WorldWideScience

Sample records for satellite-based estimates ncep

  1. Assessment of satellite-based precipitation estimates over Paraguay

    Science.gov (United States)

    Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

    2018-04-01

    Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

  2. Fine-tuning satellite-based rainfall estimates

    Science.gov (United States)

    Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

    2018-05-01

    Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

  3. 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

  4. 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 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.

  5. Connecting Satellite-Based Precipitation Estimates to Users

    Science.gov (United States)

    Huffman, George J.; Bolvin, David T.; Nelkin, Eric

    2018-01-01

    Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

  6. Improving satellite-based post-fire evapotranspiration estimates in semi-arid regions

    Science.gov (United States)

    Poon, P.; Kinoshita, A. M.

    2017-12-01

    Climate change and anthropogenic factors contribute to the increased frequency, duration, and size of wildfires, which can alter ecosystem and hydrological processes. The loss of vegetation canopy and ground cover reduces interception and alters evapotranspiration (ET) dynamics in riparian areas, which can impact rainfall-runoff partitioning. Previous research evaluated the spatial and temporal trends of ET based on burn severity and observed an annual decrease of 120 mm on average for three years after fire. Building upon these results, this research focuses on the Coyote Fire in San Diego, California (USA), which burned a total of 76 km2 in 2003 to calibrate and improve satellite-based ET estimates in semi-arid regions affected by wildfire. The current work utilizes satellite-based products and techniques such as the Google Earth Engine Application programming interface (API). Various ET models (ie. Operational Simplified Surface Energy Balance Model (SSEBop)) are compared to the latent heat flux from two AmeriFlux eddy covariance towers, Sky Oaks Young (US-SO3), and Old Stand (US-SO2), from 2000 - 2015. The Old Stand tower has a low burn severity and the Young Stand tower has a moderate to high burn severity. Both towers are used to validate spatial ET estimates. Furthermore, variables and indices, such as Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and the Normalized Burn Ratio (NBR) are utilized to evaluate satellite-based ET through a multivariate statistical analysis at both sites. This point-scale study will able to improve ET estimates in spatially diverse regions. Results from this research will contribute to the development of a post-wildfire ET model for semi-arid regions. Accurate estimates of post-fire ET will provide a better representation of vegetation and hydrologic recovery, which can be used to improve hydrologic models and predictions.

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

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, Manajit [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gotseff, Peter [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    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. Estimation of Volume and Freshwater Flux from the Arctic Ocean using SMAP and NCEP CFSv2

    Science.gov (United States)

    Bulusu, S.

    2017-12-01

    Spatial and temporal monitoring of sea surface salinity (SSS) plays an important role globally and especially over the Arctic Ocean. The Arctic ice melt has led to an influx of freshwater into the Arctic environment, a process that can be observed in SSS. The recently launched NASA's Soil Moisture Active Passive (SMAP) mission is primarily designed for the global monitoring of soil moisture using L- band (1.4GHz) frequency. SMAP also has the capability of measuring SSS and can thus extend the NASA's Aquarius salinity mission (ended June 7, 2015), salinity data record with improved temporal/spatial sampling. In this research an attempt is made to investigate the retrievability of SSS over the Arctic from SMAP satellite. The objectives of this study are to verify the use of SMAP sea surface salinity (and freshwater) variability in the Arctic Ocean and the extent to estimate freshwater, salt and volume flux from the Arctic Ocean. Along with SMAP data we will use NASA's Ice, Cloud,and land Elevation Satellites (ICESat and ICESat-2), and ESA's CryoSat-2, and NASA's Gravity Recovery and Climate Experiment (GRACE) satellites data to estimate ice melt in the Arctic. The preliminary results from SMAP compared well with the NCEP Climate Forecast System version 2 (CFSv2) salinity data in this region capturing patterns fairly well over the Arctic.

  9. An intercomparison and validation of satellite-based surface radiative energy flux estimates over the Arctic

    Science.gov (United States)

    Riihelä, Aku; Key, Jeffrey R.; Meirink, Jan Fokke; Kuipers Munneke, Peter; Palo, Timo; Karlsson, Karl-Göran

    2017-05-01

    Accurate determination of radiative energy fluxes over the Arctic is of crucial importance for understanding atmosphere-surface interactions, melt and refreezing cycles of the snow and ice cover, and the role of the Arctic in the global energy budget. Satellite-based estimates can provide comprehensive spatiotemporal coverage, but the accuracy and comparability of the existing data sets must be ascertained to facilitate their use. Here we compare radiative flux estimates from Clouds and the Earth's Radiant Energy System (CERES) Synoptic 1-degree (SYN1deg)/Energy Balanced and Filled, Global Energy and Water Cycle Experiment (GEWEX) surface energy budget, and our own experimental FluxNet / Satellite Application Facility on Climate Monitoring cLoud, Albedo and RAdiation (CLARA) data against in situ observations over Arctic sea ice and the Greenland Ice Sheet during summer of 2007. In general, CERES SYN1deg flux estimates agree best with in situ measurements, although with two particular limitations: (1) over sea ice the upwelling shortwave flux in CERES SYN1deg appears to be underestimated because of an underestimated surface albedo and (2) the CERES SYN1deg upwelling longwave flux over sea ice saturates during midsummer. The Advanced Very High Resolution Radiometer-based GEWEX and FluxNet-CLARA flux estimates generally show a larger range in retrieval errors relative to CERES, with contrasting tendencies relative to each other. The largest source of retrieval error in the FluxNet-CLARA downwelling shortwave flux is shown to be an overestimated cloud optical thickness. The results illustrate that satellite-based flux estimates over the Arctic are not yet homogeneous and that further efforts are necessary to investigate the differences in the surface and cloud properties which lead to disagreements in flux retrievals.

  10. Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling

    Science.gov (United States)

    Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.

    2015-01-01

    Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless

  11. Satellite-based ET estimation using Landsat 8 images and SEBAL model

    Directory of Open Access Journals (Sweden)

    Bruno Bonemberger da Silva

    Full Text Available ABSTRACT Estimation of evapotranspiration is a key factor to achieve sustainable water management in irrigated agriculture because it represents water use of crops. Satellite-based estimations provide advantages compared to direct methods as lysimeters especially when the objective is to calculate evapotranspiration at a regional scale. The present study aimed to estimate the actual evapotranspiration (ET at a regional scale, using Landsat 8 - OLI/TIRS images and complementary data collected from a weather station. SEBAL model was used in South-West Paraná, region composed of irrigated and dry agricultural areas, native vegetation and urban areas. Five Landsat 8 images, row 223 and path 78, DOY 336/2013, 19/2014, 35/2014, 131/2014 and 195/2014 were used, from which ET at daily scale was estimated as a residual of the surface energy balance to produce ET maps. The steps for obtain ET using SEBAL include radiometric calibration, calculation of the reflectance, surface albedo, vegetation indexes (NDVI, SAVI and LAI and emissivity. These parameters were obtained based on the reflective bands of the orbital sensor with temperature surface estimated from thermal band. The estimated ET values in agricultural areas, native vegetation and urban areas using SEBAL algorithm were compatible with those shown in the literature and ET errors between the ET estimates from SEBAL model and Penman Monteith FAO 56 equation were less than or equal to 1.00 mm day-1.

  12. Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

    Science.gov (United States)

    Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

    2008-01-01

    In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

  13. 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; hide

    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 < 2.5 microm (PM2.5) and nitrogen dioxide (NO2), and modelled estimates of ozone. Methods: We assigned satellite-based estimates of PM2.5 and NO2 at a spatial resolution of 0.1deg × 0.1deg and modeled estimates of ozone at a resolution of 1deg × 1deg to 183 ISAAC centers. We used center-level 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

  14. 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

  15. 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 PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 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 PM 2.5 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 PM 2.5 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 PM 2.5 estimates.

  16. 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 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.

  17. Estimating ionospheric delay using kriging: 2. Impact on satellite-based augmentation system availability

    Science.gov (United States)

    Sparks, Lawrence; Blanch, Juan; Pandya, Nitin

    2011-12-01

    An augmentation of the Global Positioning System, the Wide Area Augmentation System (WAAS) broadcasts, at each node of an ionospheric grid, an estimate of the vertical ionospheric delay and an integrity bound on the vertical delay error. To date, these quantities have been determined from a planar fit of slant delay measurements, projected to vertical using an obliquity factor specified by the standard thin shell model of the ionosphere. In a future WAAS upgrade (WAAS Follow-On Release 3), however, they will be calculated using an established, geo-statistical estimation technique known as kriging that generally provides higher estimate accuracy than planar fit estimation. This paper analyzes the impact of kriging on system availability. In a preliminary assessment, kriging is found to produce improvements in availability of up to 15%.

  18. An improvement of satellite-based algorithm for gross primary production estimation optimized over Korea

    Science.gov (United States)

    Pi, Kyoung-Jin; Han, Kyung-Soo; Kim, In-Hwan; Kim, Sang-Il; Lee, Min-Ji

    2011-11-01

    Monitoring the global gross primary production (GPP) is relevant to understanding the global carbon cycle and evaluating the effects of interannual climate variation on food and fiber production. GPP, the flux of carbon into ecosystems via photosynthetic assimilation, is an important variable in the global carbon cycle and a key process in land surface-atmosphere interactions. The Moderate-resolution Imaging Spectroradiometer (MODIS) is one of the primary global monitoring sensors. MODIS GPP has some of the problems that have been proven in several studies. Therefore this study was to solve the regional mismatch that occurs when using the MODIS GPP global product over Korea. To solve this problem, we estimated each of the GPP component variables separately to improve the GPP estimates. We compared our GPP estimates with validation GPP data to assess their accuracy. For all sites, the correlation was close with high significance (R2 = 0.8164, RMSE = 0.6126 g.C.m-2.d-1, bias = -0.0271 g.C.m-2.d-1). We also compared our results to those of other models. The component variables tended to be either over- or under-estimated when compared to those in other studies over the Korean peninsula, although the estimated GPP was better. The results of this study will likely improve carbon cycle modeling by capturing finer patterns with an integrated method of remote sensing. Keywords: VEGETATION, Gross Primary Production, MODIS.

  19. 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.

  20. 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.

  1. 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.

  2. Satellite-based estimates of surface water dynamics in the Congo River Basin

    Science.gov (United States)

    Becker, M.; Papa, F.; Frappart, F.; Alsdorf, D.; Calmant, S.; da Silva, J. Santos; Prigent, C.; Seyler, F.

    2018-04-01

    In the Congo River Basin (CRB), due to the lack of contemporary in situ observations, there is a limited understanding of the large-scale variability of its present-day hydrologic components and their link with climate. In this context, remote sensing observations provide a unique opportunity to better characterize those dynamics. Analyzing the Global Inundation Extent Multi-Satellite (GIEMS) time series, we first show that surface water extent (SWE) exhibits marked seasonal patterns, well distributed along the major rivers and their tributaries, and with two annual maxima located: i) in the lakes region of the Lwalaba sub-basin and ii) in the "Cuvette Centrale", including Tumba and Mai-Ndombe Lakes. At an interannual time scale, we show that SWE variability is influenced by ENSO and the Indian Ocean dipole events. We then estimate water level maps and surface water storage (SWS) in floodplains, lakes, rivers and wetlands of the CRB, over the period 2003-2007, using a multi-satellite approach, which combines the GIEMS dataset with the water level measurements derived from the ENVISAT altimeter heights. The mean annual variation in SWS in the CRB is 81 ± 24 km3 and contributes to 19 ± 5% of the annual variations of GRACE-derived terrestrial water storage (33 ± 7% in the Middle Congo). It represents also ∼6 ± 2% of the annual water volume that flows from the Congo River into the Atlantic Ocean.

  3. The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

    Science.gov (United States)

    Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

    2018-01-01

    Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

  4. 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.

  5. A Comparison of Two Above-Ground Biomass Estimation Techniques Integrating Satellite-Based Remotely Sensed Data and Ground Data for Tropical and Semiarid Forests in Puerto Rico

    Science.gov (United States)

    Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA)...

  6. 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

  7. 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

  8. 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

  9. 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...

  10. 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.

  11. NCEP Central Operations

    Science.gov (United States)

    ) NCO Organizational Chart NOAA's Weather and Climate Operational Supercomputing System is known as Climate Climate Prediction Climate Archives Weather Safety Storm Ready NOAA Central Library Photo Library NCO's MISSION * Execute the NCEP operational model suite - Create climate, weather, ocean, space and

  12. 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.

  13. 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

  14. 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

    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...... kg·DM/ha) than models based exclusively on FAPAR metrics (R2 = 0.63; RMSE = 550 kg·DM/ha) or agrometeorological variables (R2 = 0.55; RMSE = 585 kg·DM/ha). All the models provided reasonable outputs and showed a decrease in the mean annual yield with increasing latitude, together with an increase...

  15. 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.

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

    Science.gov (United States)

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

    2017-12-01

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

  17. Simulation of the Impact of New Aircraft- and Satellite-based Ocean Surface Wind Measurements on Estimates of Hurricane Intensity

    Science.gov (United States)

    Uhlhorn, Eric; Atlas, Robert; Black, Peter; Buckley, Courtney; Chen, Shuyi; El-Nimri, Salem; Hood, Robbie; Johnson, James; Jones, Linwood; Miller, Timothy; hide

    2009-01-01

    The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor currently under development to enhance real-time hurricane ocean surface wind observations. HIRAD builds on the capabilities of the Stepped Frequency Microwave Radiometer (SFMR), which now operates on NOAA P-3, G-4, and AFRC C-130 aircraft. Unlike the SFMR, which measures wind speed and rain rate along the ground track directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (approximately 3 times the aircraft altitude). To demonstrate potential improvement in the measurement of peak hurricane winds, we present a set of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing platforms (air, surface, and space-based) are simulated from the output of a high-resolution (approximately 1.7 km) numerical model. Simulated retrieval errors due to both instrument noise as well as model function accuracy are considered over the expected range of incidence angles, wind speeds and rain rates. Based on numerous simulated flight patterns and data source combinations, statistics are developed to describe relationships between the observed and true (from the model s perspective) peak wind speed. These results have implications for improving the estimation of hurricane intensity (as defined by the peak sustained wind anywhere in the storm), which may often go un-observed due to sampling limitations.

  18. Analysis of Groundwater Anomalies Estimated by GRACE and GLDAS Satellite-based Hydrological Model in the Gulf of Mexico

    Science.gov (United States)

    Lotfata, A.; Ambinakudige, S.

    2017-12-01

    Coastal regions face a higher risk of flooding. A rise in sea-level increases flooding chances in low-lying areas. A major concern is the effect of sea-level rise on the depth of the fresh water/salt water interface in the aquifers of the coastal regions. A sea-level change rise impacts the hydrological system of the aquifers. Salt water intrusion into fresh water aquifers increase water table levels. Flooding prone areas in the coast are at a higher risk of salt water intrusion. The Gulf coast is one of the most vulnerable flood areas due to its natural weather patterns. There is not yet a local assessment of the relation between groundwater level and sea-level rising. This study investigates the projected sea-level rise models and the anomalous groundwater level during January 2002 to December 2016. We used the NASA Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) satellite data in the analysis. We accounted the leakage error and the measurement error in GRACE data. GLDAS data was used to calculate the groundwater storage from the total water storage estimated using GRACE data (ΔGW=ΔTWS (soil moisture, surface water, groundwater, and canopy water) - ΔGLDAS (soil moisture, surface water, and canopy water)). The preliminary results indicate that the total water storage is increasing in parts of the Gulf of Mexico. GRACE data show high soil wetness and groundwater levels in Mississippi, Alabama and Texas coasts. Because sea-level rise increases the probability of flooding in the Gulf coast and affects the groundwater, we will analyze probable interactions between sea-level rise and groundwater in the study area. To understand regional sea-level rise patterns, we will investigate GRACE Ocean data along the Gulf coasts. We will quantify ocean total water storage, its salinity, and its relationship with the groundwater level variations in the Gulf coast.

  19. Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

    Science.gov (United States)

    Mitchell, K. E.

    2006-12-01

    The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global

  20. NCEP BUFRLIB Software User Guide

    Science.gov (United States)

    Integration Branch > Decoders > BUFRLIB BUFRLIB Software User Guide This document set describes how to use the NCEP BUFRLIB software to encode or decode BUFR messages. It is not intended to be a primer on background knowledge of the basic concepts of BUFR and will focus solely on how to use the BUFRLIB software

  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. Atmospheric balance of the humidity and estimate of the precipitation recycled in Colombia according to the re-analysis NCEP/NCAR

    International Nuclear Information System (INIS)

    Cuartas, Adriana; Poveda, German

    2002-01-01

    The magnitudes of the entrance humidity flows and exit are considered and the amount of precipitable water at different levels from the atmospheric column on Colombia. The water balance is quantified in the Colombian atmosphere; the regions and the atmospheric levels of entrance and exit of humidity are identified. The hypothesis that in the long term the net atmospheric humidity influence must be equal to the average of long term of the net run-off is verified. In addition, the percentage of recycled precipitation is considered on the Colombian territory. The variability during the two phases of the ENSO is analyzed. The calculations are made with the information of the climatic project Reanalysis developed by the National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR), with the collaboration of the National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite of the U.S.A. For this work it was counted on monthly information of 41 years between 1958-1998. The hydrological information was obtained from the project Balances Hidrologicos de Colombia, 1999, made by the Posgrado de Recursos Hidraulicos, de la Universidad Nacional, with the support of COLCIENCIAS and the Unidad de Planeacion Minero Energetica-UPME. The results showed the average value of the net influence of humidity to the atmosphere of Colombia is of 5716 mm/year, with a great variability in both phases of the ENSO. The greater humidity advection towards Colombia occurs in the low levels of pressure (between 1000 and 850 hPa), and originating of all the directions, mainly of trade winds of the east and trade winds of the west. Also one was that the greater humidity transport towards Colombia occurs in trimesters DJF and MAM, with average values 505,1 and 606,6 mm/year, respectively. It was observed that the hypothesis that in the long term, the net atmospheric flux, is equal to the net terrestrial run-off, reasonably is adapted for

  3. Prevalence of metabolic syndrome using NCEP-ATPIII and ...

    African Journals Online (AJOL)

    To estimate the prevalence of metabolic syndrome using ınternational dietetics federation (IDF) versus National cholesterol education program; adult treatment panel III (NCEP-ATPIII) definitions in Turkish adults. A cross-sectional study was conducted on a total of 1531 (male 758 and female 773) Turkish adults, aged ...

  4. 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 is...

  5. Estimation of Satellite-Based SO42- and NH4+ Composition of Ambient Fine Particulate Matter Over China Using Chemical Transport Model

    Science.gov (United States)

    Si, Y.; Li, S.; Chen, L.; Yu, C.; Zhu, W.

    2018-04-01

    Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1° × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of -35.9 %, NME of 48.2 %, ARB_50 % of 53.68 % for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42- and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42-: -0.61 %; NH4+: -0.21 %), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004-2007 and 2008-2011, followed by a negative trend over the period 2012-2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as

  6. 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....

  7. Satellite-based estimates of long-term exposure to fine particulate matter are associated with C-reactive protein in 30 034 Taiwanese adults.

    Science.gov (United States)

    Zhang, Zilong; Chang, Ly-Yun; Lau, Alexis K H; Chan, Ta-Chien; Chieh Chuang, Yuan; Chan, Jimmy; Lin, Changqing; Kai Jiang, Wun; Dear, Keith; Zee, Benny C Y; Yeoh, Eng-Kiong; Hoek, Gerard; Tam, Tony; Qian Lao, Xiang

    2017-08-01

    Particulate matter (PM) air pollution is associated with the risk of cardiovascular morbidity and mortality. However, the biological mechanism underlying the associations remains unclear. Atherosclerosis, the underlying pathology of cardiovascular disease, is a chronic inflammatory process. We therefore investigated the association of long-term exposure to fine PM (PM2.5) with C-reactive protein (CRP), a sensitive marker of systemic inflammation, in a large Taiwanese population. Participants were from a large cohort who participated in a standard medical examination programme with measurements of high-sensitivity CRP between 2007 and 2014. We used a spatiotemporal model to estimate 2-year average PM2.5 exposure at each participant's address, based on satellite-derived aerosol optical depth data. General regression models were used for baseline data analysis and mixed-effects linear regression models were used for repeated data analysis to investigate the associations between PM2.5 exposure and CRP, adjusting for a wide range of potential confounders. In this population of 30 034 participants with 39 096 measurements, every 5 μg/m3 PM2.5 increment was associated with a 1.31% increase in CRP [95% confidence interval (CI): 1.00%, 1.63%) after adjusting for confounders. For those participants with repeated CRP measurements, no significant changes were observed between the first and last measurements (0.88 mg/l vs 0.89 mg/l, P = 0.337). The PM2.5 concentrations remained stable over time between 2007 and 2014. Long-term exposure to PM2.5 is associated with increased level of systemic inflammation, supporting the biological link between PM2.5 air pollution and deteriorating cardiovascular health. Air pollution reduction should be an important strategy to prevent cardiovascular disease. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association

  8. Assessing the Suitability and Limitations of Satellite-based Measurements for Estimating CO, CO2, NO2 and O3 Concentrations over the Niger Delta

    Science.gov (United States)

    Fagbeja, M. A.; Hill, J. L.; Chatterton, T. J.; Longhurst, J. W.; Akinyede, J. O.

    2011-12-01

    Space-based satellite sensor technology may provide important tools in the study and assessment of national, regional and local air pollution. However, the application of optical satellite sensor observation of atmospheric trace gases, including those considered to be 'air pollutants', within the lower latitudes is limited due to prevailing climatic conditions. The lack of appropriate air pollution ground monitoring stations within the tropical belt reduces the ability to verify and calibrate space-based measurements. This paper considers the suitability of satellite remotely sensed data in estimating concentrations of atmospheric trace gases in view of the prevailing climate over the Niger Delta region. The methodological approach involved identifying suitable satellite data products and using the ArcGIS Geostatistical Analyst kriging interpolation technique to generate surface concentrations from satellite column measurements. The observed results are considered in the context of the climate of the study area. Using data from January 2001 to December 2005, an assessment of the suitability of satellite sensor data to interpolate column concentrations of trace gases over the Niger Delta has been undertaken and indicates varying degrees of reliability. The level of reliability of the interpolated surfaces is predicated on the number and spatial distributions of column measurements. Accounting for the two climatic seasons in the region, the interpolation of total column concentrations of CO and CO2 from SCIAMACHY produced both reliable and unreliable results over inland parts of the region during the dry season, while mainly unreliable results are observed over the coastal parts especially during the rainy season due to inadequate column measurements. The interpolation of tropospheric measurements of NO2 and O3 from GOME and OMI respectively produced reliable results all year. This is thought to be due to the spatial distribution of available column measurements

  9. 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.

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

    International Nuclear Information System (INIS)

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

    1998-01-01

    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

  11. Satellite-based laser windsounder

    International Nuclear Information System (INIS)

    Schultz, J.F.; Czuchlewski, S.J.; Quick, C.R.

    1997-01-01

    This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project''s primary objective is to determine the technical feasibility of using satellite-based laser wind sensing systems for detailed study of winds, aerosols, and particulates around and downstream of suspected proliferation facilities. Extensive interactions with the relevant operational organization resulted in enthusiastic support and useful guidance with respect to measurement requirements and priorities. Four candidate wind sensing techniques were evaluated, and the incoherent Doppler technique was selected. A small satellite concept design study was completed to identify the technical issues inherent in a proof-of-concept small satellite mission. Use of a Mach-Zehnder interferometer instead of a Fabry-Perot would significantly simplify the optical train and could reduce weight, and possibly power, requirements with no loss of performance. A breadboard Mach-Zehnder interferometer-based system has been built to verify these predictions. Detailed plans were made for resolving other issues through construction and testing of a ground-based lidar system in collaboration with the University of Wisconsin, and through numerical lidar wind data assimilation studies

  12. Satellite Based Cropland Carbon Monitoring System

    Science.gov (United States)

    Bandaru, V.; Jones, C. D.; Sedano, F.; Sahajpal, R.; Jin, H.; Skakun, S.; Pnvr, K.; Kommareddy, A.; Reddy, A.; Hurtt, G. C.; Izaurralde, R. C.

    2017-12-01

    Agricultural croplands act as both sources and sinks of atmospheric carbon dioxide (CO2); absorbing CO2 through photosynthesis, releasing CO2 through autotrophic and heterotrophic respiration, and sequestering CO2 in vegetation and soils. Part of the carbon captured in vegetation can be transported and utilized elsewhere through the activities of food, fiber, and energy production. As well, a portion of carbon in soils can be exported somewhere else by wind, water, and tillage erosion. Thus, it is important to quantify how land use and land management practices affect the net carbon balance of croplands. To monitor the impacts of various agricultural activities on carbon balance and to develop management strategies to make croplands to behave as net carbon sinks, it is of paramount importance to develop consistent and high resolution cropland carbon flux estimates. Croplands are typically characterized by fine scale heterogeneity; therefore, for accurate carbon flux estimates, it is necessary to account for the contribution of each crop type and their spatial distribution. As part of NASA CMS funded project, a satellite based Cropland Carbon Monitoring System (CCMS) was developed to estimate spatially resolved crop specific carbon fluxes over large regions. This modeling framework uses remote sensing version of Environmental Policy Integrated Climate Model and satellite derived crop parameters (e.g. leaf area index (LAI)) to determine vertical and lateral carbon fluxes. The crop type LAI product was developed based on the inversion of PRO-SAIL radiative transfer model and downscaled MODIS reflectance. The crop emergence and harvesting dates were estimated based on MODIS NDVI and crop growing degree days. To evaluate the performance of CCMS framework, it was implemented over croplands of Nebraska, and estimated carbon fluxes for major crops (i.e. corn, soybean, winter wheat, grain sorghum, alfalfa) grown in 2015. Key findings of the CCMS framework will be presented

  13. Satellite-Based Precipitation Datasets

    Science.gov (United States)

    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  14. Leo satellite-based telecommunication network concepts

    Science.gov (United States)

    Aiken, John G.; Swan, Peter A.; Leopold, Ray J.

    1991-01-01

    Design considerations are discussed for Low Earth Orbit (LEO) satellite based telecommunications networks. The satellites are assumed to be connected to each other via intersatellite links. They are connected to the end user either directly or through gateways to other networks. Frequency reuse, circuit switching, packet switching, call handoff, and routing for these systems are discussed by analogy with terrestrial cellular (mobile radio) telecommunication systems.

  15. 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...

  16. 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

  17. Using satellite-based measurements to explore ...

    Science.gov (United States)

    New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently spatially averaged) measurements of atmospheric conditions to diagnose the occurrence of NPF and NPF characteristics. We demonstrate the potential for using satellite-measurements of insolation (UV), trace gas concentrations (sulfur dioxide (SO2), nitrogen dioxide (NO2), ammonia (NH3), formaldehyde (HCHO), ozone (O3)), aerosol optical properties (aerosol optical depth (AOD), Ångström exponent (AE)), and a proxy of biogenic volatile organic compound emissions (leaf area index (LAI), temperature (T)) as predictors for NPF characteristics: formation rates, growth rates, survival probabilities, and ultrafine particle (UFP) concentrations at five locations across North America. NPF at all sites is most frequent in spring, exhibits a one-day autocorrelation, and is associated with low condensational sink (AOD×AE) and HCHO concentrations, and high UV. However, there are important site-to-site variations in NPF frequency and characteristics, and in which of the predictor variables (particularly gas concentrations) significantly contribute to the explanatory power of regression models built to predict those characteristics. This finding may provide a partial explanation for the reported spatia

  18. Estimating the accuracy of the technique of reconstructing the rotational motion of a satellite based on the measurements of its angular velocity and the magnetic field of the Earth

    Science.gov (United States)

    Belyaev, M. Yu.; Volkov, O. N.; Monakhov, M. I.; Sazonov, V. V.

    2017-09-01

    The paper has studied the accuracy of the technique that allows the rotational motion of the Earth artificial satellites (AES) to be reconstructed based on the data of onboard measurements of angular velocity vectors and the strength of the Earth magnetic field (EMF). The technique is based on kinematic equations of the rotational motion of a rigid body. Both types of measurement data collected over some time interval have been processed jointly. The angular velocity measurements have been approximated using convenient formulas, which are substituted into the kinematic differential equations for the quaternion that specifies the transition from the body-fixed coordinate system of a satellite to the inertial coordinate system. Thus obtained equations represent a kinematic model of the rotational motion of a satellite. The solution of these equations, which approximate real motion, has been found by the least-square method from the condition of best fitting between the data of measurements of the EMF strength vector and its calculated values. The accuracy of the technique has been estimated by processing the data obtained from the board of the service module of the International Space Station ( ISS). The reconstruction of station motion using the aforementioned technique has been compared with the telemetry data on the actual motion of the station. The technique has allowed us to reconstruct the station motion in the orbital orientation mode with a maximum error less than 0.6° and the turns with a maximal error of less than 1.2°.

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

    African Journals Online (AJOL)

    ... of densely-invaded riparian areas is likely more pronounced. We concluded that the clearing of IAPs by the WFW programme has a positive effect on the availability of water resources through a reduction in ET. Keywords: invasive alien plants; indigenous vegetation; remote sensing; water use; evapotranspiration; SEBAL; ...

  20. 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

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

    KAUST Repository

    Lopez Valencia, Oliver Miguel

    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

  2. Satellite-based monitoring of cotton evapotranspiration

    Science.gov (United States)

    Dalezios, Nicolas; Dercas, Nicholas; Tarquis, Ana Maria

    2016-04-01

    Water for agricultural use represents the largest share among all water uses. Vulnerability in agriculture is influenced, among others, by extended periods of water shortage in regions exposed to droughts. Advanced technological approaches and methodologies, including remote sensing, are increasingly incorporated for the assessment of irrigation water requirements. In this paper, remote sensing techniques are integrated for the estimation and monitoring of crop evapotranspiration ETc. The study area is Thessaly central Greece, which is a drought-prone agricultural region. Cotton fields in a small agricultural sub-catchment in Thessaly are used as an experimental site. Daily meteorological data and weekly field data are recorded throughout seven (2004-2010) growing seasons for the computation of reference evapotranspiration ETo, crop coefficient Kc and cotton crop ETc based on conventional data. Satellite data (Landsat TM) for the corresponding period are processed to estimate cotton crop coefficient Kc and cotton crop ETc and delineate its spatiotemporal variability. The methodology is applied for monitoring Kc and ETc during the growing season in the selected sub-catchment. Several error statistics are used showing very good agreement with ground-truth observations.

  3. A satellite-based global landslide model

    Directory of Open Access Journals (Sweden)

    A. Farahmand

    2013-05-01

    Full Text Available Landslides are devastating phenomena that cause huge damage around the world. This paper presents a quasi-global landslide model derived using satellite precipitation data, land-use land cover maps, and 250 m topography information. This suggested landslide model is based on the Support Vector Machines (SVM, a machine learning algorithm. The National Aeronautics and Space Administration (NASA Goddard Space Flight Center (GSFC landslide inventory data is used as observations and reference data. In all, 70% of the data are used for model development and training, whereas 30% are used for validation and verification. The results of 100 random subsamples of available landslide observations revealed that the suggested landslide model can predict historical landslides reliably. The average error of 100 iterations of landslide prediction is estimated to be approximately 7%, while approximately 2% false landslide events are observed.

  4. Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

    2012-12-01

    Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

  5. Satellite based Ocean Forecasting, the SOFT project

    Science.gov (United States)

    Stemmann, L.; Tintoré, J.; Moneris, S.

    2003-04-01

    The knowledge of future oceanic conditions would have enormous impact on human marine related areas. For such reasons, a number of international efforts are being carried out to obtain reliable and manageable ocean forecasting systems. Among the possible techniques that can be used to estimate the near future states of the ocean, an ocean forecasting system based on satellite imagery is developped through the Satelitte based Ocean ForecasTing project (SOFT). SOFT, established by the European Commission, considers the development of a forecasting system of the ocean space-time variability based on satellite data by using Artificial Intelligence techniques. This system will be merged with numerical simulation approaches, via assimilation techniques, to get a hybrid SOFT-numerical forecasting system of improved performance. The results of the project will provide efficient forecasting of sea-surface temperature structures, currents, dynamic height, and biological activity associated to chlorophyll fields. All these quantities could give valuable information on the planning and management of human activities in marine environments such as navigation, fisheries, pollution control, or coastal management. A detailed identification of present or new needs and potential end-users concerned by such an operational tool is being performed. The project would study solutions adapted to these specific needs.

  6. Satellite-based assessment of grassland yields

    Science.gov (United States)

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

    2015-04-01

    Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available, cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.

  7. An assessment of the surface climate in the NCEP climate forecast system reanalysis

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Wanqiu; Xie, Pingping; Yoo, Soo-Hyun; Xue, Yan; Kumar, Arun [Climate Prediction Center, NCEP/NWS/NOAA, Camp Springs, MD (United States); Wu, Xingren [Environmental Modeling Center, NCEP/NWS/NOAA, Camp Springs, MD (United States)

    2011-10-15

    This paper analyzes surface climate variability in the climate forecast system reanalysis (CFSR) recently completed at the National Centers for Environmental Prediction (NCEP). The CFSR represents a new generation of reanalysis effort with first guess from a coupled atmosphere-ocean-sea ice-land forecast system. This study focuses on the analysis of climate variability for a set of surface variables including precipitation, surface air 2-m temperature (T2m), and surface heat fluxes. None of these quantities are assimilated directly and thus an assessment of their variability provides an independent measure of the accuracy. The CFSR is compared with observational estimates and three previous reanalyses (the NCEP/NCAR reanalysis or R1, the NCEP/DOE reanalysis or R2, and the ERA40 produced by the European Centre for Medium-Range Weather Forecasts). The CFSR has improved time-mean precipitation distribution over various regions compared to the three previous reanalyses, leading to a better representation of freshwater flux (evaporation minus precipitation). For interannual variability, the CFSR shows improved precipitation correlation with observations over the Indian Ocean, Maritime Continent, and western Pacific. The T2m of the CFSR is superior to R1 and R2 with more realistic interannual variability and long-term trend. On the other hand, the CFSR overestimates downward solar radiation flux over the tropical Western Hemisphere warm pool, consistent with a negative cloudiness bias and a positive sea surface temperature bias. Meanwhile, the evaporative latent heat flux in CFSR appears to be larger than other observational estimates over most of the globe. A few deficiencies in the long-term variations are identified in the CFSR. Firstly, dramatic changes are found around 1998-2001 in the global average of a number of variables, possibly related to the changes in the assimilated satellite observations. Secondly, the use of multiple streams for the CFSR induces spurious

  8. The NCEP/NCAR 40-Year Reanalysis Project.

    Science.gov (United States)

    Kalnay, E.; Kanamitsu, M.; Kistler, R.; Collins, W.; Deaven, D.; Gandin, L.; Iredell, M.; Saha, S.; White, G.; Woollen, J.; Zhu, Y.; Leetmaa, A.; Reynolds, B.; Chelliah, M.; Ebisuzaki, W.; Higgins, W.; Janowiak, J.; Mo, K. C.; Ropelewski, C.; Wang, J.; Jenne, Roy; Joseph, Dennis

    1996-03-01

    The NCEP and NCAR are cooperating in a project (denoted "reanalysis") to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957-96. This eliminates perceived climate jumps associated with changes in the data assimilation system.The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided by different countries and organizations. The system has been designed with advanced quality control and monitoring components, and can produce 1 mon of reanalysis per day on a Cray YMP/8 supercomputer. Different types of output archives are being created to satisfy different user needs, including a "quick look" CD-ROM (one per year) with six tropospheric and stratospheric fields available twice daily, as well as surface, top-of-the-atmosphere, and isentropic fields. Reanalysis information and selected output is also available on-line via the Internet (http//:nic.fb4.noaa.gov:8000). A special CD-ROM, containing 13 years of selected observed, daily, monthly, and climatological data from the NCEP/NCAR Re-analysis, is included with this issue. Output variables are classified into four classes, depending on the degree to which they are influenced by the observations and/or the model. For example, "C" variables (such as precipitation and surface fluxes) are completely determined

  9. 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.

  10. Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

    Science.gov (United States)

    Deng, Xueliang; Nie, Suping; Deng, Weitao; Cao, Weihua

    2018-04-01

    In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.

  11. Solar cycle signatures in the NCEP equatorial annual oscillation

    Science.gov (United States)

    Mayr, H. G.; Mengel, J. G.; Huang, F. T.; Nash, E. R.

    2009-08-01

    Our analysis of temperature and zonal wind data (1958 to 2006) from the National Center for Atmospheric Research (NCAR) reanalysis (Re-1), supplied by the National Centers for Environmental Prediction (NCEP), shows that the hemispherically symmetric 12-month equatorial annual oscillation (EAO) contains spectral signatures with periods around 11 years. Moving windows of 44 years show that, below 20 km, the 11-year modulation of the EAO is phase locked to the solar cycle (SC). The spectral features from the 48-year data record reveal modulation signatures of 9.6 and 12 years, which produce EAO variations that mimic in limited altitude regimes the varying maxima and minima of the 10.7 cm flux solar index. Above 20 km, the spectra also contain modulation signatures with periods around 11 years, but the filtered variations are too irregular to suggest that systematic SC forcing is the principal agent.

  12. Solar cycle signatures in the NCEP equatorial annual oscillation

    Directory of Open Access Journals (Sweden)

    H. G. Mayr

    2009-08-01

    Full Text Available Our analysis of temperature and zonal wind data (1958 to 2006 from the National Center for Atmospheric Research (NCAR reanalysis (Re-1, supplied by the National Centers for Environmental Prediction (NCEP, shows that the hemispherically symmetric 12-month equatorial annual oscillation (EAO contains spectral signatures with periods around 11 years. Moving windows of 44 years show that, below 20 km, the 11-year modulation of the EAO is phase locked to the solar cycle (SC. The spectral features from the 48-year data record reveal modulation signatures of 9.6 and 12 years, which produce EAO variations that mimic in limited altitude regimes the varying maxima and minima of the 10.7 cm flux solar index. Above 20 km, the spectra also contain modulation signatures with periods around 11 years, but the filtered variations are too irregular to suggest that systematic SC forcing is the principal agent.

  13. 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.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    variations are clearly visible across the domain; for instance sheltering effects caused by the land masses. The satellite based wind resource maps have two shortcomings. One is the lack of information at the higher vertical levels where wind turbines operate. The other is the limited number of overlapping...... years of WRF data – specifically the parameters heat flux, air temperature, and friction velocity – are used to calculate a long-term correction for atmospheric stability effects. The stability correction is applied to the satellite based wind resource maps together with a vertical wind profile...... from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In this presentation, satellite wind maps are used in combination with mast observations and numerical...

  15. 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.

  16. Black Sea's wind wave parameters derived from numerical simulations driven by NCEP/NCAR and NCEP CFSR reanalyses

    Science.gov (United States)

    Gippius, Fedor; Myslenkov, Stanislav; Stoliarova, Elena; Arkhipkin, Victor

    2017-04-01

    This study is focused on typical features of spatiotemporal distribution of wind wave parameters on the Black Sea. These parameters were calculated during two experiments using the third-generation spectral wind wave model SWAN. During the first run a 5x5 km rectangular grid covering the entire Black Sea was used. Forcing parameters - wind speed and direction - were derived from the NCEP/NCAR reanalysis for the period between 1948 and 2010. During the second run high resolution wind fields form the NCEP-CFSR reanalysis were used as forcing for the period from 1979 till 2010. For the period form 2011 till 2015 the second version of this reanalysis was used. The computations were performed on an unstructured computational grid with cell size depending on the sea depth. The distance between grid points varies from 10—15 km in deep-water regions till 500 m in coastal areas. Calculated values of significant wave heights (SWH) obtained during both runs were validated against instrumental measurements data. In the first case we used satellite altimetry data from the AVISO project. It turned out that calculated SWH values are typically lower than observed ones - the deviation between them was 0.3 m on the average, its maximum was of 1.67 m. Therefore, an empirical formula was applied to correct the modeling results obtained during the first experiment. For the second experiment in situ measurements performed by a Datawell buoy installed 7 km off the city Gelendzhik were used for validation. The comparison of measured and modelled values of SWH shows a good agreement between these parameters in this case. No correction was applied to the results of the second experiment. We applied the results of the NCEP/NCAR experiment to assess various features of the wave climate of the entire Black Sea. Thus, maximal SWH are observed in winter and autumn in two areas in the southwestern and northeastern parts of the sea; SWH values in these areas exceed 9 m. To define areas with most

  17. Climate Downscaling over Nordeste, Brazil, Using the NCEP RSM97.

    Science.gov (United States)

    Sun, Liqiang; Ferran Moncunill, David; Li, Huilan; Divino Moura, Antonio; de Assis de Souza Filho, Francisco

    2005-02-01

    The NCEP Regional Spectral Model (RSM), with horizontal resolution of 60 km, was used to downscale the ECHAM4.5 AGCM (T42) simulations forced with observed SSTs over northeast Brazil. An ensemble of 10 runs for the period January-June 1971-2000 was used in this study. The RSM can resolve the spatial patterns of observed seasonal precipitation and capture the interannual variability of observed seasonal precipitation as well. The AGCM bias in displacement of the Atlantic ITCZ is partially corrected in the RSM. The RSM probability distribution function of seasonal precipitation anomalies is in better agreement with observations than that of the driving AGCM. Good potential prediction skills are demonstrated by the RSM in predicting the interannual variability of regional seasonal precipitation. The RSM can also capture the interannual variability of observed precipitation at intraseasonal time scales, such as precipitation intensity distribution and dry spells. A drought index and a flooding index were adopted to indicate the severity of drought and flooding conditions, and their interannual variability was reproduced by the RSM. The overall RSM performance in the downscaled climate of the ECHAM4.5 AGCM is satisfactory over Nordeste. The primary deficiency is a systematic dry bias for precipitation simulation.

  18. [Surveying a zoological facility through satellite-based geodesy].

    Science.gov (United States)

    Böer, M; Thien, W; Tölke, D

    2000-06-01

    In the course of a thesis submitted for a diploma degree within the Fachhochschule Oldenburg the Serengeti Safaripark was surveyed in autumn and winter 1996/97 laying in the planning foundations for the application for licences from the controlling authorities. Taking into consideration the special way of keeping animals in the Serengeti Safaripark (game ranching, spacious walk-through-facilities) the intention was to employ the outstanding satellite based geodesy. This technology relies on special aerials receiving signals from 24 satellites which circle around the globe. These data are being gathered and examined. This examination produces the exact position of this aerial in a system of coordinates which allows depicting this point on a map. This procedure was used stationary (from a strictly defined point) as well as in the movement (in a moving car). Additionally conventional procedures were used when the satellite based geodesy came to its limits. Finally a detailed map of the Serengeti Safaripark was created which shows the position and size of stables and enclosures as well as wood and water areas and the sectors of the leisure park. Furthermore the established areas of the enclosures together with an already existing animal databank have flown into an information system with the help of which the stock of animals can be managed enclosure-orientated.

  19. AMOC variations in 1979-2008 simulated by NCEP operational ocean data assimilation system

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Boyin [Climate Prediction Center, NOAA, Camp Springs, MD (United States); National Climate Data Center, Asheville, NC (United States); Xue, Yan; Kumar, Arun [Climate Prediction Center, NOAA, Camp Springs, MD (United States); Behringer, David W. [Environmental Modeling Center, NOAA, Camp Springs, MD (United States)

    2012-02-15

    Variations in the Atlantic meridional overturning circulation (AMOC) between 1979 and 2008 are documented using the operational ocean analysis, the Global Ocean Data Assimilation System (GODAS), at the National Centers for Climate Prediction (NCEP). The maximum AMOC at 40 N is about 16 Sv in average with peak-to-peak variability of 3-4 Sv. The AMOC variations are dominated by an upward trend from 1980 to 1995, and a downward trend from 1995 to 2008. The maximum AMOC at 26.5 N is slightly weaker than hydrographic estimates and observations from mooring array. The dominant variability of the AMOC in 20 -65 N (the first EOF, 51% variance) is highly correlated with that in the subsurface temperature (the first EOF, 33% variance), and therefore, with density (the first EOF, 25% variance) in the North Atlantic, and is consistent with the observational estimates based on the World Ocean Database 2005. The dominant variabilities of AMOC and subsurface temperature are also analyzed in the context of possible links with the net surface heat flux, deep convection, western boundary current, and subpolar gyre. Variation in the net surface heat flux is further linked to the North Atlantic Oscillation (NAO) index which is found to lead AMOC variations by about 5 years. Our results indicate that AMOC variations can be documented based on an ocean analysis system such as GODAS. (orig.)

  20. 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.

  1. Programmable Ultra-Lightweight System Adaptable Radio Satellite Base Station

    Science.gov (United States)

    Varnavas, Kosta; Sims, Herb

    2015-01-01

    With the explosion of the CubeSat, small sat, and nanosat markets, the need for a robust, highly capable, yet affordable satellite base station, capable of telemetry capture and relay, is significant. The Programmable Ultra-Lightweight System Adaptable Radio (PULSAR) is NASA Marshall Space Flight Center's (MSFC's) software-defined digital radio, developed with previous Technology Investment Programs and Technology Transfer Office resources. The current PULSAR will have achieved a Technology Readiness Level-6 by the end of FY 2014. The extensibility of the PULSAR will allow it to be adapted to perform the tasks of a mobile base station capable of commanding, receiving, and processing satellite, rover, or planetary probe data streams with an appropriate antenna.

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  3. Improved Satellite-based Photosysnthetically Active Radiation (PAR) for Air Quality Studies

    Science.gov (United States)

    Pour Biazar, A.; McNider, R. T.; Cohan, D. S.; White, A.; Zhang, R.; Dornblaser, B.; Doty, K.; Wu, Y.; Estes, M. J.

    2015-12-01

    One of the challenges in understanding the air quality over forested regions has been the uncertainties in estimating the biogenic hydrocarbon emissions. Biogenic volatile organic compounds, BVOCs, play a critical role in atmospheric chemistry, particularly in ozone and particulate matter (PM) formation. In southeastern United States, BVOCs (mostly as isoprene) are the dominant summertime source of reactive hydrocarbon. Despite significant efforts in improving BVOC estimates, the errors in emission inventories remain a concern. Since BVOC emissions are particularly sensitive to the available photosynthetically active radiation (PAR), model errors in PAR result in large errors in emission estimates. Thus, utilization of satellite observations to estimate PAR can help in reducing emission uncertainties. Satellite-based PAR estimates rely on the technique used to derive insolation from satellite visible brightness measurements. In this study we evaluate several insolation products against surface pyranometer observations and offer a bias correction to generate a more accurate PAR product. The improved PAR product is then used in biogenic emission estimates. The improved biogenic emission estimates are compared to the emission inventories over Texas and used in air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). A series of sensitivity simulations will be performed and evaluated against Discover-AQ observations to test the impact of satellite-derived PAR on air quality simulations.

  4. 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.

  5. 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.

  6. Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

    Science.gov (United States)

    Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

  7. 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

  8. Satellite-based Drought Reporting on the Navajo Nation

    Science.gov (United States)

    McCullum, A. J. K.; Schmidt, C.; Ly, V.; Green, R.; McClellan, C.

    2017-12-01

    The Navajo Nation (NN) is the largest reservation in the US, and faces challenges related to water management during long-term and widespread drought episodes. The Navajo Nation is a federally recognized tribe, which has boundaries within Arizona, New Mexico, and Utah. The Navajo Nation has a land area of over 70,000 square kilometers. The Navajo Nation Department of Water Resources (NNDWR) reports on drought and climatic conditions through the use of regional Standardized Precipitation Index (SPI) values and a network of in-situ rainfall, streamflow, and climate data. However, these data sources lack the spatial detail and consistent measurements needed to provide a coherent understanding of the drought regime within the Nation's regional boundaries. This project, as part of NASA's Western Water Applications Office (WWAO), improves upon the recently developed Drought Severity Assessment Tool (DSAT) to ingest satellite-based precipitation data to generate SPI values for specific administrative boundaries within the reservation. The tool aims to: (1) generate SPI values and summary statistics for regions of interest on various timescales, (2) to visualize SPI values within a web-map application, and (3) produce maps and comparative statistical outputs in the format required for annual drought reporting. The co-development of the DSAT with NN partners is integral to increasing the sustained use of Earth Observations for water management applications. This tool will provide data to support the NN in allocation of drought contingency dollars to the regions most adversely impacted by declines in water availability.

  9. 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.

  10. 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.

  11. Improved Lower Mekong River Basin Hydrological Decision Making Using NASA Satellite-based Earth Observation Systems

    Science.gov (United States)

    Bolten, J. D.; Mohammed, I. N.; Srinivasan, R.; Lakshmi, V.

    2017-12-01

    Better understanding of the hydrological cycle of the Lower Mekong River Basin (LMRB) and addressing the value-added information of using remote sensing data on the spatial variability of soil moisture over the Mekong Basin is the objective of this work. In this work, we present the development and assessment of the LMRB (drainage area of 495,000 km2) Soil and Water Assessment Tool (SWAT). The coupled model framework presented is part of SERVIR, a joint capacity building venture between NASA and the U.S. Agency for International Development, providing state-of-the-art, satellite-based earth monitoring, imaging and mapping data, geospatial information, predictive models, and science applications to improve environmental decision-making among multiple developing nations. The developed LMRB SWAT model enables the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil texture, and land cover and land use data to drive SWAT model simulations over the Lower Mekong River Basin. The LMRB SWAT model driven by remote sensing climate data was calibrated and verified with observed runoff data at the watershed outlet as well as at multiple sites along the main river course. Another LMRB SWAT model set driven by in-situ climate observations was also calibrated and verified to streamflow data. Simulated soil moisture estimates from the two models were then examined and compared to a downscaled Soil Moisture Active Passive Sensor (SMAP) 36 km radiometer products. Results from this work present a framework for improving SWAT performance by utilizing a downscaled SMAP soil moisture products used for model calibration and validation. Index Terms: 1622: Earth system modeling; 1631: Land/atmosphere interactions; 1800: Hydrology; 1836 Hydrological cycles and budgets; 1840 Hydrometeorology; 1855: Remote sensing; 1866: Soil moisture; 6334: Regional Planning

  12. 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.)

  13. Dissemination of satellite-based river discharge and flood data

    Science.gov (United States)

    Kettner, A. J.; Brakenridge, G. R.; van Praag, E.; de Groeve, T.; Slayback, D. A.; Cohen, S.

    2014-12-01

    In collaboration with NASA Goddard Spaceflight Center and the European Commission Joint Research Centre, the Dartmouth Flood Observatory (DFO) daily measures and distributes: 1) river discharges, and 2) near real-time flood extents with a global coverage. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations', and observed time series cover 1998 to the present. The advantages over in-situ gauged discharges are: a) easy access to remote or due to political reasons isolated locations, b) relatively low maintenance costs to maintain a continuous observational record, and c) the capability to obtain measurements during floods, hazardous conditions that often impair or destroy in-situ stations. Two MODIS instruments aboard the NASA Terra and Aqua satellites provide global flood extent coverage at a spatial resolution of 250m. Cloud cover hampers flood extent detection; therefore we ingest 6 images (the Terra and Aqua images of each day, for three days), in combination with a cloud shadow filter, to provide daily global flood extent updates. The Flood Observatory has always made it a high priority to visualize and share its data and products through its website. Recent collaborative efforts with e.g. GeoSUR have enhanced accessibility of DFO data. A web map service has been implemented to automatically disseminate geo-referenced flood extent products into client-side GIS software. For example, for Latin America and the Caribbean region, the GeoSUR portal now displays current flood extent maps, which can be integrated and visualized with other relevant geographical data. Furthermore, the flood state of satellite-observed river discharge sites are displayed through the portal as well. Additional efforts include implementing Open Geospatial Consortium (OGC) standards to incorporate Water Markup Language (WaterML) data exchange mechanisms to further facilitate the distribution of the satellite

  14. Surface Turbulent Fluxes, 1x1 deg Monthly 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...

  15. 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...

  16. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-06-15

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  17. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Directory of Open Access Journals (Sweden)

    Haris Akram Bhatti

    2016-06-01

    Full Text Available With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA Climate Prediction Centre (CPC morphing technique (CMORPH satellite rainfall product (CMORPH in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW sizes and for sequential windows (SW’s of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE. To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r and standard deviation (SD. Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

  18. Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

    Science.gov (United States)

    Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

    2016-01-01

    With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

  19. Operational Satellite-based Surface Oil Analyses (Invited)

    Science.gov (United States)

    Streett, D.; Warren, C.

    2010-12-01

    During the Deepwater Horizon spill, NOAA imagery analysts in the Satellite Analysis Branch (SAB) issued more than 300 near-real-time satellite-based oil spill analyses. These analyses were used by the oil spill response community for planning, issuing surface oil trajectories and tasking assets (e.g., oil containment booms, skimmers, overflights). SAB analysts used both Synthetic Aperture Radar (SAR) and high resolution visible/near IR multispectral satellite imagery as well as a variety of ancillary datasets. Satellite imagery used included ENVISAT ASAR (ESA), TerraSAR-X (DLR), Cosmo-Skymed (ASI), ALOS (JAXA), Radarsat (MDA), ENVISAT MERIS (ESA), SPOT (SPOT Image Corp.), Aster (NASA), MODIS (NASA), and AVHRR (NOAA). Ancillary datasets included ocean current information, wind information, location of natural oil seeps and a variety of in situ oil observations. The analyses were available as jpegs, pdfs, shapefiles and through Google, KML files and also available on a variety of websites including Geoplatform and ERMA. From the very first analysis issued just 5 hours after the rig sank through the final analysis issued in August, the complete archive is still publicly available on the NOAA/NESDIS website http://www.ssd.noaa.gov/PS/MPS/deepwater.html SAB personnel also served as the Deepwater Horizon International Disaster Charter Project Manager (at the official request of the USGS). The Project Manager’s primary responsibility was to acquire and oversee the processing and dissemination of satellite data generously donated by numerous private companies and nations in support of the oil spill response including some of the imagery described above. SAB has begun to address a number of goals that will improve our routine oil spill response as well as help assure that we are ready for the next spill of national significance. We hope to (1) secure a steady, abundant and timely stream of suitable satellite imagery even in the absence of large-scale emergencies such as

  20. Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness

    Science.gov (United States)

    Kirschbaum, Dalia; Stanley, Thomas

    2018-03-01

    Determining the time, location, and severity of natural disaster impacts is fundamental to formulating mitigation strategies, appropriate and timely responses, and robust recovery plans. A Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to indicate potential landslide activity in near real-time. LHASA combines satellite-based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. Precipitation data from the Global Precipitation Measurement (GPM) mission are used to identify rainfall conditions from the past 7 days. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a "nowcast" is issued to indicate the times and places where landslides are more probable. When LHASA nowcasts were evaluated with a Global Landslide Catalog, the probability of detection (POD) ranged from 8% to 60%, depending on the evaluation period, precipitation product used, and the size of the spatial and temporal window considered around each landslide point. Applications of the LHASA system are also discussed, including how LHASA is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment. LHASA is intended to provide situational awareness of landslide hazards in near real-time, providing a flexible, open-source framework that can be adapted to other spatial and temporal scales based on data availability.

  1. 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....

  2. NCEP/CPC L3 Half Hourly 4km Global (60S - 60N) Merged IR V1 (GPM_MERGIR) at GES DISC

    Data.gov (United States)

    National Aeronautics and Space Administration — These data originate from NOAA/NCEP. The NOAA Climate Prediction Center/NCEP/NWS is making the data available originally in binary format, in a weekly rotating...

  3. Highlights of satellite-based forest change recognition and tracking using the ForWarn System

    Science.gov (United States)

    Steven P. Norman; William W. Hargrove; Joseph P. Spruce; William M. Christie; Sean W. Schroeder

    2013-01-01

    For a higher resolution version of this file, please use the following link: www.geobabble.orgSatellite-based remote sensing can assist forest managers with their need to recognize disturbances and track recovery. Despite the long...

  4. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Yearly Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  5. Goddard Satellite-Based Surface Turbulent Fluxes Climatology, Seasonal Grid V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie...

  6. Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

    Science.gov (United States)

    Mocko, David M.; Kumar, S. V.; Peters-Lidard, C. D.; Tian, Y.

    2011-01-01

    This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

  7. 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

  8. 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

  9. A Satellite-Based Model for Simulating Ecosystem Respiration in the Tibetan and Inner Mongolian Grasslands

    Directory of Open Access Journals (Sweden)

    Rong Ge

    2018-01-01

    Full Text Available It is important to accurately evaluate ecosystem respiration (RE in the alpine grasslands of the Tibetan Plateau and the temperate grasslands of the Inner Mongolian Plateau, as it serves as a sensitivity indicator of regional and global carbon cycles. Here, we combined flux measurements taken between 2003 and 2013 from 16 grassland sites across northern China and the corresponding MODIS land surface temperature (LST, enhanced vegetation index (EVI, and land surface water index (LSWI to build a satellite-based model to estimate RE at a regional scale. First, the dependencies of both spatial and temporal variations of RE on these biotic and climatic factors were examined explicitly. We found that plant productivity and moisture, but not temperature, can best explain the spatial pattern of RE in northern China’s grasslands; while temperature plays a major role in regulating the temporal variability of RE in the alpine grasslands, and moisture is equally as important as temperature in the temperate grasslands. However, the moisture effect on RE and the explicit representation of spatial variation process are often lacking in most of the existing satellite-based RE models. On this basis, we developed a model by comprehensively considering moisture, temperature, and productivity effects on both temporal and spatial processes of RE, and then, we evaluated the model performance. Our results showed that the model well explained the observed RE in both the alpine (R2 = 0.79, RMSE = 0.77 g C m−2 day−1 and temperate grasslands (R2 = 0.75, RMSE = 0.60 g C m−2 day−1. The inclusion of the LSWI as the water-limiting factor substantially improved the model performance in arid and semi-arid ecosystems, and the spatialized basal respiration rate as an indicator for spatial variation largely determined the regional pattern of RE. Finally, the model accurately reproduced the seasonal and inter-annual variations and spatial variability of RE, and it avoided

  10. A Satellite-Based Sunshine Duration Climate Data Record for Europe and Africa

    Directory of Open Access Journals (Sweden)

    Steffen Kothe

    2017-05-01

    Full Text Available Besides 2 m - temperature and precipitation, sunshine duration is one of the most important and commonly used parameter in climatology, with measured time series of partly more than 100 years in length. EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF presents a climate data record for daily and monthly sunshine duration (SDU for Europe and Africa. Basis for the advanced retrieval is a highly resolved satellite product of the direct solar radiation from measurements by Meteosat satellites 2 to 10. The data record covers the time period 1983 to 2015 with a spatial resolution of 0.05° × 0.05°. The comparison against ground-based data shows high agreement but also some regional differences. Sunshine duration is overestimated by the satellite-based data in many regions, compared to surface data. In West and Central Africa, low clouds seem to be the reason for a stronger overestimation of sunshine duration in this region (up to 20% for monthly sums. For most stations, the overestimation is low, with a bias below 7.5 h for monthly sums and below 0.4 h for daily sums. A high correlation of 0.91 for daily SDU and 0.96 for monthly SDU also proved the high agreement with station data. As SDU is based on a stable and homogeneous climate data record of more than 30 years length, it is highly suitable for climate applications, such as trend estimates.

  11. Satellite Based Downward Long Wave Radiation by Various Models in Northeast Asia

    Directory of Open Access Journals (Sweden)

    Chanyang Sur

    2014-01-01

    Full Text Available Satellite-based downward long wave radiation measurement under clear sky conditions in Northeast Asia was conducted using five well-known physical models (Brunt 1932, Idso and Jackson 1969, Brutsaert 1975, Satterlund 1979, Prata 1996 with a newly proposed global Rld model (Abramowitz et al. 2012. Data from two flux towers in South Korea were used to validate downward long wave radiation. Moderate resolution imaging spectroradiometer (MODIS atmospheric profile products were used to develop the Rld models. The overall root mean square error (RMSE of MODIS Rld with respect to two ecosystem-type flux towers was determined to be ≈ 20 W m-2. Based on the statistical analyses, MODIS Rld estimates with Brutsaert (1975 and Abramowitz et al. (2012 models were the most applicable for evaluating Rld for clear sky conditions in Northeast Asia. The Abramowitz Rld maps with MODIS Ta and ea showed reasonable seasonal patterns, which were well-aligned with other biophysical variables reported by previous studies. The MODIS Rld map developed in this study will be very useful for identifying spatial patterns that are not detectable from ground-based Rld measurement sites.

  12. Satellite based hydroclimatic understanding of evolution of Dengue and Zika virus

    Science.gov (United States)

    Khan, R.; Jutla, A.; Colwell, R. R.

    2017-12-01

    Vector-borne diseases are prevalent in tropical and subtropical regions especially in Africa, South America, and Asia. Vector eradication is perhaps not possible since pathogens adapt to local environment. In absence of appropriate vaccinations for Dengue and Zika virus, burden of these two infections continue to increase in several geographical locations. Aedes spp. is one of the major vectors for Dengue and Zika viruses. Etiologies on Dengue and Zika viruses are evolving, however the key question remains as to how one species of mosquito can transmit two different infections? We argue that a set of conducive environmental condition, modulated by regional climatic and weather processes, may lead to abundance of a specific virus. Using satellite based rainfall (TRMM/GPM), land surface temperature (MODIS) and dew point temperature (AIRS/MERRA), we have identified appropriate thresholds that can provide estimate on risk of abundance of Dengue or Zika viruses at least few weeks in advance. We will discuss a framework coupling satellite derived hydroclimatic and societal processes to predict environmental niches of favorability of conditions of Dengue or Zika risk in human population on a global scale.

  13. Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

    Science.gov (United States)

    Jin, Z.; Azzari, G.; Lobell, D. B.

    2016-12-01

    Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

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

    KAUST Repository

    Lopez Valencia, Oliver Miguel; Houborg, Rasmus; McCabe, Matthew

    2016-01-01

    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

  15. Intra-Seasonal Monthly Oscillations in Stratospheric NCEP Data and Model Results

    Science.gov (United States)

    Mayr, H. G.; Mengel, J. G.; Huang, F. T.; Nash, E. R.

    2009-01-01

    Intra-seasonal oscillations (ISO) are observed in the zonal-mean of mesospheric wind and temperature measurements-and the numerical spectral model (NSM) generates such oscillations. Relatively large temperature ISO are evident also in stratospheric CPC (NCEP) data at high latitudes, where the NSM produces amplitudes around 3 K at 30 km. Analyzing the NCEP data for the years 1996-2006, we find in Fourier spectra signatures of oscillations with periods between 1.7 and 3 months. With statistical confidence levels exceeding 70%, the spectral features are induced by nonlinear interactions involving the annual and semi-annual variations. The synthesized data show for the 10-year average that the temperature ISO peak in winter, having amplitudes close to 4 K. The synthesized complete spectrum for periods around 2 months produces oscillations, varying from year to year, which can reach peak amplitudes of 15 and 5 K respectively at northern and southern polar latitudes.

  16. The Implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for Global Dust Forecasting at NOAA NCEP

    Science.gov (United States)

    Lu, Cheng-Hsuan; Da Silva, Arlindo M.; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S.; Chen, Shen-Po; Chuang, Hui-Ya; hide

    2016-01-01

    The NOAA National Centers for Environmental Prediction (NCEP) implemented the NOAA Environmental Modeling System (NEMS) Global Forecast System (GFS) Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5-day dust forecasts at 1deg x 1deg resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders, as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered.

  17. The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP.

    Science.gov (United States)

    Lu, Cheng-Hsuan; da Silva, Arlindo; Wang, Jun; Moorthi, Shrinivas; Chin, Mian; Colarco, Peter; Tang, Youhua; Bhattacharjee, Partha S; Chen, Shen-Po; Chuang, Hui-Ya; Juang, Hann-Ming Henry; McQueen, Jeffery; Iredell, Mark

    2016-01-01

    The NOAA National Centers for Environmental Prediction (NCEP) implemented NEMS GFS Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5 day dust forecasts at 1°×1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered.

  18. Applications For Real Time NOMADS At NCEP To Disseminate NOAA's Operational Model Data Base

    Science.gov (United States)

    Alpert, J. C.; Wang, J.; Rutledge, G.

    2007-05-01

    A wide range of environmental information, in digital form, with metadata descriptions and supporting infrastructure is contained in the NOAA Operational Modeling Archive Distribution System (NOMADS) and its Real Time (RT) project prototype at the National Centers for Environmental Prediction (NCEP). NOMADS is now delivering on its goal of a seamless framework, from archival to real time data dissemination for NOAA's operational model data holdings. A process is under way to make NOMADS part of NCEP's operational production of products. A goal is to foster collaborations among the research and education communities, value added retailers, and public access for science and development. In the National Research Council's "Completing the Forecast", Recommendation 3.4 states: "NOMADS should be maintained and extended to include (a) long-term archives of the global and regional ensemble forecasting systems at their native resolution, and (b) re-forecast datasets to facilitate post-processing." As one of many participants of NOMADS, NCEP serves the operational model data base using data application protocol (Open-DAP) and other services for participants to serve their data sets and users to obtain them. Using the NCEP global ensemble data as an example, we show an Open-DAP (also known as DODS) client application that provides a request-and-fulfill mechanism for access to the complex ensemble matrix of holdings. As an example of the DAP service, we show a client application which accesses the Global or Regional Ensemble data set to produce user selected weather element event probabilities. The event probabilities are easily extended over model forecast time to show probability histograms defining the future trend of user selected events. This approach insures an efficient use of computer resources because users transmit only the data necessary for their tasks. Data sets are served by OPeN-DAP allowing commercial clients such as MATLAB or IDL as well as freeware clients

  19. 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.

  20. The ALTA global positioning satellite based timing system

    CERN Document Server

    Brouwer, W; Caron, B; Hewlett, J C; Holm, L; Hamilton, A H; McDonald, W J; Pinfold, J L; Schaapman, J R; Soluk, R A; Wampler, L J

    2002-01-01

    The Alberta Large-area Time-coincidence Array (ALTA) experiment uses a number of scintillation detector systems to form a sparse very large area cosmic air-shower detection array. An important scientific goal of the ALTA collaboration is to search for coincidences in the ALTA array due to large area cosmic ray phenomena. A local cosmic ray event, determined by a coincidence of the triplet of cosmic ray detectors forming a local detector system, is time stamped with a temporal coordinate obtained from a GPS receiver. The readout of the data, the local coincidence and the GPS time stamp are all performed in the local readout crate. This time stamp, along with the local shower direction is used to search for coincidences within the large area array. Using two GPS receivers and duplicate sets of ALTA electronics the timing resolution of the GPS time difference between sites was estimated to be 16 ns.

  1. 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.

  2. Advances in the Validation of Satellite-Based Maps of Volcanic Sulfur Dioxide Plumes

    Science.gov (United States)

    Realmuto, V. J.; Berk, A.; Acharya, P. K.; Kennett, R.

    2013-12-01

    The monitoring of volcanic gas emissions with gas cameras, spectrometer arrays, tethersondes, and UAVs presents new opportunities for the validation of satellite-based retrievals of gas concentrations. Gas cameras and spectrometer arrays provide instantaneous observations of the gas burden, or concentration along an optical path, over broad sections of a plume, similar to the observations acquired by nadir-viewing satellites. Tethersondes and UAVs provide us with direct measurements of the vertical profiles of gas concentrations within plumes. This presentation will focus on our current efforts to validate ASTER-based maps of sulfur dioxide plumes at Turrialba and Kilauea Volcanoes (located in Costa Rica and Hawaii, respectively). These volcanoes, which are the subjects of comprehensive monitoring programs, are challenging targets for thermal infrared (TIR) remote sensing due the warm and humid atmospheric conditions. The high spatial resolution of ASTER in the TIR (90 meters) allows us to map the plumes back to their source vents, but also requires us to pay close attention to the temperature and emissivity of the surfaces beneath the plumes. Our knowledge of the surface and atmospheric conditions is never perfect, and we employ interactive mapping techniques that allow us to evaluate the impact of these uncertainties on our estimates of plume composition. To accomplish this interactive mapping we have developed the Plume Tracker tool kit, which integrates retrieval procedures, visualization tools, and a customized version of the MODTRAN radiative transfer (RT) model under a single graphics user interface (GUI). We are in the process of porting the RT calculations to graphics processing units (GPUs) with the goal of achieving a 100-fold increase in the speed of computation relative to conventional CPU-based processing. We will report on our progress with this evolution of Plume Tracker. Portions of this research were conducted at the Jet Propulsion Laboratory

  3. 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.

    2010-01-01

    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 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...

  4. Improving Fire Emission Estimates in the eastern United States Using Satellite-Based Fuel Loading Factors

    Science.gov (United States)

    Yongqiang Liu; John J. Qu; Xianjun Hao; Wanting Wang

    2005-01-01

    Wildfires can lead to severe environmental consequences by releasing large amounts of particulate matter (PM) and precursors of ozone (Sandberg et al., 1999; Riebau and Fox, 2001). The Southeast has the most burned area among various U.S. regions (Stanturf et al., 2002) and has regionally some of the highest levels of PM and ozone in the nation. Fires have been found...

  5. 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

  6. Assessing satellite-based start-of-season trends in the US High Plains

    International Nuclear Information System (INIS)

    Lin, X; Sassenrath, G F; Hubbard, K G; Mahmood, R

    2014-01-01

    To adequately assess the effects of global warming it is necessary to address trends and impacts at the local level. This study examines phenological changes in the start-of-season (SOS) derived from satellite observations from 1982–2008 in the US High Plains region. The surface climate-based SOS was also evaluated. The averaged profiles of SOS from 37° to 49°N latitude by satellite- and climate-based methods were in reasonable agreement, especially for areas where croplands were masked out and an additional frost date threshold was adopted. The statistically significant trends of satellite-based SOS show a later spring arrival ranging from 0.1 to 4.9 days decade −1 over nine Level III ecoregions. We found the croplands generally exhibited larger trends (later arrival) than the non-croplands. The area-averaged satellite-based SOS for non-croplands (i.e. mostly grasslands) showed no significant trends. We examined the trends of temperatures, precipitation, and standardized precipitation index (SPI), as well as the strength of correlation between the satellite-based SOS and these climatic drivers. Our results indicate that satellite-based SOS trends are spatially and primarily related to annual maximum normalized difference vegetation index (NDVI, mostly in summertime) and/or annual minimum NDVI (mostly in wintertime) and these trends showed the best correlation with six-month SPI over the period 1982–2008 in the US High Plains region. (letter)

  7. 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 ...

  8. Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

    Science.gov (United States)

    Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

    2013-12-01

    Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output

  9. 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

  10. Regionalization Study of Satellite based Hydrological Model (SHM) in Hydrologically Homogeneous River Basins of India

    Science.gov (United States)

    Kumari, Babita; Paul, Pranesh Kumar; Singh, Rajendra; Mishra, Ashok; Gupta, Praveen Kumar; Singh, Raghvendra P.

    2017-04-01

    A new semi-distributed conceptual hydrological model, namely Satellite based Hydrological Model (SHM), has been developed under 'PRACRITI-2' program of Space Application Centre (SAC), Ahmedabad for sustainable water resources management of India by using data from Indian Remote Sensing satellites. Entire India is divided into 5km x 5km grid cells and properties at the center of the cells are assumed to represent the property of the cells. SHM contains five modules namely surface water, forest, snow, groundwater and routing. Two empirical equations (SCS-CN and Hargreaves) and water balance method have been used in the surface water module; the forest module is based on the calculations of water balancing & dynamics of subsurface. 2-D Boussinesq equation is used for groundwater modelling which is solved using implicit finite-difference. The routing module follows a distributed routing approach which requires flow path and network with the key point of travel time estimation. The aim of this study is to evaluate the performance of SHM using regionalization technique which also checks the usefulness of a model in data scarce condition or for ungauged basins. However, homogeneity analysis is pre-requisite to regionalization. Similarity index (Φ) and hierarchical agglomerative cluster analysis are adopted to test the homogeneity in terms of physical attributes of three basins namely Brahmani (39,033 km km^2)), Baitarani (10,982 km km^2)) and Kangsabati (9,660 km km^2)) with respect to Subarnarekha (29,196 km km^2)) basin. The results of both homogeneity analysis show that Brahmani basin is the most homogeneous with respect to Subarnarekha river basin in terms of physical characteristics (land use land cover classes, soiltype and elevation). The calibration and validation of model parameters of Brahmani basin is in progress which are to be transferred into the SHM set up of Subarnarekha basin and results are to be compared with the results of calibrated and validated

  11. 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.)

  12. Surface Turbulent Fluxes, 1x1 deg Yearly Climatology, Set1 and NCEP V2c (GSSTFYC) at GES DISC

    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...

  13. Surface Turbulent Fluxes, 1x1 deg Monthly Climatology, Set1 and NCEP V2c (GSSTFMC) at GES DISC

    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...

  14. 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

  15. Advances In Global Aerosol Modeling Applications Through Assimilation of Satellite-Based Lidar Measurements

    Science.gov (United States)

    Campbell, James; Hyer, Edward; Zhang, Jianglong; Reid, Jeffrey; Westphal, Douglas; Xian, Peng; Vaughan, Mark

    2010-05-01

    Modeling the instantaneous three-dimensional aerosol field and its downwind transport represents an endeavor with many practical benefits foreseeable to air quality, aviation, military and science agencies. The recent proliferation of multi-spectral active and passive satellite-based instruments measuring aerosol physical properties has served as an opportunity to develop and refine the techniques necessary to make such numerical modeling applications possible. Spurred by high-resolution global mapping of aerosol source regions, and combined with novel multivariate data assimilation techniques designed to consider these new data streams, operational forecasts of visibility and aerosol optical depths are now available in near real-time1. Active satellite-based aerosol profiling, accomplished using lidar instruments, represents a critical element for accurate analysis and transport modeling. Aerosol source functions, alone, can be limited in representing the macrophysical structure of injection scenarios within a model. Two-dimensional variational (2D-VAR; x, y) assimilation of aerosol optical depth from passive satellite observations significantly improves the analysis of the initial state. However, this procedure can not fully compensate for any potential vertical redistribution of mass required at the innovation step. The expense of an inaccurate vertical analysis of aerosol structure is corresponding errors downwind, since trajectory paths within successive forecast runs will likely diverge with height. In this paper, the application of a newly-designed system for 3D-VAR (x,y,z) assimilation of vertical aerosol extinction profiles derived from elastic-scattering lidar measurements is described [Campbell et al., 2009]. Performance is evaluated for use with the U. S. Navy Aerosol Analysis and Prediction System (NAAPS) by assimilating NASA/CNES satellite-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 0.532 μm measurements [Winker et al., 2009

  16. Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 4. Operational Description and Qualitative Assessment.

    Science.gov (United States)

    1974-02-01

    The volume presents a description of how the Satellite-Based Advanced Air Traffic Management System (SAATMS) operates and a qualitative assessment of the system. The operational description includes the services, functions, and tasks performed by the...

  17. Using satellite-based measurements to explore spatiotemporal scales and variability of drivers of new particle formation

    Science.gov (United States)

    New particle formation (NPF) can potentially alter regional climate by increasing aerosol particle (hereafter particle) number concentrations and ultimately cloud condensation nuclei. The large scales on which NPF is manifest indicate potential to use satellite-based (inherently ...

  18. Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities

    Science.gov (United States)

    Schemm, J. E.; Long, L.; Baxter, S.

    2013-12-01

    Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities Jae-Kyung E. Schemm, Lindsey Long and Stephen Baxter Climate Prediction Center, NCEP/NWS/NOAA Predictability of intraseasonal tropical storm (TS) activities is assessed using the 1999-2010 CFSv2 hindcast suite. Weekly TS activities in the CFSv2 45-day forecasts were determined using the TS detection and tracking method devised by Carmago and Zebiak (2002). The forecast periods are divided into weekly intervals for Week 1 through Week 6, and also the 30-day mean. The TS activities in those intervals are compared to the observed activities based on the NHC HURDAT and JTWC Best Track datasets. The CFSv2 45-day hindcast suite is made of forecast runs initialized at 00, 06, 12 and 18Z every day during the 1999 - 2010 period. For predictability evaluation, forecast TS activities are analyzed based on 20-member ensemble forecasts comprised of 45-day runs made during the most recent 5 days prior to the verification period. The forecast TS activities are evaluated in terms of the number of storms, genesis locations and storm tracks during the weekly periods. The CFSv2 forecasts are shown to have a fair level of skill in predicting the number of storms over the Atlantic Basin with the temporal correlation scores ranging from 0.73 for Week 1 forecasts to 0.63 for Week 6, and the average RMS errors ranging from 0.86 to 1.07 during the 1999-2010 hurricane season. Also, the forecast track density distribution and false alarm statistics are compiled using the hindcast analyses. In real-time applications of the intraseasonal TS activity forecasts, the climatological TS forecast statistics will be used to make the model bias corrections in terms of the storm counts, track distribution and removal of false alarms. An operational implementation of the weekly TS activity prediction is planned for early 2014 to provide an objective input for the CPC's Global Tropical Hazards

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

    Science.gov (United States)

    Belochitski, A.; Krueger, S. K.; Moorthi, S.; Bogenschutz, P.; Cheng, A.

    2017-12-01

    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, comparatively few new prognostic variables needs to be introduced, making the technique computationally efficient. In the base version of SHOC it is SGS turbulent kinetic energy (TKE), and in the developmental version — SGS TKE, and variances of total water and moist static energy (MSE). SHOC is now incorporated into a version of GFS that will become a part of the NOAA Next Generation Global Prediction System based around NOAA GFDL's FV3 dynamical core, NOAA Environmental Modeling System (NEMS) coupled modeling infrastructure software, and a set novel physical parameterizations. Turbulent diffusion coefficients computed by SHOC are now used in place of those produced by the boundary layer turbulence and shallow convection parameterizations. Large scale microphysics scheme is no longer used to calculate cloud fraction or the large-scale condensation/deposition. Instead, SHOC provides these quantities. Radiative transfer parameterization uses cloudiness computed by SHOC. An outstanding problem with implementation of SHOC in the NCEP global models is excessively large high level tropical cloudiness. Comparison of the moments of the SGS PDF diagnosed by SHOC to the moments calculated in a GigaLES simulation of tropical deep convection case (GATE), shows that SHOC diagnoses too narrow PDF distributions of total cloud water and MSE in the areas of deep convective detrainment. A subsequent sensitivity study of SHOC's diagnosed cloud fraction (CF) to higher order input moments of the SGS PDF

  20. 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

  1. 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

  2. Satellite-based evidence of wavelength-dependent aerosol absorption in biomass burning smoke inferred from Ozone Monitoring Instrument

    Directory of Open Access Journals (Sweden)

    H. Jethva

    2011-10-01

    Full Text Available We provide satellite-based evidence of the spectral dependence of absorption in biomass burning aerosols over South America using near-UV measurements made by the Ozone Monitoring Instrument (OMI during 2005–2007. In the current near-UV OMI aerosol algorithm (OMAERUV, it is implicitly assumed that the only absorbing component in carbonaceous aerosols is black carbon whose imaginary component of the refractive index is wavelength independent. With this assumption, OMI-derived aerosol optical depth (AOD is found to be significantly over-estimated compared to that of AERONET at several sites during intense biomass burning events (August-September. Other well-known sources of error affecting the near-UV method of aerosol retrieval do not explain the large observed AOD discrepancies between the satellite and the ground-based observations. A number of studies have revealed strong spectral dependence in carbonaceous aerosol absorption in the near-UV region suggesting the presence of organic carbon in biomass burning generated aerosols. A sensitivity analysis examining the importance of accounting for the presence of wavelength-dependent aerosol absorption in carbonaceous particles in satellite-based remote sensing was carried out in this work. The results convincingly show that the inclusion of spectrally-dependent aerosol absorption in the radiative transfer calculations leads to a more accurate characterization of the atmospheric load of carbonaceous aerosols. The use of a new set of aerosol models assuming wavelength-dependent aerosol absorption in the near-UV region (Absorption Angstrom Exponent λ−2.5 to −3.0 improved the OMAERUV retrieval results by significantly reducing the AOD bias observed when gray aerosols were assumed. In addition, the new retrieval of single-scattering albedo is in better agreement with those of AERONET within the uncertainties (ΔSSA = ±0.03. The new colored carbonaceous aerosol model was also found to

  3. 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

  4. Evaluation of energy fluxes in the NCEP climate forecast system version 2.0 (CFSv2)

    Science.gov (United States)

    Rai, Archana; Saha, Subodh Kumar

    2018-01-01

    The energy fluxes at the surface and top of the atmosphere (TOA) from a long free run by the NCEP climate forecast system version 2.0 (CFSv2) are validated against several observation and reanalysis datasets. This study focuses on the annual mean energy fluxes and tries to link it with the systematic cold biases in the 2 m air temperature, particularly over the land regions. The imbalance in the long term mean global averaged energy fluxes are also evaluated. The global averaged imbalance at the surface and at the TOA is found to be 0.37 and 6.43 Wm-2, respectively. It is shown that CFSv2 overestimates the land surface albedo, particularly over the snow region, which in turn contributes to the cold biases in 2 m air temperature. On the other hand, surface albedo is highly underestimated over the coastal region around Antarctica and that may have contributed to the warm bias over that oceanic region. This study highlights the need for improvements in the parameterization of snow/sea-ice albedo scheme for a realistic simulation of surface temperature and that may have implications on the global energy imbalance in the model.

  5. Predictable patterns of the Asian and Indo-Pacific summer precipitation in the NCEP CFS

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Jianyin [CMA Institute of Tropical and Marine Meteorology, Guangzhou, Guangdong (China); Yang, Song; Kumar, Arun [NOAA/NWS/NCEP Climate Prediction Center, Camp Springs, MD (United States); Hu, Zeng-Zhen [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); Huang, Bohua [George Mason University, Department of Climate Dynamics, Fairfax, VA (United States); Zhang, Zuqiang [CMA National Climate Center, Beijing (China)

    2009-06-15

    The predictable patterns of the Asian and Indo-Pacific summer precipitation in the NCEP climate forecast system (CFS) are depicted by applying a maximized signal-to-noise empirical orthogonal function analysis. The CFS captures the two most dominant modes of observed climate patterns. The first most dominant mode is characterized by the climate features of the onset years of El Nino-Southern Oscillation (ENSO), with strong precipitation signals over the tropical eastern Indian and western Pacific oceans, Southeast Asia, and tropical Asian monsoon regions including the Bay of Bengal and the South China Sea. The second most dominant mode is characterized by the climate features of the decay years of ENSO, with weakening signals over the western-central Pacific and strengthening signals over the Indian Ocean. The CFS is capable of predicting the most dominant modes several months in advance. It is also highly skillful in capturing the air-sea interaction processes associated with the precipitation features, as demonstrated in sea surface temperature and wind patterns. (orig.)

  6. Extratropical cyclone variability in the Northern Hemisphere winter from the NCEP/NCAR reanalysis data

    Energy Technology Data Exchange (ETDEWEB)

    Gulev, S.K.; Zolina, O.; Grigoriev, S. [AN SSSR, Moscow (USSR). Inst. Okeanologii

    2001-07-01

    The winter climatology of Northern Hemisphere cyclone activity was derived from 6-hourly NCEP/NCAR reanalysis data for the period from 1958 to 1999, using software which provides improved accuracy in cyclone identification in comparison to numerical tracking schemes. Cyclone characteristics over the Kuroshio and Gulfstream are very different to those over continental North America and the Arctic. Analysis of Northern Hemisphere cyclones shows secular and decadal-scale changes in cyclone frequency, intensity, lifetime and deepening rates. The western Pacific and Atlantic are characterized by an increase in cyclone intensity and deepening during the 42-year period, although the eastern Pacific and continental North America demonstrate opposite tendencies in most cyclone characteristics. There is an increase of the number of cyclones in the Arctic and in the western Pacific and a downward tendency over the Gulf Stream and subpolar Pacific. Decadal scale variability in cyclone activity over the Atlantic and Pacific exhibits south-north dipole-like patterns. Atlantic and Pacific cyclone activity associated with the NAO and PNA is analyzed. Atlantic cyclone frequency demonstrates a high correlation with NAO and reflects the NAO shift in the mid 1970s, associated with considerable changes in European storm tracks. The PNA is largely linked to the eastern Pacific cyclone frequencies, and controls cyclone activity over the Gulf region and the North American coast during the last two decades. Assessment of the accuracy of the results and comparison with those derived using numerical algorithms, shows that biases inherent in numerical procedures are not negligible. (orig.)

  7. BALTEX water and energy budgets in the NCEP/DOE reanalysis II

    Energy Technology Data Exchange (ETDEWEB)

    Roads, J. [Experimental Climate Prediction Center, Scripps Institution of Oceanography, La Jolla, CA (United States); Raschke, E. [Meteorologisches Institut der Universitaet Hamburg (Germany); Rocke, B. [Institute for Coastal Research, GKSS Research Center, Geesthacht (Germany)

    2002-07-01

    Water and energy budgets from the National Centers for Environmental Prediction/Dept. of Energy (NCEP/DOE) reanalysis II (NCEPRII) are described for the Baltic Sea catchment and sea (BALTEX). Annually, NCEPRII shows 0.7 mm d{sup -1} of atmospheric moisture converged into the land region with a corresponding runoff of 0.7 mm d{sup -1} to the Baltic Sea, consistent with observations. However, precipitation is too low; evaporation is too large; runoff does not have an appropriate winter minimum and spring maximum; the assimilation and surface nudging are too large. Important hydroclimatic characteristics can still be discerned. During summer, atmospheric water vapor, precipitation, evaporation, and surface and atmospheric radiative heating increase and the atmospheric radiative cooling, dry static energy convergence decrease. There are large contrasts between the sea and land; during winter sensible heat is transferred from the sea to the atmosphere and sea evaporation and precipitation are largest during the fall and winter; somewhat opposite behavior occurs over land. (orig.)

  8. A near real-time satellite-based global drought climate data record

    International Nuclear Information System (INIS)

    AghaKouchak, Amir; Nakhjiri, Navid

    2012-01-01

    Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

  9. From extended integrity monitoring to the safety evaluation of satellite-based localisation system

    International Nuclear Information System (INIS)

    Legrand, Cyril; Beugin, Julie; Marais, Juliette; Conrard, Blaise; El-Koursi, El-Miloudi; Berbineau, Marion

    2016-01-01

    Global Navigation Satellite Systems (GNSS) such as GPS, already used in aeronautics for safety-related applications, can play a major role in railway safety by allowing a train to locate itself safely. However, in order to implement this positioning solution in any embedded system, its performances must be evaluated according to railway standards. The evaluation of GNSS performances is not based on the same attributes class than RAMS evaluation. Face to these diffculties, we propose to express the integrity attribute, performance of satellite-based localisation. This attribute comes from aeronautical standards and for a hybridised GNSS with inertial system. To achieve this objective, the integrity attribute must be extended to this kind of system and algorithms initially devoted to GNSS integrity monitoring only must be adapted. Thereafter, the formalisation of this integrity attribute permits us to analyse the safety quantitatively through the probabilities of integrity risk and wrong-side failure. In this paper, after an introductory discussion about the use of localisation systems in railway safety context together with integrity issues, a particular integrity monitoring is proposed and described. The detection events of this algorithm permit us to conclude about safety level of satellite-based localisation system.

  10. Characterizing hydrological activities over Yangtze River basin using the new HUST-Grace2016 model, MODIS, and NCEP/NCAR data

    Science.gov (United States)

    Zhou, H.; Luo, Z.; Tangdamrongsub, N.; He, L.

    2017-12-01

    Accurate TWS estimation is important to evaluate the situation of the water resource over the Yangtze River basin. This study exploits the TWS observation from the new gravity model, HUST-Grace06, which is developed by a new low-frequency noise processing strategy. A novel GRACE post-processing approach is proposed to enhance the quality of the TWS estimate, and the improved TWS is used to characterize the hydrological activities over the Yangtze River basin. The approach includes the effective noise reduction and the leakage error mitigation based on forward modeling. The HUST-Grace06 derived TWS presents good agreement with the CSR mascon solution as well as the PCR-GLOBWB hydrological model. Particularly, our solution provides remarkable performance in identifying the extreme climate events e.g., flood and drought over the Yangtze River basin. In addition, for the first time, the NCEP/NCAR reanalysis data is incorporated with GRACE in the exploration of the climate induced hydrological activities. The comparison between GRACE and the MODIS-derived NDVI data is also conducted to investigate their connection regarding temporal and spatial distribution. The analysis suggests that the terrestrial reflectance data can be used to represent the TWS information. Importantly, such information can be used to fill the missing data in case of the early termination of GRACE or during the prelaunch of the GRACE Follow-On mission.

  11. Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hye-Mi; Webster, Peter J.; Curry, Judith A.; Toma, Violeta E. [Georgia Institute of Technology, School of Earth and Atmospheric Science, Atlanta, GA (United States)

    2012-12-15

    The seasonal prediction skill of the Asian summer monsoon is assessed using retrospective predictions (1982-2009) from the ECMWF System 4 (SYS4) and NCEP CFS version 2 (CFSv2) seasonal prediction systems. In both SYS4 and CFSv2, a cold bias of sea-surface temperature (SST) is found over the equatorial Pacific, North Atlantic, Indian Oceans and over a broad region in the Southern Hemisphere relative to observations. In contrast, a warm bias is found over the northern part of North Pacific and North Atlantic. Excessive precipitation is found along the ITCZ, equatorial Atlantic, equatorial Indian Ocean and the maritime continent. The southwest monsoon flow and the Somali Jet are stronger in SYS4, while the south-easterly trade winds over the tropical Indian Ocean, the Somali Jet and the subtropical northwestern Pacific high are weaker in CFSv2 relative to the reanalysis. In both systems, the prediction of SST, precipitation and low-level zonal wind has greatest skill in the tropical belt, especially over the central and eastern Pacific where the influence of El Nino-Southern Oscillation (ENSO) is dominant. Both modeling systems capture the global monsoon and the large-scale monsoon wind variability well, while at the same time performing poorly in simulating monsoon precipitation. The Asian monsoon prediction skill increases with the ENSO amplitude, although the models simulate an overly strong impact of ENSO on the monsoon. Overall, the monsoon predictive skill is lower than the ENSO skill in both modeling systems but both systems show greater predictive skill compared to persistence. (orig.)

  12. 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

  13. Equatorial annual oscillation with QBO-driven 5-year modulation in NCEP data

    Directory of Open Access Journals (Sweden)

    H. G. Mayr

    2007-02-01

    Full Text Available An analysis is presented of the stratospheric zonal wind and temperature variations supplied by the National Center for Environmental Prediction (NCEP. The derived zonal-mean variations are employed. Stimulated by modeling studies, the data are separated into the hemispherically symmetric and anti-symmetric components, and spectral analysis is applied to study the 12-month annual oscillation (AO and the quasi-biennial oscillation (QBO. For data samples that cover as much as 40 years, the zonal wind results reveal a pronounced 5-year modulation of the symmetric AO in the lower stratosphere, which is confined to equatorial latitudes. This modulation is also seen in the temperature variations but extends to high latitudes, qualitatively consistent with published model results. A comparison between different time intervals of the data indicates that the signature of the 5-year oscillation is larger when the QBO of 30 months is more pronounced. Thus there is circumstantial evidence that this particular QBO period is involved in generating the oscillation as was shown in a modeling study (Mayr et al., 2000. In agreement with the model, the spectral analysis also reveals a weak anti-symmetric 5-year oscillation in the zonal wind data, which could interact with the strong anti-symmetric AO to produce the modulation of the symmetric AO. The 30-month QBO is well suited to be synchronized by, and phase-locked to, the equatorial semi-annual oscillation (SAO, and this may explain why this QBO periodicity and its 5-year spin-off are observed to persist for many cycles.

  14. Equatorial Annual Oscillation with QBO-driven 5-year Modulation in NCEP Data

    Science.gov (United States)

    Mayr, H. G.; Mengel, J. G.; Huang, F. T.; Nash, E. R.

    2007-01-01

    An analysis is presented of the zonal wind and temperature variations supplied by the National Center for Environmental Prediction (NCEP), which have been assimilated in the Reanalysis and the Climate Prediction Center (CCP) data sets. The derived zonal-mean variations are employed. Stimulated by modeling studies, the data are separated into the hemispherically symmetric and anti-symmetric components, and spectral analysis is applied to study the annual 12-month oscillation and Quasi-biennial Oscillation (QBO). For data samples that cover as much as 40 years, the results reveal a pronounced 5-year modulation of the symmetric AO in the lower stratosphere, which is confined to equatorial latitudes. This modulation is also inferred for the temperature variations but extends to high latitudes, qualitatively consistent with published model results. A comparison between different data samples indicates that the signature of the 5-year oscillation is larger when the QBO of 30 months is more pronounced. Thus there is circumstantial evidence that this periodicity of the QBO is involved in generating the oscillation. The spectral analysis shows that there is a weak anti-symmetric 5-year oscillation in the zonal winds, which could interact with the large antisymmetric A0 to produce the modulation of the symmetric AO as was shown in earlier modeling studies. According to these studies, the 30-month QBO tends to be synchronized by the equatorial Semi-annual Oscillation (SAO), and this would explain why the inferred 5-year modulation is observed to persist and is phase locked over several cycles.

  15. 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.)

  16. Daily modes of South Asian summer monsoon variability in the NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Achuthavarier, Deepthi; Krishnamurthy, V. [George Mason University, Department of Atmospheric, Oceanic and Earth Sciences, Fairfax, VA (United States); Institute of Global Environment and Society, Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States)

    2011-05-15

    The leading modes of daily variability of the Indian summer monsoon in the climate forecast system (CFS), a coupled general circulation model, of the National Centers for Environmental Predictions (NCEP) are examined. The space-time structures of the daily modes are obtained by applying multi-channel singular spectrum analysis (MSSA) on the daily anomalies of rainfall. Relations of the daily modes to intraseasonal and interannual variability of the monsoon are investigated. The CFS has three intraseasonal oscillations with periods around 106, 57 and 30 days with a combined variance of 7%. The 106-day mode has spatial structure and propagation features similar to the northeastward propagating 45-day mode in the observations except for its longer period. The 57-day mode, despite being in the same time scale as of the observations has poor eastward propagation. The 30-day mode is northwestward propagating and is similar to its observational counterpart. The 106-day mode is specific to the model and should not be mistaken for a new scale of variability in observations. The dominant interannual signal is related to El Nino-Southern Oscillation (ENSO), and, unlike in the observations, has maximum variance in the eastern equatorial Indian Ocean. Although the Indian Ocean Dipole (IOD) mode was not obtained as a separate mode in the rainfall, the ENSO signal has good correlations with the dipole variability, which, therefore, indicates the dominance of ENSO in the model. The interannual variability is largely determined by the ENSO signal over the regions where it has maximum variance. The interannual variability of the intraseasonal oscillations is smaller in comparison. (orig.)

  17. ENSO, IOD and Indian Summer Monsoon in NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Pokhrel, Samir; Chaudhari, H.S.; Saha, Subodh K.; Dhakate, Ashish; Yadav, R.K.; Salunke, Kiran; Mahapatra, S.; Rao, Suryachandra A. [Indian Institute of Tropical Meteorology, Pashan, Pune (India)

    2012-11-15

    El Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Indian Summer Monsoon rainfall features are explored statistically and dynamically using National Centers for Environment Prediction (NCEP) Climate Forecast System (CFSv1) freerun in relation to observations. The 100 years of freerun provides a sufficiently long homogeneous data set to find out the mean state, periodicity, coherence among these climatic events and also the influence of ENSO and IOD on the Indian monsoon. Differences in the occurrence of seasonal precipitation between the observations and CFS freerun are examined as a coupled ocean-atmosphere system. CFS simulated ENSO and IOD patterns and their associated tropical Walker and regional Hadley circulation in pure ENSO (PEN), pure IOD (PIO) and coexisting ENSO-IOD (PEI) events have some similarity to the observations. PEN composites are much closer to the observation as compared to PIO and PEI composites, which suggest a better ENSO prediction and its associated teleconnections as compared to IOD and combined phenomenon. Similar to the observation, the model simulation also show that the decrease in the Indian summer monsoon rainfall during ENSO phases is associated with a descending motion of anomalous Walker circulation and the increase in the Indian summer monsoon rainfall during IOD phase is associated with the ascending branch of anomalous regional Hadley circulation. During co-existing ENSO and IOD years, however, the fate of Indian summer monsoon is dictated by the combined influence of both of them. The shift in the anomalous descending and ascending branches of the Walker and Hadley circulation may be somewhat attributed to the cold (warm) bias over eastern (western) equatorial Indian Ocean basin, respectively in the model. This study will be useful for identifying some of the limitations of the CFS model and consequently it will be helpful in improving the model to unravel the realistic coupled ocean-atmosphere interactions

  18. Ground-and satellite-based evidence of the biophysical mechanisms behind the greening Sahel

    DEFF Research Database (Denmark)

    Brandt, Martin Stefan; Mbow, Cheikh; Diouf, Abdoul A.

    2015-01-01

    After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness...... over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass...... remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass...

  19. 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...

  20. Network design consideration of a satellite-based mobile communications system

    Science.gov (United States)

    Yan, T.-Y.

    1986-01-01

    Technical considerations for the Mobile Satellite Experiment (MSAT-X), the ground segment testbed for the low-cost spectral efficient satellite-based mobile communications technologies being developed for the 1990's, are discussed. The Network Management Center contains a flexible resource sharing algorithm, the Demand Assigned Multiple Access scheme, which partitions the satellite transponder bandwidth among voice, data, and request channels. Satellite use of multiple UHF beams permits frequency reuse. The backhaul communications and the Telemetry, Tracking and Control traffic are provided through a single full-coverage SHF beam. Mobile Terminals communicate with the satellite using UHF. All communications including SHF-SHF between Base Stations and/or Gateways, are routed through the satellite. Because MSAT-X is an experimental network, higher level network protocols (which are service-specific) will be developed only to test the operation of the lowest three levels, the physical, data link, and network layers.

  1. 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

  2. Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

    Science.gov (United States)

    Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

    2016-03-01

    Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

  3. Current trends in satellite based emergency mapping - the need for harmonisation

    Science.gov (United States)

    Voigt, Stefan

    2013-04-01

    During the past years, the availability and use of satellite image data to support disaster management and humanitarian relief organisations has largely increased. The automation and data processing techniques are greatly improving as well as the capacity in accessing and processing satellite imagery in getting better globally. More and more global activities via the internet and through global organisations like the United Nations or the International Charter Space and Major Disaster engage in the topic, while at the same time, more and more national or local centres engage rapid mapping operations and activities. In order to make even more effective use of this very positive increase of capacity, for the sake of operational provision of analysis results, for fast validation of satellite derived damage assessments, for better cooperation in the joint inter agency generation of rapid mapping products and for general scientific use, rapid mapping results in general need to be better harmonized, if not even standardized. In this presentation, experiences from various years of rapid mapping gained by the DLR Center for satellite based Crisis Information (ZKI) within the context of the national activities, the International Charter Space and Major Disasters, GMES/Copernicus etc. are reported. Furthermore, an overview on how automation, quality assurance and optimization can be achieved through standard operation procedures within a rapid mapping workflow is given. Building on this long term rapid mapping experience, and building on the DLR initiative to set in pace an "International Working Group on Satellite Based Emergency Mapping" current trends in rapid mapping are discussed and thoughts on how the sharing of rapid mapping information can be optimized by harmonizing analysis results and data structures are presented. Such an harmonization of analysis procedures, nomenclatures and representations of data as well as meta data are the basis to better cooperate within

  4. Hydrological real-time modelling in the Zambezi river basin using satellite-based soil moisture and rainfall data

    Directory of Open Access Journals (Sweden)

    P. Meier

    2011-03-01

    Full Text Available Reliable real-time forecasts of the discharge can provide valuable information for the management of a river basin system. For the management of ecological releases even discharge forecasts with moderate accuracy can be beneficial. Sequential data assimilation using the Ensemble Kalman Filter provides a tool that is both efficient and robust for a real-time modelling framework. One key parameter in a hydrological system is the soil moisture, which recently can be characterized by satellite based measurements. A forecasting framework for the prediction of discharges is developed and applied to three different sub-basins of the Zambezi River Basin. The model is solely based on remote sensing data providing soil moisture and rainfall estimates. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by a radar scatterometer. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag which is dependent on the size and the dominant runoff process in the catchment. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The conceptual model developed is based on two storage compartments. The processes modeled include evaporation losses, infiltration and percolation. The application of this model in a real-time modelling framework yields good results in watersheds where soil storage is an important factor. The lead time of the forecast is dependent on the size and the retention capacity of the watershed. For the largest watershed a forecast over 40 days can be provided. However, the quality of the forecast increases significantly with decreasing prediction time. In a watershed with little soil storage and a quick response to rainfall events, the performance is relatively poor and the lead time is as short as 10 days only.

  5. 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.

  6. East Asian winter monsoon forecasting schemes based on the NCEP's climate forecast system

    Science.gov (United States)

    Tian, Baoqiang; Fan, Ke; Yang, Hongqing

    2017-12-01

    The East Asian winter monsoon (EAWM) is the major climate system in the Northern Hemisphere during boreal winter. In this study, we developed two schemes to improve the forecasting skill of the interannual variability of the EAWM index (EAWMI) using the interannual increment prediction method, also known as the DY method. First, we found that version 2 of the NCEP's Climate Forecast System (CFSv2) showed higher skill in predicting the EAWMI in DY form than not. So, based on the advantage of the DY method, Scheme-I was obtained by adding the EAWMI DY predicted by CFSv2 to the observed EAWMI in the previous year. This scheme showed higher forecasting skill than CFSv2. Specifically, during 1983-2016, the temporal correlation coefficient between the Scheme-I-predicted and observed EAWMI was 0.47, exceeding the 99% significance level, with the root-mean-square error (RMSE) decreased by 12%. The autumn Arctic sea ice and North Pacific sea surface temperature (SST) are two important external forcing factors for the interannual variability of the EAWM. Therefore, a second (hybrid) prediction scheme, Scheme-II, was also developed. This scheme not only involved the EAWMI DY of CFSv2, but also the sea-ice concentration (SIC) observed the previous autumn in the Laptev and East Siberian seas and the temporal coefficients of the third mode of the North Pacific SST in DY form. We found that a negative SIC anomaly in the preceding autumn over the Laptev and the East Siberian seas could lead to a significant enhancement of the Aleutian low and East Asian westerly jet in the following winter. However, the intensity of the winter Siberian high was mainly affected by the third mode of the North Pacific autumn SST. Scheme-I and Scheme-II also showed higher predictive ability for the EAWMI in negative anomaly years compared to CFSv2. More importantly, the improvement in the prediction skill of the EAWMI by the new schemes, especially for Scheme-II, could enhance the forecasting skill of

  7. Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

    Energy Technology Data Exchange (ETDEWEB)

    Pattanaik, D.R. [India Meteorological Department (IMD), New Delhi (India); Kumar, Arun [Climate Prediction Center, National Centre for Environmental Prediction (NCEP)/NWS/NOAA, Camp Springs, MD (United States)

    2010-03-15

    The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50 E-110 E and 10 S-35 N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon

  8. 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.

  9. Efficient all solid-state UV source for satellite-based lidar applications.

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, Darrell Jewell; Smith, Arlee Virgil

    2003-07-01

    A satellite-based UV-DIAL measurement system would allow continuous global monitoring of ozone concentration in the upper atmosphere. However such systems remain difficult to implement because aerosol-scattering return signals for satellite-based lidars are very weak. A suitable system must produce high-energy UV pulses at multiple wavelengths with very high efficiency. For example, a nanosecond system operating at 10 Hz must generate approximately 1 J per pulse at 308-320 nm. An efficient space-qualified wavelength-agile system based on a single UV source that can meet this requirement is probably not available using current laser technology. As an alternative, we're pursuing a multi-source approach employing all-solid-state modules that individually generate 300-320 nm light with pulse energies in the range of 50-200 mJ, with transform-limited bandwidths and good beam quality. Pulses from the individual sources can be incoherently summed to obtain the required single-pulse energy. These sources use sum-frequency mixing of the 532 nm second harmonic of an Nd:YAG pump laser with 731-803 nm light derived from a recently-developed, state-of-the-art, nanosecond optical parametric oscillator. Two source configurations are under development, one using extra-cavity sum-frequency mixing, and the other intra-cavity sum-frequency mixing. In either configuration, we hope to obtain sum-frequency mixing efficiency approaching 60% by carefully matching the spatial and temporal properties of the laser and OPO pulses. This ideal balance of green and near-IR photons requires an injection-seeded Nd:YAG pump-laser with very high beam quality, and an OPO exhibiting unusually high conversion efficiency and exceptional signal beam quality. The OPO employs a singly-resonant high-Fresnel-number image-rotating self-injection-seeded nonplanar-ring cavity that achieves pump depletion > 65% and produces signal beams with M{sup 2} {approx} 3 at pulse energies exceeding 50 mJ. Pump beam

  10. Multitemporal Monitoring of the Air Quality in Bulgaria by Satellite Based Instruments

    Science.gov (United States)

    Nikolov, Hristo; Borisova, Denitsa

    2015-04-01

    Nowadays the effect on climate changes on the population and environment caused by air pollutants at local and regional scale by pollution concentrations higher than allowed is undisputable. Main sources of gas releases are due to anthropogenic emissions caused by the economic and domestic activities of the inhabitants, and to less extent having natural origin. Complementary to pollutants emissions the local weather parameters such as temperature, precipitation, wind speed, clouds, atmospheric water vapor, and wind direction control the chemical reactions in the atmosphere. It should be noted that intrinsic property of the air pollution is its "transboundary-ness" and this is why the air quality (AQ) is not affecting the population of one single country only. This why the exchange of information concerning AQ at EU level is subject to well established legislation and one of EU flagship initiatives for standardization in data exchange, namely INSPIRE, has to cope with. It should be noted that although good reporting mechanism with regard to AQ is already established between EU member states national networks suffer from a serious disadvantage - they don't form a regular grid which is a prerequisite for verification of pollutants transport modeling. Alternative sources of information for AQ are the satellite observations (i.e. OMI, TOMS instruments) providing daily data for ones of the major contributors to air pollution such as O3, NOX and SO2. Those data form regular grids and are processed the same day of the acquisition so they could be used in verification of the outputs generated by numerical modeling of the AQ and pollution transfer. In this research we present results on multitemporal monitoring of several regional "hot spots" responsible for greenhouse gases emissions in Bulgaria with emphasis on satellite-based instruments. Other output from this study is a method for validation of the AQ forecasts and also providing feedback to the service that prepares

  11. 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...

  12. 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...

  13. The modified NCEP ATP III criteria maybe better than the IDF criteria in diagnosing Metabolic Syndrome among Malays in Kuala Lumpur

    Directory of Open Access Journals (Sweden)

    Bulgiba Awang

    2010-11-01

    Full Text Available Abstract Background Metabolic Syndrome is associated with increased risk for type 2 diabetes and cardiovascular diseases. However, different diagnostic criteria have been recommended by different expert groups. In Malaysia, there is a lack of research comparing these different diagnostic criteria. Therefore, it is our aim to study the concordance between the IDF and the modified NCEP ATP III definitions of Metabolic Syndrome among a Malay cohort in Kuala Lumpur; and to demonstrate if all participants have the same cardiometabolic risks. Methods This was an analytical cross sectional study. Ethics approval was obtained and informed consent was given by all participants. Anthropometric measurements, blood pressure, fasting blood glucose and lipid profile were taken following standard protocols. Results Metabolic Syndrome was diagnosed in 41.4% and 38.2% participants using the modified NCEP and IDF criteria respectively. Among those diagnosed with Metabolic Syndrome by modified NCEP, 7.6% were missed by the IDF criteria. Participants diagnosed by the modified NCEP criteria had lower BMI and waist circumference but had higher cardiometabolic risks than those diagnosed with both criteria. Their blood pressure, glucose, total cholesterol and triglyceride were more adverse than the IDF group. This demonstrated that central obesity may not be a prerequisite for the development of increased cardiometabolic risks within this Malay cohort. Conclusion Metabolic syndrome is common in this Malay cohort regardless of the criterion used. The modified NCEP ATP III criteria may be more suitable in diagnosis of metabolic syndrome for this Malay cohort.

  14. Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

    Science.gov (United States)

    Liu, Z.; Shie, C. L.; Meyer, D. J.

    2017-12-01

    Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

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

    Science.gov (United States)

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

    2017-05-01

    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 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.

  16. 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.

  17. Satellite-based emission constraint for nitrogen oxides: Capability and uncertainty

    Science.gov (United States)

    Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.

    2013-12-01

    Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.

  18. New perspectives for satellite-based archaeological research in the ancient territory of Hierapolis (Turkey

    Directory of Open Access Journals (Sweden)

    R. Lasaponara

    2008-11-01

    Full Text Available This paper deals with the use of satellite QuickBird images to find traces of past human activity in the ancient territory of Hierapolis (Turkey. This is one of the most important archaeological sites in Turkey, and in 1988 it was inscribed in the UNESCO World Heritage list. Although over the years the archaeological site of Hierapolis has been excavated, restored and well documented, up to now the territory around the ancient urban area is still largely unknown. The current research project, still in progress, aims to search the area neighbouring Hierapolis believed to have been under the control of the city for a long time and, therefore, expected to be very rich in archaeological evidence. In order to investigate a large area around the ancient Hierapolis and discover potential archaeological remains, QuickBird images were adopted.

    Results from satellite-based analysis allowed us to find several unknown rural settlements dating back to early Imperial Roman and the Byzantine age. Two significant test sites were focused on in this paper in order to characterize the different spectral responses observed for different types of archaeological features (shadow and soil marks. Principal Component Analysis and spectral indices were computed to enhance archaeological marks and make identification easier. The capability of the QuickBird data set (panchromatic, multispectral channel, PCA and spectral indices in searching for archaeological marks was assessed in a quantitative way by using a specific indicator.

  19. Does Urban Form Affect Urban NO2? Satellite-Based Evidence for More than 1200 Cities.

    Science.gov (United States)

    Bechle, Matthew J; Millet, Dylan B; Marshall, Julian D

    2017-11-07

    Modifying urban form may be a strategy to mitigate urban air pollution. For example, evidence suggests that urban form can affect motor vehicle usage, a major contributor to urban air pollution. We use satellite-based measurements of urban form and nitrogen dioxide (NO 2 ) to explore relationships between urban form and air pollution for a global data  set of 1274 cities. Three of the urban form metrics studied (contiguity, circularity, and vegetation) have a statistically significant relationship with urban NO 2 ; their combined effect could be substantial. As illustration, if findings presented here are causal, that would suggest that if Christchurch, New Zealand (a city at the 75th percentile for all three urban-form metrics, and with a network of buses, trams, and bicycle facilities) was transformed to match the urban form of Indio - Cathedral City, California, United States (a city at the 25th percentile for those same metrics, and exhibiting sprawl-like suburban development), our models suggest that Christchurch's NO 2 concentrations would be ∼60% higher than its current level. We also find that the combined effect of urban form on NO 2 is larger for small cities (β × IQR = -0.46 for cities urban population and are where much of the future urban growth is expected to occur. This work highlights the need for future study of how changes in urban form and related land use and transportation policies impact urban air pollution, especially for small cities.

  20. 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)

  1. The attitude inversion method of geostationary satellites based on unscented particle filter

    Science.gov (United States)

    Du, Xiaoping; Wang, Yang; Hu, Heng; Gou, Ruixin; Liu, Hao

    2018-04-01

    The attitude information of geostationary satellites is difficult to be obtained since they are presented in non-resolved images on the ground observation equipment in space object surveillance. In this paper, an attitude inversion method for geostationary satellite based on Unscented Particle Filter (UPF) and ground photometric data is presented. The inversion algorithm based on UPF is proposed aiming at the strong non-linear feature in the photometric data inversion for satellite attitude, which combines the advantage of Unscented Kalman Filter (UKF) and Particle Filter (PF). This update method improves the particle selection based on the idea of UKF to redesign the importance density function. Moreover, it uses the RMS-UKF to partially correct the prediction covariance matrix, which improves the applicability of the attitude inversion method in view of UKF and the particle degradation and dilution of the attitude inversion method based on PF. This paper describes the main principles and steps of algorithm in detail, correctness, accuracy, stability and applicability of the method are verified by simulation experiment and scaling experiment in the end. The results show that the proposed method can effectively solve the problem of particle degradation and depletion in the attitude inversion method on account of PF, and the problem that UKF is not suitable for the strong non-linear attitude inversion. However, the inversion accuracy is obviously superior to UKF and PF, in addition, in the case of the inversion with large attitude error that can inverse the attitude with small particles and high precision.

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

    International Nuclear Information System (INIS)

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

    2000-01-01

    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. Satellite-based trends of solar radiation and cloud parameters in Europe

    Science.gov (United States)

    Pfeifroth, Uwe; Bojanowski, Jedrzej S.; Clerbaux, Nicolas; Manara, Veronica; Sanchez-Lorenzo, Arturo; Trentmann, Jörg; Walawender, Jakub P.; Hollmann, Rainer

    2018-04-01

    Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

  4. Climatology and Structures of Southwest Vortices in NCEP Climate Forecast System Reanalysis

    Science.gov (United States)

    Feng, Xinyuan; Liu, Changhai; Fan, Guangzhou; Liu, Xiaodong; Feng, Caiyun

    2017-04-01

    A southwest vortex (SWV) refers to the meso-α-scale cyclonic low-pressure system originating in southwest China, as a result of interactions of large-scale circulations and the specific multi-scale topography, such as the Tibetan Plateau, Hengduan Mountain and Sichuan Basin. It is a high-impact precipitation-generating weather system in southwestern China, in the Yangtze River valley and even in north China. This paper reports on a systematic investigation of its climatological and structural characteristics over the 32-yr period of 1979-2010 using the high-resolution NCEP Climate Forecast System Reanalysis data. The present study has the several unique features. First, the new generation reanalysis product possesses high spatial and temporal resolution, arguably being more suitable for mesoscale vortex studies as compared to the preceding reanalysis datasets and moreover enabling an examination of the diurnal behavior. Second, our 32-yr statistics are capable of producing a robust representation of the SWV climatology. Third, the application of an objective identification methodology avoids some subjective ambiguities in the manual approach that has exclusively been adopted before. Lastly, a systematic exploration of thermodynamic and kinematic structures is conducted, unlike the previous exclusive heavy-rain-generating case studies. Our major findings are summarized as follows. The SWV is a common regional weather system with an annual count of 73. Two primary source regions are identified, located in the Sichuan Basin and southeast flank of the Tibetan Plateau, respectively. The genesis displays striking seasonality, characteristic of a spring-summer (March-August) preference with a peak in May. Remarkable diurnal variations are present, with two active periods around 07 and 19 Local Time. There exist prominent regional disparities in both the seasonal and diurnal variability though. A large portion of the vortices travel a rather limited distance due partially

  5. 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.

  6. An intercomparison of satellite-based daily evapotranspiration estimates under different eco-climatic regions in South Africa

    CSIR Research Space (South Africa)

    Majozi, Nobuhle P

    2017-03-01

    Full Text Available ), while windspeed and direction were measured at 2.5 m height using an RM Young wind sentry (Mod l 03001—Campbell Scientific Ltd., Logan, UT, USA), a d solar irradiance was monitored using a pyranometer (Apogee Instru ents, Lo an, UT, USA). R infall... a CS500 probe (Vaisala, Helsinki, Finland), while windspeed and direction were measured at 2.5 m height using an RM Young wind sentry (Model 03001—Campbell Scientific Ltd., Logan, UT, USA), and solar irradiance was monitored using a pyranometer...

  7. 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,

  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. 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 ...

  10. The use of geostationary satellite based rainfall estimation and rainfall-runoff modelling for regional flash flood assessment

    OpenAIRE

    Suseno, Dwi Prabowo Yuga

    2013-01-01

    The availability of rainfall triggered hazard information such as flash flood is crucial in the flood disaster management and mitigation. However, providing that information is mainly hampered by the shortage of data because of the sparse, uneven or absence the hydrological or meteorological observation. Remote sensing techniques that make frequent observations with continuous spatial coverage provide useful information for detecting the hydrometeorological phenomena such as rainfall and floo...

  11. An assessment of TropFlux and NCEP air-sea fluxes on ROMS simulations over the Bay of Bengal region

    Science.gov (United States)

    Dey, Dipanjan; Sil, Sourav; Jana, Sudip; Pramanik, Saikat; Pandey, P. C.

    2017-12-01

    This study presents an assessment of the TropFlux and the National Centers for Environmental Prediction (NCEP) reanalysis air-sea fluxes in simulating the surface and subsurface oceanic parameters over the Bay of Bengal (BoB) region during 2002-2014 using the Regional Ocean Modelling System (ROMS). The assessment has been made by comparing the simulated fields with in-situ and satellite observations. The simulated surface and subsurface temperatures in the TropFlux forced experiment (TropFlux-E) show better agreement with the Research Moored Array for African-Asian-Australian Monsoon Analysis (RAMA) and Argo observations than the NCEP forced experiment (NCEP-E). The BoB domain averaged sea surface temperature (SST) simulated in the NCEP-E is consistently cooler than the satellite SST, with a root mean square error (RMSE) of 0.79 °C. Moreover, NCEP-E shows a limitation in simulating the observed seasonal cycle of the SST due to substantial underestimation of the pre-monsoon SST peak. These limitations are mostly due to the lower values of the NCEP net heat flux. The seasonal and interannual variations of SST in the TropFlux-E are better comparable to the observations with correlations and skills more than 0.80 and 0.90 respectively. However, SST is overestimated during summer monsoon periods mainly due to higher net heat flux. The superiority of TropFlux forcing over the NCEP reanalysis can also be seen when simulating the interannual variabilities of the magnitude and vertical extent of Wyrtki jets at two equatorial RAMA buoy locations. The jet is weaker in the NCEP-E relative to the TropFlux-E and observations. The simulated sea surface height anomalies (SSHA) from both the experiments are able to capture the regions of positive and negative SSHA with respect to satellite-derived altimeter data with better performance in the TropFlux-E. The speed of the westward propagating Rossby wave along 18°N in the TropFlux-E is found to be about 4.7 cm/s, which is close to

  12. Air traffic management system design using satellite based geo-positioning and communications assets

    Science.gov (United States)

    Horkin, Phil

    1995-01-01

    The current FAA and ICAO FANS vision of Air Traffic Management will transition the functions of Communications, Navigation, and Surveillance to satellite based assets in the 21st century. Fundamental to widespread acceptance of this vision is a geo-positioning system that can provide worldwide access with best case differential GPS performance, but without the associated problems. A robust communications capability linking-up aircraft and towers to meet the voice and data requirements is also essential. The current GPS constellation does not provide continuous global coverage with a sufficient number of satellites to meet the precision landing requirements as set by the world community. Periodic loss of the minimum number of satellites in view creates an integrity problem, which prevents GPS from becoming the primary system for navigation. Furthermore, there is reluctance on the part of many countries to depend on assets like GPS and GLONASS which are controlled by military communities. This paper addresses these concerns and provides a system solving the key issues associated with navigation, automatic dependent surveillance, and flexible communications. It contains an independent GPS-like navigation system with 27 satellites providing global coverage with a minimum of six in view at all times. Robust communications is provided by a network of TDMA/FDMA communications payloads contained on these satellites. This network can support simultaneous communications for up to 30,000 links, nearly enough to simultaneously support three times the current global fleet of jumbo air passenger aircraft. All of the required hardware is directly traceable to existing designs.

  13. 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.

  14. Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel.

    Science.gov (United States)

    Brandt, Martin; Mbow, Cheikh; Diouf, Abdoul A; Verger, Aleixandre; Samimi, Cyrus; Fensholt, Rasmus

    2015-04-01

    After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal. © 2014 John Wiley & Sons Ltd.

  15. Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

    Science.gov (United States)

    Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman

    2018-06-01

    Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

  16. 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.

  17. Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

    Science.gov (United States)

    Williams, Jack G.; Rosser, Nick J.; Kincey, Mark E.; Benjamin, Jessica; Oven, Katie J.; Densmore, Alexander L.; Milledge, David G.; Robinson, Tom R.; Jordan, Colm A.; Dijkstra, Tom A.

    2018-01-01

    Landslides triggered by large earthquakes in mountainous regions contribute significantly to overall earthquake losses and pose a major secondary hazard that can persist for months or years. While scientific investigations of coseismic landsliding are increasingly common, there is no protocol for rapid (hours-to-days) humanitarian-facing landslide assessment and no published recognition of what is possible and what is useful to compile immediately after the event. Drawing on the 2015 Mw 7.8 Gorkha earthquake in Nepal, we consider how quickly a landslide assessment based upon manual satellite-based emergency mapping (SEM) can be realistically achieved and review the decisions taken by analysts to ascertain the timeliness and type of useful information that can be generated. We find that, at present, many forms of landslide assessment are too slow to generate relative to the speed of a humanitarian response, despite increasingly rapid access to high-quality imagery. Importantly, the value of information on landslides evolves rapidly as a disaster response develops, so identifying the purpose, timescales, and end users of a post-earthquake landslide assessment is essential to inform the approach taken. It is clear that discussions are needed on the form and timing of landslide assessments, and how best to present and share this information, before rather than after an earthquake strikes. In this paper, we share the lessons learned from the Gorkha earthquake, with the aim of informing the approach taken by scientists to understand the evolving landslide hazard in future events and the expectations of the humanitarian community involved in disaster response.

  18. A six year satellite-based assessment of the regional variations in aerosol indirect effects

    Directory of Open Access Journals (Sweden)

    T. A. Jones

    2009-06-01

    Full Text Available Aerosols act as cloud condensation nuclei (CCN for cloud water droplets, and changes in aerosol concentrations have significant microphysical impacts on the corresponding cloud properties. Moderate Resolution Imaging Spectroradiometer (MODIS aerosol and cloud properties are combined with NCEP Reanalysis data for six different regions around the globe between March 2000 and December 2005 to study the effects of different aerosol, cloud, and atmospheric conditions on the aerosol indirect effect (AIE. Emphasis is placed in examining the relative importance of aerosol concentration, type, and atmospheric conditions (mainly vertical motion to AIE from region to region.

    Results show that in most regions, AIE has a distinct seasonal cycle, though the cycle varies in significance and period from region to region. In the Arabian Sea (AS, the six-year mean anthropogenic + dust AIE is −0.27 Wm−2 and is greatest during the summer months (<−2.0 Wm−2 during which aerosol concentrations (from both dust and anthropogenic sources are greatest. Comparing AIE as a function of thin (LWP<20 gm−2 vs. thick (LWP≥20 gm−2 clouds under conditions of large scale ascent or decent at 850 hPa showed that AIE is greatest for thick clouds during periods of upward vertical motion. In the Bay of Bengal, AIE is negligible owing to less favorable atmospheric conditions, a lower concentration of aerosols, and a non-alignment of aerosol and cloud layers. In the eastern North Atlantic, AIE is weakly positive (+0.1 Wm−2 with dust aerosol concentration being much greater than the anthropogenic or sea salt components. However, elevated dust in this region exists above the maritime cloud layers and does not have a hygroscopic coating, which occurs in AS, preventing the dust from acting as CCN and limiting AIE. The Western Atlantic has a large anthropogenic aerosol concentration transported from the eastern

  19. 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

  20. 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

  1. Evaluation of Satellite-Based Precipitation Products from IMERG V04A and V03D, CMORPH and TMPA with Gauged Rainfall in Three Climatologic Zones in China

    Directory of Open Access Journals (Sweden)

    Guanghua Wei

    2017-12-01

    Full Text Available A critical evaluation of the newly released precipitation data set is very important for both the end users and data developers. Meanwhile, the evaluation may provide a benchmark for the product’s continued development and future improvement. To these ends, the four precipitation estimates including IMERG (the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement V04A, IMERG V03D, CMORPH (the Climate Prediction Center Morphing technique-CRT and TRMM (the Tropical Rainfall Measuring Mission 3B42 are systematically evaluated against the gauge precipitation estimates at multiple spatiotemporal scales from 1 June 2014 to 30 November 2015 over three different topographic and climatic watersheds in China. Meanwhile, the statistical methods are utilized to quantize the performance of the four satellite-based precipitation estimates. The results show that: (1 over the Tibetan Plateau cold region, among all products, IMERG V04A underestimates precipitation with the largest RB (−46.98% during the study period and the similar results are seen at the seasonal scale. However, IMERG V03D demonstrates the best performance according to RB (7.46%, RMSE (0.44 mm/day and RRMSE (28.37%. Except for in summer, TRMM 3B42 perform better than CMORPH according to RMSEs, RRMSEs and Rs; (2 within the semi-humid Huaihe River Basin, IMERG V04A has a slight advantage over the other three satellite-based precipitation products with the lowest RMSE (0.32 mm/day during the evaluation period and followed by IMERG V03D, TRMM 3B42 and CMORPH orderly; (3 over the arid/semi-arid Weihe River Basin, in comparison with the other three products, TRMM 3B42 demonstrates the best performance with the lowest RMSE (0.1 mm/day, RRMSE (8.44% and highest R (0.92 during the study period. Meanwhile, IMERG V03D perform better than IMERG V04A according all the statistical indicators; (4 in winter, IMERG V04A and IMERG V03D tend to underestimate the total precipitation

  2. 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.

  3. 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

  4. Goddard Satellite-Based Surface Turbulent Fluxes, 0.25x0.25 deg, Daily Grid, V3, (GSSTF_F14) V3

    Data.gov (United States)

    National Aeronautics and Space Administration — These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr....

  5. 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

  6. 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

  7. 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.

  8. A change detection strategy for monitoring vegetative and land-use cover types using remotely-sensed, satellite-based data

    International Nuclear Information System (INIS)

    Hallum, C.

    1993-01-01

    Changes to the environment are of critical concern in the world today; consequently, monitoring such changes and assessing their impacts are tasks demanding considerably higher priority. The ecological impacts of the natural global cycles of gases and particulates in the earth's atmosphere are highly influenced by the extent of changes to vegetative canopy characteristics which dictates the need for capability to detect and assess the magnitude of such changes. The primary emphasis of this paper is on the determination of the size and configuration of the sampling unit that maximizes the probability of its intersection with a 'change' area. Assessment of the significance of the 'change' in a given locality is also addressed and relies on a statistical approach that compares the number of elemental units exceeding a reflectance threshold when compared to a previous point in time. Consideration is also given to a technical framework that supports quantifying the magnitude of the 'change' over large areas (i.e., the estimated area changing from forest to agricultural land-use). The latter entails a multistage approach which utilizes satellite-based and other related data sources

  9. Extension of the TAMSAT satellite-based rainfall monitoring over Africa and from 1983 to present

    OpenAIRE

    Tarnavsky, Elena; Grimes, David; Maidment, Ross; Black, Emily; Allan, Richard; Stringer, Marc; Chadwick, Robin; Kayitakire, Francois

    2014-01-01

    Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the produ...

  10. Strategies for satellite-based monitoring of CO2 from distributed area and point sources

    Science.gov (United States)

    Schwandner, Florian M.; Miller, Charles E.; Duren, Riley M.; Natraj, Vijay; Eldering, Annmarie; Gunson, Michael R.; Crisp, David

    2014-05-01

    and sensor provides the full range of temporal sampling needed to characterize distributed area and point source emissions. For instance, point source emission patterns will vary with source strength, wind speed and direction. Because wind speed, direction and other environmental factors change rapidly, short term variabilities should be sampled. For detailed target selection and pointing verification, important lessons have already been learned and strategies devised during JAXA's GOSAT mission (Schwandner et al, 2013). The fact that competing spatial and temporal requirements drive satellite remote sensing sampling strategies dictates a systematic, multi-factor consideration of potential solutions. Factors to consider include vista, revisit frequency, integration times, spatial resolution, and spatial coverage. No single satellite-based remote sensing solution can address this problem for all scales. It is therefore of paramount importance for the international community to develop and maintain a constellation of atmospheric CO2 monitoring satellites that complement each other in their temporal and spatial observation capabilities: Polar sun-synchronous orbits (fixed local solar time, no diurnal information) with agile pointing allow global sampling of known distributed area and point sources like megacities, power plants and volcanoes with daily to weekly temporal revisits and moderate to high spatial resolution. Extensive targeting of distributed area and point sources comes at the expense of reduced mapping or spatial coverage, and the important contextual information that comes with large-scale contiguous spatial sampling. Polar sun-synchronous orbits with push-broom swath-mapping but limited pointing agility may allow mapping of individual source plumes and their spatial variability, but will depend on fortuitous environmental conditions during the observing period. These solutions typically have longer times between revisits, limiting their ability to resolve

  11. Seasonal prediction and predictability of Eurasian spring snow water equivalent in NCEP Climate Forecast System version 2 reforecasts

    Science.gov (United States)

    He, Qiong; Zuo, Zhiyan; Zhang, Renhe; Zhang, Ruonan

    2018-01-01

    The spring snow water equivalent (SWE) over Eurasia plays an important role in East Asian and Indian monsoon rainfall. This study evaluates the seasonal prediction capability of NCEP Climate Forecast System version 2 (CFSv2) retrospective forecasts (1983-2010) for the Eurasian spring SWE. The results demonstrate that CFSv2 is able to represent the climatological distribution of the observed Eurasian spring SWE with a lead time of 1-3 months, with the maximum SWE occurring over western Siberia and Northeastern Europe. For a longer lead time, the SWE is exaggerated in CFSv2 because the start of snow ablation in CFSv2 lags behind that of the observation, and the simulated snowmelt rate is less than that in the observation. Generally, CFSv2 can simulate the interannual variations of the Eurasian spring SWE 1-5 months ahead of time but with an exaggerated magnitude. Additionally, the downtrend in CFSv2 is also overestimated. Because the initial conditions (ICs) are related to the corresponding simulation results significantly, the robust interannual variability and the downtrend in the ICs are most likely the causes for these biases. Moreover, CFSv2 exhibits a high potential predictability for the Eurasian spring SWE, especially the spring SWE over Siberia, with a lead time of 1-5 months. For forecasts with lead times longer than 5 months, the model predictability gradually decreases mainly due to the rapid decrease in the model signal.

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

    Science.gov (United States)

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

    2017-03-01

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

  13. Simulation of monsoon intraseasonal variability in NCEP CFSv2 and its role on systematic bias

    Science.gov (United States)

    Goswami, Bidyut B.; Deshpande, Medha; Mukhopadhyay, P.; Saha, Subodh K.; Rao, Suryachandra A.; Murthugudde, Raghu; Goswami, B. N.

    2014-11-01

    We have evaluated the simulation of Indian summer monsoon and its intraseasonal oscillations in the National Centers for Environmental Prediction climate forecast system model version 2 (CFSv2). The dry bias over the Indian landmass in the mean monsoon rainfall is one of the major concerns. In spite of this dry bias, CFSv2 shows a reasonable northward propagation of convection at intraseasonal (30-60 day) time scale. In order to document and understand this dry bias over the Indian landmass in CFSv2 simulations, a two pronged investigation is carried out on the two major facets of Indian summer monsoon: one, the air-sea interactions and two, the large scale vertical heating structure in the model. Our analysis shows a possible bias in the co-evolution of convection and sea surface temperature in CFSv2 over the equatorial Indian Ocean. It is also found that the simulated large scale vertical heat source (Q1) and moisture sink (Q2) over the Indian region are biased relative to observational estimates. Finally, this study provides a possible explanation for the dry precipitation bias over the Indian landmass in the simulated mean monsoon on the basis of the biases associated with the simulated ocean-atmospheric processes and the vertical heating structure. This study also throws some light on the puzzle of CFSv2 exhibiting a reasonable northward propagation at the intraseasonal time scale (30-60 day) despite a drier monsoon over the Indian land mass.

  14. 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 ...

  15. 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.

  16. Application of the system of assimilation of climatic data (CDAS) of the Project NCEP/NCAR - Reanalysis Dates Set For climatological and synoptic ends

    International Nuclear Information System (INIS)

    Zea Mazo, Jorge Anibal; Leon Aristizabal Gloria Esperanza; Eslava Ramirez, Jesus Antonio

    2001-01-01

    In response to an increasing demand of meteorological information on a synoptic scale and the need for a better and more precise knowledge of the different atmospheric fields on a local, regional and global scale, the program known as GRADS, developed by COLA in the US, has been implemented. to show graphically meteorological patterns at the surface and at different levels in the troposphere and lower stratosphere based on high-quality grid data prepared by NCEP/NCAR (NOAA)

  17. Satellite-based Calibration of Heat Flux at the Ocean Surface

    Science.gov (United States)

    Barron, C. N.; Dastugue, J. M.; May, J. C.; Rowley, C. D.; Smith, S. R.; Spence, P. L.; Gremes-Cordero, S.

    2016-02-01

    Model forecasts of upper ocean heat content and variability on diurnal to daily scales are highly dependent on estimates of heat flux through the air-sea interface. Satellite remote sensing is applied to not only inform the initial ocean state but also to mitigate errors in surface heat flux and model representations affecting the distribution of heat in the upper ocean. Traditional assimilation of sea surface temperature (SST) observations re-centers ocean models at the start of each forecast cycle. Subsequent evolution depends on estimates of surface heat fluxes and upper-ocean processes over the forecast period. The COFFEE project (Calibration of Ocean Forcing with satellite Flux Estimates) endeavors to correct ocean forecast bias through a responsive error partition among surface heat flux and ocean dynamics sources. A suite of experiments in the southern California Current demonstrates a range of COFFEE capabilities, showing the impact on forecast error relative to a baseline three-dimensional variational (3DVAR) assimilation using Navy operational global or regional atmospheric forcing. COFFEE addresses satellite-calibration of surface fluxes to estimate surface error covariances and links these to the ocean interior. Experiment cases combine different levels of flux calibration with different assimilation alternatives. The cases may use the original fluxes, apply full satellite corrections during the forecast period, or extend hindcast corrections into the forecast period. Assimilation is either baseline 3DVAR or standard strong-constraint 4DVAR, with work proceeding to add a 4DVAR expanded to include a weak constraint treatment of the surface flux errors. Covariance of flux errors is estimated from the recent time series of forecast and calibrated flux terms. While the California Current examples are shown, the approach is equally applicable to other regions. These approaches within a 3DVAR application are anticipated to be useful for global and larger

  18. 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

  19. Studying Vegetation Salinity: From the Field View to a Satellite-Based Perspective

    Directory of Open Access Journals (Sweden)

    Rachel Lugassi

    2017-02-01

    Full Text Available Salinization of irrigated lands in the semi-arid Jezreel Valley, Northern Israel results in soil-structure deterioration and crop damage. We formulated a generic rule for estimating salinity of different vegetation types by studying the relationship between Cl/Na and different spectral slopes in the visible–near infrared–shortwave infrared (VIS–NIR–SWIR spectral range using both field measurements and satellite imagery (Sentinel-2. For the field study, the slope-based model was integrated with conventional partial least squares (PLS analyses. Differences in 14 spectral ranges, indicating changes in salinity levels, were identified across the VIS–NIR–SWIR region (350–2500 nm. Next, two different models were run using PLS regression: (i using spectral slope data across these ranges; and (ii using preprocessed spectral reflectance. The best model for predicting Cl content was based on continuum removal reflectance (R2 = 0.84. Satisfactory correlations were obtained using the slope-based PLS model (R2 = 0.77 for Cl and R2 = 0.63 for Na. Thus, salinity contents in fresh plants could be estimated, despite masking of some spectral regions by water absorbance. Finally, we estimated the most sensitive spectral channels for monitoring vegetation salinity from a satellite perspective. We evaluated the recently available Sentinel-2 imagery’s ability to distinguish variability in vegetation salinity levels. The best estimate of a Sentinel-2-based vegetation salinity index was generated based on a ratio between calculated slopes: the 490–665 nm and 705–1610 nm. This index was denoted as the Sentinel-2-based vegetation salinity index (SVSI (band 4 − band 2/(band 5 + band 11.

  20. Comparison of the seasonal climate simulated by the pattern CCM3 and the data of the reanalysis NCEP/NCAR with the observed data of the temperature of the air and the precipitation in Colombia

    International Nuclear Information System (INIS)

    Leon Aristizabal, Gloria Esperanza; Zea Mazo, Jorge Anibal

    2001-01-01

    In this work we carry out a comparison of the simulations of the climatic model CCM3, the data of the NCEP/NCAR Reanalysis and real data, by the practical significance of the model based on the observed differences

  1. 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

  2. Dynamical Downscaling of Seasonal Climate Prediction over Nordeste Brazil with ECHAM3 and NCEP's Regional Spectral Models at IRI.

    Science.gov (United States)

    Nobre, Paulo; Moura, Antonio D.; Sun, Liqiang

    2001-12-01

    This study presents an evaluation of a seasonal climate forecast done with the International Research Institute for Climate Prediction (IRI) dynamical forecast system (regional model nested into a general circulation model) over northern South America for January-April 1999, encompassing the rainy season over Brazil's Nordeste. The one-way nesting is one in two tiers: first the NCEP's Regional Spectral Model (RSM) runs with an 80-km grid mesh forced by the ECHAM3 atmospheric general circulation model (AGCM) outputs; then the RSM runs with a finer grid mesh (20 km) forced by the forecasts generated by the RSM-80. An ensemble of three realizations is done. Lower boundary conditions over the oceans for both ECHAM and RSM model runs are sea surface temperature forecasts over the tropical oceans. Soil moisture is initialized by ECHAM's inputs. The rainfall forecasts generated by the regional model are compared with those of the AGCM and observations. It is shown that the regional model at 80-km resolution improves upon the AGCM rainfall forecast, reducing both seasonal bias and root-mean-square error. On the other hand, the RSM-20 forecasts presented larger errors, with spatial patterns that resemble those of local topography. The better forecast of the position and width of the intertropical convergence zone (ITCZ) over the tropical Atlantic by the RSM-80 model is one of the principal reasons for better-forecast scores of the RSM-80 relative to the AGCM. The regional model improved the spatial as well as the temporal details of rainfall distribution, and also presenting the minimum spread among the ensemble members. The statistics of synoptic-scale weather variability on seasonal timescales were best forecast with the regional 80-km model over the Nordeste. The possibility of forecasting the frequency distribution of dry and wet spells within the rainy season is encouraging.

  3. Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter

    International Nuclear Information System (INIS)

    Kim, Hye-Mi; Webster, Peter J.; Curry, Judith A.

    2012-01-01

    The seasonal prediction skill for the Northern Hemisphere winter is assessed using retrospective predictions (1982-2010) from the ECMWF System 4 (Sys4) and National Center for Environmental Prediction (NCEP) CFS version 2 (CFSv2) coupled atmosphere-ocean seasonal climate prediction systems. Sys4 shows a cold bias in the equatorial Pacific but a warm bias is found in the North Pacific and part of the North Atlantic. The CFSv2 has strong warm bias from the cold tongue region of the eastern Pacific to the equatorial central Pacific and cold bias in broad areas over the North Pacific and the North Atlantic. A cold bias in the Southern Hemisphere is common in both reforecasts. In addition, excessive precipitation is found in the equatorial Pacific, the equatorial Indian Ocean and the western Pacific in Sys4, and in the South Pacific, the southern Indian Ocean and the western Pacific in CFSv2. A dry bias is found for both modeling systems over South America and northern Australia. The mean prediction skill of 2 meter temperature (2mT) and precipitation anomalies are greater over the tropics than the extra-tropics and also greater over ocean than land. The prediction skill of tropical 2mT and precipitation is greater in strong El Nino Southern Oscillation (ENSO) winters than in weak ENSO winters. Both models predict the year-to-year ENSO variation quite accurately, although sea surface temperature trend bias in CFSv2 over the tropical Pacific results in lower prediction skill for the CFSv2 relative to the Sys4. Both models capture the main ENSO teleconnection pattern of strong anomalies over the tropics, the North Pacific and the North America. However, both models have difficulty in forecasting the year-to-year winter temperature variability over the US and northern Europe. (orig.)

  4. Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere Winter

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hye-Mi; Webster, Peter J.; Curry, Judith A. [Georgia Institute of Technology, School of Earth and Atmospheric Science, Atlanta, GA (United States)

    2012-12-15

    The seasonal prediction skill for the Northern Hemisphere winter is assessed using retrospective predictions (1982-2010) from the ECMWF System 4 (Sys4) and National Center for Environmental Prediction (NCEP) CFS version 2 (CFSv2) coupled atmosphere-ocean seasonal climate prediction systems. Sys4 shows a cold bias in the equatorial Pacific but a warm bias is found in the North Pacific and part of the North Atlantic. The CFSv2 has strong warm bias from the cold tongue region of the eastern Pacific to the equatorial central Pacific and cold bias in broad areas over the North Pacific and the North Atlantic. A cold bias in the Southern Hemisphere is common in both reforecasts. In addition, excessive precipitation is found in the equatorial Pacific, the equatorial Indian Ocean and the western Pacific in Sys4, and in the South Pacific, the southern Indian Ocean and the western Pacific in CFSv2. A dry bias is found for both modeling systems over South America and northern Australia. The mean prediction skill of 2 meter temperature (2mT) and precipitation anomalies are greater over the tropics than the extra-tropics and also greater over ocean than land. The prediction skill of tropical 2mT and precipitation is greater in strong El Nino Southern Oscillation (ENSO) winters than in weak ENSO winters. Both models predict the year-to-year ENSO variation quite accurately, although sea surface temperature trend bias in CFSv2 over the tropical Pacific results in lower prediction skill for the CFSv2 relative to the Sys4. Both models capture the main ENSO teleconnection pattern of strong anomalies over the tropics, the North Pacific and the North America. However, both models have difficulty in forecasting the year-to-year winter temperature variability over the US and northern Europe. (orig.)

  5. 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

  6. 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.

  7. A novel cross-satellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom

    Science.gov (United States)

    Page, Benjamin P.; Kumar, Abhishek; Mishra, Deepak R.

    2018-04-01

    As the frequency of cyanobacterial harmful algal blooms (CyanoHABs) become more common in recreational lakes and water supply reservoirs, demand for rapid detection and temporal monitoring will be imminent for effective management. The goal of this study was to demonstrate a novel and potentially operational cross-satellite based protocol for synoptic monitoring of rapidly evolving and increasingly common CyanoHABs in inland waters. The analysis involved a novel way to cross-calibrate a chlorophyll-a (Chl-a) detection model for the Landsat-8 OLI sensor from the relationship between the normalized difference chlorophyll index and the floating algal index derived from Sentinel-2A on a coinciding overpass date during the summer CyanoHAB bloom in Utah Lake. This aided in the construction of a time-series phenology of the Utah Lake CyanoHAB event. Spatio-temporal cyanobacterial density maps from both Sentinel-2A and Landsat-8 sensors revealed that the bloom started in the first week of July 2016 (July 3rd, mean cell count: 9163 cells/mL), reached peak in mid-July (July 15th, mean cell count: 108176 cells/mL), and reduced in August (August 24th, mean cell count: 9145 cells/mL). Analysis of physical and meteorological factors suggested a complex interaction between landscape processes (high surface runoff), climatic conditions (high temperature, high rainfall followed by negligible rainfall, stable wind), and water quality (low water level, high Chl-a) which created a supportive environment for triggering these blooms in Utah Lake. This cross satellite-based monitoring methods can be a great tool for regular monitoring and will reduce the budget cost for monitoring and predicting CyanoHABs in large lakes.

  8. Spatial and temporal interpolation of satellite-based aerosol optical depth measurements over North America using B-splines

    Science.gov (United States)

    Pfister, Nicolas; O'Neill, Norman T.; Aube, Martin; Nguyen, Minh-Nghia; Bechamp-Laganiere, Xavier; Besnier, Albert; Corriveau, Louis; Gasse, Geremie; Levert, Etienne; Plante, Danick

    2005-08-01

    Satellite-based measurements of aerosol optical depth (AOD) over land are obtained from an inversion procedure applied to dense dark vegetation pixels of remotely sensed images. The limited number of pixels over which the inversion procedure can be applied leaves many areas with little or no AOD data. Moreover, satellite coverage by sensors such as MODIS yields only daily images of a given region with four sequential overpasses required to straddle mid-latitude North America. Ground based AOD data from AERONET sun photometers are available on a more continuous basis but only at approximately fifty locations throughout North America. The object of this work is to produce a complete and coherent mapping of AOD over North America with a spatial resolution of 0.1 degree and a frequency of three hours by interpolating MODIS satellite-based data together with available AERONET ground based measurements. Before being interpolated, the MODIS AOD data extracted from different passes are synchronized to the mapping time using analyzed wind fields from the Global Multiscale Model (Meteorological Service of Canada). This approach amounts to a trajectory type of simplified atmospheric dynamics correction method. The spatial interpolation is performed using a weighted least squares method applied to bicubic B-spline functions defined on a rectangular grid. The least squares method enables one to weight the data accordingly to the measurement errors while the B-splines properties of local support and C2 continuity offer a good approximation of AOD behaviour viewed as a function of time and space.

  9. 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

    2016-08-31

    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.

  10. 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.

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

    KAUST Repository

    McCabe, Matthew; Houborg, Rasmus; Rosas, Jorge; Ershadi, Ali; Anderson, Martha; Hain, Christopher

    2015-01-01

    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.

  12. 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.

  13. Costs and benefits of satellite-based tools for irrigation management

    Directory of Open Access Journals (Sweden)

    Francesco eVuolo

    2015-07-01

    Full Text Available This paper presents the results of a collaborative work with farmers and a cost-benefit analysis of geospatial technologies applied to irrigation water management in the semi-arid agricultural area in Lower Austria. We use Earth observation (EO data to estimate crop evapotranspiration (ET and webGIS technologies to deliver maps and irrigation advice to farmers. The study reports the technical and qualitative evaluation performed during a demonstration phase in 2013 and provides an outlook to future developments. The calculation of the benefits is based on a comparison of the irrigation volumes estimated from satellite vs. the irrigation supplied by the farmers. In most cases, the amount of water supplied was equal to the maximum amount of water required by crops. At the same time high variability was observed for the different irrigation units and crop types. Our data clearly indicates that economic benefits could be achieved by reducing irrigation volumes, especially for water-intensive crops. Regarding the qualitative evaluation, most of the farmers expressed a very positive interest in the provided information. In particular, information related to crop ET was appreciated as this helps to make better informed decisions on irrigation. The majority of farmers (54% also expressed a general willingness to pay, either directly or via cost sharing, for such a service. Based on different cost scenarios, we calculated the cost of the service. Considering 20,000 ha regularly irrigated land, the advisory service would cost between 2.5 and 4.3 €/ha per year depending on the type of satellite data used. For comparison, irrigation costs range between 400 and 1000 €/ha per year for a typical irrigation volume of 2,000 cubic meters per ha. With a correct irrigation application, more than 10% of the water and energy could be saved in water-intensive crops, which is equivalent to an economic benefit of 40-100 €/ha per year.

  14. 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

  15. NCEP SST Analysis

    Science.gov (United States)

    Organization Search Go Search Polar Go MMAB SST Analysis Main page About MMAB Our Mission Our Personnel EMC Branches Global Climate & Weather Modeling Mesoscale Modeling Marine Modeling and Analysis Contact EMC (RTG_SST_HR) analysis For a regional map, click the desired area in the global SST analysis and anomaly maps

  16. An assessment of commonly employed satellite-based remote sensors for mapping mangrove species in Mexico using an NDVI-based classification scheme.

    Science.gov (United States)

    Valderrama-Landeros, L; Flores-de-Santiago, F; Kovacs, J M; Flores-Verdugo, F

    2017-12-14

    Optimizing the classification accuracy of a mangrove forest is of utmost importance for conservation practitioners. Mangrove forest mapping using satellite-based remote sensing techniques is by far the most common method of classification currently used given the logistical difficulties of field endeavors in these forested wetlands. However, there is now an abundance of options from which to choose in regards to satellite sensors, which has led to substantially different estimations of mangrove forest location and extent with particular concern for degraded systems. The objective of this study was to assess the accuracy of mangrove forest classification using different remotely sensed data sources (i.e., Landsat-8, SPOT-5, Sentinel-2, and WorldView-2) for a system located along the Pacific coast of Mexico. Specifically, we examined a stressed semiarid mangrove forest which offers a variety of conditions such as dead areas, degraded stands, healthy mangroves, and very dense mangrove island formations. The results indicated that Landsat-8 (30 m per pixel) had  the lowest overall accuracy at 64% and that WorldView-2 (1.6 m per pixel) had the highest at 93%. Moreover, the SPOT-5 and the Sentinel-2 classifications (10 m per pixel) were very similar having accuracies of 75 and 78%, respectively. In comparison to WorldView-2, the other sensors overestimated the extent of Laguncularia racemosa and underestimated the extent of Rhizophora mangle. When considering such type of sensors, the higher spatial resolution can be particularly important in mapping small mangrove islands that often occur in degraded mangrove systems.

  17. 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

  18. 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

  19. National satellite-based humid tropical forest change assessment in Peru in support of REDD+ implementation

    Science.gov (United States)

    Potapov, P. V.; Dempewolf, J.; Talero, Y.; Hansen, M. C.; Stehman, S. V.; Vargas, C.; Rojas, E. J.; Castillo, D.; Mendoza, E.; Calderón, A.; Giudice, R.; Malaga, N.; Zutta, B. R.

    2014-12-01

    Transparent, consistent, and accurate national forest monitoring is required for successful implementation of reducing emissions from deforestation and forest degradation (REDD+) programs. Collecting baseline information on forest extent and rates of forest loss is a first step for national forest monitoring in support of REDD+. Peru, with the second largest extent of Amazon basin rainforest, has made significant progress in advancing its forest monitoring capabilities. We present a national-scale humid tropical forest cover loss map derived by the Ministry of Environment REDD+ team in Peru. The map quantifies forest loss from 2000 to 2011 within the Peruvian portion of the Amazon basin using a rapid, semi-automated approach. The available archive of Landsat imagery (11 654 scenes) was processed and employed for change detection to obtain annual gross forest cover loss maps. A stratified sampling design and a combination of Landsat (30 m) and RapidEye (5 m) imagery as reference data were used to estimate the primary forest cover area, total gross forest cover loss area, proportion of primary forest clearing, and to validate the Landsat-based map. Sample-based estimates showed that 92.63% (SE = 2.16%) of the humid tropical forest biome area within the country was covered by primary forest in the year 2000. Total gross forest cover loss from 2000 to 2011 equaled 2.44% (SE = 0.16%) of the humid tropical forest biome area. Forest loss comprised 1.32% (SE = 0.37%) of primary forest area and 9.08% (SE = 4.04%) of secondary forest area. Validation confirmed a high accuracy of the Landsat-based forest cover loss map, with a producer’s accuracy of 75.4% and user’s accuracy of 92.2%. The majority of forest loss was due to clearing (92%) with the rest attributed to natural processes (flooding, fires, and windstorms). The implemented Landsat data processing and classification system may be used for operational annual forest cover loss updates at the national level for REDD

  20. National satellite-based humid tropical forest change assessment in Peru in support of REDD+ implementation

    International Nuclear Information System (INIS)

    Potapov, P V; Dempewolf, J; Talero, Y; Hansen, M C; Stehman, S V; Vargas, C; Rojas, E J; Calderón, A; Giudice, R; Malaga, N; Zutta, B R; Castillo, D; Mendoza, E

    2014-01-01

    Transparent, consistent, and accurate national forest monitoring is required for successful implementation of reducing emissions from deforestation and forest degradation (REDD+) programs. Collecting baseline information on forest extent and rates of forest loss is a first step for national forest monitoring in support of REDD+. Peru, with the second largest extent of Amazon basin rainforest, has made significant progress in advancing its forest monitoring capabilities. We present a national-scale humid tropical forest cover loss map derived by the Ministry of Environment REDD+ team in Peru. The map quantifies forest loss from 2000 to 2011 within the Peruvian portion of the Amazon basin using a rapid, semi-automated approach. The available archive of Landsat imagery (11 654 scenes) was processed and employed for change detection to obtain annual gross forest cover loss maps. A stratified sampling design and a combination of Landsat (30 m) and RapidEye (5 m) imagery as reference data were used to estimate the primary forest cover area, total gross forest cover loss area, proportion of primary forest clearing, and to validate the Landsat-based map. Sample-based estimates showed that 92.63% (SE = 2.16%) of the humid tropical forest biome area within the country was covered by primary forest in the year 2000. Total gross forest cover loss from 2000 to 2011 equaled 2.44% (SE = 0.16%) of the humid tropical forest biome area. Forest loss comprised 1.32% (SE = 0.37%) of primary forest area and 9.08% (SE = 4.04%) of secondary forest area. Validation confirmed a high accuracy of the Landsat-based forest cover loss map, with a producer’s accuracy of 75.4% and user’s accuracy of 92.2%. The majority of forest loss was due to clearing (92%) with the rest attributed to natural processes (flooding, fires, and windstorms). The implemented Landsat data processing and classification system may be used for operational annual forest cover loss updates at the national level

  1. Validation of near infrared satellite based algorithms to relative atmospheric water vapour content over land

    International Nuclear Information System (INIS)

    Serpolla, A.; Bonafoni, S.; Basili, P.; Biondi, R.; Arino, O.

    2009-01-01

    This paper presents the validation results of ENVISAT MERIS and TERRA MODIS retrieval algorithms for atmospheric Water Vapour Content (WVC) estimation in clear sky condition on land. The MERIS algorithms exploits the radiance ratio of the absorbing channel at 900 nm with the almost absorption-free reference at 890 nm, while the MODIS one is based on the ratio of measurements centred at near 0.905, 0.936, and 0.94 μm with atmospheric window reflectance at 0.865 and 1.24 μm. The first test was performed in the Mediterranean area using WVC provided from both ECMWF and AERONET. As a second step, the performances of the algorithms were tested exploiting WVC computed from radio sounding (RAOBs)in the North East Australia. The different comparisons with respect to reference WVC values showed an overestimation of WVC by MODIS (root mean square error percentage greater than 20%) and an acceptable performance of MERIS algorithms (root mean square error percentage around 10%) [it

  2. 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.

  3. Satellite-based Analysis of CO Variability over the Amazon Basin

    Science.gov (United States)

    Deeter, M. N.; Emmons, L. K.; Martinez-Alonso, S.; Tilmes, S.; Wiedinmyer, C.

    2017-12-01

    Pyrogenic emissions from the Amazon Basin exert significant influence on both climate and air quality but are highly variable from year to year. The ability of models to simulate the impact of biomass burning emissions on downstream atmospheric concentrations depends on (1) the quality of surface flux estimates (i.e., emissions inventories), (2) model dynamics (e.g., horizontal winds, large-scale convection and mixing) and (3) the representation of atmospheric chemical processes. With an atmospheric lifetime of a few months, carbon monoxide (CO) is a commonly used diagnostic for biomass burning. CO products are available from several satellite instruments and allow analyses of CO variability over extended regions such as the Amazon Basin with useful spatial and temporal sampling characteristics. The MOPITT ('Measurements of Pollution in the Troposphere') instrument was launched on the NASA Terra platform near the end of 1999 and is still operational. MOPITT is uniquely capable of measuring tropospheric CO concentrations using both thermal-infrared and near-infrared observations, resulting in the ability to independently retrieve lower- and upper-troposphere CO concentrations. We exploit the 18-year MOPITT record and related datasets to analyze the variability of CO over the Amazon Basin and evaluate simulations performed with the CAM-chem chemical transport model. We demonstrate that observed differences between MOPITT observations and model simulations provide important clues regarding emissions inventories, convective mixing and long-range transport.

  4. Satellite-based studies of maize yield spatial variations and their causes in China

    Science.gov (United States)

    Zhao, Y.

    2013-12-01

    Maize production in China has been expanding significantly in the past two decades, but yield has become relatively stagnant in the past few years, and needs to be improved to meet increasing demand. Multiple studies found that the gap between potential and actual yield of maize is as large as 40% to 60% of yield potential. Although a few major causes of yield gap have been qualitatively identified with surveys, there has not been spatial analysis aimed at quantifying relative importance of specific biophysical and socio-economic causes, information which would be useful for targeting interventions. This study analyzes the causes of yield variation at field and village level in Quzhou county of North China Plain (NCP). We combine remote sensing and crop modeling to estimate yields in 2009-2012, and identify fields that are consistently high or low yielding. To establish the relationship between yield and potential factors, we gather data on those factors through a household survey. We select targeted survey fields such that not only both extremes of yield distribution but also all soil texture categories in the county is covered. Our survey assesses management and biophysical factors as well as social factors such as farmers' access to agronomic knowledge, which is approximated by distance to the closest demonstration plot or 'Science and technology backyard'. Our survey covers 10 townships, 53 villages and 180 fields. Three to ten farmers are surveyed depending on the amount of variation present among sub pixels of each field. According to survey results, we extract the amount of variation within as well as between villages and or soil type. The higher within village or within field variation, the higher importance of management factors. Factors such as soil type and access to knowledge are more represented by between village variation. Through regression and analysis of variance, we gain more quantitative and thorough understanding of causes to yield variation at

  5. Assessment of the most recent satellite based digital elevation models of Egypt

    Science.gov (United States)

    Rabah, Mostafa; El-Hattab, Ahmed; Abdallah, Mohamed

    2017-12-01

    Digital Elevation Model (DEM) is crucial to a wide range of surveying and civil engineering applications worldwide. Some of the DEMs such as ASTER, SRTM1 and SRTM3 are freely available open source products. In order to evaluate the three DEMs, the contribution of EGM96 are removed and all DEMs heights are becoming ellipsoidal height. This step was done to avoid the errors occurred due to EGM96. 601 points of observed ellipsoidal heights compared with the three DEMs, the results show that the SRTM1 is the most accurate one, that produces mean height difference and standard deviations equal 2.89 and ±8.65 m respectively. In order to increase the accuracy of SRTM1 in EGYPT, a precise Global Geopotential Model (GGM) is needed to convert the SRTM1 ellipsoidal height to orthometric height, so that, we quantify the precision of most-recent released GGM (five models). The results show that, the GECO model is the best fit global models over Egypt, which produces a standard deviation of geoid undulation differences equals ±0.42 m over observed 17 HARN GPS/leveling stations. To confirm an enhanced DEM in EGYPT, the two orthometric height models (SRTM1 ellipsoidal height + EGM96) and (SRTM1 ellipsoidal height + GECO) are assessment with 17 GPS/leveling stations and 112 orthometric height stations, the results show that the estimated height differences between the SRTM1 before improvements and the enhanced model are at rate of 0.44 m and 0.06 m respectively.

  6. Intercomparison of IPCC AR4 models with ERA-40 and NCEP/NCAR reanalysis within the AFRICA-CORDEX domain

    Science.gov (United States)

    León, M.; González, Y.; Díaz, J. P.; Expósito, F. J.; Pérez, J. C.; González, A.

    2012-04-01

    One of the most useful techniques to obtain regional climate projections along the XXI century is to run a mesoscale model driven by coarse input data (initial and boundaries conditions) obtained from Atmosphere-Ocean coupled Global Circulation Models (AOGCM). This is the dynamical downscaling approach. To correctly configure the dynamical downscaling approach it is necessary to choose the correct input dataset that project the climatic situation in a more accurate way and to establish a boundary to the errors in the results associated to these input data. In this study, we consider that the agreement of models with present observations is a way to assign confidence to the quality of a model. With this aim we intercompare the surface temperature of 21 IPCC AR4 runs models with the results from the reanalysis databases ERA40 and NCEP/NCAR in the CORDEX-AFRICA domain in the period 1961-2000. Thus, we have studied the seasonal cycles of the four decades of this period in addition to the probability density functions (PDFs) of the IPCC models. The statistical study allows us to classify the IPCC AR4 models according to their discrepancies with reanalysis data for the CORDEX domain. In general, the MRI CGCM 2.3.2 IPCC AR4 model presents the best fits compared with the reanalysis databases regarding to the correlation factor, root mean square (rms) and PDF skill score. For the intercomparison with ERA-40, the percentage of points with rms lower than 2°C is over 80%, for the four decades; with 89% of the points showing correlations coefficients larger than 0.80 and a 76 % of the data presents skill-scores values, based on the common areas of the PDFs, above a threshold of 0.7. Acknowledgements The authors acknowledge to the MEC (Ministry of Education and Science, Spain) for the next supports: projects CGL2007-66477-C02-02/CLI, CGL2008-04740/CLI, CGL2010-21366-C04-01 and UNLL08-3E-007.

  7. 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

  8. Evaluation of ERA-Interim, MERRA, NCEP-DOE R2 and CFSR Reanalysis precipitation Data using Gauge Observation over Ethiopia for a period of 33 years

    Directory of Open Access Journals (Sweden)

    Tewodros Woldemariam Tesfaye

    2017-09-01

    Full Text Available The vital demand of reliable climatic and hydrologic data of fine spatial and temporal resolution triggered the employment of reanalysis datasets as a surrogate in most of the hydrological modelling exercises. This study examines the performance of four widely used reanalysis datasets: ERA-Interim, NCEP-DOE R2, MERRA and CFSR, in reproducing the spatio-temporal characteristics of observed daily precipitation of different stations spread across Ethiopia, East Africa. The appropriateness of relying on reanalysis datasets for hydrologic modelling, climate change impact assessment and regional modelling studies is assessed using various statistical and non-parametric techniques. ERA-Interim is found to exhibit higher correlation and least root mean square error values with observed daily rainfall, which is followed by CFSR and MERRA in most of the stations. The variability of daily precipitation is better captured by ERA, CFSR and MERRA, while NCEP-DOE R2 overestimated the spread of the precipitation data. While ERA overestimates the probability of moderate rainfall, it is seemingly better in capturing the probability of low rainfall. CFSR captures the overall distribution reasonable well. NCEP-DOE R2 appears to be outperforming others in capturing the probabilities of higher magnitude rainfall. Climatological seasonal cycle and the characteristics of wet and dry spells are compared further, where ERA seemingly replicates the pattern more effectively. However, observed rainfall exhibits higher frequency of short wet spells when compared to that of any reanalysis datasets. MERRA relatively underperforms in simulating the wet spell characteristics of observed daily rainfall. CFSR overestimates the mean wet spell length and mean dry spell length. Spatial trend analysis indicates that the northern and central western Ethiopia show increasing trends, whereas the Central and Eastern Ethiopia as well as the Southern Ethiopia stations show either no trend

  9. Absorbing Aerosols Above Cloud: Detection, Quantitative Retrieval, and Radiative Forcing from Satellite-based Passive Sensors

    Science.gov (United States)

    Jethva, H.; Torres, O.; Remer, L. A.; Bhartia, P. K.

    2012-12-01

    , respectively. This study constitutes the first attempt to use non-polarized and non-lidar reflectance observations-both of them shown to have above-cloud aerosols retrieval capability, to retrieve above-cloud AOT by a passive non-polarized sensor. The uncertainty analysis suggests that the present method should retrieve above-cloud AOT within -10% to 50% which mainly arises due to uncertainty associated with the single-scattering albedo assumption. Although, currently tested by making use of OMI and MODIS measurements, the present color ratio method can be equally applied to the other satellite measurements that carry similar or near-by channels in VIS region of the spectrum such as MISR and NPP/VIIRS. The capability of quantifying the above-cloud aerosol load will facilitate several aspects of cloud-aerosol interaction research such as estimation of the direct radiative forcing of aerosols above clouds; the sign of which can be opposite (warming) to cloud-free aerosol forcing (cooling), aerosol transport, indirect effects of aerosols on clouds, and hydrological cycle.

  10. An Intercomparison of Vegetation Products from Satellite-based Observations used for Soil Moisture Retrievals

    Science.gov (United States)

    Vreugdenhil, Mariette; de Jeu, Richard; Wagner, Wolfgang; Dorigo, Wouter; Hahn, Sebastian; Bloeschl, Guenter

    2013-04-01

    Vegetation and its water content affect active and passive microwave soil moisture retrievals and need to be taken into account in such retrieval methodologies. This study compares the vegetation parameterisation that is used in the TU-Wien soil moisture retrieval algorithm to other vegetation products, such as the Vegetation Optical Depth (VOD), Net Primary Production (NPP) and Leaf Area Index (LAI). When only considering the retrieval algorithm for active microwaves, which was developed by the TU-Wien, the effect of vegetation on the backscattering coefficient is described by the so-called slope [1]. The slope is the first derivative of the backscattering coefficient in relation to the incidence angle. Soil surface backscatter normally decreases quite rapidly with the incidence angle over bare or sparsely vegetated soils, whereas the contribution of dense vegetation is fairly uniform over a large range of incidence angles. Consequently, the slope becomes less steep with increasing vegetation. Because the slope is a derivate of noisy backscatter measurements, it is characterised by an even higher level of noise. Therefore, it is averaged over several years assuming that the state of the vegetation doesn't change inter-annually. The slope is compared to three dynamic vegetation products over Australia, the VOD, NPP and LAI. The VOD was retrieved from AMSR-E passive microwave data using the VUA-NASA retrieval algorithm and provides information on vegetation with a global coverage of approximately every two days [2]. LAI is defined as half the developed area of photosynthetically active elements of the vegetation per unit horizontal ground area. In this study LAI is used from the Geoland2 products derived from SPOT Vegetation*. The NPP is the net rate at which plants build up carbon through photosynthesis and is a model-based estimate from the BiosEquil model [3, 4]. Results show that VOD and slope correspond reasonably well over vegetated areas, whereas in arid

  11. 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 PM 2.5 using data from Taipei metropolis, which exhibits typical Asian city characteristics. Annual average PM 2.5 concentrations from 2006 to 2012 of 17 air quality monitoring stations established by Environmental Protection Administration of Taiwan were used for model development. PM 2.5 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 PM 2.5 while temples (r: 0.52 to 0.66) and Chinese restaurants (r: 0.31 to 0.44) were positively correlated to PM 2.5 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 PM 2.5 variation and was the dominant variable in the developed model. We suggest future studies

  12. Demonstrating the Value of Near Real-time Satellite-based Earth Observations in a Research and Education Framework

    Science.gov (United States)

    Chiu, L.; Hao, X.; Kinter, J. L.; Stearn, G.; Aliani, M.

    2017-12-01

    The launch of GOES-16 series provides an opportunity to advance near real-time applications in natural hazard detection, monitoring and warning. This study demonstrates the capability and values of receiving real-time satellite-based Earth observations over a fast terrestrial networks and processing high-resolution remote sensing data in a university environment. The demonstration system includes 4 components: 1) Near real-time data receiving and processing; 2) data analysis and visualization; 3) event detection and monitoring; and 4) information dissemination. Various tools are developed and integrated to receive and process GRB data in near real-time, produce images and value-added data products, and detect and monitor extreme weather events such as hurricane, fire, flooding, fog, lightning, etc. A web-based application system is developed to disseminate near-real satellite images and data products. The images are generated with GIS-compatible format (GeoTIFF) to enable convenient use and integration in various GIS platforms. This study enhances the capacities for undergraduate and graduate education in Earth system and climate sciences, and related applications to understand the basic principles and technology in real-time applications with remote sensing measurements. It also provides an integrated platform for near real-time monitoring of extreme weather events, which are helpful for various user communities.

  13. A comparision between satellite based and drone based remote sensing technology to achieve sustainable development: a review

    Directory of Open Access Journals (Sweden)

    Babankumar Bansod

    2017-12-01

    Full Text Available Precision agriculture is a way to manage the crop yield resources like water, fertilizers, soil, seeds in order to increase production, quality, gain and reduce squander products so that the existing system become eco-friendly. The main target of precision agriculture is to match resources and execution according to the crop and climate to ameliorate the effects of Praxis. Global Positioning System, Geographic Information System, Remote sensing technologies and various sensors are used in Precision farming for identifying the variability in field and using different methods to deal with them. Satellite based remote sensing is used to study the variability in crop and ground but suffer from various disadvantageous such as prohibited use, high price, less revisiting them, poor resolution due to great height, Unmanned Aerial Vehicle (UAV is other alternative option for application in precision farming. UAV overcomes the drawback of the ground based system, i.e. inaccessibility to muddy and very dense regions. Hovering at a peak of 500 meter - 1000 meter is good enough to offer various advantageous in image acquisition such as high spatial and temporal resolution, full flexibility, low cost. Recent studies of application of UAV in precision farming indicate advanced designing of UAV, enhancement in georeferencing and the mosaicking of image, analysis and extraction of information required for supplying a true end product to farmers. This paper also discusses the various platforms of UAV used in farming applications, its technical constraints, seclusion rites, reliability and safety.

  14. Strategic system development toward biofuel, desertification, and crop production monitoring in continental scales using satellite-based photosynthesis models

    Science.gov (United States)

    Kaneko, Daijiro

    2013-10-01

    The author regards fundamental root functions as underpinning photosynthesis activities by vegetation and as affecting environmental issues, grain production, and desertification. This paper describes the present development of monitoring and near real-time forecasting of environmental projects and crop production by approaching established operational monitoring step-by-step. The author has been developing a thematic monitoring structure (named RSEM system) which stands on satellite-based photosynthesis models over several continents for operational supports in environmental fields mentioned above. Validation methods stand not on FLUXNET but on carbon partitioning validation (CPV). The models demand continuing parameterization. The entire frame system has been built using Reanalysis meteorological data, but model accuracy remains insufficient except for that of paddy rice. The author shall accomplish the system that incorporates global environmental forces. Regarding crop production applications, industrialization in developing countries achieved through direct investment by economically developed nations raises their income, resulting in increased food demand. Last year, China began to import rice as it had in the past with grains of maize, wheat, and soybeans. Important agro-potential countries make efforts to cultivate new crop lands in South America, Africa, and Eastern Europe. Trends toward less food sustainability and stability are continuing, with exacerbation by rapid social and climate changes. Operational monitoring of carbon sequestration by herbaceous and bore plants converges with efforts at bio-energy, crop production monitoring, and socio-environmental projects such as CDM A/R, combating desertification, and bio-diversity.

  15. A study on spectral energy for the end of the twentieth century the basis of the NCEP reanalysis-II

    Science.gov (United States)

    Aranha, A. F.; Veiga, J. A.; Yoshida, M. C.

    2013-05-01

    The energy cycle proposed by Lorenz (1955) is composed of the behavior of the average energy from the atmosphere and characteristics of atmospheric energy deviations from this average, respectively called basic state and perturbed state. However, it is possible to discretize the energy contained in the atmosphere disturbed state, decomposing the fields of the various disturbances or harmonics wave type, so as to measure and analyze the energy of these disorders according to their number or wavelength, this methodology described second Saltzman (1957). Therefore, in view of the spectral analysis as a methodological basis, this work aims to study the energy contained by the atmosphere in disturbed state. Considering the terms of power generation potential available for nth waves due to diabatic heating, represented by (G(n)), potential energy of nth wave (P(n)) and kinetic energy of nth wave (K(n)) and the conversion of energy between the energy nth kinetic and potential energy of waves nth waves given by (C(n)). The variables used in the calculation of the terms above are, temperature (T) orthogonal components of the wind (u, v, w) and geopotential height (G) from a data set from the National Center for Environmental Prediction (NCEP) considering daily shared values on a regular grid with a spatial resolution of 2.5° × 2.5°, distributed in 12 pressure levels (1000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100 hPa ) for the 1970 to 1999 period. The results show that for kinetic energy of disturbance to nth wave, the amount of energy is somewhat dammed during for the first 10 wave numbers in this range are the planetary waves and waves. Observing this way, we can conclude that these waves are responsible for much of the kinetic energy in disturbed state. A characteristic and a difference in the distribution of energy between kinetic energy and potential energy disturbed total available to disturbance, is the derivative of the energy wavenumber presented by

  16. 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

  17. 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.

  18. 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.

  19. Comparison of Different Machine Learning Approaches for Monthly Satellite-Based Soil Moisture Downscaling over Northeast China

    Directory of Open Access Journals (Sweden)

    Yangxiaoyue Liu

    2017-12-01

    Full Text Available Although numerous satellite-based soil moisture (SM products can provide spatiotemporally continuous worldwide datasets, they can hardly be employed in characterizing fine-grained regional land surface processes, owing to their coarse spatial resolution. In this study, we proposed a machine-learning-based method to enhance SM spatial accuracy and improve the availability of SM data. Four machine learning algorithms, including classification and regression trees (CART, K-nearest neighbors (KNN, Bayesian (BAYE, and random forests (RF, were implemented to downscale the monthly European Space Agency Climate Change Initiative (ESA CCI SM product from 25-km to 1-km spatial resolution. During the regression, the land surface temperature (including daytime temperature, nighttime temperature, and diurnal fluctuation temperature, normalized difference vegetation index, surface reflections (red band, blue band, NIR band and MIR band, and digital elevation model were taken as explanatory variables to produce fine spatial resolution SM. We chose Northeast China as the study area and acquired corresponding SM data from 2003 to 2012 in unfrozen seasons. The reconstructed SM datasets were validated against in-situ measurements. The results showed that the RF-downscaled results had superior matching performance to both ESA CCI SM and in-situ measurements, and can positively respond to precipitation variation. Additionally, the RF was less affected by parameters, which revealed its robustness. Both CART and KNN ranked second. Compared to KNN, CART had a relatively close correlation with the validation data, but KNN showed preferable precision. Moreover, BAYE ranked last with significantly abnormal regression values.

  20. Spatial pattern recognition of extreme temperature climatology: assessing HadCM3 simulations via NCEP reanalyses over Europe Análise do padrão espacial da climatologia de temperaturas extremas: avaliando simulações do HadCM3 via reanálises do NCEP para a Europa

    Directory of Open Access Journals (Sweden)

    P. S. Lucio

    2007-08-01

    Full Text Available This article attempts to quantify the spatial uncertainties associated with extreme temperature’s response, by assessing data derived from climate model. This is undertaken by a comparison of the spatial pattern of a long-term time-series aggregation (1960/61-1989/90 for extreme temperatures simulated by a particular GCM (the UK Met Office - Hadley Centre climate model, HadCM3 to that of the USA NCAR NCEP Reanalyses, which are considered as ‘truth’, over the MICE (Modelling the Impacts of Climate Extremes - EU Project spatial domain. Since evaluation of models is crucial to assessing future scenarios, the aim of this study is to investigate whether the extreme values predicted by the HadCM3 climate model can simulate those produced by NCEP Reanalyses, assuming that the extremes of both models are realizations of the same spatial stochastic process. To get more useful information about the uncertainties surrounding spatial climate projection, one also has to analyze the pattern of temperature extremes in terms of their anomalies. A common technical issue in the assessment of numerical spatial models is based on the Principal Components Analysis and Bayesian Classification for spatial pattern recognition. These methodologies are very important and useful for guiding an evolutionary statistical model-building process. This study leads to the conclusion that the HadCM3 Simulations do not realistically reproduce the NCEP Reanalyses, despite the fact that the climatology of extremes has demonstrated very similar spatial patterns. It is likely therefore that such instability may persist in the future.Este artigo é um ensaio na quantificação de incertezas espaciais associadas à resposta de temperaturas extremas, avaliando dados derivados de um determinado modelo de clima. Isto é empreendido por uma comparação entre o padrão espacial de séries temporais agregadas de longo termo (1960/61-1989/90 para temperaturas extremas simuladas de um

  1. A COMPARATIVE STUDY ON SPECTRAL ENERGETICS BETWEEN THE NCEP reanalysisII in current climate AND MODEL ECHAM5 in future scenarios

    Science.gov (United States)

    Aranha, A. F.; Veiga, J. P.

    2013-12-01

    Saltzman (1957) starting Lorenz Cycle (1955) derived a set of equations that show the energy contained in the basic state and the disturbed atmosphere, decomposing in various fields disturbance wave type, so as to quantify and analyze the energy of these disorders according to their number or wavelength. Based on the methodology Saltzman, this paper aims a comparative study between the energy of the disturbed state between the NCEP reanalysis-II for the current weather conditions and model ECHAM5 scenarios for future conditions of increased concentration of greenhouse gases (RCP26, RCP45 and RCP85), considering the terms of the generation of available potential energy to nth wave due to diabatic heating, represented by (Gn), the potential energy of nth wave (Pn) and kinetic energy of nth wave (Kn), as well as the conversion of energy between kinetic energy and potential energy nth wave of nth wave, given by (Cn). Two data sets were used in the calculation of the aforementioned terms. For the data set of NCEP and ECHAM5 were used variables, temperature (T), orthogonal wind components (u, v, w) and geopotential height (L), considering daily shared values on a regular grid with spatial resolutions of 2,5 x 2.5 and 1.875 x 1.875 graus, distributed on 12 and 15 levels of pressure (1000.0, 925.0, 850.0, 700.0, 600.0, 500.0, 400.0, 300.0, 250.0, 200.0, 150.0, 100.0 hPa), (1000.0, 850.0, 700.0, 500.0, 250.0, 150.0, 100.0, 70.0, 50.0, 30.0, 10.0, 3.0, 1.0, 0.3, 0.1 hPa) for the period of 1979-1999 and 2090-2100, respectively. The results show that most of the kinetic energy of disturbance to nth waves is concentrated in the first 15 wave numbers, both for the weather-NCEP II as to ECHAM5, having more significant increase in the profile and having a RCP85 energy cascade. This increase in kinetic energy was expected due to the increased energy in the system. For Pn, increasing the potential energy is also expected in view of the increased diabatic heating, but the energy jump

  2. AIM satellite-based research bridges the unique scientific aspects of the mission to informal education programs globally

    Science.gov (United States)

    Robinson, D.; Maggi, B.

    2003-04-01

    The Education and Public Outreach (EPO) component of the satellite-based research mission "Aeronomy of Ice In the Mesosphere" (AIM) will bridge the unique scientific aspects of the mission to informal education organizations. The informal education materials developed by the EPO will utilize AIM data and educate the public about the environmental implications associated with the data. This will assist with creating a scientifically literate workforce and in developing a citizenry capable of making educated decisions related to environmental policies and laws. The objective of the AIM mission is to understand the mechanisms that cause Polar Mesospheric Clouds (PMCs) to form, how their presence affects the atmosphere, and how change in the atmosphere affects them. PMCs are sometimes known as Noctilucent Clouds (NLCs) because of their visibility during the night from appropriate locations. The phenomenon of PMCs is an observable indicator of global change, a concern to all citizens. Recent sightings of these clouds over populated regions have compelled AIM educators to expand informal education opportunities to communities worldwide. Collaborations with informal organizations include: Museums/Science Centers; NASA Sun-Earth Connection Forum; Alaska Native Ways of Knowing Project; Amateur Noctilucent Cloud Observers Organization; National Parks Education Programs; After School Science Clubs; Public Broadcasting Associations; and National Public Radio. The Native Ways of Knowing Project is an excellent example of informal collaboration with the AIM EPO. This Alaska based project will assist native peoples of the state with photographing NLCs for the EPO website. It will also aid the EPO with developing materials for informal organizations that incorporate traditional native knowledge and science, related to the sky. Another AIM collaboration that will offer citizens lasting informal education opportunities is the one established with the United States National Parks

  3. Satellite-Based Evaluation of the Post-Fire Recovery Process from the Worst Forest Fire Case in South Korea

    Directory of Open Access Journals (Sweden)

    Jae-Hyun Ryu

    2018-06-01

    different, using only one satellite-based indicator will not be suitable to understand the post-fire recovery process. NBR, NDVI, and GPP can be combined. Further studies will require more approaches using various terms of indices.

  4. Ground and satellite-based remote sensing of mineral dust using AERI spectra and MODIS thermal infrared window brightness temperatures

    Science.gov (United States)

    Hansell, Richard Allen, Jr.

    The radiative effects of dust aerosol on our climate system have yet to be fully understood and remain a topic of contemporary research. To investigate these effects, detection/retrieval methods for dust events over major dust outbreak and transport areas have been developed using satellite and ground-based approaches. To this end, both the shortwave and longwave surface radiative forcing of dust aerosol were investigated. The ground-based remote sensing approach uses the Atmospheric Emitted Radiance Interferometer brightness temperature spectra to detect mineral dust events and to retrieve their properties. Taking advantage of the high spectral resolution of the AERI instrument, absorptive differences in prescribed thermal IR window sub-band channels were exploited to differentiate dust from cirrus clouds. AERI data collected during the UAE2 at Al-Ain UAE was employed for dust retrieval. Assuming a specified dust composition model a priori and using the light scattering programs of T-matrix and the finite difference time domain methods for oblate spheroids and hexagonal plates, respectively, dust optical depths have been retrieved and compared to those inferred from a collocated and coincident AERONET sun-photometer dataset. The retrieved optical depths were then used to determine the dust longwave surface forcing during the UAE2. Likewise, dust shortwave surface forcing is investigated employing a differential technique from previous field studies. The satellite-based approach uses MODIS thermal infrared brightness temperature window data for the simultaneous detection/separation of mineral dust and cirrus clouds. Based on the spectral variability of dust emissivity at the 3.75, 8.6, 11 and 12 mum wavelengths, the D*-parameter, BTD-slope and BTD3-11 tests are combined to identify dust and cirrus. MODIS data for the three dust-laden scenes have been analyzed to demonstrate the effectiveness of this detection/separation method. Detected daytime dust and cloud

  5. ¿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.

  6. 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 .g. West Africa, South America), bio- fuel use (e.g. south Asia), monsoonal conditions (e.g. West Africa, Southeast Asia), and mineral dust (e.g. West Africa, Middle East). Exact site placement depends on specific part- nerships and the availability.... Meas. Tech., 8, 505–521, 2015 www.atmos-meas-tech.net/8/505/2015/ G. Snider et al.: SPARTAN 511 filter mass (PM2.5,dry,9 d): PM2.5,dry−1 h = PM2.5,dry,9 d bsp,dry−1 h bsp,dry,9 d . (2) The “dry” subscript refers to the low humidity conditions at which...

  7. Seasonal to Interannual Variability of Satellite-Based Precipitation Estimates in the Pacific Ocean Associated with ENSO from 1998 to 2014

    Directory of Open Access Journals (Sweden)

    Xueyan Hou

    2016-10-01

    Full Text Available Based on a widely used satellite precipitation product (TRMM Multi-satellite Precipitation Analysis 3B43, we analyzed the spatiotemporal variability of precipitation over the Pacific Ocean for 1998–2014 at seasonal and interannual timescales, separately, using the conventional empirical orthogonal function (EOF and investigated the seasonal patterns associated with El Niño–Southern Oscillation (ENSO cycles using season-reliant empirical orthogonal function (SEOF analysis. Lagged correlation analysis was also applied to derive the lead/lag correlations of the first two SEOF modes for precipitation with Pacific Decadal Oscillation (PDO and two types of El Niño, i.e., central Pacific (CP El Niño and eastern Pacific (EP El Niño. We found that: (1 The first two seasonal EOF modes for precipitation represent the annual cycle of precipitation variations for the Pacific Ocean and the first interannual EOF mode shows the spatiotemporal variability associated with ENSO; (2 The first SEOF mode for precipitation is simultaneously associated with the development of El Niño and most likely coincides with CP El Niño. The second SEOF mode lagged behind ENSO by one year and is associated with post-El Niño years. PDO modulates precipitation variability significantly only when ENSO occurs by strengthening and prolonging the impacts of ENSO; (3 Seasonally evolving patterns of the first two SEOF modes represent the consecutive precipitation patterns associated with the entire development of EP El Niño and the following recovery year. The most significant variation occurs over the tropical Pacific, especially in the Intertropical Convergence Zone (ITCZ and South Pacific Convergence Zone (SPCZ; (4 Dry conditions in the western basin of the warm pool and wet conditions along the ITCZ and SPCZ bands during the mature phase of El Niño are associated with warm sea surface temperatures in the central tropical Pacific, and a subtropical anticyclone dominating over the northwestern Pacific. These findings may be useful for prediction of seasonal precipitation anomalies over the Pacific Ocean during El Niño years and recovery years.

  8. Education and Public Outreach for the PICASSO-CENA Satellite-Based Research Mission: K-12 Students Use Sun Photometers to Assist Scientists in Validating Atmospheric Data

    Science.gov (United States)

    Robinson, D. Q.

    2001-05-01

    Hampton University, a historically black university, is leading the Education and Public Outreach (EPO) portion of the PICASSO-CENA satellite-based research mission. Currently scheduled for launch in 2004, PICASSO-CENA will use LIDAR (LIght Detection and Ranging), to study earth's atmosphere. The PICASSO-CENA Outreach program works with scientists, teachers, and students to better understand the effects of clouds and aerosols on earth's atmosphere. This program actively involves students nationwide in NASA research by having them obtain sun photometer measurements from their schools and homes for comparison with data collected by the PICASSO-CENA mission. Students collect data from their classroom ground observations and report the data via the Internet. Scientists will use the data from the PICASSO-CENA research and the student ground-truthing observations to improve predications about climatic change. The two-band passive remote sensing sun photometer is designed for student use as a stand alone instrument to study atmospheric turbidity or in conjunction with satellite data to provide ground-truthing. The instrument will collect measurements of column optical depth from the ground level. These measurements will not only give the students an appreciation for atmospheric turbidity, but will also provide quantitative correlative information to the PICASSO-CENA mission on ground-level optical depth. Student data obtained in this manner will be sufficiently accurate for scientists to use as ground truthing. Thus, students will have the opportunity to be involved with a NASA satellite-based research mission.

  9. Combining tower mixing ratio and community model data to estimate regional-scale net ecosystem carbon exchange by boundary layer inversion over four flux towers in the United States

    Science.gov (United States)

    Xueri Dang; Chun-Ta Lai; David Y. Hollinger; Andrew J. Schauer; Jingfeng Xiao; J. William Munger; Clenton Owensby; James R. Ehleringer

    2011-01-01

    We evaluated an idealized boundary layer (BL) model with simple parameterizations using vertical transport information from community model outputs (NCAR/NCEP Reanalysis and ECMWF Interim Analysis) to estimate regional-scale net CO2 fluxes from 2002 to 2007 at three forest and one grassland flux sites in the United States. The BL modeling...

  10. Satellite-based monitoring of cyanobacteria blooms from 2002–2011 for 11 reservoirs with watersheds along an agricultural gradient

    Science.gov (United States)

    Imagery acquired by the Envisat Medium Resolution Imaging Spectrometer from 2002-2011 was used to estimate cyanobacteria cell densities for 11 reservoirs in Indiana, Ohio, and Kentucky, USA (surface areas 8–43 km2; 864 total images spanning May–September). This initia...

  11. Assessment of Export Efficiency Equations in the Southern Ocean Applied to Satellite-Based Net Primary Production

    Science.gov (United States)

    Arteaga, Lionel; Haëntjens, Nils; Boss, Emmanuel; Johnson, Kenneth S.; Sarmiento, Jorge L.

    2018-04-01

    Carbon export efficiency (e-ratio) is defined as the fraction of organic carbon fixed through net primary production (NPP) that is exported out of the surface productive layer of the ocean. Recent observations for the Southern Ocean suggest a negative e-ratio versus NPP relationship, and a reduced dependency of export efficiency on temperature, different than in the global domain. In this study, we complement information from a passive satellite sensor with novel space-based lidar observations of ocean particulate backscattering to infer NPP over the entire annual cycle, and estimate Southern Ocean export rates from five different empirical models of export efficiency. Inferred Southern Ocean NPP falls within the range of previous studies, with a mean estimate of 15.8 (± 3.9) Pg C yr-1 for the region south of 30°S during the 2005-2016 period. We find that an export efficiency model that accounts for silica(Si)-ballasting, which is constrained by observations with a negative e-ratio versus NPP relationship, shows the best agreement with in situ-based estimates of annual net community production (annual export of 2.7 ± 0.6 Pg C yr-1 south of 30°S). By contrast, models based on the analysis of global observations with a positive e-ratio versus NPP relationship predict annually integrated export rates that are ˜ 33% higher than the Si-dependent model. Our results suggest that accounting for Si-induced ballasting is important for the estimation of carbon export in the Southern Ocean.

  12. A comparison of explosive cyclone characteristics in recent reanalyses: NCEP CFSR, JRA-55, and ERA-Interim

    Science.gov (United States)

    Kita, Y.; Waseda, T.

    2016-12-01

    Explosive cyclones (EXPCs) were investigated in three recent reanalyses. Their tracking methods is diverse among researchers, and additionally reanalysis data they use are various. Reanalysis data are essential as initial conditions to implement a downscale simulation with high accuracy. In this study, characteristics of EXPCs in three recent reanalyses were investigated from several perspectives: track densities, minimum MSLP (Mean Sea Level Pressure), and radius of EXPCs. The tracking method of extratropical cyclones (ECs) is to track local minimum of MSLP. The domain is limited to Eastern Asia and the North Pacific Ocean (lat20°:70°, lon100°:200°), and target period is 2000-2014. Fig.1 shows that the frequencies of EXPCs, which is defined as ECs whose MSLP drops by over 12hPa in 12hours, are greatly different, noting that extracted EXPCs are those whose most deepening phases were located around Japan (lat20°:60°, lon110°:160°). In addition, they are dissimilar to those in a previous EXPCs database (Kawamura et al.) and results in weather map analyses. The differences between each frequency might be caused by MSLP at their centers: there were sometimes small gaps of a few hPa. The minimum MSLP and effective radius were also investigated, but distributions of effective radii of EXPCs did not show significant difference (Fig.2). Thus, the gaps of central MSLP just matter in the differences of their trends. To evaluate the path density of EXPCs, two-dimensional kernel density estimation was conducted. The kernel densities of EXPCs' tracks in three reanalyses seem similar: they accumulated apparently above ocean (not shown). Two-dimensional kernel densities of EXPCs' most deepening points accumulated above Sea of Japan, Kuroshio and Extension. Therefore, it is proved that there are considerable differences in numbers of EXPCs depending on reanalyses, while the general characteristics of EXPCs just have little difference. It is worthwhile to say that careful

  13. A Study of Extreme Events in Subseasonal Forecasts Made by a High Resolution Version of the NCEP Climate Forecast System

    Science.gov (United States)

    Saha, S.; Vandendool, H. M.; Johansson, A.; Vintzileos, A.; Pan, H.; Thiaw, C.

    2005-05-01

    Actual estimations of the aerosol effect on the radiation budget are affected by a large uncertainties mainly due to the high inhomogeneity and variability of atmospheric aerosol, in terms of concentration, shape, size distribution, refractive index and vertical distribution. Long-term measurements of vertical profiles of aerosol optical properties are needed to reduce these uncertainties. At CNR-IMAA (40° 36'N, 15° 44' E, 760 m above sea level), a lidar system for aerosol study is operative since May 2000 in the framework of EARLINET (European Aerosol Research Lidar Network). Until August 2005, it provided independent measurements of aerosol extinction and backscatter at 355 nm and aerosol backscatter profiles at 532 nm. After an upgrade of the system, it provides independent measurements of aerosol extinction and backscatter profiles at 355 and 532 nm, and of aerosol backscatter profiles at 1064 nm and depolarization ratio at 532 nm. For these measurements, lidar ratio at 355 and 532 nm and Angstrom exponent profiles at 355/532 nm are also obtained. Starting on May 2000, systematic measurements are performed three times per week according to the EARLINET schedule and further measurements are performed in order to investigate particular events, like dust intrusions, volcanic eruptions and forest fires. A climatological study has been carried out in terms of the seasonal behavior of the PBL height and of the aerosol optical properties calculated inside the PBL itself. In the free troposphere, an high occurrences of Saharan dust intrusions (about 1 day of Saharan dust intrusion every 10 days) has been observed at CNR-IMAA because of the short distance from the Sahara region. During 6 years of observations, very peculiar cases of volcanic aerosol emitted by Etna volcano and aerosol released by large forest fires burning occurred in Alaska and Canada have been observed in the free troposphere at our site. Particular attention is devoted to lidar ratio both for the

  14. Monturaqui meteorite impact crater, Chile: A field test of the utility of satellite-based mapping of ejecta at small craters

    Science.gov (United States)

    Rathbun, K.; Ukstins, I.; Drop, S.

    2017-12-01

    Monturaqui Crater is a small ( 350 m diameter), simple meteorite impact crater located in the Atacama Desert of northern Chile that was emplaced in Ordovician granite overlain by discontinuous Pliocene ignimbrite. Ejecta deposits are granite and ignimbrite, with lesser amounts of dark impact melt and rare tektites and iron shale. The impact restructured existing drainage systems in the area that have subsequently eroded through the ejecta. Satellite-based mapping and modeling, including a synthesis of photographic satellite imagery and ASTER thermal infrared imagery in ArcGIS, were used to construct a basic geological interpretation of the site with special emphasis on understanding ejecta distribution patterns. This was combined with field-based mapping to construct a high-resolution geologic map of the crater and its ejecta blanket and field check the satellite-based geologic interpretation. The satellite- and modeling-based interpretation suggests a well-preserved crater with an intact, heterogeneous ejecta blanket that has been subjected to moderate erosion. In contrast, field mapping shows that the crater has a heavily-eroded rim and ejecta blanket, and the ejecta is more heterogeneous than previously thought. In addition, the erosion rate at Monturaqui is much higher than erosion rates reported elsewhere in the Atacama Desert. The bulk compositions of the target rocks at Monturaqui are similar and the ejecta deposits are highly heterogeneous, so distinguishing between them with remote sensing is less effective than with direct field observations. In particular, the resolution of available imagery for the site is too low to resolve critical details that are readily apparent in the field on the scale of 10s of cm, and which significantly alter the geologic interpretation. The limiting factors for effective remote interpretation at Monturaqui are its target composition and crater size relative to the resolution of the remote sensing methods employed. This

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. Rapid Moment Magnitude Estimation Using Strong Motion Derived Static Displacements

    OpenAIRE

    Muzli, Muzli; Asch, Guenter; Saul, Joachim; Murjaya, Jaya

    2015-01-01

    The static surface deformation can be recovered from strong motion records. Compared to satellite-based measurements such as GPS or InSAR, the advantage of strong motion records is that they have the potential to provide real-time coseismic static displacements. The use of these valuable data was optimized for the moment magnitude estimation. A centroid grid search method was introduced to calculate the moment magnitude by using1 model. The method to data sets was applied of the 2011...

  1. 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.

  2. 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

  3. 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

  4. 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

  5. Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

    Science.gov (United States)

    Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

    2017-12-01

    In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields

  6. 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

  7. Detecting robust signals of interannual variability of gross primary productivity in Asia from multiple terrestrial carbon cycle models and long-term satellite-based vegetation data

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.

    2014-12-01

    Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently

  8. Validation of the space fields and the median zonal of the temperature of the air in surface and of the precipitation in Colombia, simulated by the pattern CCM3 and the data of the NCEP/NCAR Reanalysis

    International Nuclear Information System (INIS)

    Zea Mazo, Jorge Anibal; Leon Aristizabal Gloria Esperanza; Eslava Ramirez, Jesus Antonio

    2001-01-01

    This work presents an analysis of the basic fields of the surface temperature and the precipitation for the national territory, from two sources of information: the data originated by the national meteorological network and the generated ones at world-wide level by means of the NCEP/NCAR Reanalysis project for the assimilation of data coming from diverse world-wide networks. With them reference scenes are constructed to validate the CCM3 model which is used like tool for the projection of the climatic change in Colombia

  9. Lipid Treatment Assessment Project (L-TAP Study : a survey in 13 cities in Indonesia to evaluate the percentages of dyslipidemic patients achieving NCEP LDL-C target goals after treatment

    Directory of Open Access Journals (Sweden)

    Rinambaan W.M. Kaligis

    2001-06-01

    Full Text Available Clinical trials have demonstrated significant benefit from low density lipoprotein cholesterol (LDL-C lowering for primary and secondary prevention of cardiovascular disease. In the US, it is well recognized that a substantial number of hypercholesterolemic patients were not treated to the LDL-C goals recommended by the National Cholesterol Education Program (NCEP guidelines. In 1996, the Indonesian Heart Association (PERKI has issued guidelines recommending goals for screening and lipid treatment in Indonesia adopted from NCEP guidelines; however, the frequency of undertreatment in Indonesia is not known. The objective of this study was to determine the percentage of patients treated with lipid-lowering therapy who reached LDL-C goals as defined by NCEP guidelines in routine clinical practice. This was a cross-sectional survey targeted physicians who regularly treated dyslipidemic patients in 13 cities in Indonesia. Participating doctors were asked on their awareness of NCEP guidelines and to complete the case record form (CRF of the enrolled patients. One-hundred and eighty-eight (188 out of four hundreds (400 physicians who were invited, have participated in this study. Among the evaluable 1420 CRF, 1082 patients received statins, 301 used fibrates, 14 patients used combination drugs, and 23 others received non-drug treatments only. Success rates on achieving target LDL-C in low-risk, high-risk, and CHD groups were 73.0 %, 43.6 %, and 14.8 %, respectively. Overall success rate in patients using statins was 55.1 %, while in low-risk group, high-risk group, and CHD patients, the success rates with statin were 77.8%, 50.1%, and 18.6 %, respectively. Atorvastatin showed the highest success rate (77.4 % if compared to other statins. Only 14 % of physicians were knowledgeable about the NCEP goals. Conclusion : A large number of dyslipidemic patients who were on lipid-lowering therapy were not achieving the recommended LDL-C target

  10. 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.

  11. Evaluating Coral Health in La Parguera, Puerto Rico, and Southeastern Florida: Comparison of Satellite-Based Sea Surface Temperature to In Situ Observations

    Science.gov (United States)

    Gomez, A. M.; McDonald, K. C.; Shein, K. A.; Devries, S. L.; Armstrong, R.; Carlo, M.

    2017-12-01

    The third global coral bleaching event, which began in mid-2014, is a major environmental stressor that has been causing significant documented damage to coral reefs in all tropical ocean basins. This worldwide phenomenon is the longest and largest coral bleaching event on record and now finally appears to be ending. During this event, some coral colonies proved to be more resilient to increased ocean temperatures while others bleached severely. This research investigates the spatial and temporal variability of bleaching stress on coral reefs in La Parguera, Puerto Rico, and Southeastern Florida to help further understand the role of temperature and light in coral bleaching. We examine the microclimate within two coral reef systems, using in situ collections of temperature and light data from data loggers deployed throughout Cayo Enrique and Cayo Mario in La Parguera, and Lauderdale-By-The-Sea in FLorida. The in situ measurements are compared to NOAA Coral Reef Watch's 5-km sea surface temperature data as well as to the associated Light Stress Damage Product. Research outcomes include statistical analyses of in situ measurements with satellite datasets supporting enhanced interpretation of satellite-based SST and light products, and ecological niche modeling to assess where corals could potentially survive under future climate conditions. Additional understanding of the microclimate encompassing coral reefs and improved satellite SST and light data will ultimately help coral reef ecosystem managers and policy makers in prioritizing resources toward the monitoring and protection of coral reef ecosystems.

  12. Towards a more objective evaluation of modelled land-carbon trends using atmospheric CO2 and satellite-based vegetation activity observations

    Directory of Open Access Journals (Sweden)

    D. Dalmonech

    2013-06-01

    Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular the net land–atmosphere carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to better understand 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 novel 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 that the uncertainty of both data and evaluation methodology is largely unknown or difficult to quantify. Based on these considerations, we introduce a baseline benchmark – a minimum test that any model 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 pinpointing of specific model deficiencies that would not be possible by the sole use of atmospheric CO2 observations.

  13. 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

  14. 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

  15. SATELLITE BASED EDUCATION AND TRAINING IN REMOTE SENSING AND GEO-INFORMATION: AN E-LEARNING APPROACH TO MEET THE GROWING DEMANDS IN INDIA

    Directory of Open Access Journals (Sweden)

    P. L. N. Raju

    2012-07-01

    Full Text Available 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

  16. The Feasibility of Tropospheric and Total Ozone Determination Using a Fabry-perot Interferometer as a Satellite-based Nadir-viewing Atmospheric Sensor. Ph.D. Thesis

    Science.gov (United States)

    Larar, Allen Maurice

    1993-01-01

    Monitoring of the global distribution of tropospheric ozone (O3) is desirable for enhanced scientific understanding as well as to potentially lessen the ill-health impacts associated with exposure to elevated concentrations in the lower atmosphere. Such a capability can be achieved using a satellite-based device making high spectral resolution measurements with high signal-to-noise ratios; this would enable observation in the pressure-broadened wings of strong O3 lines while minimizing the impact of undesirable signal contributions associated with, for example, the terrestrial surface, interfering species, and clouds. The Fabry-Perot Interferometer (FPI) provides high spectral resolution and high throughput capabilities that are essential for this measurement task. Through proper selection of channel spectral regions, the FPI optimized for tropospheric O3 measurements can simultaneously observe a stratospheric component and thus the total O3 column abundance. Decreasing stratospheric O3 concentrations may lead to an increase in biologically harmful solar ultraviolet radiation reaching the earth's surface, which is detrimental to health. In this research, a conceptual instrument design to achieve the desired measurement has been formulated. This involves a double-etalon fixed-gap series configuration FPI along with an ultra-narrow bandpass filter to achieve single-order operation with an overall spectral resolution of approximately .068 cm(exp -1). A spectral region of about 1 cm(exp -1) wide centered at 1054.73 cm(exp -1) within the strong 9.6 micron ozone infrared band is sampled with 24 spectral channels. Other design characteristics include operation from a nadir-viewing satellite configuration utilizing a 9 inch (diameter) telescope and achieving horizontal spatial resolution with a 50 km nadir footprint. A retrieval technique has been implemented and is demonstrated for a tropical atmosphere possessing enhanced tropospheric ozone amounts. An error analysis

  17. 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

  18. 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

  19. Total Discharge Estimation in the Korean Peninsula Using Multi-Satellite Products

    Directory of Open Access Journals (Sweden)

    Jae Young Seo

    2017-07-01

    Full Text Available Estimation of total discharge is necessary to understand the hydrological cycle and to manage water resources efficiently. However, the task is problematic in an area where ground observations are limited. The North Korea region is one example. Here, the total discharge was estimated based on the water balance using multiple satellite products. They are the terrestrial water storage changes (TWSC derived from the Gravity Recovery and Climate Experiment (GRACE, precipitation from the Tropical Rainfall Measuring Mission (TRMM, and evapotranspiration from the Moderate Resolution Imaging Spectroradiometer (MODIS. The satellite-based discharge was compared with land surface model products of the Global Land Data Assimilation System (GLDAS, and a positive relationship between the results was obtained (r = 0.70–0.86; bias = −9.08–16.99 mm/month; RMSE = 36.90–62.56 mm/month; NSE = 0.01–0.62. Among the four land surface models of GLDAS (CLM, Mosaic, Noah, and VIC, CLM corresponded best with the satellite-based discharge, satellite-based discharge has a tendency to slightly overestimate compared to model-based discharge (CLM, Mosaic, Noah, and VIC in the dry season. Also, the total discharge data based on the Precipitation-Runoff Modeling System (PRMS and the in situ discharge for major five river basins in South Korea show comparable seasonality and high correlation with the satellite-based discharge. In spite of the relatively low spatial resolution of GRACE, and loss of information incurred during the process of integrating three different satellite products, the proposed methodology can be a practical tool to estimate the total discharge with reasonable accuracy, especially in a region with scarce hydrologic data.

  20. Assessment of Wind Datasets for Estimating Offshore Wind Energy along the Central California Coast

    Science.gov (United States)

    Wang, Y. H.; Walter, R. K.; Ruttenberg, B.; White, C.

    2017-12-01

    Offshore renewable energy along the central California coastline has gained significant interest in recent years. We present a comprehensive analysis of near-surface wind datasets available in this region to facilitate future estimates of wind power generation potential. The analyses are based on local NDBC buoys, satellite-based measurements (QuickSCAT and CCMP V2.0), reanalysis products (NARR and MERRA), and a regional climate model (WRF). There are substantial differences in the diurnal signal during different months among the various products (i.e., satellite-based, reanalysis, and modeled) relative to the local buoys. Moreover, the datasets tended to underestimate wind speed under light wind conditions and overestimate under strong wind conditions. In addition to point-to-point comparisons against local buoys, the spatial variations of bias and error in both the reanalysis products and WRF model data in this region were compared against satellite-based measurements. NARR's bias and root-mean-square-error were generally small in the study domain and decreased with distance from coastlines. Although its smaller spatial resolution is likely to be insufficient to reveal local effects, the small bias and error in near-surface winds, as well as the availability of wind data at the proposed turbine hub heights, suggests that NARR is an ideal candidate for use in offshore wind energy production estimates along the central California coast. The framework utilized here could be applied in other site-specific regions where offshore renewable energy is being considered.

  1. Describing the spatio-temporal variability of vines and soil by satellite-based spectral indices: A case study in Apulia (South Italy)

    Science.gov (United States)

    Borgogno-Mondino, E.; Novello, V.; Lessio, A.; de Palma, L.

    2018-06-01

    A time series of Landsat 8 OLI (L8 OLI) multispectral images acquired between May 2013 and February 2016 were used to investigate vigour, vine and soil water content in a vineyard of Moscato Reale (syn. Moscato Bianco) sited in the Castel del Monte DOCG area. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated and compared with vine midday stem water potential (ΨMDstem) and soil volume water content (VWC), to calibrate estimation models. Estimation models were calibrated using already existing ground observation datasets from previous ordinary vineyard management operations: ΨMDstem was measured at two different locations in vineyard at 6 different dates in summer 2014; VWC was continuously measured from June to October 2014 and from January to September 2015. Results showed that: a) vine stem water potential can be locally estimated with an accuracy ranging from ±0.046 (high vigour vines) to ±0.127 (low vigour vines) MPa; b) soil volume water content can be locally estimated with an accuracy of about ±1.7%. Medium resolution satellite imagery proved, therefore, to be effective, at vineyard level, to describe vigour, vine and soil water status and their seasonality. This is an important issue to focus on since, as Landsat 8 images are free, the entire process is economic enough to be consistent with cost and incoming of the farming system.

  2. Seeking an optimal algorithm for a new satellite-based Sea Ice Drift Climate Data Record : Motivations, plans and initial results from the ESA CCI Sea Ice project

    DEFF Research Database (Denmark)

    Lavergne, T.; Dybkjær, Gorm; Girard-Ardhuin, Fanny

    The Sea Ice Essential Climate Variable (ECV) as defined by GCOS pertains of both sea ice concentration, thickness, and drift. Now in its second phase, the ESA CCI Sea Ice project is conducting the necessary research efforts to address sea ice drift.Accurate estimates of sea ice drift direction an...... in the final product. This contribution reviews the motivation for the work, the plans for sea ice drift algorithms intercomparison and selection, and early results from our activity....

  3. 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......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....

  4. Mitigating Satellite-Based Fire Sampling Limitations in Deriving Biomass Burning Emission Rates: Application to WRF-Chem Model Over the Northern sub-Saharan African Region

    Science.gov (United States)

    Wang, Jun; Yue, Yun; Wang, Yi; Ichoku, Charles; Ellison, Luke; Zeng, Jing

    2018-01-01

    Largely used in several independent estimates of fire emissions, fire products based on MODIS sensors aboard the Terra and Aqua polar-orbiting satellites have a number of inherent limitations, including (a) inability to detect fires below clouds, (b) significant decrease of detection sensitivity at the edge of scan where pixel sizes are much larger than at nadir, and (c) gaps between adjacent swaths in tropical regions. To remedy these limitations, an empirical method is developed here and applied to correct fire emission estimates based on MODIS pixel level fire radiative power measurements and emission coefficients from the Fire Energetics and Emissions Research (FEER) biomass burning emission inventory. The analysis was performed for January 2010 over the northern sub-Saharan African region. Simulations from WRF-Chem model using original and adjusted emissions are compared with the aerosol optical depth (AOD) products from MODIS and AERONET as well as aerosol vertical profile from CALIOP data. The comparison confirmed an 30-50% improvement in the model simulation performance (in terms of correlation, bias, and spatial pattern of AOD with respect to observations) by the adjusted emissions that not only increases the original emission amount by a factor of two but also results in the spatially continuous estimates of instantaneous fire emissions at daily time scales. Such improvement cannot be achieved by simply scaling the original emission across the study domain. Even with this improvement, a factor of two underestimations still exists in the modeled AOD, which is within the current global fire emissions uncertainty envelope.

  5. 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

  6. Integrated Power and Attitude Control Design of Satellites Based on a Fuzzy Adaptive Disturbance Observer Using Variable-Speed Control Moment Gyros

    Directory of Open Access Journals (Sweden)

    Zhongyi Chu

    2016-01-01

    Full Text Available To satisfy the requirements for small satellites that seek agile slewing with peak power, this paper investigates integrated power and attitude control using variable-speed control moment gyros (VSCMGs that consider the mass and inertia of gimbals and wheels. The paper also details the process for developing the controller by considering various environments in which the controller may be implemented. A fuzzy adaptive disturbance observer (FADO is proposed to estimate and compensate for the effects of equivalent disturbances. The algorithms can simultaneously track attitude and power. The simulation results illustrate the effectiveness of the control approach, which exhibits an improvement of 80 percent compared with alternate approaches that do not employ a FADO.

  7. Estimating Net Primary Production of Swedish Forest Landscapes by Combining Mechanistic Modeling and Remote Sensing

    DEFF Research Database (Denmark)

    Tagesson, Håkan Torbern; Smith, Benjamin; Løfgren, Anders

    2009-01-01

    and the Beer-Lambert law. LAI estimates were compared with satellite-extrapolated field estimates of LAI, and the results were generally acceptable. NPP estimates directly from the dynamic vegetation model and estimates obtained by combining the model estimates with remote sensing information were, on average......The aim of this study was to investigate a combination of satellite images of leaf area index (LAI) with processbased vegetation modeling for the accurate assessment of the carbon balances of Swedish forest ecosystems at the scale of a landscape. Monthly climatologic data were used as inputs...... in a dynamic vegetation model, the Lund Potsdam Jena-General Ecosystem Simulator. Model estimates of net primary production (NPP) and the fraction of absorbed photosynthetic active radiation were constrained by combining them with satellite-based LAI images using a general light use efficiency (LUE) model...

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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 observati......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....

  13. Satellite Based Analysis of Wood Biomass and Fuelwood Sustainability in Senegal: Developing Approaches for Long-Term Monitoring in the SERVIR-West Africa Region

    Science.gov (United States)

    Hanan, N. P.; Anchang, J.; Dieye, A. M.; Yero, K.; Tredennick, A. T.

    2017-12-01

    Rural populations in most of Africa are highly dependent on woody biomass (wood or charcoal) for cooking and heating. Many rural families gather wood locally, while urban populations often rely on small-scale commercial charcoal producers, who make charcoal in rural areas for transport to urban centers. Given that cooking is essential for conversion of inedible protein and carbohydrate substrates into edible food, fuelwood is an essential part of the food security puzzle for most African families. The SERVIR program is a partnership between USAID, NASA and regional institutions designed to enhance access to, and application of, earth observation data for economic development and natural resource management in less developed countries. In this paper, we report on a SERVIR West Africa collaboration to develop above-ground wood biomass estimates using moderate resolution ( 20 m) data from Sentinel-1 and Sentinel-2 satellites, incorporating field data for calibration and validation, and using data retrieval and analysis workflows that can be replicated by SERVIR partners across the region. Using the country of Senegal as a test case, we analyze the spatial distribution of biomass stocks in relation to fuelwood demand to assess supply-demand patterns across scales from local (village), to district, regional and national scales.

  14. Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

    Science.gov (United States)

    Di Vittorio, Alan V.; Negrón-Juárez, Robinson I.; Higuchi, Niro; Chambers, Jeffrey Q.

    2014-03-01

    Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies.

  15. Tropical forest carbon balance: effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass

    International Nuclear Information System (INIS)

    Di Vittorio, Alan V; Negrón-Juárez, Robinson I; Chambers, Jeffrey Q; Higuchi, Niro

    2014-01-01

    Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949–54) reported that Central Amazon plots missed 9–17% of tree mortality, and here we address ‘why’ by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies. (paper)

  16. 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

    2015-08-01

    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 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 early warning of food insecurity during drought years for these identified zones.

  17. Retrieval of High-Resolution Atmospheric Particulate Matter Concentrations from Satellite-Based Aerosol Optical Thickness over the Pearl River Delta Area, China

    Directory of Open Access Journals (Sweden)

    Lili Li

    2015-06-01

    Full Text Available Satellite remote sensing offers an effective approach to estimate indicators of air quality on a large scale. It is critically significant for air quality monitoring in areas experiencing rapid urbanization and consequently severe air pollution, like the Pearl River Delta (PRD in China. This paper starts with examining ground observations of particulate matter (PM and the relationship between PM10 (particles smaller than 10 μm and aerosol optical thickness (AOT by analyzing observations on the sampling sites in the PRD. A linear regression (R2 = 0.51 is carried out using MODIS-derived 500 m-resolution AOT and PM10 concentration from monitoring stations. Data of atmospheric boundary layer (ABL height and relative humidity are used to make vertical and humidity corrections on AOT. Results after correction show higher correlations (R2 = 0.55 between extinction coefficient and PM10. However, coarse spatial resolution of meteorological data affects the smoothness of retrieved maps, which suggests high-resolution and accurate meteorological data are critical to increase retrieval accuracy of PM. Finally, the model provides the spatial distribution maps of instantaneous and yearly average PM10 over the PRD. It is proved that observed PM10 is more relevant to yearly mean AOT than instantaneous values.

  18. Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

    Science.gov (United States)

    Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

    2016-01-01

    We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

  19. 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.

  20. Using ground- and satellite-based measurements and models to quantify response to multiple disturbances and climate change in South African semi-arid ecosystems

    Science.gov (United States)

    Falge, Eva; Brümmer, Christian; Schmullius, Christiane; Scholes, Robert; Twine, Wayne; Mudau, Azwitamisi; Midgley, Guy; Hickler, Thomas; Bradshaw, Karen; Lück, Wolfgang; Thiel-Clemen, Thomas; du Toit, Justin; Sankaran, Vaith; Kutsch, Werner

    2016-04-01

    Sub-Saharan Africa currently experiences significant changes in shrubland, savanna and mixed woodland ecosystems driving degradation, affecting fire frequency and water availability, and eventually fueling climate change. 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. For a network of research clusters along an aridity gradient in South Africa, we measure greenhouse gas exchange, ecosystem structure and eco-physiological properties as affected by land use change at paired sites with natural and altered vegetation. We set up dynamic vegetation models and individual-based models to predict ecosystem dynamics under (post) disturbance managements. We monitor vegetation amount and heterogeneity using remotely sensed images and aerial photography over several decades to examine time series of land cover change. Finally, we investigate livelihood strategies with focus on carbon balance components to develop sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation of estimates obtained from eddy covariance, model approaches and satellite derivations. We envision our methodological approach on a network of research clusters a valuable means to investigate potential linkages to concepts of adaptive resilience.

  1. 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.

  2. Understanding of crop phenology using satellite-based retrievals and climate factors – a case study on spring maize in Northeast China plain

    International Nuclear Information System (INIS)

    Shuai, Yanmin; Xie, Donghui; Wang, Peijuan; Wu, Menxin

    2014-01-01

    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

  3. 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...

  4. 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...

  5. 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.

  6. NCEP ATP III dan Framingham score

    OpenAIRE

    Hasan, Refli; Fahila, Reny

    2016-01-01

    Laporan ini merupakan Program Pendidikan Kolesterol National yang diperbaharui yaitu pedoman klinis untuk melakukan pengujian kolesterol dan manajemen. ATP III dibuat berdasarkan bukti dan laporan ekstensif yang akan menjadi referensi dan rekomendasi ilmiah. Laporan ATP III dapat dijadikan pedoman untuk pemberian terapi penurun kolesterol yang intensif dalam praktek. Pedoman ini hanya sebagai informasi , tidak dapat mempengaruhi secara mutlak dalam penilaian klinis dokter yang akhirnya menent...

  7. 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 < 0.7) for all 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

  8. Investigation of CO, C2H6 and aerosols over Eastern Canada during BORTAS 2011 using ground-based and satellite-based observations and model simulations

    Science.gov (United States)

    Griffin, Debora; Franklin, Jonathan; Parrington, Mark; Whaley, Cynthia; Hopper, Jason; Lesins, Glen; Tereszchuk, Keith; Walker, Kaley A.; Drummond, James R.; Palmer, Paul; Strong, Kimberly; Duck, Thomas J.; Abboud, Ihab; Dan, Lin; O'Neill, Norm; Clerbaux, Cathy; Coheur, Pierre; Bernath, Peter F.; Hyer, Edward; Kliever, Jenny

    2013-04-01

    We present the results of total column measurements of CO and C2H6 and aerosol optical depth (AOD) during the Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS-B) campaign over Eastern Canada. Ground-based observations, using Fourier transform spectrometers (FTSs) and sun photometers, were carried out in July and August 2011. They were taken in Halifax, Nova Scotia, which is an ideal location to monitor the outflow of boreal fires from North America, and in Toronto, Ontario. Measurements of enhanced fine mode AOD were highly correlated with enhancements in coincident trace gas (CO and C2H6) observations between 19 and 21 July 2011, which is typical for a smoke plume event. In this study, we will focus on the identification of the origin and the transport of this smoke plume. We use back-trajectories calculated by the Canadian Meteorological Centre (CMC) as well as FLEXPART forward-trajectories to demonstrate that the enhanced CO, C2H6 and fine mode AOD seen near Halifax and Toronto did originate from forest fires in Northwestern Ontario, that occurred between 17 and 19 July 2011. In addition, total column measurements of CO from the satellite-borne Infrared Atmospheric Sounding Interferometer (IASI) have been used to trace the smoke plume and to confirm the origin of the CO enhancement. Furthermore, the emission ratio (ERC2H6-CO) and the emission factor (EFC2H6) of C2H6 (with respect to the CO emission) were estimated from these ground-based observations. The C2H6 emission results from boreal fires in Northwestern Ontario agree well with C2H6 emission measurements from other boreal regions, and are relatively high compared to other geographical regions. The ground-based CO and C2H6 observations were compared with output from the 3-D global chemical transport model GEOS-Chem, using the inventory of the Fire Locating And Monitoring of Burning Emissions (FLAMBE). Good agreement was found for

  9. Invitation to a forum: architecting operational `next generation' earth monitoring satellites based on best modeling, existing sensor capabilities, with constellation efficiencies to secure trusted datasets for the next 20 years

    Science.gov (United States)

    Helmuth, Douglas B.; Bell, Raymond M.; Grant, David A.; Lentz, Christopher A.

    2012-09-01

    Architecting the operational Next Generation of earth monitoring satellites based on matured climate modeling, reuse of existing sensor & satellite capabilities, attention to affordability and evolutionary improvements integrated with constellation efficiencies - becomes our collective goal for an open architectural design forum. Understanding the earth's climate and collecting requisite signatures over the next 30 years is a shared mandate by many of the world's governments. But there remains a daunting challenge to bridge scientific missions to 'operational' systems that truly support the demands of decision makers, scientific investigators and global users' requirements for trusted data. In this paper we will suggest an architectural structure that takes advantage of current earth modeling examples including cross-model verification and a first order set of critical climate parameters and metrics; that in turn, are matched up with existing space borne collection capabilities and sensors. The tools used and the frameworks offered are designed to allow collaborative overlays by other stakeholders nominating different critical parameters and their own treaded connections to existing international collection experience. These aggregate design suggestions will be held up to group review and prioritized as potential constellation solutions including incremental and spiral developments - including cost benefits and organizational opportunities. This Part IV effort is focused on being an inclusive 'Next Gen Constellation' design discussion and is the natural extension to earlier papers.

  10. A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009.

    Science.gov (United States)

    Gardner, Alex S; Moholdt, Geir; Cogley, J Graham; Wouters, Bert; Arendt, Anthony A; Wahr, John; Berthier, Etienne; Hock, Regine; Pfeffer, W Tad; Kaser, Georg; Ligtenberg, Stefan R M; Bolch, Tobias; Sharp, Martin J; Hagen, Jon Ove; van den Broeke, Michiel R; Paul, Frank

    2013-05-17

    Glaciers distinct from the Greenland and Antarctic Ice Sheets are losing large amounts of water to the world's oceans. However, estimates of their contribution to sea level rise disagree. We provide a consensus estimate by standardizing existing, and creating new, mass-budget estimates from satellite gravimetry and altimetry and from local glaciological records. In many regions, local measurements are more negative than satellite-based estimates. All regions lost mass during 2003-2009, with the largest losses from Arctic Canada, Alaska, coastal Greenland, the southern Andes, and high-mountain Asia, but there was little loss from glaciers in Antarctica. Over this period, the global mass budget was -259 ± 28 gigatons per year, equivalent to the combined loss from both ice sheets and accounting for 29 ± 13% of the observed sea level rise.

  11. 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.

  12. 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.

  13. Estimating Spring Condensation on the Great Lakes

    Science.gov (United States)

    Meyer, A.; Welp, L.

    2017-12-01

    The Laurentian Great Lakes region provides opportunities for shipping, recreation, and consumptive water use to a large part of the United States and Canada. Water levels in the lakes fluctuate yearly, but attempts to model the system are inadequate because the water and energy budgets are still not fully understood. For example, water levels in the Great Lakes experienced a 15-year low period ending in 2013, the recovery of which has been attributed partially to decreased evaporation and increased precipitation and runoff. Unlike precipitation, the exchange of water vapor between the lake and the atmosphere through evaporation or condensation is difficult to measure directly. However, estimates have been constructed using off-shore eddy covariance direct measurements of latent heat fluxes, remote sensing observations, and a small network of monitoring buoys. When the lake surface temperature is colder than air temperature as it is in spring, condensation is larger than evaporation. This is a relatively small component of the net annual water budget of the lakes, but the total amount of condensation may be important for seasonal energy fluxes and atmospheric deposition of pollutants and nutrients to the lakes. Seasonal energy fluxes determine, and are influenced by, ice cover, water and air temperatures, and evaporation in the Great Lakes. We aim to quantify the amount of spring condensation on the Great Lakes using the National Center for Atmospheric Prediction North American Regional Reanalysis (NCEP NARR) Data for Winter 2013 to Spring 2017 and compare the condensation values of spring seasons following high volume, high duration and low volume, low duration ice cover.

  14. Estimating Utility

    DEFF Research Database (Denmark)

    Arndt, Channing; Simler, Kenneth R.

    2010-01-01

    A fundamental premise of absolute poverty lines is that they represent the same level of utility through time and space. Disturbingly, a series of recent studies in middle- and low-income economies show that even carefully derived poverty lines rarely satisfy this premise. This article proposes a......, with the current approach tending to systematically overestimate (underestimate) poverty in urban (rural) zones.......A fundamental premise of absolute poverty lines is that they represent the same level of utility through time and space. Disturbingly, a series of recent studies in middle- and low-income economies show that even carefully derived poverty lines rarely satisfy this premise. This article proposes...... 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...

  15. Open-Source Python Modules to Estimate Level Ice Thickness from Ice Charts

    Science.gov (United States)

    Geiger, C. A.; Deliberty, T. L.; Bernstein, E. R.; Helfrich, S.

    2012-12-01

    A collaborative research effort between the University of Delaware (UD) and National Ice Center (NIC) addresses the task of providing open-source translations of sea ice stage-of-development into level ice thickness estimates on a 4km grid for the Interactive Multisensor Snow and Ice Mapping System (IMS). The characteristics for stage-of-development are quantified from remote sensing imagery with estimates of level ice thickness categories originating from World Meteorological Organization (WMO) egg coded ice charts codified since the 1970s. Conversions utilize Python scripting modules which transform electronic ice charts with WMO egg code characteristics into five level ice thickness categories, in centimeters, (0-10, 10-30, 30-70, 70-120, >120cm) and five ice types (open water, first year pack ice, fast ice, multiyear ice, and glacial ice with a reserve slot for deformed ice fractions). Both level ice thickness categories and ice concentration fractions are reported with uncertainties propagated based on WMO ice stage ranges which serve as proxy estimates for standard deviation. These products are in preparation for use by NCEP, CMC, and NAVO by 2014 based on their modeling requirements for daily products in near-real time. In addition to development, continuing research tests the value of these estimated products against in situ observations to improve both value and uncertainty estimates.

  16. 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

  17. Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

    Science.gov (United States)

    Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

    2013-04-01

    The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

  18. Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods

    Science.gov (United States)

    Senay, G.B.; Leake, S.; Nagler, P.L.; Artan, G.; Dickinson, J.; Cordova, J.T.; Glenn, E.P.

    2011-01-01

    Evapotranspiration (ET) is an important hydrological process that can be studied and estimated at multiple spatial scales ranging from a leaf to a river basin. We present a review of methods in estimating basin scale ET and its applications in understanding basin water balance dynamics. The review focuses on two aspects of ET: (i) how the basin scale water balance approach is used to estimate ET; and (ii) how ‘direct’ measurement and modelling approaches are used to estimate basin scale ET. Obviously, the basin water balance-based ET requires the availability of good precipitation and discharge data to calculate ET as a residual on longer time scales (annual) where net storage changes are assumed to be negligible. ET estimated from such a basin water balance principle is generally used for validating the performance of ET models. On the other hand, many of the direct estimation methods involve the use of remotely sensed data to estimate spatially explicit ET and use basin-wide averaging to estimate basin scale ET. The direct methods can be grouped into soil moisture balance modelling, satellite-based vegetation index methods, and methods based on satellite land surface temperature measurements that convert potential ET into actual ET using a proportionality relationship. The review also includes the use of complementary ET estimation principles for large area applications. The review identifies the need to compare and evaluate the different ET approaches using standard data sets in basins covering different hydro-climatic regions of the world.

  19. 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.

  20. Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets

    KAUST Repository

    Sun, Ying; Stein, Michael L.

    2014-01-01

    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.

  1. Variance estimation for generalized Cavalieri estimators

    OpenAIRE

    Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen

    2011-01-01

    The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.

  2. Off-shore Wind Atlas of the Central Aegean Sea: A simple comparison of NCEP/NCAR RE-analysis data, QuickSCAT and ENVISAT Synthetic Aperture Radar (SAR) by use of Wind Atlas Method

    DEFF Research Database (Denmark)

    Bingöl, Ferhat; Hasager, Charlotte Bay; Karagali, Ioanna

    2012-01-01

    model results). Unfortunately all of these methods are still under development and do not provide data acceptable for bankable wind assessment reports. On the other hand, they give good indications of the geographical distribution of the wind resources and that is very useful for decision making...... to high costs, but with the new developments in floating turbine design, it seems that offshore wind parks in deep waters will also be a possibility in the future. Whether on-shore or offshore, the first step of a site assessment is to estimate the wind resources. Usually well-known conventional methods...... are used to produce estimates of wind resources by means of at least one year data from a single or multiple points on the terrain. This criterion is dicult to satisfy in offshore locations where measurements are costly and sparse. Therefore other methods are required (e.g satellite imagery or reanalysis...

  3. High-resolution refinement of a storm loss model and estimation of return periods of loss-intensive storms over Germany

    Directory of Open Access Journals (Sweden)

    M. G. Donat

    2011-10-01

    Full Text Available A refined model for the calculation of storm losses is presented, making use of high-resolution insurance loss records for Germany and allowing loss estimates on a spatial level of administrative districts and for single storm events. Storm losses are calculated on the basis of wind speeds from both ERA-Interim and NCEP reanalyses. The loss model reproduces the spatial distribution of observed losses well by taking specific regional loss characteristics into account. This also permits high-accuracy estimates of total cumulated losses, though slightly underestimating the country-wide loss sums for storm "Kyrill", the most severe event in the insurance loss records from 1997 to 2007. A larger deviation, which is assigned to the relatively coarse resolution of the NCEP reanalysis, is only found for one specific rather small-scale event, not adequately captured by this dataset.

    The loss model is subsequently applied to the complete reanalysis period to extend the storm event catalogue to cover years when no systematic insurance records are available. This allows the consideration of loss-intensive storm events back to 1948, enlarging the event catalogue to cover the recent 60+ years, and to investigate the statistical characteristics of severe storm loss events in Germany based on a larger sample than provided by the insurance records only. Extreme value analysis is applied to the loss data to estimate the return periods of loss-intensive storms, yielding a return period for storm "Kyrill", for example, of approximately 15 to 21 years.

  4. 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.

  5. Observationally constrained estimates of carbonaceous aerosol radiative forcing.

    Science.gov (United States)

    Chung, Chul E; Ramanathan, V; Decremer, Damien

    2012-07-17

    Carbonaceous aerosols (CA) emitted by fossil and biomass fuels consist of black carbon (BC), a strong absorber of solar radiation, and organic matter (OM). OM scatters as well as absorbs solar radiation. The absorbing component of OM, which is ignored in most climate models, is referred to as brown carbon (BrC). Model estimates of the global CA radiative forcing range from 0 to 0.7 Wm(-2), to be compared with the Intergovernmental Panel on Climate Change's estimate for the pre-Industrial to the present net radiative forcing of about 1.6 Wm(-2). This study provides a model-independent, observationally based estimate of the CA direct radiative forcing. Ground-based aerosol network data is integrated with field data and satellite-based aerosol observations to provide a decadal (2001 through 2009) global view of the CA optical properties and direct radiative forcing. The estimated global CA direct radiative effect is about 0.75 Wm(-2) (0.5 to 1.0). This study identifies the global importance of BrC, which is shown to contribute about 20% to 550-nm CA solar absorption globally. Because of the inclusion of BrC, the net effect of OM is close to zero and the CA forcing is nearly equal to that of BC. The CA direct radiative forcing is estimated to be about 0.65 (0.5 to about 0.8) Wm(-2), thus comparable to or exceeding that by methane. Caused in part by BrC absorption, CAs have a net warming effect even over open biomass-burning regions in Africa and the Amazon.

  6. 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.

  7. 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

    across the city center from June to September confirming that, in Milan, urban heating is not an occasional phenomenon. Furthermore, this study shows the utility of space missions to monitor the metropolis heat islands if they are able to provide nighttime observations when CLHI peaks are generally......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...... 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...

  8. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2014-10-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

  9. REDRAW-Based Evapotranspiration Estimation in Chongli, North China

    Science.gov (United States)

    Zhang, Z.; Wang, Z.

    2017-12-01

    Evapotranspiration (ET) is the key component of hydrological cycle and spatial estimates of ET are important elements of atmospheric circulation and hydrologic models. Quantifying the ET over large region is significant for water resources planning, hydrologic water balances, water rights management, and water division. In this study, Evapotranspiration (ET) was estimated using REDRAW model in the Chongli on 2014. REDRAW is a satellite-based balance algorithm with reference dry and wet limits model developed to estimate ET. Remote sensing data obtained from MODIS and meteorological data from China Meteorological Data Sharing Service System were used in ET model. In order to analyze the distribution and time variation of ET over the study region, daily, monthly and yearly ET were calculated for the study area, and ET of different land cover types were calculated. In terms of the monthly ET, the figure was low in winter and high in other seasons, and reaches the maximum value in August, showing a high monthly difference. The ET value of water body was the highest and that of barren or sparse vegetation were the lowest, which accorded with local actual condition. Evaluating spatial temporal distribution of actual ET could assist to understand the water consumption regularity in region and figure out the effect from different land cover, which helped to establish links between land use, water allocation, and water use planning in study region. Due to the groundwater recession in north China, the evaluation of regional total water resources become increasingly essential, and the result of this study can be used to plan the water use. As the Chongli will prepare the ski slopes for Winter Olympics on 2022, accuracy estimation of actual ET can efficiently resolve water conflict and relieve water scarcity.

  10. Estimation of the uncertainty in wind power forecasting

    International Nuclear Information System (INIS)

    Pinson, P.

    2006-03-01

    WIND POWER experiences a tremendous development of its installed capacities in Europe. Though, the intermittence of wind generation causes difficulties in the management of power systems. Also, in the context of the deregulation of electricity markets, wind energy is penalized by its intermittent nature. It is recognized today that the forecasting of wind power for horizons up to 2/3-day ahead eases the integration of wind generation. Wind power forecasts are traditionally provided in the form of point predictions, which correspond to the most-likely power production for a given horizon. That sole information is not sufficient for developing optimal management or trading strategies. Therefore, we investigate on possible ways for estimating the uncertainty of wind power forecasts. The characteristics of the prediction uncertainty are described by a thorough study of the performance of some of the state-of-the-art approaches, and by underlining the influence of some variables e.g. level of predicted power on distributions of prediction errors. Then, a generic method for the estimation of prediction intervals is introduced. This statistical method is non-parametric and utilizes fuzzy logic concepts for integrating expertise on the prediction uncertainty characteristics. By estimating several prediction intervals at once, one obtains predictive distributions of wind power output. The proposed method is evaluated in terms of its reliability, sharpness and resolution. In parallel, we explore the potential use of ensemble predictions for skill forecasting. Wind power ensemble forecasts are obtained either by converting meteorological ensembles (from ECMWF and NCEP) to power or by applying a poor man's temporal approach. A proposal for the definition of prediction risk indices is given, reflecting the disagreement between ensemble members over a set of successive look-ahead times. Such prediction risk indices may comprise a more comprehensive signal on the expected level

  11. 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.

    2016-01-01

    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 approximately100 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.

  12. 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.

  13. Farm Level Assessment of Irrigation Performance for Dairy Pastures in the Goulburn-Murray District of Australia by Combining Satellite-Based Measures with Weather and Water Delivery Information

    Directory of Open Access Journals (Sweden)

    Mohammad Abuzar

    2017-08-01

    Full Text Available Pasture performance of 924 dairy farms in a major irrigation district of Australia was investigated for their water use and water productivity during the 2015-2016 summer which was the peak irrigation period. Using satellite images from Landsat-8 and Sentinel-2, estimates of crop coefficient (Kc were determined on the basis of a strong linear relationship between crop evapotranspiration (ETc and vegetation index (NDVI of pasture in the region. Utilizing estimates of Kc and crop water requirement (CWR, NDVI-dependent estimates of Irrigation Water Requirement (IWR were derived based on the soil water balance model. In combination with daily weather information and seasonal irrigation water supply records, IWR was the key component in the understanding of current irrigation status at farm level, and deriving two irrigation performance indicators: (1 Relative Irrigation Water Use (RIWU and (2 Total Irrigation Water Productivity (TIWP. A slightly higher proportion of farm irrigators were found to be either matching the irrigation requirement or under-watering (RIWU ≤ 1.0. According to TIWP, a few dairy farms (3% were found to be in the category of high yield potential with excess water use, and very few (1% in the category of limited water supply to pastures of high yield potential. A relatively high number of farms were found to be in the category where excess water was supplied to pastures of low-medium yield potential (27%, and farms where water supply compromised pastures with a sub-maximal vegetation status (15%. The results of this study will assist in objectively identifying where significant improvement in efficient irrigation water use can be achieved.

  14. Tropical Cyclone Intensity Estimation Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Maskey, Manil; Cecil, Dan; Ramachandran, Rahul; Miller, Jeffrey J.

    2018-01-01

    Estimating tropical cyclone intensity by just using satellite image is a challenging problem. With successful application of the Dvorak technique for more than 30 years along with some modifications and improvements, it is still used worldwide for tropical cyclone intensity estimation. A number of semi-automated techniques have been derived using the original Dvorak technique. However, these techniques suffer from subjective bias as evident from the most recent estimations on October 10, 2017 at 1500 UTC for Tropical Storm Ophelia: The Dvorak intensity estimates ranged from T2.3/33 kt (Tropical Cyclone Number 2.3/33 knots) from UW-CIMSS (University of Wisconsin-Madison - Cooperative Institute for Meteorological Satellite Studies) to T3.0/45 kt from TAFB (the National Hurricane Center's Tropical Analysis and Forecast Branch) to T4.0/65 kt from SAB (NOAA/NESDIS Satellite Analysis Branch). In this particular case, two human experts at TAFB and SAB differed by 20 knots in their Dvorak analyses, and the automated version at the University of Wisconsin was 12 knots lower than either of them. The National Hurricane Center (NHC) estimates about 10-20 percent uncertainty in its post analysis when only satellite based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to tropical cyclone intensity. This study aims to utilize deep learning, the current state of the art in pattern recognition and image recognition, to address the need for an automated and objective tropical cyclone intensity estimation. Deep learning is a multi-layer neural network consisting of several layers of simple computational units. It learns discriminative features without relying on a human expert to identify which features are important. Our study mainly focuses on convolutional neural network (CNN), a deep learning algorithm, to develop an objective tropical cyclone intensity estimation. CNN is a supervised learning

  15. 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.

  16. Evaluation and adjustment of altimeter measurement and numerical hindcast in wave height trend estimation in China's coastal seas

    Science.gov (United States)

    Li, Shuiqing; Guan, Shoude; Hou, Yijun; Liu, Yahao; Bi, Fan

    2018-05-01

    A long-term trend of significant wave height (SWH) in China's coastal seas was examined based on three datasets derived from satellite measurements and numerical hindcasts. One set of altimeter data were obtained from the GlobWave, while the other two datasets of numerical hindcasts were obtained from the third-generation wind wave model, WAVEWATCH III, forced by wind fields from the Cross-Calibrated Multi-Platform (CCMP) and NCEP's Climate Forecast System Reanalysis (CFSR). The mean and extreme wave trends were estimated for the period 1992-2010 with respect to the annual mean and the 99th-percentile values of SWH, respectively. The altimeter wave trend estimates feature considerable uncertainties owing to the sparse sampling rate. Furthermore, the extreme wave trend tends to be overestimated because of the increasing sampling rate over time. Numerical wave trends strongly depend on the quality of the wind fields, as the CCMP waves significantly overestimate the wave trend, whereas the CFSR waves tend to underestimate the trend. Corresponding adjustments were applied which effectively improved the trend estimates from the altimeter and numerical data. The adjusted results show generally increasing mean wave trends, while the extreme wave trends are more spatially-varied, from decreasing trends prevailing in the South China Sea to significant increasing trends mainly in the East China Sea.

  17. Evaluation of alternative model-data fusion approaches in water balance estimation across Australia

    Science.gov (United States)

    van Dijk, A. I. J. M.; Renzullo, L. J.

    2009-04-01

    Australia's national agencies are developing a continental modelling system to provide a range of water information services. It will include rolling water balance estimation to underpin national water accounts, water resources assessments that interpret current water resources availability and trends in a historical context, and water resources predictions coupled to climate and weather forecasting. The nation-wide coverage, currency, accuracy, and consistency required means that remote sensing will need to play an important role along with in-situ observations. Different approaches to blending models and observations can be considered. Integration of on-ground and remote sensing data into land surface models in atmospheric applications often involves state updating through model-data assimilation techniques. By comparison, retrospective water balance estimation and hydrological scenario modelling to date has mostly relied on static parameter fitting against observations and has made little use of earth observation. The model-data fusion approach most appropriate for a continental water balance estimation system will need to consider the trade-off between computational overhead and the accuracy gains achieved when using more sophisticated synthesis techniques and additional observations. This trade-off was investigated using a landscape hydrological model and satellite-based estimates of soil moisture and vegetation properties for aseveral gauged test catchments in southeast Australia.

  18. Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

    Science.gov (United States)

    He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

    2017-12-01

    Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, pcrop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

  19. Estimating snow depth of alpine snowpack via airborne multifrequency passive microwave radiance observations: Colorado, USA

    Science.gov (United States)

    Kim, R. S.; Durand, M. T.; Li, D.; Baldo, E.; Margulis, S. A.; Dumont, M.; Morin, S.

    2017-12-01

    This paper presents a newly-proposed snow depth retrieval approach for mountainous deep snow using airborne multifrequency passive microwave (PM) radiance observation. In contrast to previous snow depth estimations using satellite PM radiance assimilation, the newly-proposed method utilized single flight observation and deployed the snow hydrologic models. This method is promising since the satellite-based retrieval methods have difficulties to estimate snow depth due to their coarse resolution and computational effort. Indeed, this approach consists of particle filter using combinations of multiple PM frequencies and multi-layer snow physical model (i.e., Crocus) to resolve melt-refreeze crusts. The method was performed over NASA Cold Land Processes Experiment (CLPX) area in Colorado during 2002 and 2003. Results showed that there was a significant improvement over the prior snow depth estimates and the capability to reduce the prior snow depth biases. When applying our snow depth retrieval algorithm using a combination of four PM frequencies (10.7,18.7, 37.0 and 89.0 GHz), the RMSE values were reduced by 48 % at the snow depth transects sites where forest density was less than 5% despite deep snow conditions. This method displayed a sensitivity to different combinations of frequencies, model stratigraphy (i.e. different number of layering scheme for snow physical model) and estimation methods (particle filter and Kalman filter). The prior RMSE values at the forest-covered areas were reduced by 37 - 42 % even in the presence of forest cover.

  20. Variable Kernel Density Estimation

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1992-01-01

    We investigate some of the possibilities for improvement of univariate and multivariate kernel density estimates by varying the window over the domain of estimation, pointwise and globally. Two general approaches are to vary the window width by the point of estimation and by point of the sample observation. The first possibility is shown to be of little efficacy in one variable. In particular, nearest-neighbor estimators in all versions perform poorly in one and two dimensions, but begin to b...

  1. Fuel Burn Estimation Model

    Science.gov (United States)

    Chatterji, Gano

    2011-01-01

    Conclusions: Validated the fuel estimation procedure using flight test data. A good fuel model can be created if weight and fuel data are available. Error in assumed takeoff weight results in similar amount of error in the fuel estimate. Fuel estimation error bounds can be determined.

  2. Optimal fault signal estimation

    NARCIS (Netherlands)

    Stoorvogel, Antonie Arij; Niemann, H.H.; Saberi, A.; Sannuti, P.

    2002-01-01

    We consider here both fault identification and fault signal estimation. Regarding fault identification, we seek either exact or almost fault identification. On the other hand, regarding fault signal estimation, we seek either $H_2$ optimal, $H_2$ suboptimal or Hinfinity suboptimal estimation. By

  3. 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...

  4. 1km Global Terrestrial Carbon Flux: Estimations and Evaluations

    Science.gov (United States)

    Murakami, K.; Sasai, T.; Kato, S.; Saito, M.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.

    2017-12-01

    Estimating global scale of the terrestrial carbon flux change with high accuracy and high resolution is important to understand global environmental changes. Furthermore the estimations of the global spatiotemporal distribution may contribute to the political and social activities such as REDD+. In order to reveal the current state of terrestrial carbon fluxes covering all over the world and a decadal scale. The satellite-based diagnostic biosphere model is suitable for achieving this purpose owing to observing on the present global land surface condition uniformly at some time interval. In this study, we estimated the global terrestrial carbon fluxes with 1km grids by using the terrestrial biosphere model (BEAMS). And we evaluated our new carbon flux estimations on various spatial scales and showed the transition of forest carbon stocks in some regions. Because BEAMS required high resolution meteorological data and satellite data as input data, we made 1km interpolated data using a kriging method. The data used in this study were JRA-55, GPCP, GOSAT L4B atmospheric CO2 data as meteorological data, and MODIS land product as land surface satellite data. Interpolating process was performed on the meteorological data because of insufficient resolution, but not on MODIS data. We evaluated our new carbon flux estimations using the flux tower measurement (FLUXNET2015 Datasets) in a point scale. We used 166 sites data for evaluating our model results. These flux sites are classified following vegetation type (DBF, EBF, ENF, mixed forests, grass lands, croplands, shrub lands, Savannas, wetlands). In global scale, the BEAMS estimations was underestimated compared to the flux measurements in the case of carbon uptake and release. The monthly variations of NEP showed relatively high correlations in DBF and mixed forests, but the correlation coefficients of EBF, ENF, and grass lands were less than 0.5. In the meteorological factors, air temperature and solar radiation showed

  5. 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.

  6. Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

    Science.gov (United States)

    Madani, N.; Kimball, J. S.; Running, S. W.

    2014-12-01

    Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE plant trait information can explain spatial heterogeneity in LUEopt, leading to improved GPP estimates from satellite based LUE models.

  7. Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

    Science.gov (United States)

    Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

    2017-12-01

    Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

  8. Investigation of CO, C2H6 and aerosols in a boreal fire plume over eastern Canada during BORTAS 2011 using ground- and satellite-based observations and model simulations

    Directory of Open Access Journals (Sweden)

    D. Griffin

    2013-10-01

    Full Text Available We present the results of total column measurements of CO, C2H6 and fine-mode aerosol optical depth (AOD during the "Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites" (BORTAS-B campaign over eastern Canada. Ground-based observations, using Fourier transform spectrometers (FTSs and sun photometers, were carried out in July and August 2011. These measurements were taken in Halifax, Nova Scotia, which is an ideal location to monitor the outflow of boreal fires from North America, and also in Toronto, Ontario. Measurements of fine-mode AOD enhancements were highly correlated with enhancements in coincident trace gas (CO and C2H6 observations between 19 and 21 July 2011, which is typical for a smoke plume event. In this paper, we focus on the identification of the origin and the transport of this smoke plume. We use back trajectories calculated by the Canadian Meteorological Centre as well as FLEXPART forward trajectories to demonstrate that the enhanced CO, C2H6 and fine-mode AOD seen near Halifax and Toronto originated from forest fires in northwestern Ontario that occurred between 17 and 19 July 2011. In addition, total column measurements of CO from the satellite-borne Infrared Atmospheric Sounding Interferometer (IASI have been used to trace the smoke plume and to confirm the origin of the CO enhancement. Furthermore, the enhancement ratio – that is, in this case equivalent to the emission ratio (ERC2H6/CO – was estimated from these ground-based observations. These C2H6 emission results from boreal fires in northwestern Ontario agree well with C2H6 emission measurements from other boreal regions, and are relatively high compared to fires from other geographical regions. The ground-based CO and C2H6 observations were compared with outputs from the 3-D global chemical transport model GEOS-Chem, using the Fire Locating And Modeling of Burning Emissions (FLAMBE inventory

  9. Investigation of CO, C2H6 and aerosols in a boreal fire plume over eastern Canada during BORTAS 2011 using ground- and satellite-based observations and model simulations

    Science.gov (United States)

    Griffin, D.; Walker, K. A.; Franklin, J. E.; Parrington, M.; Whaley, C.; Hopper, J.; Drummond, J. R.; Palmer, P. I.; Strong, K.; Duck, T. J.; Abboud, I.; Bernath, P. F.; Clerbaux, C.; Coheur, P.-F.; Curry, K. R.; Dan, L.; Hyer, E.; Kliever, J.; Lesins, G.; Maurice, M.; Saha, A.; Tereszchuk, K.; Weaver, D.

    2013-10-01

    We present the results of total column measurements of CO, C2H6 and fine-mode aerosol optical depth (AOD) during the "Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites" (BORTAS-B) campaign over eastern Canada. Ground-based observations, using Fourier transform spectrometers (FTSs) and sun photometers, were carried out in July and August 2011. These measurements were taken in Halifax, Nova Scotia, which is an ideal location to monitor the outflow of boreal fires from North America, and also in Toronto, Ontario. Measurements of fine-mode AOD enhancements were highly correlated with enhancements in coincident trace gas (CO and C2H6) observations between 19 and 21 July 2011, which is typical for a smoke plume event. In this paper, we focus on the identification of the origin and the transport of this smoke plume. We use back trajectories calculated by the Canadian Meteorological Centre as well as FLEXPART forward trajectories to demonstrate that the enhanced CO, C2H6 and fine-mode AOD seen near Halifax and Toronto originated from forest fires in northwestern Ontario that occurred between 17 and 19 July 2011. In addition, total column measurements of CO from the satellite-borne Infrared Atmospheric Sounding Interferometer (IASI) have been used to trace the smoke plume and to confirm the origin of the CO enhancement. Furthermore, the enhancement ratio - that is, in this case equivalent to the emission ratio (ERC2H6/CO) - was estimated from these ground-based observations. These C2H6 emission results from boreal fires in northwestern Ontario agree well with C2H6 emission measurements from other boreal regions, and are relatively high compared to fires from other geographical regions. The ground-based CO and C2H6 observations were compared with outputs from the 3-D global chemical transport model GEOS-Chem, using the Fire Locating And Modeling of Burning Emissions (FLAMBE) inventory. Agreement within the

  10. NCEP-GTS Marine Observations in BUFR format

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Telecommunications System (GTS) is a major component of transmitting global meteorological data, consisting of both in situ and satellite observations....

  11. NCEP North American Regional Reanalysis (NARR), for 1979 to Present

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The North America Regional Reanalysis (NARR) Project is a reanalysis of historical observations using a 32-km version of the National Centers for Environmental...

  12. Tropical systematic and random error energetics based on NCEP ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Systematic error growth rate peak is observed at wavenumber 2 up to 4-day forecast then .... the influence of summer systematic error and ran- ... total exchange. When the error energy budgets are examined in spectral domain, one may ask ques- tions on the error growth at a certain wavenum- ber from its interaction with ...

  13. NCEP-GTS Marine Observations in IMMA format

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Telecommunications System (GTS) is a major component of transmitting global meteorological data, consisting of both in situ and satellite observations....

  14. Extreme Winds from the NCEP/NCAR Reanalysis Data

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Mann, Jakob

    2009-01-01

    wind. We examined extreme winds in different places where the strongest wind events are weather phenomena of different scales, including the mid-latitude lows in Denmark, channelling winds in the Gulf of Suez, typhoons in the western North Pacific, cyclones in the Caribbean Sea, local strong winds...

  15. 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

  16. Adjusting estimative prediction limits

    OpenAIRE

    Masao Ueki; Kaoru Fueda

    2007-01-01

    This note presents a direct adjustment of the estimative prediction limit to reduce the coverage error from a target value to third-order accuracy. The adjustment is asymptotically equivalent to those of Barndorff-Nielsen & Cox (1994, 1996) and Vidoni (1998). It has a simpler form with a plug-in estimator of the coverage probability of the estimative limit at the target value. Copyright 2007, Oxford University Press.

  17. Estimation of measurement variances

    International Nuclear Information System (INIS)

    Anon.

    1981-01-01

    In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time

  18. 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

  19. 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.

  20. Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

    Directory of Open Access Journals (Sweden)

    Mauro Rossi

    2017-12-01

    Full Text Available Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF are compared with the National Aeronautics and Space Administration (NASA Tropical Rainfall Measuring Mission (TRMM products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

  1. A Remote-Sensing Driven Tool for Estimating Crop Stress and Yields

    Directory of Open Access Journals (Sweden)

    Martha C. Anderson

    2013-07-01

    Full Text Available Biophysical crop simulation models are normally forced with precipitation data recorded with either gauges or ground-based radar. However, ground-based recording networks are not available at spatial and temporal scales needed to drive the models at many critical places on earth. An alternative would be to employ satellite-based observations of either precipitation or soil moisture. Satellite observations of precipitation are currently not considered capable of forcing the models with sufficient accuracy for crop yield predictions. However, deduction of soil moisture from space-based platforms is in a more advanced state than are precipitation estimates so that these data may be capable of forcing the models with better accuracy. In this study, a mature two-source energy balance model, the Atmosphere Land Exchange Inverse (ALEXI model, was used to deduce root zone soil moisture for an area of North Alabama, USA. The soil moisture estimates were used in turn to force the state-of-the-art Decision Support System for Agrotechnology Transfer (DSSAT crop simulation model. The study area consisted of a mixture of rainfed and irrigated cornfields. The results indicate that the model forced with the ALEXI moisture estimates produced yield simulations that compared favorably with observed yields and with the rainfed model. The data appear to indicate that the ALEXI model did detect the soil moisture signal from the mixed rainfed/irrigation corn fields and this signal was of sufficient strength to produce adequate simulations of recorded yields over a 10 year period.

  2. 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 ...

  3. Cost function estimation

    DEFF Research Database (Denmark)

    Andersen, C K; Andersen, K; Kragh-Sørensen, P

    2000-01-01

    on these criteria, a two-part model was chosen. In this model, the probability of incurring any costs was estimated using a logistic regression, while the level of the costs was estimated in the second part of the model. The choice of model had a substantial impact on the predicted health care costs, e...

  4. 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

  5. Software cost estimation

    NARCIS (Netherlands)

    Heemstra, F.J.; Heemstra, F.J.

    1993-01-01

    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

  6. Coherence in quantum estimation

    Science.gov (United States)

    Giorda, Paolo; Allegra, Michele

    2018-01-01

    The geometry of quantum states provides a unifying framework for estimation processes based on quantum probes, and it establishes the ultimate bounds of the achievable precision. We show a relation between the statistical distance between infinitesimally close quantum states and the second order variation of the coherence of the optimal measurement basis with respect to the state of the probe. In quantum phase estimation protocols, this leads to propose coherence as the relevant resource that one has to engineer and control to optimize the estimation precision. Furthermore, the main object of the theory i.e. the symmetric logarithmic derivative, in many cases allows one to identify a proper factorization of the whole Hilbert space in two subsystems. The factorization allows one to discuss the role of coherence versus correlations in estimation protocols; to show how certain estimation processes can be completely or effectively described within a single-qubit subsystem; and to derive lower bounds for the scaling of the estimation precision with the number of probes used. We illustrate how the framework works for both noiseless and noisy estimation procedures, in particular those based on multi-qubit GHZ-states. Finally we succinctly analyze estimation protocols based on zero-temperature critical behavior. We identify the coherence that is at the heart of their efficiency, and we show how it exhibits the non-analyticities and scaling behavior proper of a large class of quantum phase transitions.

  7. Overconfidence in Interval Estimates

    Science.gov (United States)

    Soll, Jack B.; Klayman, Joshua

    2004-01-01

    Judges were asked to make numerical estimates (e.g., "In what year was the first flight of a hot air balloon?"). Judges provided high and low estimates such that they were X% sure that the correct answer lay between them. They exhibited substantial overconfidence: The correct answer fell inside their intervals much less than X% of the time. This…

  8. A MODIS-based analysis of the Val d'Agri Oil Center (South of Italy) thermal emission: an independent gas flaring estimation strategy

    Science.gov (United States)

    Pergola, Nicola; Faruolo, Mariapia; Irina, Coviello; Carolina, Filizzola; Teodosio, Lacava; Valerio, Tramutoli

    2014-05-01

    Different kinds of atmospheric pollution affect human health and the environment at local and global scale. The petroleum industry represents one of the most important environmental pollution sources, accounting for about 18% of well-to-wheels greenhouse gas (GHG) emissions. The main pollution source is represented by the flaring of gas, one of the most challenging energy and environmental problems facing the world today. The World Bank has estimated that 150 billion cubic meters of natural gas are being flared annually, that is equivalent to 30% of the European Union's gas consumption. Since 2002, satellite-based methodologies have shown their capability in providing independent and reliable estimation of gas flaring emissions, at both national and global scale. In this paper, for the first time, the potential of satellite data in estimating gas flaring volumes emitted from a single on-shore crude oil pre-treatment plant, i.e. the Ente Nazionale Idrocarburi (ENI) Val d'Agri Oil Center (COVA), located in the Basilicata Region (South of Italy), was assessed. Specifically, thirteen years of night-time Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired in the medium and thermal infrared (MIR and TIR, respectively) bands were processed. The Robust Satellite Techniques (RST) approach was implemented for identifying anomalous values of the signals under investigation (i.e. the MIR-TIR difference one), associated to the COVA flares emergency discharges. Then, the Fire Radiative Power (FRP), computed for the thermal anomalies previously identified, was correlated to the emitted gas flaring volumes, available for the COVA in the period 2003 - 2009, defining a satellite based regression model for estimating COVA gas flaring emitted volumes. The used strategy and the preliminary results of this analysis will be described in detail in this work.

  9. Adaptive Spectral Doppler Estimation

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jakobsson, Andreas; Jensen, Jørgen Arendt

    2009-01-01

    . The methods can also provide better quality of the estimated power spectral density (PSD) of the blood signal. Adaptive spectral estimation techniques are known to pro- vide good spectral resolution and contrast even when the ob- servation window is very short. The 2 adaptive techniques are tested......In this paper, 2 adaptive spectral estimation techniques are analyzed for spectral Doppler ultrasound. The purpose is to minimize the observation window needed to estimate the spectrogram to provide a better temporal resolution and gain more flexibility when designing the data acquisition sequence...... and compared with the averaged periodogram (Welch’s method). The blood power spectral capon (BPC) method is based on a standard minimum variance technique adapted to account for both averaging over slow-time and depth. The blood amplitude and phase estimation technique (BAPES) is based on finding a set...

  10. Optomechanical parameter estimation

    International Nuclear Information System (INIS)

    Ang, Shan Zheng; Tsang, Mankei; Harris, Glen I; Bowen, Warwick P

    2013-01-01

    We propose a statistical framework for the problem of parameter estimation from a noisy optomechanical system. The Cramér–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 Cramér–Rao bound most closely. Our analytic results are envisioned to be valuable to optomechanical experiment design, while the EM algorithm, with its ability to estimate most of the system parameters, is envisioned to be useful for optomechanical sensing, atomic magnetometry and fundamental tests of quantum mechanics. (paper)

  11. CHANNEL ESTIMATION TECHNIQUE

    DEFF Research Database (Denmark)

    2015-01-01

    A method includes determining a sequence of first coefficient estimates of a communication channel based on a sequence of pilots arranged according to a known pilot pattern and based on a receive signal, wherein the receive signal is based on the sequence of pilots transmitted over the communicat......A method includes determining a sequence of first coefficient estimates of a communication channel based on a sequence of pilots arranged according to a known pilot pattern and based on a receive signal, wherein the receive signal is based on the sequence of pilots transmitted over...... the communication channel. The method further includes determining a sequence of second coefficient estimates of the communication channel based on a decomposition of the first coefficient estimates in a dictionary matrix and a sparse vector of the second coefficient estimates, the dictionary matrix including...... filter characteristics of at least one known transceiver filter arranged in the communication channel....

  12. Blending Multiple Nitrogen Dioxide Data Sources for Neighborhood Estimates of Long-Term Exposure for Health Research.

    Science.gov (United States)

    Hanigan, Ivan C; Williamson, Grant J; Knibbs, Luke D; Horsley, Joshua; Rolfe, Margaret I; Cope, Martin; Barnett, Adrian G; Cowie, Christine T; Heyworth, Jane S; Serre, Marc L; Jalaludin, Bin; Morgan, Geoffrey G

    2017-11-07

    Exposure to traffic related nitrogen dioxide (NO 2 ) air pollution is associated with adverse health outcomes. Average pollutant concentrations for fixed monitoring sites are often used to estimate exposures for health studies, however these can be imprecise due to difficulty and cost of spatial modeling at the resolution of neighborhoods (e.g., a scale of tens of meters) rather than at a coarse scale (around several kilometers). The objective of this study was to derive improved estimates of neighborhood NO 2 concentrations by blending measurements with modeled predictions in Sydney, Australia (a low pollution environment). We implemented the Bayesian maximum entropy approach to blend data with uncertainty defined using informative priors. We compiled NO 2 data from fixed-site monitors, chemical transport models, and satellite-based land use regression models to estimate neighborhood annual average NO 2 . The spatial model produced a posterior probability density function of estimated annual average concentrations that spanned an order of magnitude from 3 to 35 ppb. Validation using independent data showed improvement, with root mean squared error improvement of 6% compared with the land use regression model and 16% over the chemical transport model. These estimates will be used in studies of health effects and should minimize misclassification bias.

  13. Radiation risk estimation

    International Nuclear Information System (INIS)

    Schull, W.J.; Texas Univ., Houston, TX

    1992-01-01

    Estimation of the risk of cancer following exposure to ionizing radiation remains largely empirical, and models used to adduce risk incorporate few, if any, of the advances in molecular biology of a past decade or so. These facts compromise the estimation risk where the epidemiological data are weakest, namely, at low doses and dose rates. Without a better understanding of the molecular and cellular events ionizing radiation initiates or promotes, it seems unlikely that this situation will improve. Nor will the situation improve without further attention to the identification and quantitative estimation of the effects of those host and environmental factors that enhance or attenuate risk. (author)

  14. 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...... the weak assumption of regular variation in the jump tails, along with in-fill asymptotic arguments for uniquely identifying the "large" jumps from the data. The estimation allows for very general dynamic dependencies in the jump tails, and does not restrict the continuous part of the process...... and the temporal variation in the stochastic volatility. On implementing the new estimation procedure with actual high-frequency data for the S&P 500 aggregate market portfolio, we find strong evidence for richer and more complex dynamic dependencies in the jump tails than hitherto entertained in the literature....

  15. Bridged Race Population Estimates

    Data.gov (United States)

    U.S. Department of Health & Human Services — Population estimates from "bridging" the 31 race categories used in Census 2000, as specified in the 1997 Office of Management and Budget (OMB) race and ethnicity...

  16. Estimation of measurement variances

    International Nuclear Information System (INIS)

    Jaech, J.L.

    1984-01-01

    The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented

  17. APLIKASI SPLINE ESTIMATOR TERBOBOT

    Directory of Open Access Journals (Sweden)

    I Nyoman Budiantara

    2001-01-01

    Full Text Available We considered the nonparametric regression model : Zj = X(tj + ej, j = 1,2,…,n, where X(tj is the regression curve. The random error ej are independently distributed normal with a zero mean and a variance s2/bj, bj > 0. The estimation of X obtained by minimizing a Weighted Least Square. The solution of this optimation is a Weighted Spline Polynomial. Further, we give an application of weigted spline estimator in nonparametric regression. Abstract in Bahasa Indonesia : Diberikan model regresi nonparametrik : Zj = X(tj + ej, j = 1,2,…,n, dengan X (tj kurva regresi dan ej sesatan random yang diasumsikan berdistribusi normal dengan mean nol dan variansi s2/bj, bj > 0. Estimasi kurva regresi X yang meminimumkan suatu Penalized Least Square Terbobot, merupakan estimator Polinomial Spline Natural Terbobot. Selanjutnya diberikan suatu aplikasi estimator spline terbobot dalam regresi nonparametrik. Kata kunci: Spline terbobot, Regresi nonparametrik, Penalized Least Square.

  18. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    the parameters of the model under the null hypothesis of the cointegration rank r = 1, 2, ..., p-1. This step provides consistent estimates of the cointegration degree, the cointegration vectors, the speed of adjustment to the equilibrium parameters and the common trends. In the second step we carry out a sup......-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...... to control for stochastic trend estimation effects from the first step. The critical values of the tests proposed depend only on the number of common trends under the null, p - r, and on the interval of the cointegration degrees b allowed, but not on the true cointegration degree b0. Hence, no additional...

  19. Estimation of spectral kurtosis

    Science.gov (United States)

    Sutawanir

    2017-03-01

    Rolling bearings are the most important elements in rotating machinery. Bearing frequently fall out of service for various reasons: heavy loads, unsuitable lubrications, ineffective sealing. Bearing faults may cause a decrease in performance. Analysis of bearing vibration signals has attracted attention in the field of monitoring and fault diagnosis. Bearing vibration signals give rich information for early detection of bearing failures. Spectral kurtosis, SK, is a parameter in frequency domain indicating how the impulsiveness of a signal varies with frequency. Faults in rolling bearings give rise to a series of short impulse responses as the rolling elements strike faults, SK potentially useful for determining frequency bands dominated by bearing fault signals. SK can provide a measure of the distance of the analyzed bearings from a healthy one. SK provides additional information given by the power spectral density (psd). This paper aims to explore the estimation of spectral kurtosis using short time Fourier transform known as spectrogram. The estimation of SK is similar to the estimation of psd. The estimation falls in model-free estimation and plug-in estimator. Some numerical studies using simulations are discussed to support the methodology. Spectral kurtosis of some stationary signals are analytically obtained and used in simulation study. Kurtosis of time domain has been a popular tool for detecting non-normality. Spectral kurtosis is an extension of kurtosis in frequency domain. The relationship between time domain and frequency domain analysis is establish through power spectrum-autocovariance Fourier transform. Fourier transform is the main tool for estimation in frequency domain. The power spectral density is estimated through periodogram. In this paper, the short time Fourier transform of the spectral kurtosis is reviewed, a bearing fault (inner ring and outer ring) is simulated. The bearing response, power spectrum, and spectral kurtosis are plotted to

  20. Approximate Bayesian recursive estimation

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav

    2014-01-01

    Roč. 285, č. 1 (2014), s. 100-111 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Approximate parameter estimation * Bayesian recursive estimation * Kullback–Leibler divergence * Forgetting Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.038, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/karny-0425539.pdf

  1. Ranking as parameter estimation

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Guy, Tatiana Valentine

    2009-01-01

    Roč. 4, č. 2 (2009), s. 142-158 ISSN 1745-7645 R&D Projects: GA MŠk 2C06001; GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : ranking * Bayesian estimation * negotiation * modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/AS/karny- ranking as parameter estimation.pdf

  2. Maximal combustion temperature estimation

    International Nuclear Information System (INIS)

    Golodova, E; Shchepakina, E

    2006-01-01

    This work is concerned with the phenomenon of delayed loss of stability and the estimation of the maximal temperature of safe combustion. Using the qualitative theory of singular perturbations and canard techniques we determine the maximal temperature on the trajectories located in the transition region between the slow combustion regime and the explosive one. This approach is used to estimate the maximal temperature of safe combustion in multi-phase combustion models

  3. Spatial and decadal variations in satellite-based terrestrial ...

    Indian Academy of Sciences (India)

    Zhaolu Zhang

    2017-12-02

    Dec 2, 2017 ... State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, ... factors. Remote sensing has provided many land surface biophysical ...... at the landscape scale; Can. J. Rem.

  4. Proposed systems configurations for a satellite based ISDN

    Science.gov (United States)

    Capece, M.; Pavesi, B.; Tozzi, P.; Galligan, K. P.

    This paper summarizes concepts developed during a study for the ESA in which the evolution of ISDN capability and the impact in the satellite land mobile area are examined. Following the progressive steps of the expected ISDN implementation and the potential market penetration, a space based system capable of satisfying particular user services classes has been investigated. The approach used is to establish a comparison between the requirements of potential mobile users and the services already envisaged by ISDN, identifying the service subclasses that might be adopted in a mobile environment through a satellite system. Two system alternatives, with different ISDN compatibility, have been identified. The first option allows a partial compatibility, by providing the central stations of the earth segment with suitable interface units. The second option permits a full integration, operating on the satellite on-board capabilities.

  5. A Satellite-Based Lagrangian View on Phytoplankton Dynamics

    Science.gov (United States)

    Lehahn, Yoav; d'Ovidio, Francesco; Koren, Ilan

    2018-01-01

    The well-lit upper layer of the open ocean is a dynamical environment that hosts approximately half of global primary production. In the remote parts of this environment, distant from the coast and from the seabed, there is no obvious spatially fixed reference frame for describing the dynamics of the microscopic drifting organisms responsible for this immense production of organic matter—the phytoplankton. Thus, a natural perspective for studying phytoplankton dynamics is to follow the trajectories of water parcels in which the organisms are embedded. With the advent of satellite oceanography, this Lagrangian perspective has provided valuable information on different aspects of phytoplankton dynamics, including bloom initiation and termination, spatial distribution patterns, biodiversity, export of carbon to the deep ocean, and, more recently, bottom-up mechanisms that affect the distribution and behavior of higher-trophic-level organisms. Upcoming submesoscale-resolving satellite observations and swarms of autonomous platforms open the way to the integration of vertical dynamics into the Lagrangian view of phytoplankton dynamics.

  6. Satellite-based technique for nowcasting of thunderstorms over ...

    Indian Academy of Sciences (India)

    Suman Goyal

    2017-08-31

    Aug 31, 2017 ... 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 ... of actual development of cumulonimbus clouds, ... MCS over Indian region using Infrared Channel ... (2016) based on case study of.

  7. Tracking target objects orbiting earth using satellite-based telescopes

    Science.gov (United States)

    De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

    2014-10-14

    A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

  8. Creating a Satellite-Based Record of Tropospheric Ozone

    Science.gov (United States)

    Oetjen, Hilke; Payne, Vivienne H.; Kulawik, Susan S.; Eldering, Annmarie; Worden, John; Edwards, David P.; Francis, Gene L.; Worden, Helen M.

    2013-01-01

    The TES retrieval algorithm has been applied to IASI radiances. We compare the retrieved ozone profiles with ozone sonde profiles for mid-latitudes for the year 2008. We find a positive bias in the IASI ozone profiles in the UTLS region of up to 22 %. The spatial coverage of the IASI instrument allows sampling of effectively the same air mass with several IASI scenes simultaneously. Comparisons of the root-mean-square of an ensemble of IASI profiles to theoretical errors indicate that the measurement noise and the interference of temperature and water vapour on the retrieval together mostly explain the empirically derived random errors. The total degrees of freedom for signal of the retrieval for ozone are 3.1 +/- 0.2 and the tropospheric degrees of freedom are 1.0 +/- 0.2 for the described cases. IASI ozone profiles agree within the error bars with coincident ozone profiles derived from a TES stare sequence for the ozone sonde station at Bratt's Lake (50.2 deg N, 104.7 deg W).

  9. A Satellite Based Fog Study of the Korean Peninsula

    National Research Council Canada - National Science Library

    McDonald, David K

    2007-01-01

    Fog has always been a difficult phenomenon to forecast. Its unpredictable nature and propensity to quickly decrease visibilities have had adverse effects on military operations for many years across the Korean peninsula...

  10. Potential markets for a satellite-based mobile communications system

    Science.gov (United States)

    Jamieson, W. M.; Peet, C. S.; Bengston, R. J.

    1976-01-01

    The objective of the study was to define the market needs for improved land mobile communications systems. Within the context of this objective, the following goals were set: (1) characterize the present mobile communications industry; (2) determine the market for an improved system for mobile communications; and (3) define the system requirements as seen from the potential customer's viewpoint. The scope of the study was defined by the following parameters: (1) markets were confined to U.S. and Canada; (2) range of operation generally exceeded 20 miles, but this was not restrictive; (3) the classes of potential users considered included all private sector users, and non-military public sector users; (4) the time span examined was 1975 to 1985; and (5) highly localized users were generally excluded - e.g., taxicabs, and local paging.

  11. Validation of a satellite-based cyclogenesis technique over the ...

    Indian Academy of Sciences (India)

    its intensification into a TC is very essential for the management of TC disaster. .... cast System (GFS) data fields as well as con- ... score and relative operating characteristic, showed ..... The authors acknowledge the support provided by.

  12. Satellite -Based Networks for U-Health & U-Learning

    Science.gov (United States)

    Graschew, G.; Roelofs, T. A.; Rakowsky, S.; Schlag, P. M.

    2008-08-01

    The use of modern Information and Communication Technologies (ICT) as enabling tools for healthcare services (eHealth) introduces new ways of creating ubiquitous access to high-level medical care for all, anytime and anywhere (uHealth). Satellite communication constitutes one of the most flexible methods of broadband communication offering high reliability and cost-effectiveness of connections meeting telemedicine communication requirements. Global networks and the use of computers for educational purposes stimulate and support the development of virtual universities for e-learning. Especially real-time interactive applications can play an important role in tailored and personalised services.

  13. A Satellite-Based Lagrangian View on Phytoplankton Dynamics.

    Science.gov (United States)

    Lehahn, Yoav; d'Ovidio, Francesco; Koren, Ilan

    2018-01-03

    The well-lit upper layer of the open ocean is a dynamical environment that hosts approximately half of global primary production. In the remote parts of this environment, distant from the coast and from the seabed, there is no obvious spatially fixed reference frame for describing the dynamics of the microscopic drifting organisms responsible for this immense production of organic matter-the phytoplankton. Thus, a natural perspective for studying phytoplankton dynamics is to follow the trajectories of water parcels in which the organisms are embedded. With the advent of satellite oceanography, this Lagrangian perspective has provided valuable information on different aspects of phytoplankton dynamics, including bloom initiation and termination, spatial distribution patterns, biodiversity, export of carbon to the deep ocean, and, more recently, bottom-up mechanisms that affect the distribution and behavior of higher-trophic-level organisms. Upcoming submesoscale-resolving satellite observations and swarms of autonomous platforms open the way to the integration of vertical dynamics into the Lagrangian view of phytoplankton dynamics.

  14. Validation of satellite based precipitation over diverse topography of Pakistan

    Science.gov (United States)

    Iqbal, Muhammad Farooq; Athar, H.

    2018-03-01

    This study evaluates the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product data with 0.25° × 0.25° spatial and post-real-time 3 h temporal resolution using point-based Surface Precipitation Gauge (SPG) data from 40 stations, for the period 1998-2013, and using gridded Asian Precipitation ˗ Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) data abbreviated as APH data with 0.25° × 0.25° spatial and daily temporal resolution for the period 1998-2007, over vulnerable and data sparse regions of Pakistan (24-37° N and 62-75° E). To evaluate the performance of TMPA relative to SPG and APH, four commonly used statistical indicator metrics including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC) are employed on daily, monthly, seasonal as well as on annual timescales. The TMPA slightly overestimated both SPG and APH at daily, monthly, and annual timescales, however close results were obtained between TMPA and SPG as compared to those between TMPA and APH, on the same timescale. The TMPA overestimated both SPG and APH during the Pre-Monsoon and Monsoon seasons, whereas it underestimated during the Post-Monsoon and Winter seasons, with different magnitudes. Agreement between TMPA and SPG was good in plain and medium elevation regions, whereas TMPA overestimated APH in 31 stations. The magnitudes of MAE and RMSE were high at daily timescale as compared to monthly and annual timescales. Relatively large MAE was observed in stations located over high elevation regions, whereas minor MAE was recorded in plain area stations at daily, monthly, and annual timescales. A strong positive linear relationship between TMPA and SPG was established at monthly (0.98), seasonal (0.93 to 0.98) and annual (0.97) timescales. Precipitation increased with the increase of elevation, and not only elevation but latitude also affected the intensity and amount of precipitation in Pakistan. It is evident that TMPA overestimates SPG in some regions and seasons and underestimates in other regions and seasons. It is thus determined from the current study that TMPA gives better results on annual, seasonal, and monthly timescales as compared to daily timescale. The TMPA might be used in all the four seasons including Winter, Pre-Monsoon, Monsoon, and Post-Monsoon. The TMPA mostly underestimates both SPG and APH in high elevation regions, whereas in plain and medium elevation regions it gives better results. This study concludes that TMPA can be a good substitute of SPG for water resource management in plain and medium elevation regions in central and northern parts of Pakistan, during all four seasons.

  15. Estimation of Atmospheric Methane Surface Fluxes Using a Global 3-D Chemical Transport Model

    Science.gov (United States)

    Chen, Y.; Prinn, R.

    2003-12-01

    Accurate determination of atmospheric methane surface fluxes is an important and challenging problem in global biogeochemical cycles. We use inverse modeling to estimate annual, seasonal, and interannual CH4 fluxes between 1996 and 2001. The fluxes include 7 time-varying seasonal (3 wetland, rice, and 3 biomass burning) and 3 steady aseasonal (animals/waste, coal, and gas) global processes. To simulate atmospheric methane, we use the 3-D chemical transport model MATCH driven by NCEP reanalyzed observed winds at a resolution of T42 ( ˜2.8° x 2.8° ) in the horizontal and 28 levels (1000 - 3 mb) in the vertical. By combining existing datasets of individual processes, we construct a reference emissions field that represents our prior guess of the total CH4 surface flux. For the methane sink, we use a prescribed, annually-repeating OH field scaled to fit methyl chloroform observations. MATCH is used to produce both the reference run from the reference emissions, and the time-dependent sensitivities that relate individual emission processes to observations. The observational data include CH4 time-series from ˜15 high-frequency (in-situ) and ˜50 low-frequency (flask) observing sites. Most of the high-frequency data, at a time resolution of 40-60 minutes, have not previously been used in global scale inversions. In the inversion, the high-frequency data generally have greater weight than the weekly flask data because they better define the observational monthly means. The Kalman Filter is used as the optimal inversion technique to solve for emissions between 1996-2001. At each step in the inversion, new monthly observations are utilized and new emissions estimates are produced. The optimized emissions represent deviations from the reference emissions that lead to a better fit to the observations. The seasonal processes are optimized for each month, and contain the methane seasonality and interannual variability. The aseasonal processes, which are less variable, are

  16. Evaluations of carbon fluxes estimated by top-down and bottom-up approaches

    Science.gov (United States)

    Murakami, K.; Sasai, T.; Kato, S.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.; Nasahara, K.; Matsunaga, T.

    2013-12-01

    There are two types of estimating carbon fluxes using satellite observation data, and these are referred to as top-down and bottom-up approaches. Many uncertainties are however still remain in these carbon flux estimations, because the true values of carbon flux are still unclear and estimations vary according to the type of the model (e.g. a transport model, a process based model) and input data. The CO2 fluxes in these approaches are estimated by using different satellite data such as the distribution of CO2 concentration in the top-down approach and the land cover information (e.g. leaf area, surface temperature) in the bottom-up approach. The satellite-based CO2 flux estimations with reduced uncertainty can be used efficiently for identifications of large emission area and carbon stocks of forest area. In this study, we evaluated the carbon flux estimates from two approaches by comparing with each other. The Greenhouse gases Observing SATellite (GOSAT) has been observing atmospheric CO2 concentrations since 2009. GOSAT L4A data product is the monthly CO2 flux estimations for 64 sub-continental regions and is estimated by using GOSAT FTS SWIR L2 XCO2 data and atmospheric tracer transport model. We used GOSAT L4A CO2 flux as top-down approach estimations and net ecosystem productions (NEP) estimated by the diagnostic type biosphere model BEAMS as bottom-up approach estimations. BEAMS NEP is only natural land CO2 flux, so we used GOSAT L4A CO2 flux after subtraction of anthropogenic CO2 emissions and oceanic CO2 flux. We compared with two approach in temperate north-east Asia region. This region is covered by grassland and crop land (about 60 %), forest (about 20 %) and bare ground (about 20 %). The temporal variation for one year period was indicated similar trends between two approaches. Furthermore we show the comparison of CO2 flux estimations in other sub-continental regions.

  17. Estimation of crop water requirements using remote sensing for operational water resources management

    Science.gov (United States)

    Vasiliades, Lampros; Spiliotopoulos, Marios; Tzabiras, John; Loukas, Athanasios; Mylopoulos, Nikitas

    2015-06-01

    An integrated modeling system, developed in the framework of "Hydromentor" research project, is applied to evaluate crop water requirements for operational water resources management at Lake Karla watershed, Greece. The framework includes coupled components for operation of hydrotechnical projects (reservoir operation and irrigation works) and estimation of agricultural water demands at several spatial scales using remote sensing. The study area was sub-divided into irrigation zones based on land use maps derived from Landsat 5 TM images for the year 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) was used to derive actual evapotranspiration (ET) and crop coefficient (ETrF) values from Landsat TM imagery. Agricultural water needs were estimated using the FAO method for each zone and each control node of the system for a number of water resources management strategies. Two operational strategies of hydro-technical project development (present situation without operation of the reservoir and future situation with the operation of the reservoir) are coupled with three water demand strategies. In total, eight (8) water management strategies are evaluated and compared. The results show that, under the existing operational water resources management strategies, the crop water requirements are quite large. However, the operation of the proposed hydro-technical projects in Lake Karla watershed coupled with water demand management measures, like improvement of existing water distribution systems, change of irrigation methods, and changes of crop cultivation could alleviate the problem and lead to sustainable and ecological use of water resources in the study area.

  18. Estimation of daily global solar irradiation by coupling ground measurements of bright sunshine hours to satellite imagery

    International Nuclear Information System (INIS)

    Ener Rusen, Selmin; Hammer, Annette; Akinoglu, Bulent G.

    2013-01-01

    In this work, the current version of the satellite-based HELIOSAT method and ground-based linear Ångström–Prescott type relations are used in combination. The first approach is based on the use of a correlation between daily bright sunshine hours (s) and cloud index (n). In the second approach a new correlation is proposed between daily solar irradiation and daily data of s and n which is based on a physical parameterization. The performances of the proposed two combined models are tested against conventional methods. We test the use of obtained correlation coefficients for nearby locations. Our results show that the use of sunshine duration together with the cloud index is quite satisfactory in the estimation of daily horizontal global solar irradiation. We propose to use the new approaches to estimate daily global irradiation when the bright sunshine hours data is available for the location of interest, provided that some regression coefficients are determined using the data of a nearby station. In addition, if surface data for a close location does not exist then it is recommended to use satellite models like HELIOSAT or the new approaches instead the Ångström type models. - Highlights: • Satellite imagery together with surface measurements in solar radiation estimation. • The new coupled and conventional models (satellite and ground-based) are analyzed. • New models result in highly accurate estimation of daily global solar irradiation

  19. Estimating Gross Primary Production in Cropland with High Spatial and Temporal Scale Remote Sensing Data

    Science.gov (United States)

    Lin, S.; Li, J.; Liu, Q.

    2018-04-01

    Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.

  20. Uncertainty estimation of the velocity model for stations of the TrigNet GPS network

    Science.gov (United States)

    Hackl, M.; Malservisi, R.; Hugentobler, U.

    2010-12-01

    Satellite based geodetic techniques - above all GPS - provide an outstanding tool to measure crustal motions. They are widely used to derive geodetic velocity models that are applied in geodynamics to determine rotations of tectonic blocks, to localize active geological features, and to estimate rheological properties of the crust and the underlying asthenosphere. However, it is not a trivial task to derive GPS velocities and their uncertainties from positioning time series. In general time series are assumed to be represented by linear models (sometimes offsets, annual, and semi-annual signals are included) and noise. It has been shown that error models accounting only for white noise tend to underestimate the uncertainties of rates derived from long time series and that different colored noise components (flicker noise, random walk, etc.) need to be considered. However, a thorough error analysis including power spectra analyses and maximum likelihood estimates is computationally expensive and is usually not carried out for every site, but the uncertainties are scaled by latitude dependent factors. Analyses of the South Africa continuous GPS network TrigNet indicate that the scaled uncertainties overestimate the velocity errors. So we applied a method similar to the Allan Variance that is commonly used in the estimation of clock uncertainties and is able to account for time dependent probability density functions (colored noise) to the TrigNet time series. Comparisons with synthetic data show that the noise can be represented quite well by a power law model in combination with a seasonal signal in agreement with previous studies, which allows for a reliable estimation of the velocity error. Finally, we compared these estimates to the results obtained by spectral analyses using CATS. Small differences may originate from non-normal distribution of the noise.

  1. Single snapshot DOA estimation

    Science.gov (United States)

    Häcker, P.; Yang, B.

    2010-10-01

    In array signal processing, direction of arrival (DOA) estimation has been studied for decades. Many algorithms have been proposed and their performance has been studied thoroughly. Yet, most of these works are focused on the asymptotic case of a large number of snapshots. In automotive radar applications like driver assistance systems, however, only a small number of snapshots of the radar sensor array or, in the worst case, a single snapshot is available for DOA estimation. In this paper, we investigate and compare different DOA estimators with respect to their single snapshot performance. The main focus is on the estimation accuracy and the angular resolution in multi-target scenarios including difficult situations like correlated targets and large target power differences. We will show that some algorithms lose their ability to resolve targets or do not work properly at all. Other sophisticated algorithms do not show a superior performance as expected. It turns out that the deterministic maximum likelihood estimator is a good choice under these hard conditions.

  2. Thermodynamic estimation: Ionic materials

    International Nuclear Information System (INIS)

    Glasser, Leslie

    2013-01-01

    Thermodynamics establishes equilibrium relations among thermodynamic parameters (“properties”) and delineates the effects of variation of the thermodynamic functions (typically temperature and pressure) on those parameters. However, classical thermodynamics does not provide values for the necessary thermodynamic properties, which must be established by extra-thermodynamic means such as experiment, theoretical calculation, or empirical estimation. While many values may be found in the numerous collected tables in the literature, these are necessarily incomplete because either the experimental measurements have not been made or the materials may be hypothetical. The current paper presents a number of simple and relible estimation methods for thermodynamic properties, principally for ionic materials. The results may also be used as a check for obvious errors in published values. The estimation methods described are typically based on addition of properties of individual ions, or sums of properties of neutral ion groups (such as “double” salts, in the Simple Salt Approximation), or based upon correlations such as with formula unit volumes (Volume-Based Thermodynamics). - Graphical abstract: Thermodynamic properties of ionic materials may be readily estimated by summation of the properties of individual ions, by summation of the properties of ‘double salts’, and by correlation with formula volume. Such estimates may fill gaps in the literature, and may also be used as checks of published values. This simplicity arises from exploitation of the fact that repulsive energy terms are of short range and very similar across materials, while coulombic interactions provide a very large component of the attractive energy in ionic systems. Display Omitted - Highlights: • Estimation methods for thermodynamic properties of ionic materials are introduced. • Methods are based on summation of single ions, multiple salts, and correlations. • Heat capacity, entropy

  3. Distribution load estimation - DLE

    Energy Technology Data Exchange (ETDEWEB)

    Seppaelae, A. [VTT Energy, Espoo (Finland)

    1996-12-31

    The load research project has produced statistical information in the form of load models to convert the figures of annual energy consumption to hourly load values. The reliability of load models is limited to a certain network because many local circumstances are different from utility to utility and time to time. Therefore there is a need to make improvements in the load models. Distribution load estimation (DLE) is the method developed here to improve load estimates from the load models. The method is also quite cheap to apply as it utilises information that is already available in SCADA systems

  4. Generalized estimating equations

    CERN Document Server

    Hardin, James W

    2002-01-01

    Although powerful and flexible, the method of generalized linear models (GLM) is limited in its ability to accurately deal with longitudinal and clustered data. Developed specifically to accommodate these data types, the method of Generalized Estimating Equations (GEE) extends the GLM algorithm to accommodate the correlated data encountered in health research, social science, biology, and other related fields.Generalized Estimating Equations provides the first complete treatment of GEE methodology in all of its variations. After introducing the subject and reviewing GLM, the authors examine th

  5. Digital Quantum Estimation

    Science.gov (United States)

    Hassani, Majid; Macchiavello, Chiara; Maccone, Lorenzo

    2017-11-01

    Quantum metrology calculates the ultimate precision of all estimation strategies, measuring what is their root-mean-square error (RMSE) and their Fisher information. Here, instead, we ask how many bits of the parameter we can recover; namely, we derive an information-theoretic quantum metrology. In this setting, we redefine "Heisenberg bound" and "standard quantum limit" (the usual benchmarks in the quantum estimation theory) and show that the former can be attained only by sequential strategies or parallel strategies that employ entanglement among probes, whereas parallel-separable strategies are limited by the latter. We highlight the differences between this setting and the RMSE-based one.

  6. Distribution load estimation - DLE

    Energy Technology Data Exchange (ETDEWEB)

    Seppaelae, A [VTT Energy, Espoo (Finland)

    1997-12-31

    The load research project has produced statistical information in the form of load models to convert the figures of annual energy consumption to hourly load values. The reliability of load models is limited to a certain network because many local circumstances are different from utility to utility and time to time. Therefore there is a need to make improvements in the load models. Distribution load estimation (DLE) is the method developed here to improve load estimates from the load models. The method is also quite cheap to apply as it utilises information that is already available in SCADA systems

  7. Derivation and analysis of a high-resolution estimate of global permafrost zonation

    Directory of Open Access Journals (Sweden)

    S. Gruber

    2012-02-01

    Full Text Available Permafrost underlies much of Earth's surface and interacts with climate, eco-systems and human systems. It is a complex phenomenon controlled by climate and (sub- surface properties and reacts to change with variable delay. Heterogeneity and sparse data challenge the modeling of its spatial distribution. Currently, there is no data set to adequately inform global studies of permafrost. The available data set for the Northern Hemisphere is frequently used for model evaluation, but its quality and consistency are difficult to assess. Here, a global model of permafrost extent and dataset of permafrost zonation are presented and discussed, extending earlier studies by including the Southern Hemisphere, by consistent data and methods, by attention to uncertainty and scaling. Established relationships between air temperature and the occurrence of permafrost are re-formulated into a model that is parametrized using published estimates. It is run with a high-resolution (<1 km global elevation data and air temperatures based on the NCAR-NCEP reanalysis and CRU TS 2.0. The resulting data provide more spatial detail and a consistent extrapolation to remote regions, while aggregated values resemble previous studies. The estimated uncertainties affect regional patterns and aggregate number, and provide interesting insight. The permafrost area, i.e. the actual surface area underlain by permafrost, north of 60° S is estimated to be 13–18 × 106 km2 or 9–14 % of the exposed land surface. The global permafrost area including Antarctic and sub-sea permafrost is estimated to be 16–21 × 106 km2. The global permafrost region, i.e. the exposed land surface below which some permafrost can be expected, is estimated to be 22 ± 3 × 106 km2. A large proportion of this exhibits considerable topography and spatially-discontinuous permafrost, underscoring the importance of attention to scaling issues

  8. Are Low-order Covariance Estimates Useful in Error Analyses?

    Science.gov (United States)

    Baker, D. F.; Schimel, D.

    2005-12-01

    Atmospheric trace gas inversions, using modeled atmospheric transport to infer surface sources and sinks from measured concentrations, are most commonly done using least-squares techniques that return not only an estimate of the state (the surface fluxes) but also the covariance matrix describing the uncertainty in that estimate. Besides allowing one to place error bars around the estimate, the covariance matrix may be used in simulation studies to learn what uncertainties would be expected from various hypothetical observing strategies. This error analysis capability is routinely used in designing instrumentation, measurement campaigns, and satellite observing strategies. For example, Rayner, et al (2002) examined the ability of satellite-based column-integrated CO2 measurements to constrain monthly-average CO2 fluxes for about 100 emission regions using this approach. Exact solutions for both state vector and covariance matrix become computationally infeasible, however, when the surface fluxes are solved at finer resolution (e.g., daily in time, under 500 km in space). It is precisely at these finer scales, however, that one would hope to be able to estimate fluxes using high-density satellite measurements. Non-exact estimation methods such as variational data assimilation or the ensemble Kalman filter could be used, but they achieve their computational savings by obtaining an only approximate state estimate and a low-order approximation of the true covariance. One would like to be able to use this covariance matrix to do the same sort of error analyses as are done with the full-rank covariance, but is it correct to do so? Here we compare uncertainties and `information content' derived from full-rank covariance matrices obtained from a direct, batch least squares inversion to those from the incomplete-rank covariance matrices given by a variational data assimilation approach solved with a variable metric minimization technique (the Broyden-Fletcher- Goldfarb

  9. Estimating Delays In ASIC's

    Science.gov (United States)

    Burke, Gary; Nesheiwat, Jeffrey; Su, Ling

    1994-01-01

    Verification is important aspect of process of designing application-specific integrated circuit (ASIC). Design must not only be functionally accurate, but must also maintain correct timing. IFA, Intelligent Front Annotation program, assists in verifying timing of ASIC early in design process. This program speeds design-and-verification cycle by estimating delays before layouts completed. Written in C language.

  10. Organizational flexibility estimation

    OpenAIRE

    Komarynets, Sofia

    2013-01-01

    By the help of parametric estimation the evaluation scale of organizational flexibility and its parameters was formed. Definite degrees of organizational flexibility and its parameters for the Lviv region enterprises were determined. Grouping of the enterprises under the existing scale was carried out. Special recommendations to correct the enterprises behaviour were given.

  11. On Functional Calculus Estimates

    NARCIS (Netherlands)

    Schwenninger, F.L.

    2015-01-01

    This thesis presents various results within the field of operator theory that are formulated in estimates for functional calculi. Functional calculus is the general concept of defining operators of the form $f(A)$, where f is a function and $A$ is an operator, typically on a Banach space. Norm

  12. Estimation of vector velocity

    DEFF Research Database (Denmark)

    2000-01-01

    Using a pulsed ultrasound field, the two-dimensional velocity vector can be determined with the invention. The method uses a transversally modulated ultrasound field for probing the moving medium under investigation. A modified autocorrelation approach is used in the velocity estimation. The new...

  13. Quantifying IT estimation risks

    NARCIS (Netherlands)

    Kulk, G.P.; Peters, R.J.; Verhoef, C.

    2009-01-01

    A statistical method is proposed for quantifying the impact of factors that influence the quality of the estimation of costs for IT-enabled business projects. We call these factors risk drivers as they influence the risk of the misestimation of project costs. The method can effortlessly be

  14. Numerical Estimation in Preschoolers

    Science.gov (United States)

    Berteletti, Ilaria; Lucangeli, Daniela; Piazza, Manuela; Dehaene, Stanislas; Zorzi, Marco

    2010-01-01

    Children's sense of numbers before formal education is thought to rely on an approximate number system based on logarithmically compressed analog magnitudes that increases in resolution throughout childhood. School-age children performing a numerical estimation task have been shown to increasingly rely on a formally appropriate, linear…

  15. Estimating Gender Wage Gaps

    Science.gov (United States)

    McDonald, Judith A.; Thornton, Robert J.

    2011-01-01

    Course research projects that use easy-to-access real-world data and that generate findings with which undergraduate students can readily identify are hard to find. The authors describe a project that requires students to estimate the current female-male earnings gap for new college graduates. The project also enables students to see to what…

  16. Fast fundamental frequency estimation

    DEFF Research Database (Denmark)

    Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm; Jensen, Jesper Rindom

    2017-01-01

    Modelling signals as being periodic is common in many applications. Such periodic signals can be represented by a weighted sum of sinusoids with frequencies being an integer multiple of the fundamental frequency. Due to its widespread use, numerous methods have been proposed to estimate the funda...

  17. On Gnostical Estimates

    Czech Academy of Sciences Publication Activity Database

    Fabián, Zdeněk

    2017-01-01

    Roč. 56, č. 2 (2017), s. 125-132 ISSN 0973-1377 Institutional support: RVO:67985807 Keywords : gnostic theory * statistics * robust estimates Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability http://www.ceser.in/ceserp/index.php/ijamas/article/view/4707

  18. Estimation of morbidity effects

    International Nuclear Information System (INIS)

    Ostro, B.

    1994-01-01

    Many researchers have related exposure to ambient air pollution to respiratory morbidity. To be included in this review and analysis, however, several criteria had to be met. First, a careful study design and a methodology that generated quantitative dose-response estimates were required. Therefore, there was a focus on time-series regression analyses relating daily incidence of morbidity to air pollution in a single city or metropolitan area. Studies that used weekly or monthly average concentrations or that involved particulate measurements in poorly characterized metropolitan areas (e.g., one monitor representing a large region) were not included in this review. Second, studies that minimized confounding ad omitted variables were included. For example, research that compared two cities or regions and characterized them as 'high' and 'low' pollution area were not included because of potential confounding by other factors in the respective areas. Third, concern for the effects of seasonality and weather had to be demonstrated. This could be accomplished by either stratifying and analyzing the data by season, by examining the independent effects of temperature and humidity, and/or by correcting the model for possible autocorrelation. A fourth criterion for study inclusion was that the study had to include a reasonably complete analysis of the data. Such analysis would include an careful exploration of the primary hypothesis as well as possible examination of te robustness and sensitivity of the results to alternative functional forms, specifications, and influential data points. When studies reported the results of these alternative analyses, the quantitative estimates that were judged as most representative of the overall findings were those that were summarized in this paper. Finally, for inclusion in the review of particulate matter, the study had to provide a measure of particle concentration that could be converted into PM10, particulate matter below 10

  19. Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

    Science.gov (United States)

    Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

    2008-07-01

    SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

  20. Uncertainty estimation of the velocity model for the TrigNet GPS network

    Science.gov (United States)

    Hackl, Matthias; Malservisi, Rocco; Hugentobler, Urs; Wonnacott, Richard

    2010-05-01

    Satellite based geodetic techniques - above all GPS - provide an outstanding tool to measure crustal motions. They are widely used to derive geodetic velocity models that are applied in geodynamics to determine rotations of tectonic blocks, to localize active geological features, and to estimate rheological properties of the crust and the underlying asthenosphere. However, it is not a trivial task to derive GPS velocities and their uncertainties from positioning time series. In general time series are assumed to be represented by linear models (sometimes offsets, annual, and semi-annual signals are included) and noise. It has been shown that models accounting only for white noise tend to underestimate the uncertainties of rates derived from long time series and that different colored noise components (flicker noise, random walk, etc.) need to be considered. However, a thorough error analysis including power spectra analyses and maximum likelihood estimates is quite demanding and are usually not carried out for every site, but the uncertainties are scaled by latitude dependent factors. Analyses of the South Africa continuous GPS network TrigNet indicate that the scaled uncertainties overestimate the velocity errors. So we applied a method similar to the Allan Variance that is commonly used in the estimation of clock uncertainties and is able to account for time dependent probability density functions (colored noise) to the TrigNet time series. Finally, we compared these estimates to the results obtained by spectral analyses using CATS. Comparisons with synthetic data show that the noise can be represented quite well by a power law model in combination with a seasonal signal in agreement with previous studies.

  1. Estimating Field Scale Crop Evapotranspiration using Landsat and MODIS Satellite Observations

    Science.gov (United States)

    Wong, A.; Jin, Y.; Snyder, R. L.; Daniele, Z.; Gao, F.

    2016-12-01

    Irrigation accounts for 80% of human freshwater consumption, and most of it return to the atmosphere through Evapotranspiration (ET). Given the challenges of already-stressed water resources and ground water regulation in California, a cost-effective, timely, and consistent spatial estimate of crop ET, from the farm to watershed level, is becoming increasingly important. The Priestley-Taylor (PT) approach, calibrated with field data and driven by satellite observations, shows great promise for accurate ET estimates across diverse ecosystems. We here aim to improve the robustness of the PT approach in agricultural lands, to enable growers and farm managers to tailor irrigation management based on in-field spatial variability and in-season variation. We optimized the PT coefficients for each crop type with available ET measurements from eddy covariance towers and/or surface renewal stations at six crop fields (Alfalfa, Almond, Citrus, Corn, Pistachio and Rice) in California. Good agreement was found between satellite-based estimates and field measurements of net radiation, with a RMSE of less than 36 W m-2. The crop type specific optimization performed well, with a RMSE of 30 W m-2 and a correlation of 0.81 for predicted daily latent heat flux. The calibrated algorithm was used to estimate ET at 30 m resolution over the Sacramento-San Joaquin Delta region for 2015 water year. It captures well the seasonal dynamics and spatial distribution of ET in Sacramento-San Joaquin Delta. A continuous monitoring of the dynamics and spatial heterogeneity of canopy and consumptive water use at a field scale, will help the growers to be well prepared and informed to adaptively manage water, canopy, and grove density to maximize the yield with the least amount of water.

  2. Daily SST fields produced by blending infrared and microwave radiometer estimates

    Digital Repository Service at National Institute of Oceanography (India)

    Sreejith, O.P.; Shenoi, S.S.C.

    Measurement of Sea Surface Temperature (SST) using satellite based sensors have matured during the last decade. The infrared measurements, using the AVHRR sensor, flown onboard the NOAA satellites, have been used for the generation of high...

  3. Histogram Estimators of Bivariate Densities

    National Research Council Canada - National Science Library

    Husemann, Joyce A

    1986-01-01

    One-dimensional fixed-interval histogram estimators of univariate probability density functions are less efficient than the analogous variable-interval estimators which are constructed from intervals...

  4. Reconciling Top-Down and Bottom-Up Estimates of Oil and Gas Methane Emissions in the Barnett Shale

    Science.gov (United States)

    Hamburg, S.

    2015-12-01

    Top-down approaches that use aircraft, tower, or satellite-based measurements of well-mixed air to quantify regional methane emissions have typically estimated higher emissions from the natural gas supply chain when compared to bottom-up inventories. A coordinated research campaign in October 2013 used simultaneous top-down and bottom-up approaches to quantify total and fossil methane emissions in the Barnett Shale region of Texas. Research teams have published individual results including aircraft mass-balance estimates of regional emissions and a bottom-up, 25-county region spatially-resolved inventory. This work synthesizes data from the campaign to directly compare top-down and bottom-up estimates. A new analytical approach uses statistical estimators to integrate facility emission rate distributions from unbiased and targeted high emission site datasets, which more rigorously incorporates the fat-tail of skewed distributions to estimate regional emissions of well pads, compressor stations, and processing plants. The updated spatially-resolved inventory was used to estimate total and fossil methane emissions from spatial domains that match seven individual aircraft mass balance flights. Source apportionment of top-down emissions between fossil and biogenic methane was corroborated with two independent analyses of methane and ethane ratios. Reconciling top-down and bottom-up estimates of fossil methane emissions leads to more accurate assessment of natural gas supply chain emission rates and the relative contribution of high emission sites. These results increase our confidence in our understanding of the climate impacts of natural gas relative to more carbon-intensive fossil fuels and the potential effectiveness of mitigation strategies.

  5. Preliminary Results from Powell Research Group on Integrating GRACE Satellite and Ground-based Estimates of Groundwater Storage Changes

    Science.gov (United States)

    Scanlon, B. R.; Zhang, Z.; Reitz, M.; Rodell, M.; Sanford, W. E.; Save, H.; Wiese, D. N.; Croteau, M. J.; McGuire, V. L.; Pool, D. R.; Faunt, C. C.; Zell, W.

    2017-12-01

    Groundwater storage depletion is a critical issue for many of the major aquifers in the U.S., particularly during intense droughts. GRACE (Gravity Recovery and Climate Experiment) satellite-based estimates of groundwater storage changes have attracted considerable media attention in the U.S. and globally and interest in GRACE products continues to increase. For this reason, a Powell Research Group was formed to: (1) Assess variations in groundwater storage using a variety of GRACE products and other storage components (snow, surface water, and soil moisture) for major aquifers in the U.S., (2) Quantify long-term trends in groundwater storage from ground-based monitoring and regional and national modeling, and (3) Use ground-based monitoring and modeling to interpret GRACE water storage changes within the context of extreme droughts and over-exploitation of groundwater. The group now has preliminary estimates from long-term trends and seasonal fluctuations in water storage using different GRACE solutions, including CSR, JPL and GSFC. Approaches to quantifying uncertainties in GRACE data are included. This work also shows how GRACE sees groundwater depletion in unconfined versus confined aquifers, and plans for future work will link GRACE data to regional groundwater models. The wealth of ground-based observations for the U.S. provides a unique opportunity to assess the reliability of GRACE-based estimates of groundwater storage changes.

  6. Automatic trend estimation

    CERN Document Server

    Vamos¸, C˘alin

    2013-01-01

    Our book introduces a method to evaluate the accuracy of trend estimation algorithms under conditions similar to those encountered in real time series processing. This method is based on Monte Carlo experiments with artificial time series numerically generated by an original algorithm. The second part of the book contains several automatic algorithms for trend estimation and time series partitioning. The source codes of the computer programs implementing these original automatic algorithms are given in the appendix and will be freely available on the web. The book contains clear statement of the conditions and the approximations under which the algorithms work, as well as the proper interpretation of their results. We illustrate the functioning of the analyzed algorithms by processing time series from astrophysics, finance, biophysics, and paleoclimatology. The numerical experiment method extensively used in our book is already in common use in computational and statistical physics.

  7. Distribution load estimation (DLE)

    Energy Technology Data Exchange (ETDEWEB)

    Seppaelae, A; Lehtonen, M [VTT Energy, Espoo (Finland)

    1998-08-01

    The load research has produced customer class load models to convert the customers` annual energy consumption to hourly load values. The reliability of load models applied from a nation-wide sample is limited in any specific network because many local circumstances are different from utility to utility and time to time. Therefore there is a need to find improvements to the load models or, in general, improvements to the load estimates. In Distribution Load Estimation (DLE) the measurements from the network are utilized to improve the customer class load models. The results of DLE will be new load models that better correspond to the loading of the distribution network but are still close to the original load models obtained by load research. The principal data flow of DLE is presented

  8. Estimating ISABELLE shielding requirements

    International Nuclear Information System (INIS)

    Stevens, A.J.; Thorndike, A.M.

    1976-01-01

    Estimates were made of the shielding thicknesses required at various points around the ISABELLE ring. Both hadron and muon requirements are considered. Radiation levels at the outside of the shield and at the BNL site boundary are kept at or below 1000 mrem per year and 5 mrem/year respectively. Muon requirements are based on the Wang formula for pion spectra, and the hadron requirements on the hadron cascade program CYLKAZ of Ranft. A muon shield thickness of 77 meters of sand is indicated outside the ring in one area, and hadron shields equivalent to from 2.7 to 5.6 meters in thickness of sand above the ring. The suggested safety allowance would increase these values to 86 meters and 4.0 to 7.2 meters respectively. There are many uncertainties in such estimates, but these last figures are considered to be rather conservative

  9. Variance Function Estimation. Revision.

    Science.gov (United States)

    1987-03-01

    UNLSIFIED RFOSR-TR-87-±112 F49620-85-C-O144 F/C 12/3 NL EEEEEEh LOUA28~ ~ L53 11uLoo MICROOP REOUINTS-’HR ------ N L E U INARF-% - IS %~1 %i % 0111...and 9 jointly. If 7,, 0. and are any preliminary estimators for 71, 6. and 3. define 71 and 6 to be the solutions of (4.1) N1 IN2 (7., ’ Td " ~ - / =0P

  10. Estimating Risk Parameters

    OpenAIRE

    Aswath Damodaran

    1999-01-01

    Over the last three decades, the capital asset pricing model has occupied a central and often controversial place in most corporate finance analysts’ tool chests. The model requires three inputs to compute expected returns – a riskfree rate, a beta for an asset and an expected risk premium for the market portfolio (over and above the riskfree rate). Betas are estimated, by most practitioners, by regressing returns on an asset against a stock index, with the slope of the regression being the b...

  11. Estimating Venezuelas Latent Inflation

    OpenAIRE

    Juan Carlos Bencomo; Hugo J. Montesinos; Hugo M. Montesinos; Jose Roberto Rondo

    2011-01-01

    Percent variation of the consumer price index (CPI) is the inflation indicator most widely used. This indicator, however, has some drawbacks. In addition to measurement errors of the CPI, there is a problem of incongruence between the definition of inflation as a sustained and generalized increase of prices and the traditional measure associated with the CPI. We use data from 1991 to 2005 to estimate a complementary indicator for Venezuela, the highest inflation country in Latin America. Late...

  12. Chernobyl source term estimation

    International Nuclear Information System (INIS)

    Gudiksen, P.H.; Harvey, T.F.; Lange, R.

    1990-09-01

    The Chernobyl source term available for long-range transport was estimated by integration of radiological measurements with atmospheric dispersion modeling and by reactor core radionuclide inventory estimation in conjunction with WASH-1400 release fractions associated with specific chemical groups. The model simulations revealed that the radioactive cloud became segmented during the first day, with the lower section heading toward Scandinavia and the upper part heading in a southeasterly direction with subsequent transport across Asia to Japan, the North Pacific, and the west coast of North America. By optimizing the agreement between the observed cloud arrival times and duration of peak concentrations measured over Europe, Japan, Kuwait, and the US with the model predicted concentrations, it was possible to derive source term estimates for those radionuclides measured in airborne radioactivity. This was extended to radionuclides that were largely unmeasured in the environment by performing a reactor core radionuclide inventory analysis to obtain release fractions for the various chemical transport groups. These analyses indicated that essentially all of the noble gases, 60% of the radioiodines, 40% of the radiocesium, 10% of the tellurium and about 1% or less of the more refractory elements were released. These estimates are in excellent agreement with those obtained on the basis of worldwide deposition measurements. The Chernobyl source term was several orders of magnitude greater than those associated with the Windscale and TMI reactor accidents. However, the 137 Cs from the Chernobyl event is about 6% of that released by the US and USSR atmospheric nuclear weapon tests, while the 131 I and 90 Sr released by the Chernobyl accident was only about 0.1% of that released by the weapon tests. 13 refs., 2 figs., 7 tabs

  13. Estimating Corporate Yield Curves

    OpenAIRE

    Antionio Diaz; Frank Skinner

    2001-01-01

    This paper represents the first study of retail deposit spreads of UK financial institutions using stochastic interest rate modelling and the market comparable approach. By replicating quoted fixed deposit rates using the Black Derman and Toy (1990) stochastic interest rate model, we find that the spread between fixed and variable rates of interest can be modeled (and priced) using an interest rate swap analogy. We also find that we can estimate an individual bank deposit yield curve as a spr...

  14. An Estimate of Biogenic Emissions of Volatile Organic Compounds during Summertime in China (7 pp).

    Science.gov (United States)

    Heinrich, Almut

    2007-01-01

    and Aim. An accurate estimation of biogenic emissions of VOC (volatile organic compounds) is necessary for better understanding a series of current environmental problems such as summertime smog and global climate change. However, very limited studies have been reported on such emissions in China. The aim of this paper is to present an estimate of biogenic VOC emissions during summertime in China, and discuss its uncertainties and potential areas for further investigations. This study was mainly based on field data and related research available so far in China and abroad, including distributions of land use and vegetations, biomass densities and emission potentials. VOC were grouped into isoprene, monoterpenes and other VOC (OVOC). Emission potentials of forests were determined for 22 genera or species, and then assigned to 33 forest ecosystems. The NCEP/NCAR reanalysis database was used as standard environmental conditions. A typical summertime of July 1999 was chosen for detailed calculations. The biogenic VOC emissions in China in July were estimated to be 2.3×1012gC, with 42% as isoprene, 19% as monoterpenes and 39% as OVOC. About 77.3% of the emissions are generated from forests and woodlands. The averaged emission intensity was 4.11 mgC m-2 hr-1 for forests and 1.12 mgC m-2 hr-1 for all types of vegetations in China during the summertime. The uncertainty in the results arose from both the data and the assumptions used in the extrapolations. Generally, uncertainty in the field measurements is relatively small. A large part of the uncertainty mainly comes from the taxonomic method to assign emission potentials to unmeasured species, while the ARGR method serves to estimate leaf biomass and the emission algorithms to describe light and temperature dependence. This study describes a picture of the biogenic VOC emissions during summertime in China. Due to the uneven spatial and temporal distributions, biogenic VOC emissions may play an important role in the

  15. Estimation of inspection effort

    International Nuclear Information System (INIS)

    Mullen, M.F.; Wincek, M.A.

    1979-06-01

    An overview of IAEA inspection activities is presented, and the problem of evaluating the effectiveness of an inspection is discussed. Two models are described - an effort model and an effectiveness model. The effort model breaks the IAEA's inspection effort into components; the amount of effort required for each component is estimated; and the total effort is determined by summing the effort for each component. The effectiveness model quantifies the effectiveness of inspections in terms of probabilities of detection and quantities of material to be detected, if diverted over a specific period. The method is applied to a 200 metric ton per year low-enriched uranium fuel fabrication facility. A description of the model plant is presented, a safeguards approach is outlined, and sampling plans are calculated. The required inspection effort is estimated and the results are compared to IAEA estimates. Some other applications of the method are discussed briefly. Examples are presented which demonstrate how the method might be useful in formulating guidelines for inspection planning and in establishing technical criteria for safeguards implementation

  16. Qualitative Robustness in Estimation

    Directory of Open Access Journals (Sweden)

    Mohammed Nasser

    2012-07-01

    Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of   qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.

  17. Estimating directional epistasis

    Science.gov (United States)

    Le Rouzic, Arnaud

    2014-01-01

    Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences. PMID:25071828

  18. Adaptive Nonparametric Variance Estimation for a Ratio Estimator ...

    African Journals Online (AJOL)

    Kernel estimators for smooth curves require modifications when estimating near end points of the support, both for practical and asymptotic reasons. The construction of such boundary kernels as solutions of variational problem is a difficult exercise. For estimating the error variance of a ratio estimator, we suggest an ...

  19. Validation of the CHIRPS Satellite Rainfall Estimates over Eastern of Africa

    Science.gov (United States)

    Dinku, T.; Funk, C. C.; Tadesse, T.; Ceccato, P.

    2017-12-01

    Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time scales. The evaluation was done by comparing the satellite products with rain gauge data from about 1200 stations. The is unprecedented number of validation stations for this region covering. The results provide a unique region-wide understanding of how satellite products perform over different climatic/geographic (low lands, mountainous regions, and coastal) regions. The CHIRP and CHIRPS products were also compared with two similar satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the latest release of the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product. A comparison was also done between the latest release of the TAMSAT product

  20. MODIS-based global terrestrial estimates of gross primary productivity and evapotranspiration

    Science.gov (United States)

    Ryu, Y.; Baldocchi, D. D.; Kobayashi, H.; Li, J.; van Ingen, C.; Agarwal, D.; Jackson, K.; Humphrey, M.

    2010-12-01

    We propose a novel approach to quantify gross primary productivity (GPP) and evapotranspiration (ET) at global scale (5 km resolution with 8-day interval). The MODIS-based, process-oriented approach couples photosynthesis, evaporation, two-leaf energy balance and nitrogen, which are different from the previous satellite-based approaches. We couple information from MODIS with flux towers to assess the drivers and parameters of GPP and ET. Incoming shortwave radiation components (direct and diffuse PAR, NIR) under all sky condition are modeled using a Monte-Carlo based atmospheric radiative transfer model. The MODIS Level 2 Atmospheric products are gridded and overlaid with MODIS Land products to produce spatially compatible forcing variables. GPP is modeled using a two-leaf model (sunlit and shaded leaf) and the maximum carboxylation rate is estimated using albedo-Nitrogen-leaf trait relations. The GPP is used to calculate canopy conductance via Ball-Berry model. Then, we apply Penman-Monteith equation to calculate evapotranspiration. The process-oriented approach allows us to investigate the main drivers of GPP and ET at global scale. Finally we explore the spatial and temporal variability of GPP and ET at global scale.

  1. Estimation of Lung Ventilation

    Science.gov (United States)

    Ding, Kai; Cao, Kunlin; Du, Kaifang; Amelon, Ryan; Christensen, Gary E.; Raghavan, Madhavan; Reinhardt, Joseph M.

    Since the primary function of the lung is gas exchange, ventilation can be interpreted as an index of lung function in addition to perfusion. Injury and disease processes can alter lung function on a global and/or a local level. MDCT can be used to acquire multiple static breath-hold CT images of the lung taken at different lung volumes, or with proper respiratory control, 4DCT images of the lung reconstructed at different respiratory phases. Image registration can be applied to this data to estimate a deformation field that transforms the lung from one volume configuration to the other. This deformation field can be analyzed to estimate local lung tissue expansion, calculate voxel-by-voxel intensity change, and make biomechanical measurements. The physiologic significance of the registration-based measures of respiratory function can be established by comparing to more conventional measurements, such as nuclear medicine or contrast wash-in/wash-out studies with CT or MR. An important emerging application of these methods is the detection of pulmonary function change in subjects undergoing radiation therapy (RT) for lung cancer. During RT, treatment is commonly limited to sub-therapeutic doses due to unintended toxicity to normal lung tissue. Measurement of pulmonary function may be useful as a planning tool during RT planning, may be useful for tracking the progression of toxicity to nearby normal tissue during RT, and can be used to evaluate the effectiveness of a treatment post-therapy. This chapter reviews the basic measures to estimate regional ventilation from image registration of CT images, the comparison of them to the existing golden standard and the application in radiation therapy.

  2. Estimating Subjective Probabilities

    DEFF Research Database (Denmark)

    Andersen, Steffen; Fountain, John; Harrison, Glenn W.

    2014-01-01

    either construct elicitation mechanisms that control for risk aversion, or construct elicitation mechanisms which undertake 'calibrating adjustments' to elicited reports. We illustrate how the joint estimation of risk attitudes and subjective probabilities can provide the calibration adjustments...... that theory calls for. We illustrate this approach using data from a controlled experiment with real monetary consequences to the subjects. This allows the observer to make inferences about the latent subjective probability, under virtually any well-specified model of choice under subjective risk, while still...

  3. Estimating NHL Scoring Rates

    OpenAIRE

    Buttrey, Samuel E.; Washburn, Alan R.; Price, Wilson L.; Operations Research

    2011-01-01

    The article of record as published may be located at http://dx.doi.org/10.2202/1559-0410.1334 We propose a model to estimate the rates at which NHL teams score and yield goals. In the model, goals occur as if from a Poisson process whose rate depends on the two teams playing, the home-ice advantage, and the manpower (power-play, short-handed) situation. Data on all the games from the 2008-2009 season was downloaded and processed into a form suitable for the analysis. The model...

  4. Risk estimation and evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Ferguson, R A.D.

    1982-10-01

    Risk assessment involves subjectivity, which makes objective decision making difficult in the nuclear power debate. The author reviews the process and uncertainties of estimating risks as well as the potential for misinterpretation and misuse. Risk data from a variety of aspects cannot be summed because the significance of different risks is not comparable. A method for including political, social, moral, psychological, and economic factors, environmental impacts, catastrophes, and benefits in the evaluation process could involve a broad base of lay and technical consultants, who would explain and argue their evaluation positions. 15 references. (DCK)

  5. Estimating Gear Teeth Stiffness

    DEFF Research Database (Denmark)

    Pedersen, Niels Leergaard

    2013-01-01

    The estimation of gear stiffness is important for determining the load distribution between the gear teeth when two sets of teeth are in contact. Two factors have a major influence on the stiffness; firstly the boundary condition through the gear rim size included in the stiffness calculation...... and secondly the size of the contact. In the FE calculation the true gear tooth root profile is applied. The meshing stiffness’s of gears are highly non-linear, it is however found that the stiffness of an individual tooth can be expressed in a linear form assuming that the contact length is constant....

  6. Mixtures Estimation and Applications

    CERN Document Server

    Mengersen, Kerrie; Titterington, Mike

    2011-01-01

    This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject

  7. Robust Wave Resource Estimation

    DEFF Research Database (Denmark)

    Lavelle, John; Kofoed, Jens Peter

    2013-01-01

    density estimates of the PDF as a function both of Hm0 and Tp, and Hm0 and T0;2, together with the mean wave power per unit crest length, Pw, as a function of Hm0 and T0;2. The wave elevation parameters, from which the wave parameters are calculated, are filtered to correct or remove spurious data....... An overview is given of the methods used to do this, and a method for identifying outliers of the wave elevation data, based on the joint distribution of wave elevations and accelerations, is presented. The limitations of using a JONSWAP spectrum to model the measured wave spectra as a function of Hm0 and T0......;2 or Hm0 and Tp for the Hanstholm site data are demonstrated. As an alternative, the non-parametric loess method, which does not rely on any assumptions about the shape of the wave elevation spectra, is used to accurately estimate Pw as a function of Hm0 and T0;2....

  8. Estimations of actual availability

    International Nuclear Information System (INIS)

    Molan, M.; Molan, G.

    2001-01-01

    Adaptation of working environment (social, organizational, physical and physical) should assure higher level of workers' availability and consequently higher level of workers' performance. A special theoretical model for description of connections between environmental factors, human availability and performance was developed and validated. The central part of the model is evaluations of human actual availability in the real working situation or fitness for duties self-estimation. The model was tested in different working environments. On the numerous (2000) workers, standardized values and critical limits for an availability questionnaire were defined. Standardized method was used in identification of the most important impact of environmental factors. Identified problems were eliminated by investments in the organization in modification of selection and training procedures in humanization of working .environment. For workers with behavioural and health problems individual consultancy was offered. The described method is a tool for identification of impacts. In combination with behavioural analyses and mathematical analyses of connections, it offers possibilities to keep adequate level of human availability and fitness for duty in each real working situation. The model should be a tool for achieving adequate level of nuclear safety by keeping the adequate level of workers' availability and fitness for duty. For each individual worker possibility for estimation of level of actual fitness for duty is possible. Effects of prolonged work and additional tasks should be evaluated. Evaluations of health status effects and ageing are possible on the individual level. (author)

  9. A hybrid downscaling procedure for estimating the vertical distribution of ambient temperature in local scale

    Science.gov (United States)

    Yiannikopoulou, I.; Philippopoulos, K.; Deligiorgi, D.

    2012-04-01

    The vertical thermal structure of the atmosphere is defined by a combination of dynamic and radiation transfer processes and plays an important role in describing the meteorological conditions at local scales. The scope of this work is to develop and quantify the predictive ability of a hybrid dynamic-statistical downscaling procedure to estimate the vertical profile of ambient temperature at finer spatial scales. The study focuses on the warm period of the year (June - August) and the method is applied to an urban coastal site (Hellinikon), located in eastern Mediterranean. The two-step methodology initially involves the dynamic downscaling of coarse resolution climate data via the RegCM4.0 regional climate model and subsequently the statistical downscaling of the modeled outputs by developing and training site-specific artificial neural networks (ANN). The 2.5ox2.5o gridded NCEP-DOE Reanalysis 2 dataset is used as initial and boundary conditions for the dynamic downscaling element of the methodology, which enhances the regional representivity of the dataset to 20km and provides modeled fields in 18 vertical levels. The regional climate modeling results are compared versus the upper-air Hellinikon radiosonde observations and the mean absolute error (MAE) is calculated between the four grid point values nearest to the station and the ambient temperature at the standard and significant pressure levels. The statistical downscaling element of the methodology consists of an ensemble of ANN models, one for each pressure level, which are trained separately and employ the regional scale RegCM4.0 output. The ANN models are theoretically capable of estimating any measurable input-output function to any desired degree of accuracy. In this study they are used as non-linear function approximators for identifying the relationship between a number of predictor variables and the ambient temperature at the various vertical levels. An insight of the statistically derived input

  10. Comparison of variance estimators for metaanalysis of instrumental variable estimates

    NARCIS (Netherlands)

    Schmidt, A. F.; Hingorani, A. D.; Jefferis, B. J.; White, J.; Groenwold, R. H H; Dudbridge, F.; Ben-Shlomo, Y.; Chaturvedi, N.; Engmann, J.; Hughes, A.; Humphries, S.; Hypponen, E.; Kivimaki, M.; Kuh, D.; Kumari, M.; Menon, U.; Morris, R.; Power, C.; Price, J.; Wannamethee, G.; Whincup, P.

    2016-01-01

    Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two

  11. Introduction to variance estimation

    CERN Document Server

    Wolter, Kirk M

    2007-01-01

    We live in the information age. Statistical surveys are used every day to determine or evaluate public policy and to make important business decisions. Correct methods for computing the precision of the survey data and for making inferences to the target population are absolutely essential to sound decision making. Now in its second edition, Introduction to Variance Estimation has for more than twenty years provided the definitive account of the theory and methods for correct precision calculations and inference, including examples of modern, complex surveys in which the methods have been used successfully. The book provides instruction on the methods that are vital to data-driven decision making in business, government, and academe. It will appeal to survey statisticians and other scientists engaged in the planning and conduct of survey research, and to those analyzing survey data and charged with extracting compelling information from such data. It will appeal to graduate students and university faculty who...

  12. Estimating Discount Rates

    Directory of Open Access Journals (Sweden)

    Laurence Booth

    2015-04-01

    Full Text Available Discount rates are essential to applied finance, especially in setting prices for regulated utilities and valuing the liabilities of insurance companies and defined benefit pension plans. This paper reviews the basic building blocks for estimating discount rates. It also examines market risk premiums, as well as what constitutes a benchmark fair or required rate of return, in the aftermath of the financial crisis and the U.S. Federal Reserve’s bond-buying program. Some of the results are disconcerting. In Canada, utilities and pension regulators responded to the crash in different ways. Utilities regulators haven’t passed on the full impact of low interest rates, so that consumers face higher prices than they should whereas pension regulators have done the opposite, and forced some contributors to pay more. In both cases this is opposite to the desired effect of monetary policy which is to stimulate aggregate demand. A comprehensive survey of global finance professionals carried out last year provides some clues as to where adjustments are needed. In the U.S., the average equity market required return was estimated at 8.0 per cent; Canada’s is 7.40 per cent, due to the lower market risk premium and the lower risk-free rate. This paper adds a wealth of historic and survey data to conclude that the ideal base long-term interest rate used in risk premium models should be 4.0 per cent, producing an overall expected market return of 9-10.0 per cent. The same data indicate that allowed returns to utilities are currently too high, while the use of current bond yields in solvency valuations of pension plans and life insurers is unhelpful unless there is a realistic expectation that the plans will soon be terminated.

  13. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2015-04-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

  14. Deepwater Horizon - Estimating surface oil volume distribution in real time

    Science.gov (United States)

    Lehr, B.; Simecek-Beatty, D.; Leifer, I.

    2011-12-01

    Spill responders to the Deepwater Horizon (DWH) oil spill required both the relative spatial distribution and total oil volume of the surface oil. The former was needed on a daily basis to plan and direct local surface recovery and treatment operations. The latter was needed less frequently to provide information for strategic response planning. Unfortunately, the standard spill observation methods were inadequate for an oil spill this size, and new, experimental, methods, were not ready to meet the operational demands of near real-time results. Traditional surface oil estimation tools for large spills include satellite-based sensors to define the spatial extent (but not thickness) of the oil, complemented with trained observers in small aircraft, sometimes supplemented by active or passive remote sensing equipment, to determine surface percent coverage of the 'thick' part of the slick, where the vast majority of the surface oil exists. These tools were also applied to DWH in the early days of the spill but the shear size of the spill prevented synoptic information of the surface slick through the use small aircraft. Also, satellite images of the spill, while large in number, varied considerably in image quality, requiring skilled interpretation of them to identify oil and eliminate false positives. Qualified staff to perform this task were soon in short supply. However, large spills are often events that overcome organizational inertia to the use of new technology. Two prime examples in DWH were the application of hyper-spectral scans from a high-altitude aircraft and more traditional fixed-wing aircraft using multi-spectral scans processed by use of a neural network to determine, respectively, absolute or relative oil thickness. But, with new technology, come new challenges. The hyper-spectral instrument required special viewing conditions that were not present on a daily basis and analysis infrastructure to process the data that was not available at the command

  15. Toxicity Estimation Software Tool (TEST)

    Science.gov (United States)

    The Toxicity Estimation Software Tool (TEST) was developed to allow users to easily estimate the toxicity of chemicals using Quantitative Structure Activity Relationships (QSARs) methodologies. QSARs are mathematical models used to predict measures of toxicity from the physical c...

  16. Sampling and estimating recreational use.

    Science.gov (United States)

    Timothy G. Gregoire; Gregory J. Buhyoff

    1999-01-01

    Probability sampling methods applicable to estimate recreational use are presented. Both single- and multiple-access recreation sites are considered. One- and two-stage sampling methods are presented. Estimation of recreational use is presented in a series of examples.

  17. Flexible and efficient estimating equations for variogram estimation

    KAUST Repository

    Sun, Ying; Chang, Xiaohui; Guan, Yongtao

    2018-01-01

    Variogram estimation plays a vastly important role in spatial modeling. Different methods for variogram estimation can be largely classified into least squares methods and likelihood based methods. A general framework to estimate the variogram through a set of estimating equations is proposed. This approach serves as an alternative approach to likelihood based methods and includes commonly used least squares approaches as its special cases. The proposed method is highly efficient as a low dimensional representation of the weight matrix is employed. The statistical efficiency of various estimators is explored and the lag effect is examined. An application to a hydrology dataset is also presented.

  18. Flexible and efficient estimating equations for variogram estimation

    KAUST Repository

    Sun, Ying

    2018-01-11

    Variogram estimation plays a vastly important role in spatial modeling. Different methods for variogram estimation can be largely classified into least squares methods and likelihood based methods. A general framework to estimate the variogram through a set of estimating equations is proposed. This approach serves as an alternative approach to likelihood based methods and includes commonly used least squares approaches as its special cases. The proposed method is highly efficient as a low dimensional representation of the weight matrix is employed. The statistical efficiency of various estimators is explored and the lag effect is examined. An application to a hydrology dataset is also presented.

  19. Improved Estimates of Thermodynamic Parameters

    Science.gov (United States)

    Lawson, D. D.

    1982-01-01

    Techniques refined for estimating heat of vaporization and other parameters from molecular structure. Using parabolic equation with three adjustable parameters, heat of vaporization can be used to estimate boiling point, and vice versa. Boiling points and vapor pressures for some nonpolar liquids were estimated by improved method and compared with previously reported values. Technique for estimating thermodynamic parameters should make it easier for engineers to choose among candidate heat-exchange fluids for thermochemical cycles.

  20. State estimation in networked systems

    NARCIS (Netherlands)

    Sijs, J.

    2012-01-01

    This thesis considers state estimation strategies for networked systems. State estimation refers to a method for computing the unknown state of a dynamic process by combining sensor measurements with predictions from a process model. The most well known method for state estimation is the Kalman

  1. Global Polynomial Kernel Hazard Estimation

    DEFF Research Database (Denmark)

    Hiabu, Munir; Miranda, Maria Dolores Martínez; Nielsen, Jens Perch

    2015-01-01

    This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...

  2. Uveal melanoma: Estimating prognosis

    Directory of Open Access Journals (Sweden)

    Swathi Kaliki

    2015-01-01

    Full Text Available Uveal melanoma is the most common primary malignant tumor of the eye in adults, predominantly found in Caucasians. Local tumor control of uveal melanoma is excellent, yet this malignancy is associated with relatively high mortality secondary to metastasis. Various clinical, histopathological, cytogenetic features and gene expression features help in estimating the prognosis of uveal melanoma. The clinical features associated with poor prognosis in patients with uveal melanoma include older age at presentation, male gender, larger tumor basal diameter and thickness, ciliary body location, diffuse tumor configuration, association with ocular/oculodermal melanocytosis, extraocular tumor extension, and advanced tumor staging by American Joint Committee on Cancer classification. Histopathological features suggestive of poor prognosis include epithelioid cell type, high mitotic activity, higher values of mean diameter of ten largest nucleoli, higher microvascular density, extravascular matrix patterns, tumor-infiltrating lymphocytes, tumor-infiltrating macrophages, higher expression of insulin-like growth factor-1 receptor, and higher expression of human leukocyte antigen Class I and II. Monosomy 3, 1p loss, 6q loss, and 8q and those classified as Class II by gene expression are predictive of poor prognosis of uveal melanoma. In this review, we discuss the prognostic factors of uveal melanoma. A database search was performed on PubMed, using the terms "uvea," "iris," "ciliary body," "choroid," "melanoma," "uveal melanoma" and "prognosis," "metastasis," "genetic testing," "gene expression profiling." Relevant English language articles were extracted, reviewed, and referenced appropriately.

  3. Satellite-Enhanced Dynamical Downscaling of Extreme Events

    Science.gov (United States)

    Nunes, A.

    2015-12-01

    Severe weather events can be the triggers of environmental disasters in regions particularly susceptible to changes in hydrometeorological conditions. In that regard, the reconstruction of past extreme weather events can help in the assessment of vulnerability and risk mitigation actions. Using novel modeling approaches, dynamical downscaling of long-term integrations from global circulation models can be useful for risk analysis, providing more accurate climate information at regional scales. Originally developed at the National Centers for Environmental Prediction (NCEP), the Regional Spectral Model (RSM) is being used in the dynamical downscaling of global reanalysis, within the South American Hydroclimate Reconstruction Project. Here, RSM combines scale-selective bias correction with assimilation of satellite-based precipitation estimates to downscale extreme weather occurrences. Scale-selective bias correction is a method employed in the downscaling, similar to the spectral nudging technique, in which the downscaled solution develops in agreement with its coarse boundaries. Precipitation assimilation acts on modeled deep-convection, drives the land-surface variables, and therefore the hydrological cycle. During the downscaling of extreme events that took place in Brazil in recent years, RSM continuously assimilated NCEP Climate Prediction Center morphing technique precipitation rates. As a result, RSM performed better than its global (reanalysis) forcing, showing more consistent hydrometeorological fields compared with more sophisticated global reanalyses. Ultimately, RSM analyses might provide better-quality initial conditions for high-resolution numerical predictions in metropolitan areas, leading to more reliable short-term forecasting of severe local storms.

  4. The satellite-based remote sensing of particulate matter (PM) in support to urban air quality: PM variability and hot spots within the Cordoba city (Argentina) as revealed by the high-resolution MAIAC-algorithm retrievals applied to a ten-years dataset (2

    Science.gov (United States)

    Della Ceca, Lara Sofia; Carreras, Hebe A.; Lyapustin, Alexei I.; Barnaba, Francesca

    2016-04-01

    Particulate matter (PM) is one of the major harmful pollutants to public health and the environment [1]. In developed countries, specific air-quality legislation establis