assess the performances of RST in terms of sensitivity and reliability in providing independent estimations of gas flaring volumes in such conditions. In detail, RST was implemented for 13 years of Moderate Resolution Imaging Spectroradiometer (MODIS) medium and thermal infrared data in order to identify the highly radiant records associated with the COVA flare emergency discharges. Then, using data provided by ENI about gas flaring volumes in the period 2003-2009, a MODIS-based regression model was developed and tested. The results achieved indicate that the such a model is able to estimate, with a good level of accuracy (R2 of 0.83), emitted gas flaring volumes at COVA.

  18. Assessment of ionospheric Joule heating by GUMICS-4 MHD simulation, AMIE, and satellite-based statistics: towards a synthesis

    Science.gov (United States)

    Palmroth, M.; Janhunen, P.; Pulkkinen, T. I.; Aksnes, A.; Lu, G.; Østgaard, N.; Watermann, J.; Reeves, G. D.; Germany, G. A.

    2005-09-01

    We investigate the Northern Hemisphere Joule heating from several observational and computational sources with the purpose of calibrating a previously identified functional dependence between solar wind parameters and ionospheric total energy consumption computed from a global magnetohydrodynamic (MHD) simulation (Grand Unified Magnetosphere Ionosphere Coupling Simulation, GUMICS-4). In this paper, the calibration focuses on determining the amount and temporal characteristics of Northern Hemisphere Joule heating. Joule heating during a substorm is estimated from global observations, including electric fields provided by Super Dual Auroral Network (SuperDARN) and Pedersen conductances given by the ultraviolet (UV) and X-ray imagers on board the Polar satellite. Furthermore, Joule heating is assessed from several activity index proxies, large statistical surveys, assimilative data methods (AMIE), and the global MHD simulation GUMICS-4. We show that the temporal and spatial variation of the Joule heating computed from the GUMICS-4 simulation is consistent with observational and statistical methods. However, the different observational methods do not give a consistent estimate for the magnitude of the global Joule heating. We suggest that multiplying the GUMICS-4 total Joule heating by a factor of 10 approximates the observed Joule heating reasonably well. The lesser amount of Joule heating in GUMICS-4 is essentially caused by weaker Region 2 currents and polar cap potentials. We also show by theoretical arguments that multiplying independent measurements of averaged electric fields and Pedersen conductances yields an overestimation of Joule heating. Keywords. Ionosphere (Auroral ionosphere; Modeling and forecasting; Electric fields and currents)

  19. Assessment of surface dryness due to deforestation using satellite-based temperature-vegetation dryness index (TVDI) in Rondônia, Amazon

    Science.gov (United States)

    Ryu, J. H.; Cho, J.

    2016-12-01

    The Rondônia is the most deforested region in the Amazon due to human activities such as forest lumbering for the several decades. The deforestation affects to water cycle because evapotranspiration was reduced, and then soil moisture and precipitation will be changed. In this study, we assess surface dryness using satellite-based data such as moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), normalized difference vegetation index (NDVI), albedo, TRMM Multi-sensor Precipitation Analysis (TMPA) precipitation from 2002 to 2014, and Global Ozone Monitoring Experiment-2 (GOME-2) sun-induced fluorescence (SIF) from 2007 to 2014. Temperature-vegetation dryness index (TVDI) was calculated using LST and NDVI to evaluate surface dryness during dry season (June-July). TVDI relatively represents the surface dryness on specific area and period. Forest, deforesting and deforested regions were selected in the Rondônia to assess the relative changes on surface dryness occurred from human activity. The relative TVDI (rTVDI) at deforesting region increased because of deforestation, it means that surface in deforesting region became more dryness. We also found that to assess the impact of deforestation using satellite-based precipitation and vegetation conditions such as NDVI and sun-induced fluorescence (SIF) is possible. The relative NDVI (rNDVI) and SIF decreased when TVDI increased, and two variables (rTVDI-rNDVI, rTVDI-SIF) had linear correlation. Thesis results can be helpful to comprehend impact of deforestation in Amazon, and to validate simulations of deforestation from hydrological models.

  20. Improving soil moisture simulation to support Agricultural Water Resource Management using Satellite-based water cycle observations

    Science.gov (United States)

    Gupta, Manika; Bolten, John; Lakshmi, Venkat

    2016-04-01

    Efficient and sustainable irrigation systems require optimization of operational parameters such as irrigation amount which are dependent on the soil hydraulic parameters that affect the model's accuracy in simulating soil water content. However, it is a scientific challenge to provide reliable estimates of soil hydraulic parameters and irrigation estimates, given the absence of continuously operating soil moisture and rain gauge network. For agricultural water resource management, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally (Wang and Qu 2009). In the current study, flood irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches below a threshold of 25%, 50% and 75% with respect to the maximum available water capacity (difference between field capacity and wilting point) and applied until the top layer is saturated. An additional important criterion needed to activate the irrigation scheme is to ensure that it is irrigation season by assuming that the greenness vegetation fraction (GVF) of the pixel exceed 0.40 of the climatological annual range of GVF (Ozdogan et al. 2010). The main hypothesis used in this study is that near-surface remote sensing soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately inverted, it would provide field capacity and wilting point soil moisture, which may be representative of that basin. Thus, genetic algorithm inverse method is employed to derive the effective parameters and derive the soil moisture deficit for the root zone by coupling of AMSR-E soil moisture with the physically based hydrological model. Model performance is evaluated using MODIS

  1. Satellite-based water use dynamics using historical Landsat data (1984-2014) in the southwestern United States

    Science.gov (United States)

    Senay, Gabriel; Schauer, Matthew; Friedrichs, MacKenzie O.; Velpuri, Naga Manohar; Singh, Ramesh K.

    2017-01-01

    Historical (1984-2014) Landsat-based ET maps were generated for Palo Verde Irrigation District (PVID) and eight other sub-basins in parts of Middle and Lower Central Valley, California. A total of 3,396 Landsat images were processed using the Operational Simplified Surface Energy balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study areas over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively strong association between SSEBop ET and validation datasets. Historical trend analysis of seven agro-hydrologic variables were done using the Seasonal Mann-Kendall test.

  2. A national satellite-based land-use regression model for air pollution exposure assessment in Australia.

    Science.gov (United States)

    Knibbs, Luke D; Hewson, Michael G; Bechle, Matthew J; Marshall, Julian D; Barnett, Adrian G

    2014-11-01

    Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006-2011. We are making our model predictions freely available for research. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. NCEP-NCAR Reanalysis 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data is from NMC initialized reanalysis (4x/day). It consists of most variables interpolated to pressure surfaces from model (sigma) surfaces.

  4. Prevalência de síndrome metabólica em indivíduos brasileiros pelos critérios de NCEP-ATPIII e IDF Prevalence of metabolic syndrome using NCEP-ATPIII and IDF definitions in Brazilian individuals

    Directory of Open Access Journals (Sweden)

    Marcelo Arruda Nakazone

    2007-10-01

    Full Text Available Objetivos. Analisar perfil bioquímico e caracterizar síndrome metabólica (SM em pacientes com acompanhamento cardiológico, conforme critérios de NCEP-ATPIII e IDF. MÉTODOS: Foram estudados 200 pacientes e 140 controles, considerando colesterol total (CT, fração de colesterol de lipoproteína de alta (HDLc, baixa (LDLc e muito baixa densidade (VLDLc, triglicérides (TG, glicemia de jejum, cintura abdominal e hipertensão arterial sistêmica (HAS. Admitiu-se nível de significância POBJECTIVE: To analyze the biochemical profile and to characterize metabolic syndrome (MS in patients with cardiologic medical assistance using NCEP-ATPIII and IDF definitions. METHODS: Two hundred patients and 140 controls were studied, considering total cholesterol (TC, HDL-cholesterol (HDLc, LDL-cholesterol (LDLc, VLDL-cholesterol (VLDLc, triglycerides (TG, fasting glycemia, abdominal waist and hypertension. Significance level was defined as P<0.05. RESULTS: Patients showed increased glycemia levels (103±31.4mg/dL and reduced HDLc levels (48±13.4mg/dL when compared to controls (88±29.7mg/dL, P<0.0001 and 53±15.9mg/dL, P=0.0075; respectively. Male controls 31-50 years old showed increased TC levels (215±40.4mg/dL, LDL-cholesterol (134±34mg/dL, VLDL-cholesterol (30±11.8mg/dL and TG (150±59.4mg/dL when compared to women (185±38.2mg/dL, P=0.0137; 111±35.8mg/dL; P=0.0324; 19±9.7mg/dL; P=0.0009; 93±49mg/dL, P=0.0010; respectively. Women over 50 years of age showed increased TC concentrations (216±35.9mg/dL, HDL-cholesterol (54±12.8mg/dL and LDL-cholesterol (138±30.8mg/dL when compared to men (190±44.7mg/dL, P=0.0103; 47±14.5mg/dL, P=0.0229; 119±33.3mg/dL; P=0.0176; respectively. NCEP-ATPIII and IDF definitions had characterized MS in 35.5% and 46% of patients, respectively, bolding glycemia, TG and hypertension. CONCLUSION: Elevated glycemia levels and reduced HDLc levels were detected in patients. Altered lipid profile observed in men 31

  5. Caracterização de eventos extremos do nível do mar em Santos e sua correspondência com as reanálises do modelo do NCEP no sudoeste do Atlântico Sul Characterization of extreme sea level events in Santos and their correspondence with the NCEP model reanalysis in the southwest of the South Atlantic

    Directory of Open Access Journals (Sweden)

    Ricardo Martins Campos

    2010-06-01

    Full Text Available Este trabalho tem como objetivo identificar a influência atmosférica em escala sinótica sobre o oceano, para eventos extremos de maré meteorológica na costa sudeste brasileira. Para isso foram utilizados dados de elevação do nível do mar do Porto de Santos-SP, campos de vento e pressão em superfície das reanálises do modelo do NCEP abrangendo o Atlântico Sul, no período de 1951 a 1990. Foi possível identificar a variabilidade sazonal e o padrão de evolução dos sistemas atmosféricos associados aos eventos extremos, de grande relevância para aplicações em prognósticos e alertas a autoridades. O outono e inverno apresentaram a maior ocorrência de extremos positivos (40,2 % e 30,8 % respectivamente, enquanto a primavera e o inverno foram as estações com maior número de extremos negativos (47,2 % e 32,3 % respectivamente. Os resultados mostram que os casos mais importantes de sobre-elevação do nível do mar ocorrem com a evolução e persistência de sistemas de baixa pressão sobre o oceano, com ventos de sudoeste acima de 8 m/s, juntamente com o anticiclone da retaguarda posicionado sobre o continente.This work aims to identify the synoptic scale atmospheric influence over the ocean for extreme events of storm surges events in the Southeastern Brazilian coast. Time series of sea surface height at the Port of Santos as well as wind and surface pressure from the NCEP reanalysis model enclosing the South Atlantic, for period 1951-1990, were used. Seasonal variability and typical evolution of atmospheric systems were found to be associated with extreme events, very relevant for applications on prognostics and warnings to authorities. Autumn and winter are seasons with the highest occurrence of positive extreme events (40.2 % and 30.8 % respectively and the spring and winter are the ones with negative extreme events (47.2 % and 32.3 % respectively. The results show that the storm surges events depend on low pressure systems

  6. Satellite-based forest monitoring: spatial and temporal forecast of growing index and short-wave infrared band.

    Science.gov (United States)

    Bayr, Caroline; Gallaun, Heinz; Kleb, Ulrike; Kornberger, Birgit; Steinegger, Martin; Winter, Martin

    2016-04-18

    For detecting anomalies or interventions in the field of forest monitoring we propose an approach based on the spatial and temporal forecast of satellite time series data. For each pixel of the satellite image three different types of forecasts are provided, namely spatial, temporal and combined spatio-temporal forecast. Spatial forecast means that a clustering algorithm is used to group the time series data based on the features normalised difference vegetation index (NDVI) and the short-wave infrared band (SWIR). For estimation of the typical temporal trajectory of the NDVI and SWIR during the vegetation period of each spatial cluster, we apply several methods of functional data analysis including functional principal component analysis, and a novel form of random regression forests with online learning (streaming) capability. The temporal forecast is carried out by means of functional time series analysis and an autoregressive integrated moving average model. The combination of the temporal forecasts, which is based on the past of the considered pixel, and spatial forecasts, which is based on highly correlated pixels within one cluster and their past, is performed by functional data analysis, and a variant of random regression forests adapted to online learning capabilities. For evaluation of the methods, the approaches are applied to a study area in Germany for monitoring forest damages caused by wind-storm, and to a study area in Spain for monitoring forest fires.

  7. Satellite-Based Technologies in Use for Extreme Nocturnal Mountain Rescue Operations: a Synergetic Approach Applying Geophysical Principles

    Science.gov (United States)

    Buchroithner, Manfred F.; Ehlert, Guido; Hetze, Bernd; Kohlschmidt, Horst; Prechtel, Nikolas

    2014-06-01

    Mountain-rescue operations require rapid response whilst also ensuring the security of the rescue teams. Rescuing people in a big rock-face is even more difficult if night or fog prevent sight. The paper presents a technical solution to optimally support, under these aggravated conditions, the location of the casualties and the navigation of the rescue team(s) in a rock-face from a coordination station. In doing so, standard components like a smartphones with GPS functionality, a data communication on a client-server basis and VR visualisation software have been adapted to the specific requirements. Remote support of the navigation in steep rocky terrain requires a highly accurate wall model which permits the local experts of the coordination station to dependably estimate geometry and structure of the rock along the rescue route and to convey necessary directives to the retrieval team. Based on terrestrial laser-scans from different locations, such a model has been generated for the mighty Dachstein South Face (Austria) and texturised with digital photographs. Over a twelve-month period, a transdisciplinary team of the Dresden University of Technology (Informatics, Electrical Engineering, Cartography) developed and integrated the various technical modules of the mountain-rescue support-system (digital rock-face model, optimised GPS data transmission between mobile device, server and client, data filtering, and dynamic visualisation component). In summer 2011 the proper functioning of the prototype was demonstrated in a rescue exercise under foggy dusk conditions.

  8. Estimating biomass consumed from fire using MODIS FRE

    Science.gov (United States)

    Ellicott, Evan; Vermote, Eric; Giglio, Louis; Roberts, Gareth

    2009-07-01

    Biomass burning is an important global phenomenon impacting atmospheric composition. Application of satellite based measures of fire radiative energy (FRE) has been shown to be effective for estimating biomass consumed, which can then be used to estimate gas and aerosol emissions. However, application of FRE has been limited in both temporal and spatial scale. In this paper we offer a methodology to estimate FRE globally for 2001-2007 at monthly time steps using MODIS. Accuracy assessment shows that our FRE estimates are precise (R2 = 0.85), but may be underestimated. Global estimates of FRE show that Africa and South America dominate biomass burning, accounting for nearly 70% of the annual FRE generated. Applying FRE-based combustion factors to Africa yields an annual average biomass burned of 716-881 Tg of dry matter (DM). Comparison with the GFEDv2 biomass burned estimates shows large annual differences suggesting significant uncertainty remains in emission estimates.

  9. Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors

    Directory of Open Access Journals (Sweden)

    B. Revilla-Romero

    2014-07-01

    locations and limitations for estimating discharge values from these daily satellite signals.

  10. SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

    Energy Technology Data Exchange (ETDEWEB)

    Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

    2002-08-01

    Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of

  11. Wi-Fi and Satellite-Based Location Techniques for Intelligent Agricultural Machinery Controlled by a Human Operator

    Directory of Open Access Journals (Sweden)

    Domagoj Drenjanac

    2014-10-01

    Full Text Available In the new agricultural scenarios, the interaction between autonomous tractors and a human operator is important when they jointly perform a task. Obtaining and exchanging accurate localization information between autonomous tractors and the human operator, working as a team, is a critical to maintaining safety, synchronization, and efficiency during the execution of a mission. An advanced localization system for both entities involved in the joint work, i.e., the autonomous tractors and the human operator, provides a basis for meeting the task requirements. In this paper, different localization techniques for a human operator and an autonomous tractor in a field environment were tested. First, we compared the localization performances of two global navigation satellite systems’ (GNSS receivers carried by the human operator: (1 an internal GNSS receiver built into a handheld device; and (2 an external DGNSS receiver with centimeter-level accuracy. To investigate autonomous tractor localization, a real-time kinematic (RTK-based localization system installed on autonomous tractor developed for agricultural applications was evaluated. Finally, a hybrid localization approach, which combines distance estimates obtained using a wireless scheme with the position of an autonomous tractor obtained using an RTK-GNSS system, is proposed. The hybrid solution is intended for user localization in unstructured environments in which the GNSS signal is obstructed. The hybrid localization approach has two components: (1 a localization algorithm based on the received signal strength indication (RSSI from the wireless environment; and (2 the acquisition of the tractor RTK coordinates when the human operator is near the tractor. In five RSSI tests, the best result achieved was an average localization error of 4 m. In tests of real-time position correction between rows, RMS error of 2.4 cm demonstrated that the passes were straight, as was desired for the

  12. Understanding the Impact of Ground Water Treatment and Evapotranspiration Parameterizations in the NCEP Climate Forecast System (CFS) on Warm Season Predictions

    Science.gov (United States)

    Ek, M. B.; Yang, R.

    2016-12-01

    Skillful short-term weather forecasts, which rely heavily on quality atmospheric initial conditions, have a fundamental limit of about two weeks owing to the chaotic nature of the atmosphere. Useful forecasts at sub-seasonal to seasonal time scales, on the other hand, require well-simulated large-scale atmospheric response to slowly varying lower boundary forcings from both the ocean and land surface. The critical importance of ocean has been recognized, where the ocean indices have been used in a variety of climate applications. In contrast, the impact of land surface anomalies, especially soil moisture and associated evaporation, has been proven notably difficult to demonstrate. The Noah Land Surface Model (LSM) is the land component of NCEP CFS version 2 (CFSv2) used for seasonal predictions. The Noah LSM originates from the Oregon State University (OSU) LSM. The evaporation control in the Noah LSM is based on the Penman-Monteith equation, which takes into account the solar radiation, relative humidity, air temperature, and soil moisture effects. The Noah LSM is configured with four soil layers with a fixed depth of 2 meters and free drainage at the bottom soil layer. This treatment assumes that the soil water table depth is well within the specified range, and also potentially misrepresents the soil moisture memory effects at seasonal time scales. To overcome the limitation, an unconfined aquifer is attached to the bottom of the soil to allow the water table to move freely up and down. In addition, in conjunction with the water table, an alternative Ball-Berry photosynthesis-based evaporation parameterization is examined to evaluate the impact from using a different evaporation control methodology. Focusing on the 2011 and 2012 intense summer droughts in the central US, seasonal ensemble forecast experiments with early May initial conditions are carried out for the two years using an enhanced version of CFSv2, where the atmospheric component of the CFSv2 is

  13. Does the modification in "critical relative humidity" of NCEP CFSv2 dictate Indian mean summer monsoon forecast? Evaluation through thermodynamical and dynamical aspects

    Science.gov (United States)

    De, S.; Hazra, Anupam; Chaudhari, Hemantkumar S.

    2016-02-01

    An accurate seasonal prediction of Indian summer monsoon rainfall (ISMR) is intriguing as well as the most challenging job for monsoon meteorologists. As there is a cause and effect relationship between clouds and precipitation, the modulation of cloud formation in a dynamical model affects profoundly on ISMR. It has already been established that the critical relative humidity (CRH) plays a crucial role on the realistic cloud formation in a general circulation model. Hence, it may be hypothesized that the proper choice of CRH can be instrumental in driving the large scale Indian monsoon by modulating the cloud formation in a global climate model. An endeavor has been made for the first time to test the above hypothesis on the NCEP-CFSv2 model in the perspective of seasonal prediction of ISMR by modifying the CRH profile. The model sensitivity experiments have been carried out for two different CRH profiles along with the existing profile during the normal (2003) and deficient (2009) monsoon years. First profile is the constant CRH following the existing one but with increased magnitude and the second one is the variable CRH at different cloud levels based on the observations and MERRA reanalysis. The ensemble mean of model runs for four initial conditions of each year has revealed that the variable CRH profile in CFSv2 represents seasonal ISMR and its variability best among the three CRH experiments linking with the thermodynamical and dynamical parameters like precipitable water, tropospheric temperature and its gradient, cloud structure and radiation, water vapour flux, systematic error energy with its nonlinear error growth and the length of the rainy seasons during the contrasting years. It has also been shown that the improved depiction of seasonal ISMR has been achieved without disturbing much the forecast biases at other global tropical regions. The indigenous part of this paper is that the CRH modification can play a seminal role in modulating the large

  14. Global Electric Circuit Implications of Combined Aircraft Storm Electric Current Measurements and Satellite-Based Diurnal Lightning Statistics

    Science.gov (United States)

    Mach, Douglas M.; Blakeslee, Richard J.; Bateman, Monte G.

    2011-01-01

    Using rotating vane electric field mills and Gerdien capacitors, we measured the electric field profile and conductivity during 850 overflights of thunderstorms and electrified shower clouds (ESCs) spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, and with positive and negative fields above the storms. Over three-quarters (78%) of the land storms had detectable lightning, while less than half (43%) of the oceanic storms had lightning. Integrating our electric field and conductivity data, we determined total conduction currents and flash rates for each overpass. With knowledge of the storm location (land or ocean) and type (with or without lightning), we determine the mean currents by location and type. The mean current for ocean thunderstorms is 1.7 A while the mean current for land thunderstorms is 1.0 A. The mean current for ocean ESCs 0.41 A and the mean current for land ESCs is 0.13 A. We did not find any significant regional or latitudinal based patterns in our total conduction currents. By combining the aircraft derived storm currents and flash rates with diurnal flash rate statistics derived from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) low Earth orbiting satellites, we reproduce the diurnal variation in the global electric circuit (i.e., the Carnegie curve) to within 4% for all but two short periods of time. The agreement with the Carnegie curve was obtained without any tuning or adjustment of the satellite or aircraft data. Given our data and assumptions, mean contributions to the global electric circuit are 1.1 kA (land) and 0.7 kA (ocean) from thunderstorms, and 0.22 kA (ocean) and 0.04 (land) from ESCs, resulting in a mean total conduction current estimate for the global electric circuit of 2.0 kA. Mean storm counts are 1100 for land

  15. Evaluation of ACCMIP ozone simulations and ozonesonde sampling biases using a satellite-based multi-constituent chemical reanalysis

    Science.gov (United States)

    Miyazaki, Kazuyuki; Bowman, Kevin

    2017-07-01

    The Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) ensemble ozone simulations for the present day from the 2000 decade simulation results are evaluated by a state-of-the-art multi-constituent atmospheric chemical reanalysis that ingests multiple satellite data including the Tropospheric Emission Spectrometer (TES), the Microwave Limb Sounder (MLS), the Ozone Monitoring Instrument (OMI), and the Measurement of Pollution in the Troposphere (MOPITT) for 2005-2009. Validation of the chemical reanalysis against global ozonesondes shows good agreement throughout the free troposphere and lower stratosphere for both seasonal and year-to-year variations, with an annual mean bias of less than 0.9 ppb in the middle and upper troposphere at the tropics and mid-latitudes. The reanalysis provides comprehensive spatiotemporal evaluation of chemistry-model performance that compliments direct ozonesonde comparisons, which are shown to suffer from significant sampling bias. The reanalysis reveals that the ACCMIP ensemble mean overestimates ozone in the northern extratropics by 6-11 ppb while underestimating by up to 18 ppb in the southern tropics over the Atlantic in the lower troposphere. Most models underestimate the spatial variability of the annual mean lower tropospheric concentrations in the extratropics of both hemispheres by up to 70 %. The ensemble mean also overestimates the seasonal amplitude by 25-70 % in the northern extratropics and overestimates the inter-hemispheric gradient by about 30 % in the lower and middle troposphere. A part of the discrepancies can be attributed to the 5-year reanalysis data for the decadal model simulations. However, these differences are less evident with the current sonde network. To estimate ozonesonde sampling biases, we computed model bias separately for global coverage and the ozonesonde network. The ozonesonde sampling bias in the evaluated model bias for the seasonal mean concentration relative to global

  16. A stable, unbiased, long-term satellite based data record of sea surface temperature from ESA's Climate Change Initiative

    Science.gov (United States)

    Rayner, Nick; Good, Simon; Merchant, Chris

    2013-04-01

    The study of climate change demands long-term, stable observational records of climate variables such as sea surface temperature (SST). ESA's Climate Change Initiative was set up to unlock the potential of satellite data records for this purpose. As part of this initiative, 13 projects were established to develop the data records for different essential climate variables - aerosol, cloud, fire, greenhouse gases, glaciers, ice sheets, land cover, ocean colour, ozone, sea ice, sea level, soil moisture and SST. In this presentation we describe the development work that has taken place in the SST project and present new prototype data products that are available now for users to trial. The SST project began in 2010 and has now produced two prototype products. The first is a long-term product (covering mid-1991 - 2010 currently, but with a view to update this in the future), which prioritises length of data record and stability over other considerations. It is based on data from the Along-Track Scanning Radiometer (ATSR) and Advanced Very-High Resolution Radiometer (AVHRR) series of satellite instruments. The product aims to combine the favourable stability and bias characteristics of ATSR data with the geographical coverage achieved with the AVHRR series. Following an algorithm selection process, an optimal estimation approach to retrieving SST from the satellite measurements from both sensors was adopted. The retrievals do not depend on in situ data and so this data record represents an independent assessment of SST change. In situ data are, however, being used to validate the resulting data. The second data product demonstrates the coverage that can be achieved using the modern satellite observing system including, for example, geostationary satellite data. Six months worth of data have been processed for this demonstration product. The prototype SST products will be released in April to users to trial in their work. The long term product will be available as

  17. Global temperature estimates in the troposphere and stratosphere: a validation study of COSMIC/FORMOSAT-3 measurements

    Directory of Open Access Journals (Sweden)

    P. Kishore

    2009-02-01

    Full Text Available This paper mainly focuses on the validation of temperature estimates derived with the newly launched Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC/Formosa Satellite 3 (FORMOSAT-3 system. The analysis is based on the radio occultation (RO data samples collected during the first year observation from April 2006 to April 2007. For the validation, we have used the operational stratospheric analyses including the National Centers for Environmental Prediction - Reanalysis (NCEP, the Japanese 25-year Reanalysis (JRA-25, and the United Kingdom Met Office (MetO data sets. Comparisons done in different formats reveal good agreement between the COSMIC and reanalysis outputs. Spatially, the largest deviations are noted in the polar latitudes, and height-wise, the tropical tropopause region noted the maximum differences (2–4 K. We found that among the three reanalysis data sets the NCEP data sets have the best resemblance with the COSMIC measurements.

  18. Design of a Satellite-based AIS Signal processor based on FPGA%基于FPGA的星载AIS信号处理器的设计

    Institute of Scientific and Technical Information of China (English)

    张喆

    2012-01-01

    According to the characters of the space-based AIS(Automatic Identification System) receiver;a system design scheme is proposed to realize the efficient receiver of signal.It is introduced the project of the hardware realization of the satellite-based AIS signal processor parts in detail and emphasized on how to realize the signal processing based on FPGA.Some simulations and experiment based on AIS receiver are presented to verifythe validity and feasibility of the proposed scheme.It is proved that this signal processor performance can meet the requirements of the space-base AIS receiver system by performing some testing.%针对星载AIS(船舶自动识别系统)接收系统提出了实现信号有效接收的总体方案。重点提供星载AIS信号处理器的硬件电路设计和基于FPGA信号处理软件设计。以AIS接收机整机为测试平台,通过仿真和试验验证了星载AIS接收机整机设计的有效性和可行性,此信号处理器可以满足星载AIS接收机的需求。

  19. Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

    Science.gov (United States)

    Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath

    2016-04-01

    Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

  20. Offshore wind resource estimation for wind energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Mouche, A.

    2010-01-01

    Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite...... observations are compared to selected offshore meteorological masts in the Baltic Sea and North Sea. The overall aim of the Norsewind project is a state-of-the-art wind atlas at 100 m height. The satellite winds are all valid at 10 m above sea level. Extrapolation to higher heights is a challenge. Mesoscale...... modeling of the winds at hub height will be compared to data from wind lidars observing at 100 m above sea level. Plans are also to compare mesoscale model results and satellite-based estimates of the offshore wind resource....

  1. ERA-Interim再分析和NCEP FNL分析资料在东南极中山站至Dome A断面的适用性研究%A SURFACE CLIMATOLOGICAL VALIDATION OF ECMWF ERA-INTERIM REANALYSIS AND NCEP FNL ANALYSIS OVER EAST ANTARCTICA

    Institute of Scientific and Technical Information of China (English)

    马永锋; 卞林根

    2014-01-01

    The reliability of the European Centre for Medium-range Weather Forecasts (ECMWF)ERA-Interim reanalys-is and the National Centers for Environmental Prediction (NCEP)FNL analysis over East Antarctica were investiga-ted by comparing observations of surface pressure,temperature,specific humidity,and winds collected in 2008 a-long the transverse route from Zhongshan Station to Dome A.Results showed that the surface temperatures of the ERA-Interim reanalysis were closer to observational data than those of the FNL analysis,with a monthly mean abso-lute deviation <1℃in Antarctic coastal areas and <2℃in interior regions.The temperatures of the FNL analysis were significantly warmer than observations on the interior plateau,especially in winter the positive biases can up to 8—1 0℃.Therefore,the FNL analysis can not be directly used to study surface temperature change on the Antarc-tic Plateau.The surface pressures of the FNL analysis were much closer to observations than those of the ERA-In-terim reanalysis,with monthly mean biases of ~1 hPa,while the ERA-Interim reanalysis showed a significant sys-temic low in coastal regions.The annual/seasonal averaged absolute biases of near surface wind speed between the ERA-Interim reanalysis,the FNL analysis,and observations were less than 1 m·s-1 over coastal and katabatic re-gions,and about 2—4 m·s-1 over the interior plateau,with absolute wind direction biases of <1 0°.In addition, the ERA-Interim reanalysis described katabatic winds more accurately than the FNL analysis.%利用2008年南极中山站至Dome A断面上观测站的近地面气象观测资料对ECMWF ERA-Interim再分析和NCEP FNL分析资料在东南极地区的适用性进行了验证。结果表明,ERA-Interim再分析资料的气温表现明显优于FNL分析资料,其与观测的年均绝对偏差在南极大陆沿岸地区<1℃,在内陆高原<2℃;而FNL分析资料的气温在南极内陆高原地区较观测明显偏

  2. Means and Trends in Solar Radiation: Results From Two Global Data Sets and Effects on Estimated Net Primary Production

    Science.gov (United States)

    Hicke, J. A.

    2005-12-01

    Downwelling surface solar radiation is an important factor driving plant productivity, and clouds and aerosols are major factors responsible for interannual variability in downwelling radiation. Global ecosystem models require spatially extensive data sets that vary interannually to capture effects that potentially drive changes in ecosystem function. Representative global solar radiation data sets include National Centers for Environmental Prediction (NCEP) reanalyses and Goddard Institute for Space Studies (GISS) calculations that included satellite observations of cloud properties. The CASA light-use efficiency model, which utilizes solar radiation and satellite-derived vegetation information, was run with the two solar radiation data sets to explore how differences affect estimated net primary production (NPP). Mean global NCEP solar radiation exceeded that from GISS by 16%, likely as a result of lower cloudiness within the NCEP reanalyses compared to satellite observations. Neither data set resulted in a significant trend in growing season radiation over the study period (1984-2000). Locally, relative differences were up to 40% in the mean and 10% in the trend of solar radiation and NPP, and varied in sign across the globe.

  3. A satellite-based climatology (1989-2012) of lake surface water temperature from AVHRR 1-km for Central European water bodies

    Science.gov (United States)

    Riffler, Michael; Wunderle, Stefan

    2013-04-01

    The temperature of lakes is an important parameter for lake ecosystems influencing the speed of physio-chemical reactions, the concentration of dissolved gazes (e.g. oxygen), and vertical mixing. Even small temperature changes might have irreversible effects on the lacustrine system due to the high specific heat capacity of water. These effects could alter the quality of lake water depending on parameters like lake size and volume. Numerous studies mention lake water temperature as an indicator of climate change and in the Global Climate Observing System (GCOS) requirements it is listed as an essential climate variable. In contrast to in situ observations, satellite imagery offers the possibility to derive spatial patterns of lake surface water temperature (LSWT) and their variability. Moreover, although for some European lakes long in situ time series are available, the temperatures of many lakes are not measured or only on a non-regular basis making these observations insufficient for climate monitoring. However, only few satellite sensors offer the possibility to analyze time series which cover more than 20 years. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown on the National Oceanic and Atmospheric Administration (NOAA) Polar Operational Environmental Satellites (POES) and on the Meteorological Operational Satellites (MetOp) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) as a heritage instrument for almost 35 years. It will be carried on for at least ten more years finally offering a unique opportunity for satellite-based climate studies. Herein we present the results from a study initiated by the Swiss GCOS office to generate a satellite-based LSWT climatology for the pre-alpine water bodies in Switzerland. It relies on the extensive AVHRR 1-km data record (1985-2012) of the Remote Sensing Research Group at the University of Bern (RSGB) and has been derived from the AVHRR/2

  4. Satellite Based Education and Training in Remote Sensing and Geo-Information AN E-Learning Approach to Meet the Growing Demands in India

    Science.gov (United States)

    Raju, P. L. N.; Gupta, P. K.

    2012-07-01

    One of the prime activities of Indian Space Research Organisation's (ISRO) Space Program is providing satellite communication services, viz., television broadcasting, mobile communication, cyclone disaster warning and rescue operations etc. so as to improve their economic conditions, disseminate technical / scientific knowledge to improve the agriculture production and education for rural people of India. ISRO, along with National Aeronautical and Space Administration (NASA) conducted experimental satellite communication project i.e. Satellite Instructional Television Experiment (SITE) using NASA's Advanced Telecommunication Satellite (i.e. ATS 6) with an objective to educate poor people of India via satellite broadcasting in 1975 and 1976, covering more than 2600 villages in six states of India and territories. Over the years India built communication satellites indigenously to meet the communication requirements of India. This has further lead to launch of an exclusive satellite from ISRO for educational purposes i.e. EDUSAT in 2004 through which rich audio-video content is transmitted / received, recreating virtual classes through interactivity. Indian Institute of Remote Sensing (IIRS) established in 1966, a premier institute in south East Asia in disseminating Remote Sensing (RS) and Geographical Information System (GIS), mainly focusing on contact based programs. But expanded the scope with satellite based Distance Learning Programs for Universities, utilizing the dedicated communication satellite i.e. EDUSAT in 2007. IIRS conducted successfully eight Distance Learning Programs in the last five years and training more than 6000 students mainly at postgraduate level from more than 60 universities /Institutions spread across India. IIRS obtained feedback and improved the programs on the continuous basis. Expanded the scope of IIRS outreach program to train user departments tailor made in any of the applications of Remote Sensing and Geoinformation, capacity

  5. Satellite-Based Tropospheric NO2 Column Trends in the Last 10 Years Over Mexican Urban Areas Measured by the Ozone Monitoring Instrument

    Science.gov (United States)

    Rivera, C. I.; Stremme, W.; Grutter, M.

    2015-12-01

    Population density and economic activities in urban agglomerations have drastically increased in many cities in Mexico during the last decade. Several factors are responsible for increased urbanization such as a shift of people from rural to urban areas while looking for better education, services and job opportunities as well as the natural growth of the urban areas themselves. Urbanization can create great social, economic and environmental pressures and changes which can easily be observed in most urban agglomerations in the world. In this study, we have focused on analyzing tropospheric NO2 (nitrogen dioxide) column trends over Mexican urban areas that have a population of at least one million inhabitants according to the latest 2010 population census. Differential Optical Absorption Spectroscopy (DOAS) measurements of NO2 conducted by the space-borne Ozone Monitoring Instrument (OMI) on board the Aura satellite between 2005 and 2014 have been used for this analysis. This dataset has allowed us to obtain a satellite-based 10-year tropospheric NO2 column trend over the most populated Mexican cities which include the dominating metropolitan area of Mexico City with more than twenty million inhabitants as well as ten other Mexican cities with a population ranging between one to five million inhabitants with a wide range of activities (commercial, agricultural or heavily industrialized) as well as two important border crossings. Distribution maps of tropospheric NO2 columns above the studied urban agglomerations were reconstructed from the analyzed OMI dataset, allowing to identify areas of interest due to clear NO2 enhancements inside these urban regions.

  6. NCEP、ECMWF及CMC全球集合预报业务系统发展综述%A Review on the developments of NCEP, ECMWF and CMC global ensemble forecast system

    Institute of Scientific and Technical Information of China (English)

    麻巨慧; 朱跃建; 王盘兴; 段明铿

    2011-01-01

    总结了目前最具代表性的3个全球集合预报系统(global ensemble forecast system,GEFS)——美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)、欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)和加拿大气象中心(Canadian Meteorological Centre,CMC)建成至今的发展概况。由于计算资源的不断扩展,各中心集合预报系统的模式分辨率、集合成员数也随之增加。同时各中心都在不断地致力于发展和完善初始和模式扰动方法,来更好地估计与初值和模式有关的不确定性,促进预报技巧的提高。其中初始扰动方法从最初的奇异向量法(ECMWF)、增殖向量法(NCEP)和观测扰动法(CMC)更新为现在的集合资料同化—奇异向量法(ECMWF)、重新尺度化集合转换法(NCEP)和集合卡尔曼滤波(CMC)。在估计模式不确定性方面,ECMWF和CMC都修订了各自的随机参数化方案和多参数化方案,NCEP最近也在模式中加入了随机全倾向扰动。为提高全球高影响天气预报的准确率,TIGGE计划(the THORPEX interactive grand global ensemble)的提出增进了国际间对多模式、多中心集合预报的合作研究,北美集合预报系统(North American ensemble forecast system,NAEFS)为建立全球多模式集合预报系统提供了业务框架,这都将有助于未来全球交互式业务预报系统的构建。

  7. Satellite Based Live and Interactive Distance Learning Program in the Field of Geoinformatics - a Perspective of Indian Institute of Remote Sensing, India

    Science.gov (United States)

    Raju, P. L. N.; Gupta, P. K.; Roy, P. S.

    2011-09-01

    Geoinformatics is a highly specialized discipline that deals with Remote Sensing, Geographical Information System (GIS), Global Positioning System (GPS) and field surveys for assessing, quantification, development and management of resources, planning and infrastructure development, utility services etc. Indian Institute of Remote Sensing (IIRS), a premier institute and one of its kinds has played a key role for capacity Building in this specialized area since its inception in 1966. Realizing the large demand, IIRS has started outreach program in basics of Remote Sensing, GIS and GPS for universities and institutions. EDUSAT (Educational Satellite) is the communication satellite built and launched by ISRO in 2004 exclusively for serving the educational sector to meet the demand for an interactive satellite based distance education system for the country. IIRS has used EDUSAT (shifted to INSAT 4 CR recently due to termination of services from EDUSAT) for its distance learning program to impart basic training in Remote Sensing, GIS and GPS, catering to the universities spread across India. The EDUSAT based training is following similar to e-learning method but has advantage of live interaction sessions between teacher and the students when the lecture is delivered using EDUSAT satellite communication. Because of its good quality reception the interactions are not constrained due to bandwidth problems of Internet. National Natural Resource Management System, Department of Space, Government of India, under Standing Committee in Training and Technology funded this unique program to conduct the basic training in Geoinformatics. IIRS conducts 6 weeks basic training course on "Remote Sensing, GIS and GPS" regularly since the year 2007. The course duration is spread over the period of 3 months beginning with the start of the academic year (1st semester) i.e., July to December every year, for university students. IIRS has utilized EDUSAT satellite for conducting 4 six weeks

  8. SATELLITE BASED LIVE AND INTERACTIVE DISTANCE LEARNING PROGRAM IN THE FIELD OF GEOINFORMATICS – A PERSPECTIVE OF INDIAN INSTITUTE OF REMOTE SENSING, INDIA

    Directory of Open Access Journals (Sweden)

    P. L. N. Raju

    2012-09-01

    Full Text Available Geoinformatics is a highly specialized discipline that deals with Remote Sensing, Geographical Information System (GIS, Global Positioning System (GPS and field surveys for assessing, quantification, development and management of resources, planning and infrastructure development, utility services etc. Indian Institute of Remote Sensing (IIRS, a premier institute and one of its kinds has played a key role for capacity Building in this specialized area since its inception in 1966. Realizing the large demand, IIRS has started outreach program in basics of Remote Sensing, GIS and GPS for universities and institutions. EDUSAT (Educational Satellite is the communication satellite built and launched by ISRO in 2004 exclusively for serving the educational sector to meet the demand for an interactive satellite based distance education system for the country. IIRS has used EDUSAT (shifted to INSAT 4 CR recently due to termination of services from EDUSAT for its distance learning program to impart basic training in Remote Sensing, GIS and GPS, catering to the universities spread across India. The EDUSAT based training is following similar to e-learning method but has advantage of live interaction sessions between teacher and the students when the lecture is delivered using EDUSAT satellite communication. Because of its good quality reception the interactions are not constrained due to bandwidth problems of Internet. National Natural Resource Management System, Department of Space, Government of India, under Standing Committee in Training and Technology funded this unique program to conduct the basic training in Geoinformatics. IIRS conducts 6 weeks basic training course on "Remote Sensing, GIS and GPS" regularly since the year 2007. The course duration is spread over the period of 3 months beginning with the start of the academic year (1st semester i.e., July to December every year, for university students. IIRS has utilized EDUSAT satellite for

  9. Understanding Droughts and their Agricultural Impact in North America at the Basin Scale through the Development of Satellite Based Drought Indicators

    Science.gov (United States)

    Munoz Hernandez, A.; Lawford, R. G.

    2012-12-01

    Drought is a major constraint severely affecting numerous agricultural regions in North America. Decision makers need timely information on the existence of a drought as well as its intensity, frequency, likely duration, and economic and social effects in order to implement adaptation strategies and minimize its impacts. Countries like Mexico and Canada face a challenge associated with the lack of consistent and reliable in-situ data that allows the computation of drought indicators at resolutions that effectively supports decision makers at the watershed scale. This study focuses on (1) the development of near-real time drought indicators at high resolution utilizing various satellite data for use in improving adaptation plans and mitigation actions at the basin level; (2) the quantification of the relationships between current and historical droughts and their agricultural impacts by evaluating thresholds for drought impacts; and (3) the assessment of the effects of existing water policies, economic subsidies, and infrastructure that affect the vulnerability of a particular region to the economic impacts of a drought. A pilot study area located in Northwest Mexico and known as the Rio Yaqui Basin was selected for this study in order to make comparisons between the satellite based indicators derived from currently available satellite products to provide an assessment of the quality of the products generated. The Rio Yaqui Basin, also referred to as the "bread basket" of Mexico, is situated in an arid to semi-arid region where highly sophisticated irrigation systems have been implemented to support extensive agriculture. Although for many years the irrigation systems acted as a safety net for the farmers, recent droughts have significantly impacted agricultural output, affected thousands of people, and increase the dependence on groundwater. The drought indices generated are used in conjunction with a decision-support model to provide information on drought impacts

  10. Is China's fifth-largest inland lake to dry-up? Incorporated hydrological and satellite-based methods for forecasting Hulun lake water levels

    Science.gov (United States)

    Cai, Zuansi; Jin, Taoyong; Li, Changyou; Ofterdinger, Ulrich; Zhang, Sheng; Ding, Aizhong; Li, Jiancheng

    2016-08-01

    Hulun Lake, China's fifth-largest inland lake, experienced severe declines in water level in the period of 2000-2010. This has prompted concerns whether the lake is drying up gradually. A multi-million US dollar engineering project to construct a water channel to transfer part of the river flow from a nearby river to maintain the water level was completed in August 2010. This study aimed to advance the understanding of the key processes controlling the lake water level variation over the last five decades, as well as investigate the impact of the river transfer engineering project on the water level. A water balance model was developed to investigate the lake water level variations over the last five decades, using hydrological and climatic data as well as satellite-based measurements and results from land surface modelling. The investigation reveals that the severe reduction of river discharge (-364 ± 64 mm/yr, ∼70% of the five-decade average) into the lake was the key factor behind the decline of the lake water level between 2000 and 2010. The decline of river discharge was due to the reduction of total runoff from the lake watershed. This was a result of the reduction of soil moisture due to the decrease of precipitation (-49 ± 45 mm/yr) over this period. The water budget calculation suggests that the groundwater component from the surrounding lake area as well as surface run off from the un-gauged area surrounding the lake contributed ∼ net 210 Mm3/yr (equivalent to ∼ 100 mm/yr) water inflows into the lake. The results also show that the water diversion project did prevent a further water level decline of over 0.5 m by the end of 2012. Overall, the monthly water balance model gave an excellent prediction of the lake water level fluctuation over the last five decades and can be a useful tool to manage lake water resources in the future.

  11. Global Monitoring RSEM System for Crop Production by Incorporating Satellite-based Photosynthesis Rates and Anomaly Data of Sea Surface Temperature

    Science.gov (United States)

    Kaneko, D.; Sakuma, H.

    2014-12-01

    The first author has been developing RSEM crop-monitoring system using satellite-based assessment of photosynthesis, incorporating meteorological conditions. Crop production comprises of several stages and plural mechanisms based on leaf photosynthesis, surface energy balance, and the maturing of grains after fixation of CO2, along with water exchange through soil vegetation-atmosphere transfer. Grain production in prime countries appears to be randomly perturbed regionally and globally. Weather for crop plants reflects turbulent phenomena of convective and advection flows in atmosphere and surface boundary layer. It has been difficult for scientists to simulate and forecast weather correctly for sufficiently long terms to crop harvesting. However, severely poor harvests related to continental events must originate from a consistent mechanism of abnormal energetic flow in the atmosphere through both land and oceans. It should be remembered that oceans have more than 100 times of energy storage compared to atmosphere and ocean currents represent gigantic energy flows, strongly affecting climate. Anomalies of Sea Surface Temperature (SST), globally known as El Niño, Indian Ocean dipole, and Atlantic Niño etc., affect the seasonal climate on a continental scale. The authors aim to combine monitoring and seasonal forecasting, considering such mechanisms through land-ocean biosphere transfer. The present system produces assessments for all continents, specifically monitoring agricultural fields of main crops. Historical regions of poor and good harvests are compared with distributions of SST anomalies, which are provided by NASA GSFC. Those comparisons fairly suggest that the Worst harvest in 1993 and the Best in 1994 relate to the offshore distribution of low temperature anomalies and high gaps in ocean surface temperatures. However, high-temperature anomalies supported good harvests because of sufficient solar radiation for photosynthesis, and poor harvests because

  12. Parameter Estimation

    DEFF Research Database (Denmark)

    2011-01-01

    of optimisation techniques coupled with dynamic solution of the underlying model. Linear and nonlinear approaches to parameter estimation are investigated. There is also the application of maximum likelihood principles in the estimation of parameters, as well as the use of orthogonal collocation to generate a set......In this chapter the importance of parameter estimation in model development is illustrated through various applications related to reaction systems. In particular, rate constants in a reaction system are obtained through parameter estimation methods. These approaches often require the application...... of algebraic equations as the basis for parameter estimation.These approaches are illustrated using estimations of kinetic constants from reaction system models....

  13. The Surface-Forced Overturning of the North Atlantic: Estimates from Modern Era Atmospheric Reanalysis Datasets

    Science.gov (United States)

    Grist, Jeremy; Josey, Simon; Marsh, Robert; Kwon, Young-Oh; Bingham, Rory; Blaker, Adam

    2014-05-01

    Estimates of the recent mean and time varying water mass transformation rates associated with North Atlantic surface-forced overturning are presented. The estimates are derived from heat and freshwater surface fluxes and sea surface temperature fields from six atmospheric reanalyses (JRA, NCEP-1, NCEP-2, ERA-I, CFSR and MERRA) together with sea surface salinity fields from two globally gridded data sets (World Ocean Atlas and EN3). The resulting twelve estimates of the 1979-2007 mean surface-forced streamfunction all depict a sub-polar cell, with maxima north of 45oN, near σ = 27.5 kgm-3, and a sub-tropical cell between 20oN and 40oN, near σ = 26.1 kgm-3. The mean magnitude of the sub-polar cell varies between 12-18 Sv, consistent with estimates of the overturning circulation from sub-surface observations. Analysis of the thermal and haline components of the surface density fluxes indicate large differences in the inferred low latitude circulation are largely due to the biases in reanalysis net heat flux fields, which range in the global mean from -13 Wm-2 to 19 Wm-2. The different estimates of temporal variability in the sub-polar cell are well correlated with each other. This suggests the uncertainty associated with the choice of reanalysis product does not critically limit the ability of the method to infer the variability in the sub-polar overturning. In contrast, the different estimates of sub-tropical variability are poorly correlated with each other, and only a subset of them capture a significant fraction of the variability in independently estimated North Atlantic Sub-Tropical Mode Water volume.

  14. Regional Bias of Satellite Precipitation Estimates

    Science.gov (United States)

    Modrick, T. M.; Georgakakos, K. P.; Spencer, C. R.

    2012-12-01

    Satellite-based estimates of precipitation have improved the spatial availability of precipitation data particularly for regions with limited gauge networks due to limited accessibility or infrastructure. Understanding the quality and reliability of satellite precipitation estimates is important, especially when the estimates are utilitized for real-time hydrologic forecasting and for fast-responding phenomena. In partnership with the World Meteorological Organization (WMO), the U.S. Agency of International Development (USAID) and the National Ocean and Atmospheric Administration (NOAA), the Hydrologic Research Center has begun implementation of real-time flash flood warning systems for diverse regions around the world. As part of this effort, bias characteristics of satellite precipitation have been examined in these various regions, such includes portions of Southeastern Asia, Southeastern Europe, the Middle East, Central America, and the southern half of the African continent. The work has focused on the Global Hydro-Estimator (GHE) precipitation product from NOAA/NESDIS. These real-time systems utilize the GHE given low latency times of this product. This presentation focuses on the characterization of precipitation bias as compared to in-situ gauge records, and the regional variations or similarities. Additional analysis is currently underway considering regional bias for other satellite precipitation products (e.g., CMORPH) for comparison with the GHE results.

  15. The Comparison of Geopotential Height Between NCEP and JRA Reanalysis Data and Sounding Data%NCEP和JRA再分析资料与探空资料的位势高度比较分析

    Institute of Scientific and Technical Information of China (English)

    田笑; 智协飞; 徐海明

    2013-01-01

    利用中国高空规定层月值数据集中的探空资料和NCEP,JRA再分析资料,对850 hPa、500hPa、100 hPa上的位势高度趋势、位势高度差值和相关程度进行了比较.结果表明:从位势高度的趋势上来看,在850 hPa、500 hPa上再分析资料能客观反映探空资料的位势高度趋势,而在100hPa上再分析资料的趋势明显偏高;从位势高度的差值来看,在850 hPa和500 hPa上再分析资料与探空资料差异较小,而在100hPa上差异明显增大;从相关性看,在500 hPa上,再分析资料与探空资料的相关性较好,而850 hPa,100 hPa再分析资料与探空资料存在显著差异,尤其是100 hPa;从不同的再分析资料看,与探空资料比较,NCEP资料的位势高度趋势、位势高度差值和位势高度相关度比JRA资料具有更高的可信度,而且东部地区和低纬再分析资料的可信度较高.%Based on China sounding data of assigned height layer in the monthly data set and NCEP and JRA reanalysis data,the tendencies,differences and correlation of geopotential height fields on the level of 850 hPa,500 hPa,100 hPa were compared in this paper.Results show that from the aspect of the geopotential height tendency,sounding data can be objectively reflected by reanalysis data on the level of 850 hPa,500 hPa,while the geopotential height tendency of reanalysis data was significantly higher than that of sounding data on the level of 100 hPa.As for the differences of the geopotential height,there was little differences on the level of 850 hPa and 500 hPa between the reanalysis data and sounding data,but on the level of 100 hPa,the differences increased obviously.The correlation between reanalysis data and sounding data was well on the level of 500 hPa,but there was obvious difference between reanalysis data and sounding data on the level of 850 hPa and 100 hPa,especially on 100 hPa.In comparison with sounding data,the tendency,difference and correlation of potential height

  16. Global (50°S-50°N) distribution of water vapor observed by COSMIC GPS RO: Comparison with GPS radiosonde, NCEP, ERA-Interim, and JRA-25 reanalysis data sets

    Science.gov (United States)

    Kishore, P.; Venkat Ratnam, M.; Namboothiri, S. P.; Velicogna, Isabella; Basha, Ghouse; Jiang, J. H.; Igarashi, K.; Rao, S. V. B.; Sivakumar, V.

    2011-08-01

    In this study, global (50°S-50°N) distribution of water vapor is investigated using COSMIC GPS RO measurements. Detailed comparisons have been made between COSMIC and high resolution GPS radiosonde measurements across 13 tropical stations and model outputs (ERA-Interim, NCEP, and JRA-25 reanalyses data sets). In comparison with independent techniques like radiosonde (Väisälä), it is found that COSMIC GPS RO wet profiles are accurate up to 7-8 km (assuming radiosonde as standard technique). In general, comparisons with corresponding seasonal means of model outputs are qualitatively in good agreement, although they differ quantitatively especially over convective regions of South America, Africa, and Indonesia. In tropical latitudes, the COSMIC specific humidity values are higher than the model outputs. Among various model outputs, ERA-Interim data set show near realistic features to that observed by COSMIC GPS RO measurements. Large asymmetry in the specific humidity distribution is observed between northern and southern hemispheres.

  17. Parameter Estimation

    DEFF Research Database (Denmark)

    Sales-Cruz, Mauricio; Heitzig, Martina; Cameron, Ian;

    2011-01-01

    of optimisation techniques coupled with dynamic solution of the underlying model. Linear and nonlinear approaches to parameter estimation are investigated. There is also the application of maximum likelihood principles in the estimation of parameters, as well as the use of orthogonal collocation to generate a set...

  18. Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

    Science.gov (United States)

    Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

    2012-01-01

    The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

  19. Satellite-Based NO2 and Model Validation in a National Prediction Model Based on Universal Kriging and Land-Use Regression.

    Science.gov (United States)

    Young, Michael T; Bechle, Matthew J; Sampson, Paul D; Szpiro, Adam A; Marshall, Julian D; Sheppard, Lianne; Kaufman, Joel D

    2016-04-05

    Epidemiological studies increasingly rely on exposure prediction models. Predictive performance of satellite data has not been evaluated in a combined land-use regression/spatial smoothing context. We performed regionalized national land-use regression with and without universal kriging on annual average NO2 measurements (1990-2012, contiguous U.S. EPA sites). Regression covariates were dimension-reduced components of 418 geographic variables including distance to roadway. We estimated model performance with two cross-validation approaches: using randomly selected groups and, in order to assess predictions to unmonitored areas, spatially clustered cross-validation groups. Ground-level NO2 was estimated from satellite-derived NO2 and was assessed as an additional regression covariate. Kriging models performed consistently better than nonkriging models. Among kriging models, conventional cross-validated R(2) (R(2)cv) averaged over all years was 0.85 for the satellite data models and 0.84 for the models without satellite data. Average spatially clustered R(2)cv was 0.74 for the satellite data models and 0.64 for the models without satellite data. The addition of either kriging or satellite data to a well-specified NO2 land-use regression model each improves prediction. Adding the satellite variable to a kriging model only marginally improves predictions in well-sampled areas (conventional cross-validation) but substantially improves predictions for points far from monitoring locations (clustered cross-validation).

  20. Satellite-based 3D structure of cloud and aerosols over the Indian Monsoon region: implications for aerosol-cloud interaction

    Science.gov (United States)

    Dey, Sagnik; Sengupta, Kamalaika; Basil, George; Das, Sushant; Nidhi, Nidhi; Dash, S. K.; Sarkar, Arjya; Srivastava, Parul; Singh, Ajit; Agarwal, P.

    2012-11-01

    Accurate knowledge of vertical distributions of aerosol and cloud fields and their space-time variations are required to reduce the uncertainty in estimated climate forcing. Here, multi-sensor (both passive and active) data were used to construct the climatology of 3-D cloud and aerosol fields over the Indian monsoon region. Multilayer clouds are found to persist throughout the year, among which cumulus and stratocumulus dominate the low clouds and cirrus dominates the high clouds. A combination of passive stereo-technique (MISR) and radiometric technique (ISCPP) captures the multilayer cloud structure as revealed by active sensor CALIOP. Coexistence of low clouds throughout the year with high aerosol concentration beneath and above leads to a transition from increasing to decreasing cloud fraction with an increase in aerosol optical depth. Such transition is rapid in the monsoon season due to convergence of low clouds to form high clouds facilitated by high aerosol loading. Further, the regional climate model RegCM 4.1 has been used to examine aerosol-cloud interaction. The aerosol-induced changes of low cloud amount are under-estimated by the model. The observation-based seasonal climatology of aerosol and cloud fields presented here may help in improving the model simulations of cloud variability and associated rainfall.

  1. Diagnosis of the Marine Low Cloud Simulation in the NCAR Community Earth System Model (CESM) and the NCEP Global Forecast System (GFS)-Modular Ocean Model v4 (MOM4) coupled model

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Heng; Mechoso, C. R.; Sun, Rui; Han, J.; Pan, H. L.; Park, S.; Hannay, Cecile; Bretherton, Christopher S.; Teixeira, J.

    2014-07-25

    We present a diagnostic analysis of the marine low cloud climatology simulated by two state-of-the-art coupled atmosphere-ocean models: the NCAR Community Earth System Model (CESM) and the NCEP Global Forecasting System (GFS). In both models, the shallow convection and boundary layer turbulence parameterizations have been recently updated: both models now use a mass-flux scheme for the parameterization of shallow convection, and a turbulence parameterization capable of handling Stratocumulus (Sc)-topped Planetary Boundary Layers (PBLs). For shallow convection, both models employ a convective trigger function based on the concept of convective inhibition and both include explicit convective overshooting/penetrative entrainment formulation. For Sc-topped PBL, both models treat explicitly turbulence mixing and cloud-top entrainment driven by cloud-top radiative cooling. Our focus is on the climatological transition from Sc to shallow Cumulus (Cu)-topped PBL in the subtropical eastern oceans. We show that in the CESM the coastal Sc-topped PBLs in the subtropical Eastern Pacific are well-simulated but the climatological transition from Sc to shallow Cu is too abrupt and happens too close to the coast. By contrast, in the GFS coupled simulation the coastal Sc amount and PBL depth are severely underestimated while the transition from Sc to shallow Cu is ³delayed² and offshore Sc cover is too extensive in the subtropical Eastern Pacific. We discuss the possible connections between such differences in the simulations and differences in the parameterizations of shallow convection and boundary layer turbulence in the two models.

  2. Satellite air temperature estimation for monitoring the canopy layer heat island of Milan

    DEFF Research Database (Denmark)

    Pichierri, Manuele; Bonafoni, Stefania; Biondi, Riccardo

    2012-01-01

    2007 and 2010 were processed. Analysis of the canopy layer heat island (CLHI) maps during summer months reveals an average heat island effect of 3–4K during nighttime (with some peaks around 5K) and a weak CLHI intensity during daytime. In addition, the satellite maps reveal a well defined island shape......In this work, satellite maps of the urban heat island of Milan are produced using satellite-based infrared sensor data. For this aim, we developed suitable algorithms employing satellite brightness temperatures for the direct air temperature estimation 2 m above the surface (canopy layer), showing...

  3. Estimating Utility

    DEFF Research Database (Denmark)

    Arndt, Channing; Simler, Kenneth R.

    2010-01-01

    an information-theoretic approach to estimating cost-of-basic-needs (CBN) poverty lines that are utility consistent. Applications to date illustrate that utility-consistent poverty measurements derived from the proposed approach and those derived from current CBN best practices often differ substantially......, with the current approach tending to systematically overestimate (underestimate) poverty in urban (rural) zones....

  4. Satellite-based remote sensing of running water habitats at large riverscape scales: Tools to analyze habitat heterogeneity for river ecosystem management

    Science.gov (United States)

    Hugue, F.; Lapointe, M.; Eaton, B. C.; Lepoutre, A.

    2016-01-01

    We illustrate an approach to quantify patterns in hydraulic habitat composition and local heterogeneity applicable at low cost over very large river extents, with selectable reach window scales. Ongoing developments in remote sensing and geographical information science massively improve efficiencies in analyzing earth surface features. With the development of new satellite sensors and drone platforms and with the lowered cost of high resolution multispectral imagery, fluvial geomorphology is experiencing a revolution in mapping streams at high resolution. Exploiting the power of aerial or satellite imagery is particularly useful in a riverscape research framework (Fausch et al., 2002), where high resolution sampling of fluvial features and very large coverage extents are needed. This study presents a satellite remote sensing method that requires very limited field calibration data to estimate over various scales ranging from 1 m to many tens or river kilometers (i) spatial composition metrics for key hydraulic mesohabitat types and (ii) reach-scale wetted habitat heterogeneity indices such as the hydromorphological index of diversity (HMID). When the purpose is hydraulic habitat characterization applied over long river networks, the proposed method (although less accurate) is much less computationally expensive and less data demanding than two dimensional computational fluid dynamics (CFD). Here, we illustrate the tools based on a Worldview 2 satellite image of the Kiamika River, near Mont Laurier, Quebec, Canada, specifically over a 17-km river reach below the Kiamika dam. In the first step, a high resolution water depth (D) map is produced from a spectral band ratio (calculated from the multispectral image), calibrated with limited field measurements. Next, based only on known river discharge and estimated cross section depths at time of image capture, empirical-based pseudo-2D hydraulic rules are used to rapidly generate a two-dimensional map of flow velocity

  5. Estimation of Volcanic Ash Plume Top Height using AATSR

    Science.gov (United States)

    Virtanen, Timo; Kolmonen, Pekka; Sogacheva, Larisa; Sundström, Anu-Maija; Rodriguez, Edith; de Leeuw, Gerrit

    2015-04-01

    The AATSR Correlation Method (ACM) height estimation algorithm is presented. The algorithm uses Advanced Along Track Scanning Radiometer (AATSR) satellite data to detect volcanic ash plumes and to estimate the plume top height. The height estimate is based on the stereo-viewing capability of the AATSR instrument, which allows to determine the parallax between the satellite's 55° forward and nadir views, and thus the corresponding height. Besides the stereo view, AATSR provides another advantage compared to other satellite based instruments. With AATSR it is possible to detect ash plumes using brightness temperature difference between thermal infrared (TIR) channels centered at 11 and 12 µm. The automatic ash detection makes the algorithm efficient in processing large quantities of data: the height estimate is calculated only for the ash-flagged pixels. In addition, it is possible to study the effect of using different wavelengths in the height estimate, ranging from visible (555 nm) to thermal infrared (12 µm). The ACM algorithm can be applied to the Sea and Land Surface Temperature Radiometer (SLSTR), scheduled for launch at the end of 2015. Accurate information on the volcanic ash position is important for air traffic safety. The ACM algorithm can provide valuable data of both horizontal and vertical ash dispersion. These data may be useful for comparisons with existing volcanic ash dispersion models and retrieval methods. We present ACM plume top height estimate results for the Eyjafjallajökull eruption, and comparisons against available ground based and satellite observations.

  6. Using new satellite based exposure methods to study the association between pregnancy pm2.5 exposure, premature birth and birth weight in Massachusetts

    Directory of Open Access Journals (Sweden)

    Kloog Itai

    2012-06-01

    Full Text Available Abstract Background Adverse birth outcomes such as low birth weight and premature birth have been previously linked with exposure to ambient air pollution. Most studies relied on a limited number of monitors in the region of interest, which can introduce exposure error or restrict the analysis to persons living near a monitor, which reduces sample size and generalizability and may create selection bias. Methods We evaluated the relationship between premature birth and birth weight with exposure to ambient particulate matter (PM2.5 levels during pregnancy in Massachusetts for a 9-year period (2000–2008. Building on a novel method we developed for predicting daily PM2.5 at the spatial resolution of a 10x10km grid across New-England, we estimated the average exposure during 30 and 90 days prior to birth as well as the full pregnancy period for each mother. We used linear and logistic mixed models to estimate the association between PM2.5 exposure and birth weight (among full term births and PM2.5 exposure and preterm birth adjusting for infant sex, maternal age, maternal race, mean income, maternal education level, prenatal care, gestational age, maternal smoking, percent of open space near mothers residence, average traffic density and mothers health. Results Birth weight was negatively associated with PM2.5 across all tested periods. For example, a 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy was significantly associated with a decrease of 13.80 g [95% confidence interval (CI = −21.10, -6.05] in birth weight after controlling for other factors, including traffic exposure. The odds ratio for a premature birth was 1.06 (95% confidence interval (CI = 1.01–1.13 for each 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy period. Conclusions The presented study suggests that exposure to PM2.5 during the last month of pregnancy contributes to risks for lower birth weight and preterm birth in

  7. Using new satellite based exposure methods to study the association between pregnancy pm2.5 exposure, premature birth and birth weight in Massachusetts

    Science.gov (United States)

    2012-01-01

    Background Adverse birth outcomes such as low birth weight and premature birth have been previously linked with exposure to ambient air pollution. Most studies relied on a limited number of monitors in the region of interest, which can introduce exposure error or restrict the analysis to persons living near a monitor, which reduces sample size and generalizability and may create selection bias. Methods We evaluated the relationship between premature birth and birth weight with exposure to ambient particulate matter (PM2.5) levels during pregnancy in Massachusetts for a 9-year period (2000–2008). Building on a novel method we developed for predicting daily PM2.5 at the spatial resolution of a 10x10km grid across New-England, we estimated the average exposure during 30 and 90 days prior to birth as well as the full pregnancy period for each mother. We used linear and logistic mixed models to estimate the association between PM2.5 exposure and birth weight (among full term births) and PM2.5 exposure and preterm birth adjusting for infant sex, maternal age, maternal race, mean income, maternal education level, prenatal care, gestational age, maternal smoking, percent of open space near mothers residence, average traffic density and mothers health. Results Birth weight was negatively associated with PM2.5 across all tested periods. For example, a 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy was significantly associated with a decrease of 13.80 g [95% confidence interval (CI) = −21.10, -6.05] in birth weight after controlling for other factors, including traffic exposure. The odds ratio for a premature birth was 1.06 (95% confidence interval (CI) = 1.01–1.13) for each 10 μg/m3 increase of PM2.5 exposure during the entire pregnancy period. Conclusions The presented study suggests that exposure to PM2.5 during the last month of pregnancy contributes to risks for lower birth weight and preterm birth in infants. PMID:22709681

  8. Using new satellite based exposure methods to study the association between pregnancy PM₂.₅ exposure, premature birth and birth weight in Massachusetts.

    Science.gov (United States)

    Kloog, Itai; Melly, Steven J; Ridgway, William L; Coull, Brent A; Schwartz, Joel

    2012-06-18

    Adverse birth outcomes such as low birth weight and premature birth have been previously linked with exposure to ambient air pollution. Most studies relied on a limited number of monitors in the region of interest, which can introduce exposure error or restrict the analysis to persons living near a monitor, which reduces sample size and generalizability and may create selection bias. We evaluated the relationship between premature birth and birth weight with exposure to ambient particulate matter (PM₂.₅) levels during pregnancy in Massachusetts for a 9-year period (2000-2008). Building on a novel method we developed for predicting daily PM₂.₅ at the spatial resolution of a 10x10 km grid across New-England, we estimated the average exposure during 30 and 90 days prior to birth as well as the full pregnancy period for each mother. We used linear and logistic mixed models to estimate the association between PM₂.₅ exposure and birth weight (among full term births) and PM₂.₅ exposure and preterm birth adjusting for infant sex, maternal age, maternal race, mean income, maternal education level, prenatal care, gestational age, maternal smoking, percent of open space near mothers residence, average traffic density and mothers health. Birth weight was negatively associated with PM₂.₅ across all tested periods. For example, a 10 μg/m³ increase of PM₂.₅ exposure during the entire pregnancy was significantly associated with a decrease of 13.80 g [95% confidence interval (CI) = -21.10, -6.05] in birth weight after controlling for other factors, including traffic exposure. The odds ratio for a premature birth was 1.06 (95% confidence interval (CI) = 1.01-1.13) for each 10 μg/m3 increase of PM₂.₅ exposure during the entire pregnancy period. The presented study suggests that exposure to PM₂.₅ during the last month of pregnancy contributes to risks for lower birth weight and preterm birth in infants.

  9. Calibration and evaluation of a flood forecasting system: Utility of numerical weather prediction model, data assimilation and satellite-based rainfall

    Science.gov (United States)

    Yucel, I.; Onen, A.; Yilmaz, K. K.; Gochis, D. J.

    2015-04-01

    A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. A comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow is then made. The ten rainfall-runoff events that occurred in the Black Sea Region were used for testing and evaluation. With the availability of streamflow data across rainfall-runoff events, the calibration is only performed on the Bartin sub-basin using two events and the calibrated parameters are then transferred to other neighboring three ungauged sub-basins in the study area. The rest of the events from all sub-basins are then used to evaluate the performance of the WRF-Hydro system with the calibrated parameters. Following model calibration, the WRF-Hydro system was capable of skillfully reproducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simulations where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, as compared with surface rain gauges, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were reduced by

  10. Autonomous navigation method of high elliptical orbit satellite based on celestial navigation and GPS%基于天文/GPS的HEO卫星自主导航方法

    Institute of Scientific and Technical Information of China (English)

    王鹏; 张迎春

    2015-01-01

    为了实现大椭圆轨道(HEO)卫星高精度自主导航,提出一种将直接敏感地平天文导航与全球定位系统(GPS)相结合的组合导航方法.首先,分析卫星轨道��2运动模型及其所受空间摄动,建立卫星轨道动力学模型;然后,分析单一使用天文导航和GPS的优缺点,根据HEO卫星对GPS的可见性,提出在远地点只采用天文导航,而在近地点采用以天文导航为主、适时引入GPS信号进行位速测量辅助修正的方法.通过计算机仿真和结果分析表明了所提出的设计方法导航精度比单一天文导航提高72.4%∼85.6%.%In order to realize autonomous and continuous navigation information outputs for high elliptical orbit(HEO) satellite, new integrated navigation system is proposed based on celestial navigation of directly sensing stellar and global positioning system(GPS) navigation. Firstly, satellite orbit motion model is established on the satellite orbit dynamics��2 model and suffered space perturbation. Moreover, performances of single-use celestial navigation or GPS are analyzed. When the satellite is near the apogee, observation system is established by using only celestial navigation. When the satellite is near the perigee, the estimate covariance is revised through incoming GPS signal to improve the celestial navigation estimate. The autonomous navigation system is designed and simulating. The results of computer simulation show that the navigation accuracy is improved by 72.4%∼85.6%compared with the celestial navigation method.

  11. Estimation of net surface shortwave radiation over the tropical Indian Ocean using geostationary satellite observations: Algorithm and validation

    Science.gov (United States)

    Shahi, Naveen R.; Thapliyal, Pradeep K.; Sharma, Rashmi; Pal, Pradip K.; Sarkar, Abhijit

    2011-09-01

    This paper presents the development of a methodology to estimate the net surface shortwave radiation (SWR) over tropical oceans using half-hourly geostationary satellite estimates of outgoing longwave radiation (OLR). The collocated data set of SWR measured at 13 buoy locations over the Indian Ocean and a Meteosat-derived OLR for the period of 2002-2009 have been used to derive an empirical relationship. The information from the solar zenith angle that determines the amount of solar radiation received at a particular location is used to normalize the SWR to nadir observation in order to make the empirical relationship location independent. As the relationship between SWR and OLR is valid mostly over the warm-pool regions, the present study restricts SWR estimation in the tropical Indian Ocean domain (30°E-110°E, 30°S-30°N). The SWR estimates are validated with an independent collocated data set and subsequently compared with the SWR estimates from the Global Energy and Water Cycle Experiment-Surface Radiation Budget V3.0 (GEWEX-SRB), International Satellite Cloud Climatology Project-Flux Data (ISCCP-FD), and National Centers for Environmental Prediction (NCEP) reanalysis for the year 2007. The present algorithm provides significantly better accuracy of SWR estimates, with a root-mean-square error of 27.3 W m-2 as compared with the values of 32.7, 37.5, and 59.6 W m-2 obtained from GEWEX-SRB, ISCCP-FD, and NCEP, respectively. The present algorithm also provides consistently better SWR compared with other available products under different sky conditions and seasons over Indian Ocean warm-pool regions.

  12. Using Small Drone (UAS) Imagery to Bridge the Gap Between Field- and Satellite-Based Measurements of Vegetation Structure and Change

    Science.gov (United States)

    Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.

    2016-12-01

    Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.

  13. Assessing ecosystem response to multiple disturbances and climate change in South Africa using ground- and satellite-based measurements and model

    Science.gov (United States)

    Kutsch, W. L.; Falge, E. M.; Brümmer, C.; Mukwashi, K.; Schmullius, C.; Hüttich, C.; Odipo, V.; Scholes, R. J.; Mudau, A.; Midgley, G.; Stevens, N.; Hickler, T.; Scheiter, S.; Martens, C.; Twine, W.; Iiyambo, T.; Bradshaw, K.; Lück, W.; Lenfers, U.; Thiel-Clemen, T.; du Toit, J.

    2015-12-01

    Sub-Saharan Africa currently experiences rapidly growing human population, intrinsically tied to substantial changes in land use on shrubland, savanna and mixed woodland ecosystems due to over-exploitation. Significant conversions driving degradation, affecting fire frequency and water availability, and fueling climate change are expected to increase in the immediate future. However, measured data of greenhouse gas emissions as affected by land use change are scarce to entirely lacking from this region. The project 'Adaptive Resilience of Southern African Ecosystems' (ARS AfricaE) conducts research and develops scenarios of ecosystem development under climate change, for management support in conservation or for planning rural area development. This will be achieved by (1) creation of a network of research clusters (paired sites with natural and altered vegetation) along an aridity gradient in South Africa for ground-based micrometeorological in-situ measurements of energy and matter fluxes, (2) linking biogeochemical functions with ecosystem structure, and eco-physiological properties, (3) description of ecosystem disturbance (and recovery) in terms of ecosystem function such as carbon balance components and water use efficiency, (4) set-up of individual-based models to predict ecosystem dynamics under (post) disturbance managements, (5) combination with long-term landscape dynamic information derived from remote sensing and aerial photography, and (6) development of sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation (by a suite of field measurements) of estimates obtained from eddy covariance, model approaches and satellite derivations.

  14. NCEP Real-time Marine Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly surface marine data gathered by NOAA's National Centers for Environmental Prediction. The basic observational data are edited, using a "trimming" procedure...

  15. NCEP Global Data Assimilation System GDAS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data is from NMC initialized analysis (2x/day). It consists of most variables interpolated to pressure surfaces from model (sigma) surfaces.

  16. NCEP Global Ocean Data Assimilation System (GODAS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The GODAS dataset is a real-time ocean analysis and a reanalysis. It is used for monitoring, retrospective analysis as well as for providing oceanic initial...

  17. Understanding of crop phenology using satellite-based retrievals and climate factors - a case study on spring maize in Northeast China plain

    Science.gov (United States)

    Shuai, Yanmin; Xie, Donghui; Wang, Peijuan; Wu, Menxin

    2014-03-01

    Land surface phenology is an efficient bio-indicator for monitoring terrestrial ecosystem variation in response to climate change. Numerous studies point out climate change plays an important role in modulating vegetation phenological events, especially in agriculture. In turn, surface changes caused by geo-biological processes can affect climate transition regionally and perhaps globally, as concluded by Intergovernmental Panel on Climate Change (IPCC) in 2001. Large amounts of research concluded that crops, as one of the most sensitive bio-indicators for climate change, can be strongly influenced by local weather such as temperature, moisture and radiation. Thus, investigating the details of weather impact and the feedback from crops can help improve our understanding of the interaction between crops and climate change at satellite scale. Our efforts start from this point, via case studies over the famous agriculture region in the Northeast China's plain to examine the response of spring maize under temperature and moisture stress. MODIS-based daily green vegetation information together with frequent field specification of the surface phenology as well as continuous measurements of the routine climatic factors during seven years (2003-2009) is used in this paper. Despite the obvious difference in scale between satellite estimations and field observations, the inter- and intra-annual variation of maize in seven-years' growth was captured successfully over three typical spring maize regions (Fuyu, Changling, and Hailun) in Northeast China. The results demonstrate that weather conditions such as changes of temperature and moisture stress provide considerable contribution to the year-to-year variations in the timing of spring maize phenological events.

  18. Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

    Science.gov (United States)

    Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

    2015-01-01

    Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia’s cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and

  19. Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data

    Science.gov (United States)

    Li, Zhanqing; Whitlock, Charles H.; Charlock, Thomas P.

    1995-01-01

    Global sets of surface radiation budget (SRB) have been obtained from satellite programs. These satellite-based estimates need validation with ground-truth observations. This study validates the estimates of monthly mean surface insolation contained in two satellite-based SRB datasets with the surface measurements made at worldwide radiation stations from the Global Energy Balance Archive (GEBA). One dataset was developed from the Earth Radiation Budget Experiment (ERBE) using the algorithm of Li et al. (ERBE/SRB), and the other from the International Satellite Cloud Climatology Project (ISCCP) using the algorithm of Pinker and Laszlo and that of Staylor (GEWEX/SRB). Since the ERBE/SRB data contain the surface net solar radiation only, the values of surface insolation were derived by making use of the surface albedo data contained GEWEX/SRB product. The resulting surface insolation has a bias error near zero and a root-mean-square error (RMSE) between 8 and 28 W/sq m. The RMSE is mainly associated with poor representation of surface observations within a grid cell. When the number of surface observations are sufficient, the random error is estimated to be about 5 W/sq m with present satellite-based estimates. In addition to demonstrating the strength of the retrieving method, the small random error demonstrates how well the ERBE derives from the monthly mean fluxes at the top of the atmosphere (TOA). A larger scatter is found for the comparison of transmissivity than for that of insolation. Month to month comparison of insolation reveals a weak seasonal trend in bias error with an amplitude of about 3 W/sq m. As for the insolation data from the GEWEX/SRB, larger bias errors of 5-10 W/sq m are evident with stronger seasonal trends and almost identical RMSEs.

  20. Global temperature estimates in the troposphere and stratosphere: a validation study of COSMIC/FORMOSAT-3 measurements

    Directory of Open Access Journals (Sweden)

    P. Kishore

    2008-05-01

    Full Text Available This paper mainly focuses on the validation of temperature estimates derived with the newly launched Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC/Formosa Satellite 3 (FORMOSAT-3 system. The analysis is based on the radio occultation (RO data sample collected during the first year observation from April 2006 to April 2007. For the validation, we have used the operational stratospheric analyses (models including the National Centers for Environmental Prediction-Reanalysis (NCEP-Reanalysis, the Japanese 25-year Reanalysis (JRA-25, and the United Kingdom Met Office (MetO data sets. Comparisons done in different formats reveal excellent agreement between the COSMIC and model outputs. Spatially, the largest deviations are noted in the polar latitudes, and height-wise, the tropical tropopause region noted the maximum differences. However, these differences are only 2–4 K. We found that among the three models the NCEP data sets have the best resemblance with the COSMIC measurements. We also have done comparison of specific humidity and refractivity profiles with other measurements/models. Specific humidity profiles show comparatively large differences at altitudes below 5 km. Refractivity profiles derived by the COSMIC and other datasets show very good agreement.

  1. Extreme air-sea surface turbulent fluxes in mid latitudes - estimation, origins and mechanisms

    Science.gov (United States)

    Gulev, Sergey; Natalia, Tilinina

    2014-05-01

    Extreme turbulent heat fluxes in the North Atlantic and North Pacific mid latitudes were estimated from the modern era and first generation reanalyses (NCEP-DOE, ERA-Interim, MERRA NCEP-CFSR, JRA-25) for the period from 1979 onwards. We used direct surface turbulent flux output as well as reanalysis state variables from which fluxes have been computed using COARE-3 bulk algorithm. For estimation of extreme flux values we analyzed surface flux probability density distribution which was approximated by Modified Fisher-Tippett distribution. In all reanalyses extreme turbulent heat fluxes amount to 1500-2000 W/m2 (for the 99th percentile) and can exceed 2000 W/m2 for higher percentiles in the western boundary current extension (WBCE) regions. Different reanalyses show significantly different shape of MFT distribution, implying considerable differences in the estimates of extreme fluxes. The highest extreme turbulent latent heat fluxes are diagnosed in NCEP-DOE, ERA-Interim and NCEP-CFSR reanalyses with the smallest being in MERRA. These differences may not necessarily reflect the differences in mean values. Analysis shows that differences in statistical properties of the state variables are the major source of differences in the shape of PDF of fluxes and in the estimates of extreme fluxes while the contribution of computational schemes used in different reanalyses is minor. The strongest differences in the characteristics of probability distributions of surface fluxes and extreme surface flux values between different reanalyses are found in the WBCE extension regions and high latitudes. In the next instance we analyzed the mechanisms responsible for forming surface turbulent fluxes and their potential role in changes of midlatitudinal heat balance. Midlatitudinal cyclones were considered as the major mechanism responsible for extreme turbulent fluxes which are typically occur during the cold air outbreaks in the rear parts of cyclones when atmospheric conditions

  2. Fault Estimation

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, H.

    2002-01-01

    This paper presents a range of optimization based approaches to fault diagnosis. A variety of fault diagnosis prob-lems are reformulated in the so-called standard problem setup introduced in the literature on robust control. Once the standard problem formulations are given, the fault diagnosis pr...... problems can be solved by standard optimization tech-niques. The proposed methods include: (1) fault diagnosis (fault estimation, (FE)) for systems with model uncertainties; (2) FE for systems with parametric faults, and (3) FE for a class of nonlinear systems.......This paper presents a range of optimization based approaches to fault diagnosis. A variety of fault diagnosis prob-lems are reformulated in the so-called standard problem setup introduced in the literature on robust control. Once the standard problem formulations are given, the fault diagnosis...

  3. Modelagem da maré meteorológica utilizando redes neurais artificiais: uma aplicação para a Baía de Paranaguá-PR, parte 2: dados meteorológicos de reanálise do NCEP/NCAR Meteorological tide modeling using an artificial neural netwok: an aplication to the Paranaguá Bay-PR: part 2: NCEP/NCAR reanalysis meterological data

    Directory of Open Access Journals (Sweden)

    Marilia Mitidieri F. de Oliveira

    2007-04-01

    Full Text Available A variabilidade do nível do mar observado e a maré meteorológica na Baía de Paranaguá-PR foram analisadas, neste trabalho, com os dados maregráficos utilizados na Parte 1 e os dados meteorológicos de reanálise do "National Centers for Environmental Prediction" (NCEP e do "National Center Atmospheric Research" (NCAR pontos de grade no oceano, próximos ao local de estudo, referentes ao mesmo período. As componentes de alta freqüência contidas nos dados de reanálise foram retiradas com o filtro passa-baixa de Thompson, descrito na Parte 1, adaptado para intervalos de 6 horas. Analisou-se as influências das variáveis meteorológicas mais remotas, nas sobre-elevações e abaixamentos do nível do mar observado, utilizando dados de reanálise de pressão e vento. Conforme descrito na Parte 1, as séries foram analisadas, estatisticamente, no domínio do tempo e da freqüência. A série maregráfica filtrada de Cananéia (SP, utilizada para verificar a existência de correlação com a série de Paranaguá, confirmou os estudos de Mesquita (1997 para o litoral Sudeste. Essa correlação foi verificada devido à proximidade da estação de Cananéia ao ponto de grade relativo à pressão. A Rede Neural Artificial (RNA desenvolvida na Parte 1 foi, então, utilizada com os dados de reanálise, mantendo-se a mesma arquitetura de rede com as máximas correlações entre as variáveis de entrada e saída, ajustando-se os parâmetros de taxa de aprendizado e momento para alcançar o melhor desempenho. Os resultados obtidos com ambas as fontes de dados foram comparados e a eficiência da rede foi semelhante à Parte 1 para as simulações de 6h e 12 h. Para as simulações de 18h e 24h, os resultados foram inferiores como os encontrados para a estação de superfície, sugerindo também, o desenvolvimento de outras arquiteturas de rede, visando melhorar as previsões para períodos maiores. Os resultados obtidos com os dados de rean

  4. Time Series Vegetation Aerodynamic Roughness Fields Estimated from MODIS Observations

    Science.gov (United States)

    Borak, Jordan S.; Jasinski, Michael F.; Crago, Richard D.

    2005-01-01

    Most land surface models used today require estimates of aerodynamic roughness length in order to characterize momentum transfer between the surface and atmosphere. The most common method of prescribing roughness is through the use of empirical look-up tables based solely on land cover class. Theoretical approaches that employ satellite-based estimates of canopy density present an attractive alternative to current look-up table approaches based on vegetation cover type that do not account for within-class variability and are oftentimes simplistic with respect to temporal variability. The current research applies Raupach s formulation of momentum aerodynamic roughness to MODIS data on a regional scale in order to estimate seasonally variable roughness and zero-plane displacement height fields using bulk land cover parameters estimated by [Jasinski, M.F., Borak, J., Crago, R., 2005. Bulk surface momentum parameters for satellite-derived vegetation fields. Agric. For. Meteorol. 133, 55-68]. Results indicate promising advances over look-up approaches with respect to characterization of vegetation roughness variability in land surface and atmospheric circulation models.

  5. Digital, Satellite-Based Aeronautical Communication

    Science.gov (United States)

    Davarian, F.

    1989-01-01

    Satellite system relays communication between aircraft and stations on ground. System offers better coverage with direct communication between air and ground, costs less and makes possible new communication services. Carries both voice and data. Because many data exchanged between aircraft and ground contain safety-related information, probability of bit errors essential.

  6. Satellite-based Tropical Cyclone Monitoring Capabilities

    Science.gov (United States)

    Hawkins, J.; Richardson, K.; Surratt, M.; Yang, S.; Lee, T. F.; Sampson, C. R.; Solbrig, J.; Kuciauskas, A. P.; Miller, S. D.; Kent, J.

    2012-12-01

    Satellite remote sensing capabilities to monitor tropical cyclone (TC) location, structure, and intensity have evolved by utilizing a combination of operational and research and development (R&D) sensors. The microwave imagers from the operational Defense Meteorological Satellite Program [Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS)] form the "base" for structure observations due to their ability to view through upper-level clouds, modest size swaths and ability to capture most storm structure features. The NASA TRMM microwave imager and precipitation radar continue their 15+ yearlong missions in serving the TC warning and research communities. The cessation of NASA's QuikSCAT satellite after more than a decade of service is sorely missed, but India's OceanSat-2 scatterometer is now providing crucial ocean surface wind vectors in addition to the Navy's WindSat ocean surface wind vector retrievals. Another Advanced Scatterometer (ASCAT) onboard EUMETSAT's MetOp-2 satellite is slated for launch soon. Passive microwave imagery has received a much needed boost with the launch of the French/Indian Megha Tropiques imager in September 2011, basically greatly supplementing the very successful NASA TRMM pathfinder with a larger swath and more frequent temporal sampling. While initial data issues have delayed data utilization, current news indicates this data will be available in 2013. Future NASA Global Precipitation Mission (GPM) sensors starting in 2014 will provide enhanced capabilities. Also, the inclusion of the new microwave sounder data from the NPP ATMS (Oct 2011) will assist in mapping TC convective structures. The National Polar orbiting Partnership (NPP) program's VIIRS sensor includes a day night band (DNB) with the capability to view TC cloud structure at night when sufficient lunar illumination exits. Examples highlighting this new capability will be discussed in concert with additional data fusion efforts.

  7. Delivery of satellite based broadband services

    Science.gov (United States)

    Chandrasekhar, M. G.; Venugopal, D.

    2007-06-01

    Availability of speedy communication links to individuals and organizations is essential to keep pace with the business and social requirements of this modern age. While the PCs have been continuously growing in processing speed and memory capabilities, the availability of broadband communication links still has not been satisfactory in many parts of the world. Recognizing the need to give fillip to the growth of broadband services and improve the broadband penetration, the telecom policies of different counties have placed special emphasis on the same. While emphasis is on the use of fiber optic and copper in local loop, satellite communications systems will play an important role in quickly establishing these services in areas where fiber and other communication systems are not available and are not likely to be available for a long time to come. To make satellite communication systems attractive for the wide spread of these services in a cost effective way special emphasis has to be given on factors affecting the cost of the bandwidth and the equipment. As broadband services are bandwidth demanding, use of bandwidth efficient modulation technique and suitable system architecture are some of the important aspects that need to be examined. Further there is a need to re-look on how information services are provided keeping in view the user requirements and broadcast capability of satellite systems over wide areas. This paper addresses some of the aspects of delivering broadband services via satellite taking Indian requirement as an example.

  8. On applicability of the photochemical-equilibrium approach for retrieval of O and H mesospheric distributions from the satellite-based measurements of the airglow emission and ozone concentration

    Science.gov (United States)

    Feigin, Alexander; Belikovich, Mikhail; Kulikov, Mikhail

    2016-04-01

    Atomic oxygen and hydrogen are known to be among key components for the photochemistry and energy balance of the Earth's atmosphere between approximately 80 and 100 km altitude (mesopause region). Therefore, obtaining information about the vertical distributions of O and H concentrations is an important task in studies of this region. Solving of this problem is rather difficult due to the absence of regular methods which allow one to direct measurements of distributions of these components in mesosphere. However, indirect methods used to retrieve O and H distributions from the satellite-based measurements of the OH and O2(1D) airglow emission, as well as the data of IR and microwave O3 measurements have a sufficiently long development history. These methods are rooted in the use of the condition of photochemical equilibrium of ozone density in the range of altitudes from 50 to 100 km. A significant factor is that an insufficient volume of such measurement data forces researchers to use approximate ("truncated") photochemical-equilibrium conditions. In particular, it is assumed that in the daytime the ozone production reaction is perfectly balanced by ozone photodissociation, whereas during the night the only ozone sink is the reaction of ozone with atomic hydrogen, which, in its turn, leads to formation of excited OH and airglow emission of the latter. The presentation analyzes applicability of the photochemical-equilibrium conditions both in the total and truncated forms for description of the spatio-temporal evolution of mesospheric ozone during a year. The analysis is based on year-long time series generated by a 3D chemical transport model, which reproduces correctly various types of atmosphere dynamics in the range of altitudes from 50 to 100 km. These data are used to determine statistics of the ratio between the correct (calculated dynamically) distributions of the O3 density and its uncontracted and truncated equilibrium values for the conditions of the

  9. Using normalized difference vegetation index to estimate carbon fluxes from small rotationally grazed pastures

    Science.gov (United States)

    Skinner, R.H.; Wylie, B.K.; Gilmanov, T.G.

    2011-01-01

    Satellite-based normalized difference vegetation index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern United States might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (submeter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the moderate resolution imaging spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007, and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on MODIS 7-d NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed from each other by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term management-induced changes in GPP at individual sites.

  10. Synthesis of integrated primary production in the Arctic Ocean: II. In situ and remotely sensed estimates

    Science.gov (United States)

    Hill, Victoria J.; Matrai, Patricia A.; Olson, Elise; Suttles, S.; Steele, Mike; Codispoti, L. A.; Zimmerman, Richard C.

    2013-03-01

    Recent warming of surface waters, accompanied by reduced ice thickness and extent may have significant consequences for climate-driven changes of primary production (PP) in the Arctic Ocean (AO). However, it has been difficult to obtain a robust benchmark estimate of pan-Arctic PP necessary for evaluating change. This paper provides an estimate of pan-Arctic PP prior to significant warming from a synthetic analysis of the ARCSS-PP database of in situ measurements collected from 1954 to 2007 and estimates derived from satellite-based observations from 1998 to 2007. Vertical profiles of in situ chlorophyll a (Chl a) and PP revealed persistent subsurface peaks in biomass and PP throughout the AO during most of the summer period. This was contradictory with the commonly assumed exponential decrease in PP with depth on which prior satellite-derived estimates were based. As remotely sensed Chl a was not a good predictor of integrated water column Chl a, accurate satellite-based modeling of vertically integrated primary production (IPPsat), requires knowledge of the subsurface distribution of phytoplankton, coincident with the remotely sensed ocean color measurements. We developed an alternative approach to modeling PP from satellite observations by incorporating climatological information on the depths of the euphotic zone and the mixed layer that control the distribution of phytoplankton that significantly improved the fidelity of satellite derived PP to in situ observations. The annual IPP of the Arctic Ocean combining both in situ and satellite based estimates was calculated here to be a minimum of 466 ± 94 Tg C yr-1 and a maximum of 993 ± 94 Tg C yr-1, when corrected for subsurface production. Inflow shelf seas account for 75% of annual IPP, while the central basin and Beaufort northern sea were the regions with the lowest annual integrated productivity, due to persistently stratified, oligotrophic and ice-covered conditions. Although the expansion of summertime

  11. Estimating the background covariance error for the Global Data Assimilation System of CPTEC/INPE

    Science.gov (United States)

    Bastarz, C. F.; Goncalves, L.

    2013-05-01

    The global data assimilation system at CPTEC/INPE, named G3Dvar is based in the Gridoint Statistical Interpolation (GSI/NCEP/GMAO) and in the general circulation model from that same center (GCM/CPTEC/INPE). The G3Dvar is a tri-dimensional variational data assimilation system that uses a Background Error Covariance Matrix (BE) fixed (in its current implementation, it uses the matrix from Global Forecast System - GFS/NCEP). The goal of this work is to present the preliminary results of the calculation of the new BE based on the GCM/CPTEC/INPE using a methodology similar to the one used for the GSI/WRFDA, called gen_be. The calculation is done in 5 distinct steps in the analysis increment space. (a) stream function and potential velocity are determined from the wind fields; (b) the mean of the stream function and potential velocity are calculated in order to obtain the perturbation fields for the remaing variables (streamfunction, potencial velocity, temperature, relative humidity and surface pressure); (c) the covariances of the perturbation fields, regression coeficients and balance between streamfunction, temperature and surface pressure are estimated. For this particular system, i.e. GCM/CPTEC/INPE, the necessity for constrains towards the statistical balance between streamfuncion and potential velocity, temperature and surface pressure will be evaluated as well as the how it affects the BE matrix calculation. Hence, this work will investigate the necessary procedures for calculating BE and show how does that differs from the standard calculation and how it is calibrated/adjusted based on the GCM/CPTEC/INPE. Results from a comparison between the main differences between the GFS BE and the newly calculated GCM/CPTEC/INPE BE are discussed in addition to an impact study using the different background error covariance matrices.

  12. Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

    KAUST Repository

    Sun, Ying

    2014-11-07

    For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.

  13. Application of satellite estimates of rainfall distribution to simulate the potential for malaria transmission in Africa

    Science.gov (United States)

    Yamana, T. K.; Eltahir, E. A.

    2009-12-01

    The Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS) is a mechanistic model developed to assess malaria risk in areas where the disease is water-limited. This model relies on precipitation inputs as its primary forcing. Until now, applications of the model have used ground-based precipitation observations. However, rain gauge networks in the areas most affected by malaria are often sparse. The increasing availability of satellite based rainfall estimates could greatly extend the range of the model. The minimum temporal resolution of precipitation data needed was determined to be one hour. The CPC Morphing technique (CMORPH ) distributed by NOAA fits this criteria, as it provides 30-minute estimates at 8km resolution. CMORPH data were compared to ground observations in four West African villages, and calibrated to reduce overestimation and false alarm biases. The calibrated CMORPH data were used to force HYDREMATS, resulting in outputs for mosquito populations, vectorial capacity and malaria transmission.

  14. Unbiased risk estimation method for covariance estimation

    CERN Document Server

    Lescornel, Hélène; Chabriac, Claudie

    2011-01-01

    We consider a model selection estimator of the covariance of a random process. Using the Unbiased Risk Estimation (URE) method, we build an estimator of the risk which allows to select an estimator in a collection of model. Then, we present an oracle inequality which ensures that the risk of the selected estimator is close to the risk of the oracle. Simulations show the efficiency of this methodology.

  15. Detection of shallow buried nonmetallic landmine and estimation of its depth at microwave X-band frequency

    Science.gov (United States)

    Tiwari, K. C.; Singh, D.; Arora, M.

    2009-05-01

    Current methods of demining are mostly ground or vehicle based and therefore extremely time consuming, risky and also do not produce low false alarm rates. Detection of landmines using airborne and satellite based sensors are a viable risk free alternative. However extracting mine like features from data captured using airborne and satellite based sensors using signal and image processing techniques with low false alarm rates is a subject of active research. Microwave remote sensing in X-band (10 GHz, 3 cm) frequency has the capability for both subsurface penetration and resolution of landmines as well as non-lethal targets. In the present study, a set of experiments under laboratory conditions have been carried out using dummy landmines without explosives buried to different depths up to 10 cm in dry smooth sand. The data generated through the experiments is processed through a series of image processing steps and a region of interest segmented using Otsu and Maximum Entropy based thresholding methods. The region of interest is masked and the average observed backscatter containing the mine further processed through an electromagnetic model developed and optimized using genetic algorithm for estimation of depth. The method does not have any requirement of separate training and test data set to train the optimizer and validate the results. The results under laboratory conditions indicate satisfactory results both for detection of shallow buried landmines and estimation of depth.

  16. Spatial estimates of snow water equivalent from reconstruction

    Science.gov (United States)

    Rittger, Karl; Bair, Edward H.; Kahl, Annelen; Dozier, Jeff

    2016-08-01

    Operational ground-based measurements of snow water equivalent (SWE) do not adequately explain spatial variability in mountainous terrain. To address this problem, we combine satellite-based retrievals of fractional snow cover for the period 2000 to 2011 with spatially distributed energy balance calculations to reconstruct SWE values throughout each melt season in the Sierra Nevada of California. Modeled solar radiation, longwave radiation, and air temperature from NLDAS drive the snowmelt model. The modeled solar radiation compares well to ground observations, but modeled longwave radiation is slightly lower than observations. Validation of reconstructed SWE with snow courses and our own snow surveys shows that the model can accurately estimate SWE at the sampled locations in a variety of topographic settings for a range of wet to dry years. The relationships of SWE with elevation and latitude are significantly different for wet, mean and dry years as well as between drainages. In all the basins studied, the relationship between remaining SWE and snow-covered area (SCA) becomes increasingly correlated from March to July as expected because SCA is an important model input. Though the SWE is calculated retrospectively SCA observations are available in near-real time and combined with historical reconstructions may be sufficient for estimating SWE with more confidence as the melt season progresses.

  17. Rice yield estimation with multi-temporal Radarsat-2 data

    Science.gov (United States)

    Chen, Chi-Farn; Son, Nguyen-Thanh; Chen, Cheng-Ru

    2015-04-01

    Rice is the most important food crop in Taiwan. Monitoring rice crop yield is thus crucial for agronomic planners to formulate successful strategies to address national food security and rice grain export issues. However, there is a real challenge for this monitoring purpose because the size of rice fields in Taiwan was generally small and fragmented, and the cropping calendar was also different from region to region. Thus, satellite-based estimation of rice crop yield requires the data that have sufficient spatial and temporal resolutions. This study aimed to develop models to estimate rice crop yield from multi-temporal Radarsat-2 data (5 m resolution). Data processing were carried out for the first rice cropping season from February to July in 2014 in the western part of Taiwan, consisting of four main steps: (1) constructing time-series backscattering coefficient data, (2) spatiotemporal noise filtering of the time-series data, (3) establishment of crop yield models using the time-series backscattering coefficients and in-situ measured yield data, and (4) model validation using field data and government's yield statistics. The results indicated that backscattering behavior varied from region to region due to changes in cultural practices and cropping calendars. The highest correlation coefficient (R2 > 0.8) was obtained at the ripening period. The robustness of the established models was evaluated by comparisons between the estimated yields and in-situ measured yield data showed satisfactory results, with the root mean squared error (RMSE) smaller than 10%. Such results were reaffirmed by the correlation analysis between the estimated yields and government's rice yield statistics (R2 > 0.8). This study demonstrates advantages of using multi-temporal Radarsat-2 backscattering data for estimating rice crop yields in Taiwan prior to the harvesting period, and thus the methods were proposed for rice yield monitoring in other regions.

  18. Liu Estimator Based on An M Estimator

    Directory of Open Access Journals (Sweden)

    Hatice ŞAMKAR

    2010-01-01

    Full Text Available Objective: In multiple linear regression analysis, multicollinearity and outliers are two main problems. In the presence of multicollinearity, biased estimation methods like ridge regression, Stein estimator, principal component regression and Liu estimator are used. On the other hand, when outliers exist in the data, the use of robust estimators reducing the effect of outliers is prefered. Material and Methods: In this study, to cope with this combined problem of multicollinearity and outliers, it is studied Liu estimator based on M estimator (Liu M estimator. In addition, mean square error (MSE criterion has been used to compare Liu M estimator with Liu estimator based on ordinary least squares (OLS estimator. Results: OLS, Huber M, Liu and Liu M estimates and MSEs of these estimates have been calculated for a data set which has been taken form a study of determinants of physical fitness. Liu M estimator has given the best performance in the data set. It is found as both MSE (?LM = 0.0078< MSE (?M = 0.0508 and MSE (?LM = 0.0078< MSE (?L= 0.0085. Conclusion: When there is both outliers and multicollinearity in a dataset, while using of robust estimators reduces the effect of outliers, it could not solve problem of multicollinearity. On the other hand, using of biased methods could solve the problem of multicollinearity, but there is still the effect of outliers on the estimates. In the occurence of both multicollinearity and outliers in a dataset, it has been shown that combining of the methods designed to deal with this problems is better than using them individually.

  19. The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates

    Science.gov (United States)

    Houghton, R. A.; Lawrence, J. L.; Hackler, J. L.; Brown, S.

    2001-01-01

    The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. We compared several estimates of forest biomass for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. We asked three questions. First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? Amazonian forests (including dead and below-ground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modeling of forest recovery following observed stand-replacing disturbances (the approach used in this research), and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.

  20. Estimating tail probabilities

    Energy Technology Data Exchange (ETDEWEB)

    Carr, D.B.; Tolley, H.D.

    1982-12-01

    This paper investigates procedures for univariate nonparametric estimation of tail probabilities. Extrapolated values for tail probabilities beyond the data are also obtained based on the shape of the density in the tail. Several estimators which use exponential weighting are described. These are compared in a Monte Carlo study to nonweighted estimators, to the empirical cdf, to an integrated kernel, to a Fourier series estimate, to a penalized likelihood estimate and a maximum likelihood estimate. Selected weighted estimators are shown to compare favorably to many of these standard estimators for the sampling distributions investigated.

  1. Modeling the uncertainty of estimating forest carbon stocks in China

    Directory of Open Access Journals (Sweden)

    T. X. Yue

    2015-12-01

    Full Text Available Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks at sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote-sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Lund-Potsdam-Jena dynamic global vegetation model (LPJ, the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations and an assimilation method for incorporating the ground sample plots into LPJ. The validation results indicated that both the data fusion and data assimilation approaches reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high accuracy surface modeling to fuse the ground sample plots with the satellite observations (HASM-SOA. The estimates produced with HASM-SOA were 26.1 and 28.4 % more accurate than the satellite-based approach and spatial interpolation of the sample plots, respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-SOA method.

  2. Analysing the uncertainty of estimating forest carbon stocks in China

    Science.gov (United States)

    Yue, Tian Xiang; Wang, Yi Fu; Du, Zheng Ping; Zhao, Ming Wei; Li Zhang, Li; Zhao, Na; Lu, Ming; Larocque, Guy R.; Wilson, John P.

    2016-07-01

    Earth surface systems are controlled by a combination of global and local factors, which cannot be understood without accounting for both the local and global components. The system dynamics cannot be recovered from the global or local controls alone. Ground forest inventory is able to accurately estimate forest carbon stocks in sample plots, but these sample plots are too sparse to support the spatial simulation of carbon stocks with required accuracy. Satellite observation is an important source of global information for the simulation of carbon stocks. Satellite remote sensing can supply spatially continuous information about the surface of forest carbon stocks, which is impossible from ground-based investigations, but their description has considerable uncertainty. In this paper, we validated the Kriging method for spatial interpolation of ground sample plots and a satellite-observation-based approach as well as an approach for fusing the ground sample plots with satellite observations. The validation results indicated that the data fusion approach reduced the uncertainty of estimating carbon stocks. The data fusion had the lowest uncertainty by using an existing method for high-accuracy surface modelling to fuse the ground sample plots with the satellite observations (HASM-S). The estimates produced with HASM-S were 26.1 and 28.4 % more accurate than the satellite-based approach and spatial interpolation of the sample plots respectively. Forest carbon stocks of 7.08 Pg were estimated for China during the period from 2004 to 2008, an increase of 2.24 Pg from 1984 to 2008, using the preferred HASM-S method.

  3. Satellite Estimates of Crop Area and Maize Yield in Zambia's Agricultural Districts

    Science.gov (United States)

    Azzari, G.; Lobell, D. B.

    2015-12-01

    Predicting crop yield and area from satellite is a valuable tool to monitor different aspects of productivity dynamics and food security. In Sub-Saharan Africa, where the agricultural landscape is complex and dominated by smallholder systems, such dynamics need to be investigated at the field scale. We leveraged the large data pool and computational power of Google Earth Engine to 1) generate 30 m resolution cover maps of selected provinces of Zambia, 2) estimate crop area, and 3) produce yearly maize yield maps using the recently developed SCYM (Scalable satellite-based Crop Yield Mapper) algorithm. We will present our results and their validation against a ground survey dataset collected yearly by the Zambia Ministry of Agriculture from about 12,500 households.

  4. Estimating Soil Moisture from Satellite Microwave Observations

    Science.gov (United States)

    Owe, M.; VandeGriend, A. A.; deJeu, R.; deVries, J.; Seyhan, E.

    1998-01-01

    Cooperative research in microwave remote sensing between the Hydrological Sciences Branch of the NASA Goddard Space Flight Center and the Earth Sciences Faculty of the Vrije Universiteit Amsterdam began with the Botswana Water and Energy Balance Experiment and has continued through a series of highly successful International Research Programs. The collaboration between these two research institutions has resulted in significant scientific achievements, most notably in the area of satellite-based microwave remote sensing of soil moisture. The Botswana Program was the first joint research initiative between these two institutions, and provided a unique data base which included historical data sets of Scanning Multifrequency Microwave Radiometer (SN4NM) data, climate information, and extensive soil moisture measurements over several large experimental sites in southeast Botswana. These data were the basis for the development of new approaches in physically-based inverse modelling of soil moisture from satellite microwave observations. Among the results from this study were quantitative estimates of vegetation transmission properties at microwave frequencies. A single polarization modelling approach which used horizontally polarized microwave observations combined with monthly composites of Normalized Difference Vegetation Index was developed, and yielded good results. After more precise field experimentation with a ground-based radiometer system, a dual-polarization approach was subsequently developed. This new approach realized significant improvements in soil moisture estimation by satellite. Results from the Botswana study were subsequently applied to a desertification monitoring study for the country of Spain within the framework of the European Community science research programs EFEDA and RESMEDES. A dual frequency approach with only microwave data was used for this application. The Microwave Polarization Difference Index (MPDI) was calculated from 37 GHz data

  5. Precipitation estimation using L-band and C-band soil moisture retrievals

    Science.gov (United States)

    Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

    2016-09-01

    An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to ˜100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

  6. Antecedent precipitation index determined from CST estimates of rainfall

    Science.gov (United States)

    Martin, David W.

    1992-01-01

    This paper deals with an experimental calculation of a satellite-based antecedent precipitation index (API). The index is also derived from daily rain images produced from infrared images using an improved version of GSFC's Convective/Stratiform Technique (CST). API is a measure of soil moisture, and is based on the notion that the amount of moisture in the soil at a given time is related to precipitation at earlier times. Four different CST programs as well as the Geostationary Operational Enviroment Satellite (GOES) Precipitation Index developed by Arkin in 1979 are compared to experimental results, for the Mississippi Valley during the month of July. Rain images are shown for the best CST code and the ARK program. Comparisons are made as to the accuracy and detail of the results for the two codes. This project demonstrates the feasibility of running the CST on a synoptic scale. The Mississippi Valley case is well suited for testing the feasibility of monitoring soil moisture by means of CST. Preliminary comparisons of CST and ARK indicate significant differences in estimates of rain amount and distribution.

  7. Estimating Evapotranspiration Using an Observation Based Terrestrial Water Budget

    Science.gov (United States)

    Rodell, Matthew; McWilliams, Eric B.; Famiglietti, James S.; Beaudoing, Hiroko K.; Nigro, Joseph

    2011-01-01

    Evapotranspiration (ET) is difficult to measure at the scales of climate models and climate variability. While satellite retrieval algorithms do exist, their accuracy is limited by the sparseness of in situ observations available for calibration and validation, which themselves may be unrepresentative of 500m and larger scale satellite footprints and grid pixels. Here, we use a combination of satellite and ground-based observations to close the water budgets of seven continental scale river basins (Mackenzie, Fraser, Nelson, Mississippi, Tocantins, Danube, and Ubangi), estimating mean ET as a residual. For any river basin, ET must equal total precipitation minus net runoff minus the change in total terrestrial water storage (TWS), in order for mass to be conserved. We make use of precipitation from two global observation-based products, archived runoff data, and TWS changes from the Gravity Recovery and Climate Experiment satellite mission. We demonstrate that while uncertainty in the water budget-based estimates of monthly ET is often too large for those estimates to be useful, the uncertainty in the mean annual cycle is small enough that it is practical for evaluating other ET products. Here, we evaluate five land surface model simulations, two operational atmospheric analyses, and a recent global reanalysis product based on our results. An important outcome is that the water budget-based ET time series in two tropical river basins, one in Brazil and the other in central Africa, exhibit a weak annual cycle, which may help to resolve debate about the strength of the annual cycle of ET in such regions and how ET is constrained throughout the year. The methods described will be useful for water and energy budget studies, weather and climate model assessments, and satellite-based ET retrieval optimization.

  8. Spurious barometric pressure acceleration in Antarctica and propagation into GRACE Antarctic mass change estimates

    Science.gov (United States)

    Kim, Byeong-Hoon; Eom, Jooyoung; Seo, Ki-Weon; Wilson, Clark R.

    2016-08-01

    Apparent acceleration in Gravity Recovery and Climate Experiment (GRACE) Antarctic ice mass time-series may reflect both ice discharge and surface mass balance contributions. However, a recent study suggests there is also contamination from errors in atmospheric pressure de-aliasing fields [European Center for Medium-Range Weather Forecast (ECMWF) operational products] used during GRACE data processing. To further examine this question, we compare GRACE atmospheric pressure de-aliasing (GAA) fields with in situ surface pressure data from coastal and inland stations. Differences between the two are likely due to GAA errors, and provide a measure of error in GRACE solutions. Time-series of differences at individual weather stations are fit to four presumed error components: annual sinusoids, a linear trend, an acceleration term and jumps at times of known ECMWF model changes. Using data from inland stations, we estimate that atmospheric pressure error causes an acceleration error of about +7.0 Gt yr-2, which is large relative to prior GRACE estimates of Antarctic ice mass acceleration in the range of -12 to -14 Gt yr-2. We also estimate apparent acceleration rates from other barometric pressure (reanalysis) fields, including ERA-Interim, MERRA and NCEP/DOE. When integrated over East Antarctica, the four mass acceleration estimates (from GAA and the three reanalysis fields) vary considerably (by ˜2-16 Gt yr-2). This shows the need for further effort to improve atmospheric mass estimates in this region of sparse in situ observations, in order to use GRACE observations to measure ice mass acceleration and related sea level change.

  9. Bootstrap Estimation for Nonparametric Efficiency Estimates

    OpenAIRE

    1995-01-01

    This paper develops a consistent bootstrap estimation procedure to obtain confidence intervals for nonparametric measures of productive efficiency. Although the methodology is illustrated in terms of technical efficiency measured by output distance functions, the technique can be easily extended to other consistent nonparametric frontier models. Variation in estimated efficiency scores is assumed to result from variation in empirical approximations to the true boundary of the production set. ...

  10. Software Cost Estimation Review

    OpenAIRE

    Ongere, Alphonce

    2013-01-01

    Software cost estimation is the process of predicting the effort, the time and the cost re-quired to complete software project successfully. It involves size measurement of the soft-ware project to be produced, estimating and allocating the effort, drawing the project schedules, and finally, estimating overall cost of the project. Accurate estimation of software project cost is an important factor for business and the welfare of software organization in general. If cost and effort estimat...

  11. Making Connections with Estimation.

    Science.gov (United States)

    Lobato, Joanne E.

    1993-01-01

    Describes four methods to structure estimation activities that enable students to make connections between their understanding of numbers and extensions of those concepts to estimating. Presents activities that connect estimation with other curricular areas, other mathematical topics, and real-world applications. (MDH)

  12. Estimation of genome length

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The genome length is a fundamental feature of a species. This note outlined the general concept and estimation method of the physical and genetic length. Some formulae for estimating the genetic length were derived in detail. As examples, the genome genetic length of Pinus pinaster Ait. and the genetic length of chromosome Ⅵ of Oryza sativa L. were estimated from partial linkage data.

  13. Estimation of late twentieth century land-cover change in California

    Science.gov (United States)

    Sleeter, Benjamin M.; Wilson, Tamara S.; Soulard, Christopher E.; Liu, Jinxun

    2011-01-01

    We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973-2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km2 and forest class at 4,722 km2. Developed lands increased by 37.6%, composing an estimated 4.2% of the state?s land cover by 2000.

  14. An Improved Approach for Estimating Daily Net Radiation over the Heihe River Basin

    Science.gov (United States)

    Wu, Bingfang; Liu, Shufu; Zhu, Weiwei; Yan, Nana; Xing, Qiang; Tan, Shen

    2017-01-01

    Net radiation plays an essential role in determining the thermal conditions of the Earth’s surface and is an important parameter for the study of land-surface processes and global climate change. In this paper, an improved satellite-based approach to estimate the daily net radiation is presented, in which sunshine duration were derived from the geostationary meteorological satellite (FY-2D) cloud classification product, the monthly empirical as and bs Angstrom coefficients for net shortwave radiation were calibrated by spatial fitting of the ground data from 1997 to 2006, and the daily net longwave radiation was calibrated with ground data from 2007 to 2010 over the Heihe River Basin in China. The estimated daily net radiation values were validated against ground data for 12 months in 2008 at four stations with different underlying surface types. The average coefficient of determination (R2) was 0.8489, and the averaged Nash-Sutcliffe equation (NSE) was 0.8356. The close agreement between the estimated daily net radiation and observations indicates that the proposed method is promising, especially given the comparison between the spatial distribution and the interpolation of sunshine duration. Potential applications include climate research, energy balance studies and the estimation of global evapotranspiration. PMID:28054976

  15. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

  16. Optomechanical parameter estimation

    CERN Document Server

    Ang, Shan Zheng; Bowen, Warwick P; Tsang, Mankei

    2013-01-01

    We propose a statistical framework for the problem of parameter estimation from a noisy optomechanical system. The Cram\\'er-Rao lower bound on the estimation errors in the long-time limit is derived and compared with the errors of radiometer and expectation-maximization (EM) algorithms in the estimation of the force noise power. When applied to experimental data, the EM estimator is found to have the lowest error and follow the Cram\\'er-Rao bound most closely. With its ability to estimate most of the system parameters, the EM algorithm is envisioned to be useful for optomechanical sensing, atomic magnetometry, and classical or quantum system identification applications in general.

  17. Hardware Accelerated Power Estimation

    CERN Document Server

    Coburn, Joel; Raghunathan, Anand

    2011-01-01

    In this paper, we present power emulation, a novel design paradigm that utilizes hardware acceleration for the purpose of fast power estimation. Power emulation is based on the observation that the functions necessary for power estimation (power model evaluation, aggregation, etc.) can be implemented as hardware circuits. Therefore, we can enhance any given design with "power estimation hardware", map it to a prototyping platform, and exercise it with any given test stimuli to obtain power consumption estimates. Our empirical studies with industrial designs reveal that power emulation can achieve significant speedups (10X to 500X) over state-of-the-art commercial register-transfer level (RTL) power estimation tools.

  18. Estimating Cosmological Parameter Covariance

    CERN Document Server

    Taylor, Andy

    2014-01-01

    We investigate the bias and error in estimates of the cosmological parameter covariance matrix, due to sampling or modelling the data covariance matrix, for likelihood width and peak scatter estimators. We show that these estimators do not coincide unless the data covariance is exactly known. For sampled data covariances, with Gaussian distributed data and parameters, the parameter covariance matrix estimated from the width of the likelihood has a Wishart distribution, from which we derive the mean and covariance. This mean is biased and we propose an unbiased estimator of the parameter covariance matrix. Comparing our analytic results to a numerical Wishart sampler of the data covariance matrix we find excellent agreement. An accurate ansatz for the mean parameter covariance for the peak scatter estimator is found, and we fit its covariance to our numerical analysis. The mean is again biased and we propose an unbiased estimator for the peak parameter covariance. For sampled data covariances the width estimat...

  19. Time Series Analysis of Remote Sensing Observations for Citrus Crop Growth Stage and Evapotranspiration Estimation

    Science.gov (United States)

    Sawant, S. A.; Chakraborty, M.; Suradhaniwar, S.; Adinarayana, J.; Durbha, S. S.

    2016-06-01

    Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions have provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one of the oldest sources of optical EO datasets. This historical and near real time EO archive is a rich source of information to understand the seasonal changes in the horticultural crops. Citrus (Mandarin / Nagpur Orange) is one of the major horticultural crops cultivated in central India. Erratic behaviour of rainfall and dependency on groundwater for irrigation has wide impact on the citrus crop yield. Also, wide variations are reported in temperature and relative humidity causing early fruit onset and increase in crop water requirement. Therefore, there is need to study the crop growth stages and crop evapotranspiration at spatio-temporal scale for managing the scarce resources. In this study, an attempt has been made to understand the citrus crop growth stages using Normalized Difference Time Series (NDVI) time series data obtained from Landsat archives (http://earthexplorer.usgs.gov/). Total 388 Landsat 4, 5, 7 and 8 scenes (from year 1990 to Aug. 2015) for Worldwide Reference System (WRS) 2, path 145 and row 45 were selected to understand seasonal variations in citrus crop growth. Considering Landsat 30 meter spatial resolution to obtain homogeneous pixels with crop cover orchards larger than 2 hectare area was selected. To consider change in wavelength bandwidth (radiometric resolution) with Landsat sensors (i.e. 4, 5, 7 and 8) NDVI has been selected to obtain continuous sensor independent time series. The obtained crop growth stage information has been used to estimate citrus basal crop coefficient information (Kcb). Satellite based Kcb estimates were used with proximal agrometeorological sensing system observed relevant weather parameters for crop ET estimation. The

  20. Present-day groundwater recharge estimation in parts of the Indian Sub-Continent

    Science.gov (United States)

    Bhanja, S. N.; Mukherjee, A.; Wada, Y.; Scanlon, B. R.; Taylor, R. G.; Rodell, M.; Malakar, P.

    2015-12-01

    Large part of global population has been dependent on groundwater as a source of fresh water. The demand would further increase with increasing population and stress associated with climate change. We tried to provide regional-scale groundwater recharge estimates in a large part of Indian Sub-Continent. A combination of ground-based, satellite-based and numerical model simulated recharge estimates were presented in the densely populated region. Three different methods: an intense network of observational wells (n>13,000 wells), a satellite (TRMM) and global land-surface model (CLM) outputs, and a global-scale hydrological model (PCR GLOBWB) were employed to calculate recharge estimates. Groundwater recharge values exhibit large spatial variations over the entire region on the basis of aquifer hydrogeology, precipitation and groundwater withdrawal patterns. Groundwater recharge estimates from all three estimation techniques were found to be higher (>300 mm/year) in fertile planes of Indus-Ganges-Brahmaputra (IGB) river basins. A combination of favorable hydrogeologic conditions (porosity, permeability etc.), comparatively higher rates of precipitation, and return flow from rapidly withdrawn irrigation water might influence occurrence of high recharge rates. However, central and southern study area experiences lower recharge rates (recharge estimates show good matches in some of the areas. Recharge estimates indicate dynamic nature of groundwater recharge as a function of precipitation, land use pattern, and hydrogeologic parameters. On a first hand basis, the estimates will help policy makers to understand groundwater recharge process over the densely populated region and finally would facilitate to implement sustainable policy for securing water security.

  1. Estimating crop net primary production using inventory data and MODIS-derived parameters

    Energy Technology Data Exchange (ETDEWEB)

    Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

    2013-06-03

    National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

  2. Improving North American gross primary production (GPP) estimates using atmospheric measurements of carbonyl sulfide (COS)

    Science.gov (United States)

    Chen, Huilin; Montzka, Steve; Andrews, Arlyn; Sweeney, Colm; Jacobson, Andy; Miller, Ben; Masarie, Ken; Jung, Martin; Gerbig, Christoph; Campbell, Elliott; Abu-Naser, Mohammad; Berry, Joe; Baker, Ian; Tans, Pieter

    2013-04-01

    Understanding the responses of gross primary production (GPP) to climate change is essential for improving our prediction of climate change. To this end, it is important to accurately partition net ecosystem exchange of carbon into GPP and respiration. Recent studies suggest that carbonyl sulfide is a useful tracer to provide a constraint on GPP, based on the fact that both COS and CO2 are simultaneously taken up by plants and the quantitative correlation between GPP and COS plant uptake. We will present an assessment of North American GPP estimates from the Simple Biosphere (SiB) model, the Carnegie-Ames-Stanford Approach (CASA) model, and the MPI-BGC model through atmospheric transport simulations of COS in a receptor oriented framework. The newly upgraded Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) will be employed to compute the influence functions, i.e. footprints, to link the surface fluxes to the concentration changes at the receptor observations. The HYSPLIT is driven by the 3-hourly archived NAM 12km meteorological data from NOAA NCEP. The background concentrations are calculated using empirical curtains along the west coast of North America that have been created by interpolating in time and space the observations at the NOAA/ESRL marine boundary layer stations and from aircraft vertical profiles. The plant uptake of COS is derived from GPP estimates of biospheric models. The soil uptake and anthropogenic emissions are from Kettle et al. 2002. In addition, we have developed a new soil flux map of COS based on observations of molecular hydrogen (H2), which shares a common soil uptake term but lacks a vegetative sink. We will also improve the GPP estimates by assimilating atmospheric observations of COS in the receptor oriented framework, and then present the assessment of the improved GPP estimates against variations of climate variables such as temperature and precipitation.

  3. Multiple data fusion for rainfall estimation using a NARX-based recurrent neural network - the development of the REIINN model

    Science.gov (United States)

    Ang, M. R. C. O.; Gonzalez, R. M.; Castro, P. P. M.

    2014-03-01

    Rainfall, one of the important elements of the hydrologic cycle, is also the most difficult to model. Thus, accurate rainfall estimation is necessary especially in localized catchment areas where variability of rainfall is extremely high. Moreover, early warning of severe rainfall through timely and accurate estimation and forecasting could help prevent disasters from flooding. This paper presents the development of two rainfall estimation models that utilize a NARX-based neural network architecture namely: REIINN 1 and REIINN 2. These REIINN models, or Rainfall Estimation by Information Integration using Neural Networks, were trained using MTSAT cloud-top temperature (CTT) images and rainfall rates from the combined rain gauge and TMPA 3B40RT datasets. Model performance was assessed using two metrics - root mean square error (RMSE) and correlation coefficient (R). REIINN 1 yielded an RMSE of 8.1423 mm/3h and an overall R of 0.74652 while REIINN 2 yielded an RMSE of 5.2303 and an overall R of 0.90373. The results, especially that of REIINN 2, are very promising for satellite-based rainfall estimation in a catchment scale. It is believed that model performance and accuracy will greatly improve with a denser and more spatially distributed in-situ rainfall measurements to calibrate the model with. The models proved the viability of using remote sensing images, with their good spatial coverage, near real time availability, and relatively inexpensive to acquire, as an alternative source for rainfall estimation to complement existing ground-based measurements.

  4. Causal Effect Estimation Methods

    OpenAIRE

    2014-01-01

    Relationship between two popular modeling frameworks of causal inference from observational data, namely, causal graphical model and potential outcome causal model is discussed. How some popular causal effect estimators found in applications of the potential outcome causal model, such as inverse probability of treatment weighted estimator and doubly robust estimator can be obtained by using the causal graphical model is shown. We confine to the simple case of binary outcome and treatment vari...

  5. Continuous Time Model Estimation

    OpenAIRE

    Carl Chiarella; Shenhuai Gao

    2004-01-01

    This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the trend model by simulation, and how to calculate standard errors from estimation of the noise model. It also discusses the numerical difficulties involved in discrete time models that bring about the unit ...

  6. Electrical estimating methods

    CERN Document Server

    Del Pico, Wayne J

    2014-01-01

    Simplify the estimating process with the latest data, materials, and practices Electrical Estimating Methods, Fourth Edition is a comprehensive guide to estimating electrical costs, with data provided by leading construction database RS Means. The book covers the materials and processes encountered by the modern contractor, and provides all the information professionals need to make the most precise estimate. The fourth edition has been updated to reflect the changing materials, techniques, and practices in the field, and provides the most recent Means cost data available. The complexity of el

  7. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for further long-run equilibrium relations with possibly different persistence levels. The fi…rst step consists in estimating......-likelihood ratio test of no-cointegration on the estimated p - r common trends that are not cointegrated under the null. The cointegration degree is re-estimated in the second step to allow for new cointegration relationships with different memory. We augment the error correction model in the second step...

  8. Generalized Agile Estimation Method

    Directory of Open Access Journals (Sweden)

    Shilpa Bahlerao

    2011-01-01

    Full Text Available Agile cost estimation process always possesses research prospects due to lack of algorithmic approaches for estimating cost, size and duration. Existing algorithmic approach i.e. Constructive Agile Estimation Algorithm (CAEA is an iterative estimation method that incorporates various vital factors affecting the estimates of the project. This method has lots of advantages but at the same time has some limitations also. These limitations may due to some factors such as number of vital factors and uncertainty involved in agile projects etc. However, a generalized agile estimation may generate realistic estimates and eliminates the need of experts. In this paper, we have proposed iterative Generalized Estimation Method (GEM and presented algorithm based on it for agile with case studies. GEM  based algorithm various project domain classes and vital factors with prioritization level. Further, it incorporates uncertainty factor to quantify the risk of project for estimating cost, size and duration. It also provides flexibility to project managers for deciding on number of vital factors, uncertainty level and project domains thereby maintaining the agility.

  9. Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi)

    Science.gov (United States)

    Kneis, D.; Chatterjee, C.; Singh, R.

    2014-07-01

    The paper examines the quality of satellite-based precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-runoff simulation. At sub-basin level (4000 to 16 000 km2) the satellite-based areal precipitation estimates were found to be moderately correlated with the gauge-based counterparts (R2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high-intensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate 80 mm day-1). At the same time, the remotely sensed rainfall rates frequently exceed the gauge-based equivalents (false alarm ratios of 0.2-0.6). In addition, the real-time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall-runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash-Sutcliffe index of 0.76-0.88 at gauges not affected by

  10. Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi

    Directory of Open Access Journals (Sweden)

    D. Kneis

    2014-07-01

    Full Text Available The paper examines the quality of satellite-based precipitation estimates for the lower Mahanadi River basin (eastern India. The considered data sets known as 3B42 and 3B42-RT (version 7/7A are routinely produced by the tropical rainfall measuring mission (TRMM from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall–runoff simulation. At sub-basin level (4000 to 16 000 km2 the satellite-based areal precipitation estimates were found to be moderately correlated with the gauge-based counterparts (R2 of 0.64–0.74 for 3B42 and 0.59–0.72 for 3B42-RT. Significant discrepancies between TRMM data and ground observations were identified at high-intensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate 80 mm day-1. At the same time, the remotely sensed rainfall rates frequently exceed the gauge-based equivalents (false alarm ratios of 0.2–0.6. In addition, the real-time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall–runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash–Sutcliffe index of 0.76–0.88 at

  11. Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi

    Directory of Open Access Journals (Sweden)

    D. Kneis

    2014-01-01

    Full Text Available The paper examines the quality of satellite-based precipitation estimates for the Lower Mahanadi River Basin (Eastern India. The considered data sets known as 3B42 and 3B42-RT (version 7/7A are routinely produced by the tropical rainfall measuring mission (TRMM from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gage-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gage data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analyzing their performance in the context of rainfall-runoff simulation. At sub-basin level (4000 to 16 000 km2 the satellite-based areal precipitation estimates were found to be moderately correlated with the gage-based counterparts (R2 of 0.64–0.74 for 3B42 and 0.59–0.72 for 3B42-RT. Significant discrepancies between TRMM data and ground observations were identified at high intensity levels. The rainfall depth derived from rain gage data is often not reflected by the TRMM estimates (hit rate 80 mm day−1. At the same time, the remotely sensed rainfall rates frequently exceed the gage-based equivalents (false alarm ratios of 0.2–0.6. In addition, the real time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalization of rain gage data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall–runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gage data were used as model input (Nash–Sutcliffe Index of 0.76–0.88 at gages not

  12. Inter-comparison of energy balance and hydrological models for land surface energy flux estimation over a whole river catchment

    DEFF Research Database (Denmark)

    Guzinski, R.; Nieto, H.; Stisen, S.

    2015-01-01

    Evapotranspiration (ET) is the main link between the natural water cycle and the land surface energy budget. Therefore water-balance and energy-balance approaches are two of the main methodologies for modelling this process. The water-balance approach is usually implemented as a complex, distribu...... derived with the energy-balance models, satellite based LST or another source) into the hydrological models. How this could be achieved and how to evaluate the improvements, or lack of thereof, is still an open research question.......-balance (TSEB) scheme, against a hydrological model, MIKE SHE, calibrated over the Skjern river catchment in western Denmark. The three models utilize different primary inputs to estimate ET (LST from different satellites in the case of remote sensing models and modelled soil moisture and heat flux in the case...

  13. Biases of five latent heat flux products and their impacts on mixed-layer temperature estimates in the South China Sea

    Science.gov (United States)

    Wang, Xin; Zhang, Rongwang; Huang, Jian; Zeng, Lili; Huang, Fei

    2017-06-01

    Five latent heat flux (LHF) products are evaluated based on in situ observations in the South China Sea (SCS), including the ECWMF ERA-Interim (ERA-I), the NCEP2, the Objectively Analyzed air-sea Fluxes (OAFlux), the Japanese 55 year Reanalysis (JRA55), and the TropFlux data sets. The results show that there are good correlations between the LHF products and observations, ranging from 0.68 to 0.74. However, mean biases of -8 to 40 W m-2 exist in the LHF products with respect to the observations. For root-mean-square errors, the OAFlux data set is the closest to the observations, followed by ERA-I and TropFlux, while the NCEP2 data set shows significant overestimation. It is found that the biases in the near-surface-specific humidity are most correlated with the biases in the LHF products, followed by the biases in the near-surface wind speed, air temperature, and sea surface temperature. The biases in the LHF products have a prominent seasonal variation that is 25 W m-2 higher in boreal winter than in summer. Using the thermal equation, it is shown that the tendency errors of the mixed-layer temperature estimated by the biases in the LHF products vary from -2.0 to 3.5°C/month in the SCS. When all of the products are averaged, the errors are reduced to a range of -0.7 to 1.5°C/month. It is noteworthy that the errors in summer are more obvious than those in winter, since a thinner mixed layer in the summer can amplify the effect of even a small bias in the LHF.

  14. Use of remote sensing for analysis and estimation of vector-borne disease

    Science.gov (United States)

    Rahman, Atiqur

    An epidemiological data of malaria cases were correlated with satellite-based vegetation health (VH) indices to investigate if they can be used as a proxy for monitoring the number of malaria cases. Mosquitoes, which spread malaria in Bangladesh, are very sensitive to environmental conditions, especially to changes in weather. Therefore, VH indices, which characterize weather conditions, were tested as indicators of mosquitoes' activities in the spread of malaria. Satellite data were presented by the following VH indices: Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). They were derived from radiances and measured by the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA afternoon polar orbiting satellites. Assessment of sensitivity of the VH was performed using correlation and regression analysis. Estimation models were validated using of Jackknife Cross-Validation procedure. Results show that the VH indices can be used for detection, and numerical estimate of the number of malaria cases. During the cooler months (January--April) when mosquitoes are less active, the correlation is low and increases considerably during the warm and wet season (April--November), for TCI in early October and for VCI in mid September. All analysis and estimation model developed here are based on data obtained for Bangladesh.

  15. TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

    Directory of Open Access Journals (Sweden)

    Patrick Marina

    2017-01-01

    Full Text Available On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL. It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %; and good correlation (CC = 0.9. These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.

  16. Analysis of long term trends of precipitation estimates acquired using radar network in Turkey

    Science.gov (United States)

    Tugrul Yilmaz, M.; Yucel, Ismail; Kamil Yilmaz, Koray

    2016-04-01

    Precipitation estimates, a vital input in many hydrological and agricultural studies, can be obtained using many different platforms (ground station-, radar-, model-, satellite-based). Satellite- and model-based estimates are spatially continuous datasets, however they lack the high resolution information many applications often require. Station-based values are actual precipitation observations, however they suffer from their nature that they are point data. These datasets may be interpolated however such end-products may have large errors over remote locations with different climate/topography/etc than the areas stations are installed. Radars have the particular advantage of having high spatial resolution information over land even though accuracy of radar-based precipitation estimates depends on the Z-R relationship, mountain blockage, target distance from the radar, spurious echoes resulting from anomalous propagation of the radar beam, bright band contamination and ground clutter. A viable method to obtain spatially and temporally high resolution consistent precipitation information is merging radar and station data to take advantage of each retrieval platform. An optimally merged product is particularly important in Turkey where complex topography exerts strong controls on the precipitation regime and in turn hampers observation efforts. There are currently 10 (additional 7 are planned) weather radars over Turkey obtaining precipitation information since 2007. This study aims to optimally merge radar precipitation data with station based observations to introduce a station-radar blended precipitation product. This study was supported by TUBITAK fund # 114Y676.

  17. Maximum likely scale estimation

    DEFF Research Database (Denmark)

    Loog, Marco; Pedersen, Kim Steenstrup; Markussen, Bo

    2005-01-01

    A maximum likelihood local scale estimation principle is presented. An actual implementation of the estimation principle uses second order moments of multiple measurements at a fixed location in the image. These measurements consist of Gaussian derivatives possibly taken at several scales and/or ...

  18. Estimator for Random Fields

    Directory of Open Access Journals (Sweden)

    Sidi Ali Ould Abdi

    2011-01-01

    Full Text Available Given a stationary multidimensional spatial process (i=(i,i∈ℝ×ℝ,i∈ℤ, we investigate a kernel estimate of the spatial conditional quantile function of the response variable i given the explicative variable i. Asymptotic normality of the kernel estimate is obtained when the sample considered is an -mixing sequence.

  19. Estimating Health Services Requirements

    Science.gov (United States)

    Alexander, H. M.

    1985-01-01

    In computer program NOROCA populations statistics from National Center for Health Statistics used with computational procedure to estimate health service utilization rates, physician demands (by specialty) and hospital bed demands (by type of service). Computational procedure applicable to health service area of any size and even used to estimate statewide demands for health services.

  20. Estimation of Jump Tails

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Todorov, Victor

    We propose a new and flexible non-parametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple-to-implement set of estimating equations associated with the compensator for the jump measure, or its "intensity", that only utilizes ...

  1. Software cost estimation

    NARCIS (Netherlands)

    Heemstra, F.J.

    1992-01-01

    The paper gives an overview of the state of the art of software cost estimation (SCE). The main questions to be answered in the paper are: (1) What are the reasons for overruns of budgets and planned durations? (2) What are the prerequisites for estimating? (3) How can software development effort be

  2. Large Deviations of Estimators

    NARCIS (Netherlands)

    Kester, A.D.M.; Kallenberg, W.C.M.

    1986-01-01

    The performance of a sequence of estimators $\\{T_n\\}$ of $g(\\theta)$ can be measured by its inaccuracy rate $-\\lim \\inf_{n\\rightarrow\\infty} n^{-1} \\log \\mathbb{P}_\\theta(\\|T_n - g(\\theta)\\| > \\varepsilon)$. For fixed $\\varepsilon > 0$ optimality of consistent estimators $\\operatorname{wrt}$ the ina

  3. Estimating Resilience Across Landscapes

    Directory of Open Access Journals (Sweden)

    Garry D. Peterson

    2002-06-01

    Full Text Available Although ecological managers typically focus on managing local or regional landscapes, they often have little ability to control or predict many of the large-scale, long-term processes that drive changes within these landscapes. This lack of control has led some ecologists to argue that ecological management should aim to produce ecosystems that are resilient to change and surprise. Unfortunately, ecological resilience is difficult to measure or estimate in the landscapes people manage. In this paper, I extend system dynamics approaches to resilience and estimate resilience using complex landscape simulation models. I use this approach to evaluate cross-scale edge, a novel empirical method for estimating resilience based on landscape pattern. Cross-scale edge provides relatively robust estimates of resilience, suggesting that, with some further development, it could be used as a management tool to provide rough and rapid estimates of areas of resilience and vulnerability within a landscape.

  4. Discrepant estimates of primary and export production from satellite algorithms, a biogeochemical model, and geochemical tracer measurements in the North Pacific Ocean

    Science.gov (United States)

    Palevsky, Hilary I.; Quay, Paul D.; Nicholson, David P.

    2016-08-01

    Estimates of primary and export production (PP and EP) based on satellite remote sensing algorithms and global biogeochemical models are widely used to provide year-round global coverage not available from direct observations. However, observational data to validate these approaches are limited. We find that no single satellite algorithm or model can reproduce seasonal and annual geochemically determined PP, export efficiency (EP/PP), and EP rates throughout the North Pacific basin, based on comparisons throughout the full annual cycle at time series stations in the subarctic and subtropical gyres and basin-wide regions sampled by container ship transects. The high-latitude regions show large PP discrepancies in winter and spring and strong effects of deep winter mixed layers on annual EP that cannot be accounted for in current satellite-based approaches. These results underscore the need to evaluate satellite- and model-based estimates using multiple productivity parameters measured over broad ocean regions throughout the annual cycle.

  5. Regional-scale NEE estimates over 4 flux towers in the US

    Science.gov (United States)

    Dang, X.; Lai, C.; Hollinger, D. Y.; Munger, J. W.; Paw U, K.; Owensby, C.; Wofsy, S. C.; Schauer, A.; Ehleringer, J.

    2010-12-01

    We modeled regional carbon dioxide (CO2) fluxes based on midday mixing ratios measured in the canopy surface layer over 6 years (2002-2007) in four AmeriFlux stations. Applying an equilibrium boundary layer approach to focus on mean CO2 balance aggregated by the atmospheric boundary layer (ABL) processes, we estimated monthly average CO2 fluxes by inverting the difference between CO2 mixing ratios in the ABL and those in the free troposphere. We used a combination of NCAR/NCEP Reanalysis and ECMWF model data to estimate mean monthly rates of vertical transport between ABL and the free troposphere. Comparison between modeled net CO2 fluxes and tower-based eddy covariance NEE measurements suggests two interesting general patterns. First, modeled regional CO2 fluxes display inter- and intra-annual variations similar to the tower NEE fluxes observed in the Rannells Prairie and Wind River Forest, whereas model discrepancies were consistently found for the Harvard Forest and Howland Forest. Second, model discrepancies show distinct temporal patterns between the two northeastern U.S. forests. At the Howland Forest site, modeled CO2 fluxes showed a lag in the onset of growing-season uptake by two months behind that of tower measurements. At the Harvard Forest, modeled CO2 fluxes agreed with the timing of growing season uptake but underestimated the magnitude of observed NEE seasonal fluctuation. This modeling inconsistency among sites can be partially attributed to the likely misrepresentation of atmospheric transport and/or CO2 gradients between ABL and the free troposphere. Remote sensing-based land cover maps indicate that spatial heterogeneity in land use and cover was very likely to explain the majority of the modeling inconsistency. We suggest that the equilibrium boundary layer budget method can serve as a routine, diagnostic tool to interpret long-term NEE observations in flux networks, providing an intermediate-level analysis to complement aircraft

  6. State and Parameter Estimation for a Coupled Ocean--Atmosphere Model

    Science.gov (United States)

    Ghil, M.; Kondrashov, D.; Sun, C.

    2006-12-01

    The El-Nino/Southern-Oscillation (ENSO) dominates interannual climate variability and plays, therefore, a key role in seasonal-to-interannual prediction. Much is known by now about the main physical mechanisms that give rise to and modulate ENSO, but the values of several parameters that enter these mechanisms are an important unknown. We apply Extended Kalman Filtering (EKF) for both model state and parameter estimation in an intermediate, nonlinear, coupled ocean--atmosphere model of ENSO. The coupled model consists of an upper-ocean, reduced-gravity model of the Tropical Pacific and a steady-state atmospheric response to the sea surface temperature (SST). The model errors are assumed to be mainly in the atmospheric wind stress, and assimilated data are equatorial Pacific SSTs. Model behavior is very sensitive to two key parameters: (i) μ, the ocean-atmosphere coupling coefficient between SST and wind stress anomalies; and (ii) δs, the surface-layer coefficient. Previous work has shown that δs determines the period of the model's self-sustained oscillation, while μ measures the degree of nonlinearity. Depending on the values of these parameters, the spatio-temporal pattern of model solutions is either that of a delayed oscillator or of a westward propagating mode. Estimation of these parameters is tested first on synthetic data and allows us to recover the delayed-oscillator mode starting from model parameter values that correspond to the westward-propagating case. Assimilation of SST data from the NCEP-NCAR Reanalysis-2 shows that the parameters can vary on fairly short time scales and switch between values that approximate the two distinct modes of ENSO behavior. Rapid adjustments of these parameters occur, in particular, during strong ENSO events. Ways to apply EKF parameter estimation efficiently to state-of-the-art coupled ocean--atmosphere GCMs will be discussed.

  7. Development of Crop Yield Estimation Method by Applying Seasonal Climate Prediction in Asia-Pacific Region

    Science.gov (United States)

    Shin, Y.; Lee, E.

    2015-12-01

    Under the influence of recent climate change, abnormal weather condition such as floods and droughts has issued frequently all over the world. The occurrence of abnormal weather in major crop production areas leads to soaring world grain prices because it influence the reduction of crop yield. Development of crop yield estimation method is important means to accommodate the global food crisis caused by abnormal weather. However, due to problems with the reliability of the seasonal climate prediction, application research on agricultural productivity has not been much progress yet. In this study, it is an object to develop long-term crop yield estimation method in major crop production countries worldwide using multi seasonal climate prediction data collected by APEC Climate Center. There are 6-month lead seasonal predictions produced by six state-of-the-art global coupled ocean-atmosphere models(MSC_CANCM3, MSC_CANCM4, NASA, NCEP, PNU, POAMA). First of all, we produce a customized climate data through temporal and spatial downscaling methods for use as a climatic input data to the global scale crop model. Next, we evaluate the uncertainty of climate prediction by applying multi seasonal climate prediction in the crop model. Because rice is the most important staple food crop in the Asia-Pacific region, we assess the reliability of the rice yields using seasonal climate prediction for main rice production countries. RMSE(Root Mean Squire Error) and TCC(Temporal Correlation Coefficient) analysis is performed in Asia-Pacific countries, major 14 rice production countries, to evaluate the reliability of the rice yield according to the climate prediction models. We compare the rice yield data obtained from FAOSTAT and estimated using the seasonal climate prediction data in Asia-Pacific countries. In addition, we show that the reliability of seasonal climate prediction according to the climate models in Asia-Pacific countries where rice cultivation is being carried out.

  8. Numerical simulation for a pollution weather process in Shenyang,Liaoning province using MM5 model and NCEP/NCAR data%利用MM5模式及NCEP资料对沈阳一次污染天气的数值模拟

    Institute of Scientific and Technical Information of China (English)

    邹旭东; 杨洪斌; 李帅彬; 刘玉彻; 汪宏宇

    2012-01-01

    利用NCEP/NCAR再分析资料和中尺度天气模式MM5对2010年1月14—19日沈阳大气污染天气系统进行模拟分析。对此次天气过程的地面和高空气压场、地面至高空各高度层随时间变化的水平风场及垂直剖面风场、垂直方向温度廓线等气象要素进行分析和模拟,描述大气污染中天气系统的变化过程,分析造成大气污染的气象要素变化。结果表明:此次污染天气过程对应地面场为长白山高压、地形槽环流型;500 hPa高空天气形势为两槽一脊,地面风场主要受高压辐散气流控制;地面至高空不同高度的水平风场均有偏南风切变和偏西风切变,垂直剖面风场对应有下沉气流,地面至高空的温度廓线出现明显的逆温。这些气象条件共同造成了持续污染天气。而500 hPa位势高度场持续长时间两槽一脊的环流形势,是造成长时间污染天气的主要原因。%Based on the NCEP/NCAR reanalysis data and the meso-scale weather model MM5,a pollution weather process in Shenyang from 14-19 January 2010 was simulated.Some meteorological elements were analyzed and simulated and these include the ground and upper air pressure fields,the horizontal and vertical wind fields from the ground to the upper level as well as their variation with time,and the vertical temperature profile etc..The variation of weather system was described in this process,and the meteorological elements causing atmospheric pollution were analyzed.The results indicate that the corresponding ground filed in this process is the Changbai Mountain high pressure and topographic trough circulation type.The upper weather situation is two troughs and one ridge at 500 hPa.The ground wind field is controlled by high pressure divergence airflow.The horizontal wind fields from the ground to the upper all have the southerly wind shear and westerly wind shear,and there is the corresponding downdraft in the vertical wind field

  9. Lunar gravitational field estimation and the effects of mismodeling upon lunar satellite orbit prediction. M.S. Thesis

    Science.gov (United States)

    Davis, John H.

    1993-01-01

    Lunar spherical harmonic gravity coefficients are estimated from simulated observations of a near-circular low altitude polar orbiter disturbed by lunar mascons. Lunar gravity sensing missions using earth-based nearside observations with and without satellite-based far-side observations are simulated and least squares maximum likelihood estimates are developed for spherical harmonic expansion fit models. Simulations and parameter estimations are performed by a modified version of the Smithsonian Astrophysical Observatory's Planetary Ephemeris Program. Two different lunar spacecraft mission phases are simulated to evaluate the estimated fit models. Results for predicting state covariances one orbit ahead are presented along with the state errors resulting from the mismodeled gravity field. The position errors from planning a lunar landing maneuver with a mismodeled gravity field are also presented. These simulations clearly demonstrate the need to include observations of satellite motion over the far side in estimating the lunar gravity field. The simulations also illustrate that the eighth degree and order expansions used in the simulated fits were unable to adequately model lunar mascons.

  10. Methods for age estimation

    Directory of Open Access Journals (Sweden)

    D. Sümeyra Demirkıran

    2014-03-01

    Full Text Available Concept of age estimation plays an important role on both civil law and regulation of criminal behaviors. In forensic medicine, age estimation is practiced for individual requests as well for request of the court. In this study it is aimed to compile the methods of age estimation and to make recommendations for the solution of the problems encountered. In radiological method the epiphyseal lines of the bones and views of the teeth are used. In order to estimate the age by comparing bone radiographs; Greulich-Pyle Atlas (GPA, Tanner-Whitehouse Atlas (TWA and “Adli Tıpta Yaş Tayini (ATYT” books are used. Bone age is found to be 2 years older averagely than chronologic age, especially in puberty, according to the forensic age estimations described in the ATYT book. For the age estimation with teeth, Demirjian method is used. In time different methods are developed by modifying Demirjian method. However no accurate method was found. Histopathological studies are done on bone marrow cellularity and dermis cells. No correlation was found between histopathoogical findings and choronologic age. Important ethical and legal issues are brought with current age estimation methods especially in teenage period. Therefore it is required to prepare atlases of bone age compatible with our society by collecting the findings of the studies in Turkey. Another recommendation could be to pay attention to the courts of age raising trials of teenage women and give special emphasis on birth and population records

  11. Multidimensional kernel estimation

    CERN Document Server

    Milosevic, Vukasin

    2015-01-01

    Kernel estimation is one of the non-parametric methods used for estimation of probability density function. Its first ROOT implementation, as part of RooFit package, has one major issue, its evaluation time is extremely slow making in almost unusable. The goal of this project was to create a new class (TKNDTree) which will follow the original idea of kernel estimation, greatly improve the evaluation time (using the TKTree class for storing the data and creating different user-controlled modes of evaluation) and add the interpolation option, for 2D case, with the help of the new Delaunnay2D class.

  12. Multi-pitch estimation

    CERN Document Server

    Christensen, Mads

    2009-01-01

    Periodic signals can be decomposed into sets of sinusoids having frequencies that are integer multiples of a fundamental frequency. The problem of finding such fundamental frequencies from noisy observations is important in many speech and audio applications, where it is commonly referred to as pitch estimation. These applications include analysis, compression, separation, enhancement, automatic transcription and many more. In this book, an introduction to pitch estimation is given and a number of statistical methods for pitch estimation are presented. The basic signal models and associated es

  13. Power system state estimation

    CERN Document Server

    Ahmad, Mukhtar

    2012-01-01

    State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy.Engineers are

  14. Robust global motion estimation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A global motion estimation method based on robust statistics is presented in this paper. By using tracked feature points instead of whole image pixels to estimate parameters the process speeds up. To further speed up the process and avoid numerical instability, an alterative description of the problem is given, and three types of solution to the problem are compared. By using a two step process, the robustness of the estimator is also improved. Automatic initial value selection is an advantage of this method. The proposed approach is illustrated by a set of examples, which shows good results with high speed.

  15. A Deep Neural Network Model for Rainfall Estimation UsingPolarimetric WSR-88