WorldWideScience

Sample records for satellite derived products

  1. Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

    Science.gov (United States)

    Nobis, T. E.

    2017-12-01

    Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

  2. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Teng, W.; Kempler, S.

    2012-01-01

    Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by

  3. Uncertainties and applications of satellite-derived coastal water quality products

    Science.gov (United States)

    Zheng, Guangming; DiGiacomo, Paul M.

    2017-12-01

    Recent and forthcoming launches of a plethora of ocean color radiometry sensors, coupled with increasingly adopted free and open data policies are expected to boost usage of satellite ocean color data and drive the demand to use these data in a quantitative and routine manner. Here we review factors that introduce uncertainties to various satellite-derived water quality products and recommend approaches to minimize the uncertainty of a specific product. We show that the regression relationships between remote-sensing reflectance and water turbidity (in terms of nephelometric units) established for different regions tend to converge and therefore it is plausible to develop a global satellite water turbidity product derived using a single algorithm. In contrast, solutions to derive suspended particulate matter concentration are much less generalizable; in one case it might be more accurate to estimate this parameter based on satellite-derived particulate backscattering coefficient, whereas in another the nonagal particulate absorption coefficient might be a better proxy. Regarding satellite-derived chlorophyll concentration, known to be subject to large uncertainties in coastal waters, studies summarized here clearly indicate that the accuracy of classical reflectance band-ratio algorithms depends largely on the contribution of phytoplankton to total light absorption coefficient as well as the degree of correlation between phytoplankton and the dominant nonalgal contributions. Our review also indicates that currently available satellite-derived water quality products are restricted to optically significant materials, whereas many users are interested in toxins, nutrients, pollutants, and pathogens. Presently, proxies or indicators for these constituents are inconsistently (and often incorrectly) developed and applied. Progress in this general direction will remain slow unless, (i) optical oceanographers and environmental scientists start collaborating more closely

  4. Exploration of satellite-derived data products for atmospheric turbulence studies

    CSIR Research Space (South Africa)

    Griffith, DJ

    2014-09-01

    Full Text Available reasonable proxy in the absence of in-situ measurements. 3.2 ORNL DAAC The Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) provides a global subsetting and time-series derivation for Moderate Resolution Imaging Spectrometer... (MODIS) data from the NASA Terra and Aqua satellite platforms. The products available for subsetting and time-series generation from the ORNL DAAC are given in Table 2. Moreover, this MODIS facility is available programmatically using the Simple Object...

  5. Assessment of Satellite Ocean Colour Radiometry and Derived Geophysical Products. Chapter 6.1

    Science.gov (United States)

    Melin, Frederic; Franz, Bryan A.

    2014-01-01

    Standardization of methods to assess and assign quality metrics to satellite ocean color radiometry and derived geophysical products has become paramount with the inclusion of the marine reflectance and chlorophyll-a concentration (Chla) as essential climate variables (ECV; [1]) and the recognition that optical remote sensing of the oceans can only contribute to climate research if and when a continuous succession of satellite missions can be shown to collectively provide a consistent, long-term record with known uncertainties. In 20 years, the community has made significant advancements toward that objective, but providing a complete uncertainty budget for all products and for all conditions remains a daunting task. In the retrieval of marine water-leaving radiance from observed top-of-atmosphere radiance, the sources of uncertainties include those associated with propagation of sensor noise and radiometric calibration and characterization errors, as well as a multitude of uncertainties associated with the modeling and removal of effects from the atmosphere and sea surface. This chapter describes some common approaches used to assess quality and consistency of ocean color satellite products and reviews the current status of uncertainty quantification in the field. Its focus is on the primary ocean color product, the spectrum of marine reflectance Rrs, but uncertainties in some derived products such as the Chla or inherent optical properties (IOPs) will also be considered.

  6. 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.

  7. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    Science.gov (United States)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  8. Using Social Media and Mobile Devices to Discover and Share Disaster Data Products Derived From Satellites

    Science.gov (United States)

    Mandl, Daniel; Cappelaere, Patrice; Frye, Stuart; Evans, John; Moe, Karen

    2014-01-01

    Data products derived from Earth observing satellites are difficult to find and share without specialized software and often times a highly paid and specialized staff. For our research effort, we endeavored to prototype a distributed architecture that depends on a standardized communication protocol and applications program interface (API) that makes it easy for anyone to discover and access disaster related data. Providers can easily supply the public with their disaster related products by building an adapter for our API. Users can use the API to browse and find products that relate to the disaster at hand, without a centralized catalogue, for example floods, and then are able to share that data via social media. Furthermore, a longerterm goal for this architecture is to enable other users who see the shared disaster product to be able to generate the same product for other areas of interest via simple point and click actions on the API on their mobile device. Furthermore, the user will be able to edit the data with on the ground local observations and return the updated information to the original repository of this information if configured for this function. This architecture leverages SensorWeb functionality [1] presented at previous IGARSS conferences. The architecture is divided into two pieces, the frontend, which is the GeoSocial API, and the backend, which is a standardized disaster node that knows how to talk to other disaster nodes, and also can communicate with the GeoSocial API. The GeoSocial API, along with the disaster node basic functionality enables crowdsourcing and thus can leverage insitu observations by people external to a group to perform tasks such as improving water reference maps, which are maps of existing water before floods. This can lower the cost of generating precision water maps. Keywords-Data Discovery, Disaster Decision Support, Disaster Management, Interoperability, CEOS WGISS Disaster Architecture

  9. CyAN satellite-derived Cyanobacteria products in support of Public Health Protection

    Science.gov (United States)

    The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management decision-making and for targeted deployment of existing government and non-government water quality monitoring resources. The Cyanobacteria Assessment Network (CyAN) is a...

  10. 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

  11. Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

    Directory of Open Access Journals (Sweden)

    T. Cohen Liechti

    2012-02-01

    Full Text Available In the framework of the African DAms ProjecT (ADAPT, an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin.

    Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42, the Famine Early Warning System product 2.0 (FEWS RFE2.0 and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC morphing technique (CMORPH are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps.

    The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each sub-basin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular meshes.

    In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating the rainfall by nearly 50%. The statistics of TRMM and FEWS estimates show quite similar results.

    Due to its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin.

  12. An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

    OpenAIRE

    Kimani, M.W.; Hoedjes, Johannes Cornelis Bernardus; Su, Z.

    2017-01-01

    Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors...

  13. An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

    Directory of Open Access Journals (Sweden)

    Margaret Wambui Kimani

    2017-05-01

    Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

  14. Accuracy Assessment of Satellite Derived Forest Cover Products in South and Southeast Asia

    Science.gov (United States)

    Gilani, H.; Xu, X.; Jain, A. K.

    2017-12-01

    South and Southeast Asia (SSEA) region occupies 16 % of worlds land area. It is home to over 50% of the world's population. The SSEA's countries are experiencing significant land-use and land-cover changes (LULCCs), primarily in agriculture, forest, and urban land. For this study, we compiled four existing global forest cover maps for year 2010 by Gong et al.(2015), Hansen et al. (2013), Sexton et al.(2013) and Shimada et al. (2014), which were all medium resolution (≤30 m) products based on Landsat and/or PALSAR satellite images. To evaluate the accuracy of these forest products, we used three types of information: (1) ground measurements, (2) high resolution satellite images and (3) forest cover maps produced at the national scale. The stratified random sampling technique was used to select a set of validation data points from the ground and high-resolution satellite images. Then the confusion matrix method was used to assess and rank the accuracy of the forest cover products for the entire SSEA region. We analyzed the spatial consistency of different forest cover maps, and further evaluated the consistency with terrain characteristics. Our study suggests that global forest cover mapping algorithms are trained and tested using limited ground measurement data. We found significant uncertainties in mountainous areas due to the topographical shadow effect and the dense tree canopies effects. The findings of this study will facilitate to improve our understanding of the forest cover dynamics and their impacts on the quantities and pathways of terrestrial carbon and nitrogen fluxes. Gong, P., et al. (2012). "Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data." International Journal of Remote Sensing 34(7): 2607-2654. Hansen, M. C., et al. (2013). "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342(6160): 850-853. Sexton, J. O., et al. (2013). "Global, 30-m resolution

  15. Statistical modeling of phenological phases in Poland based on coupling satellite derived products and gridded meteorological data

    Science.gov (United States)

    Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

    2016-04-01

    The aim of the study was to create and evaluate different statistical models for reconstructing and predicting selected phenological phases. This issue is of particular importance in Poland where national-wide phenological monitoring was abandoned in the middle of 1990s and the reactivated network was established in 2006. Authors decided to evaluate possibilities of using a wide-range of statistical modeling techniques to create synthetic archive dataset. Additionally, a robust tool for predicting the most distinguishable phenophases using only free of charge data as predictors was created. Study period covers the years 2007-2014 and contains only quality-controlled dataset of 10 species and 14 phenophases. Phenological data used in this study originates from the manual observations network run by the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB). Three kind of data sources were used as predictors: (i) satellite derived products, (ii) preprocessed gridded meteorological data, and (iii) spatial properties (longitude, latitude, altitude) of the monitoring site. Moderate-Resolution Imaging Spectroradiometer (MODIS) level-3 vegetation products were used for detecting onset dates of particular phenophases. Following indices were used: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (fPAR). Additionally, Interactive Multisensor Snow and Ice Mapping System (IMS) products were chosen to detect occurrence of snow cover. Due to highly noisy data, authors decided to take into account pixel reliability information. Besides satellite derived products (NDVI, EVI, FPAR, LAI, Snow cover), a wide group of observational data and agrometeorological indices derived from the European Climate Assessment & Dataset (ECA&D) were used as a potential predictors: cumulative growing degree days (GDD), cumulative growing precipitation days (GPD

  16. On the reliable use of satellite-derived surface water products for global flood monitoring

    Science.gov (United States)

    Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

    2015-12-01

    Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

  17. Application of the Coastal and Marine Ecological Classification Standard using Satellite-derived and Modeled Data Products for Pelagic Habitats in the Northern Gulf of Mexico

    Science.gov (United States)

    Satellite-derived data for sea surface temperature, salinity, chlorophyll; euphotic depth; and modeled bottom to surface temperature differences (Delta t) were evaluated to assess the utility of these products as proxies for in situ measurements. The data were used to classify su...

  18. Does quality control matter? Surface urban heat island intensity variations estimated by satellite-derived land surface temperature products

    Science.gov (United States)

    Lai, Jiameng; Zhan, Wenfeng; Huang, Fan; Quan, Jinling; Hu, Leiqiu; Gao, Lun; Ju, Weimin

    2018-05-01

    The temporally regular and spatially comprehensive monitoring of surface urban heat islands (SUHIs) have been extremely difficult, until the advent of satellite-based land surface temperature (LST) products. However, these LST products have relatively higher errors compared to in situ measurements. This has resulted in comparatively inaccurate estimations of SUHI indicators and, consequently, may have distorted interpretations of SUHIs. Although reports have shown that LST qualities are important for SUHI interpretations, systematic investigations of the response of SUHI indicators to LST qualities across cities with dissimilar bioclimates are rare. To address this issue, we chose eighty-six major cities across mainland China and analyzed SUHI intensity (SUHII) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The LST-based SUHII differences due to inclusion or exclusion of MODIS quality control (QC) flags (i.e., ΔSUHII) were evaluated. Our major findings included, but are not limited to, the following four aspects: (1) SUHIIs can be significantly impacted by MODIS QC flags, and the associated QC-induced ΔSUHIIs generally accounted for 24.3% (29.9%) of the total SUHII value during the day (night); (2) the ΔSUHIIs differed between seasons, with considerable differences between transitional (spring and autumn) and extreme (summer and winter) seasons; (3) significant discrepancies also appeared among cities located in northern and southern regions, with northern cities often possessing higher annual mean ΔSUHIIs. The internal variations of ΔSUHIIs within individual cities also showed high heterogeneity, with ΔSUHII variations that generally exceeded 5.0 K (3.0 K) in northern (southern) cities; (4) ΔSUHIIs were negatively related to SUHIIs and cloud cover percentages (mostly in transitional seasons). No significant relationship was found in the extreme seasons. Our findings highlight the need to be extremely cautious when using LST

  19. Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

    Directory of Open Access Journals (Sweden)

    Gijs Simons

    2016-03-01

    Full Text Available With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P and land use/land cover (LULC is currently being expanded with the application of actual evapotranspiration (ETact algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products.

  20. Oceanic Weather Decision Support for Unmanned Global Hawk Science Missions into Hurricanes with Tailored Satellite Derived Products

    Science.gov (United States)

    Feltz, Wayne; Griffin, Sarah; Velden, Christopher; Zipser, Ed; Cecil, Daniel; Braun, Scott

    2017-04-01

    The purpose of this presentation is to identify in-flight hazards to high-altitude aircraft, namely the Global Hawk. The Global Hawk was used during Septembers 2012-2016 as part of two NASA funded Hurricane Sentinel-3 field campaigns to over-fly hurricanes in the Atlantic Ocean. This talk identifies the cause of severe turbulence experienced over Hurricane Emily (2005) and how a combination of NOAA funded GOES-R algorithm derived cloud top heights/tropical overshooting tops using GOES-13/SEVIRI imager radiances, and lightning information are used to identify areas of potential turbulence for near real-time navigation decision support. Several examples will demonstrate how the Global Hawk pilots remotely received and used real-time satellite derived cloud and lightning detection information to keep the aircraft safely above clouds and avoid regions of potential turbulence.

  1. Assessment of satellite derived diffuse attenuation coefficients ...

    Science.gov (United States)

    Optical data collected in coastal waters off South Florida and in the Caribbean Sea between January 2009 and December 2010 were used to evaluate products derived with three bio-optical inversion algorithms applied to MOIDS/Aqua, MODIS/Terra, and SeaWiFS satellite observations. The products included the diffuse attenuation coefficient at 490 nm (Kd_490) and for the visible range (Kd_PAR), and euphotic depth (Zeu, corresponding to 1% of the surface incident photosynthetically available radiation or PAR). Above-water hyperspectral reflectance data collected over optically shallow waters of the Florida Keys between June 1997 and August 2011 were used to help understand algorithm performance over optically shallow waters. The in situ data covered a variety of water types in South Florida and the Caribbean Sea, ranging from deep clear waters, turbid coastal waters, and optically shallow waters (Kd_490 range of ~0.03 – 1.29m-1). An algorithm based on Inherent Optical Properties (IOPs) showed the best performance (RMSD turbidity or shallow bottom contamination. Similar results were obtained when only in situ data were used to evaluate algorithm performance. The excellent agreement between satellite-derived remote sensing reflectance (Rrs) and in situ Rrs suggested that

  2. Neuron-Derived ADAM10 Production Stimulates Peripheral Nerve Injury-Induced Neuropathic Pain by Cleavage of E-Cadherin in Satellite Glial Cells.

    Science.gov (United States)

    Li, Jian; Ouyang, Qing; Chen, Cheng-Wen; Chen, Qian-Bo; Li, Xiang-Nan; Xiang, Zheng-Hua; Yuan, Hong-Bin

    2017-09-01

    Increasing evidence suggests the potential involvement of metalloproteinase family proteins in the pathogenesis of neuropathic pain, although the underlying mechanisms remain elusive. Using the spinal nerve ligation model, we investigated whether ADAM10 proteins participate in pain regulation. By implementing invitro methods, we produced a purified culture of satellite glial cells to study the underlying mechanisms of ADAM10 in regulating neuropathic pain. Results showed that the ADAM10 protein was expressed in calcitonin gene-related peptide (CGRP)-containing neurons of the dorsal root ganglia, and expression was upregulated following spinal nerve ligation surgery invivo. Intrathecal administration of GI254023X, an ADAM10 selective inhibitor, to the rats one to three days after spinal nerve ligation surgery attenuated the spinal nerve ligation-induced mechanical allodynia and thermal hyperalgesia. Intrathecal injection of ADAM10 recombinant protein simulated pain behavior in normal rats to a similar extent as those treated by spinal nerve ligation surgery. These results raised a question about the relative contribution of ADAM10 in pain regulation. Further results showed that ADAM10 might act by cleaving E-cadherin, which is mainly expressed in satellite glial cells. GI254023X reversed spinal nerve ligation-induced downregulation of E-cadherin and activation of cyclooxygenase 2 after spinal nerve ligation. β-catenin, which creates a complex with E-cadherin in the membranes of satellite glial cells, was also downregulated by spinal nerve ligation surgery in satellite glial cells. Finally, knockdown expression of β-catenin by lentiviral infection in purified satellite glial cells increased expression of inducible nitric oxide synthase and cyclooxygenase 2. Our findings indicate that neuron-derived ADAM10 production stimulates peripheral nerve injury-induced neuropathic pain by cleaving E-cadherin in satellite glial cells. © 2017 American Academy of Pain Medicine

  3. Satellite derived bathymetry: mapping the Irish coastline

    Science.gov (United States)

    Monteys, X.; Cahalane, C.; Harris, P.; Hanafin, J.

    2017-12-01

    Ireland has a varied coastline in excess of 3000 km in length largely characterized by extended shallow environments. The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods or airborne LiDAR techniques as demonstrated in the Irish INFOMAR program. Thus, large coastal areas in Ireland, and much of the coastal zone worldwide remain unmapped using modern techniques and is poorly understood. Earth Observations (EO) missions are currently being used to derive timely, cost effective, and quality controlled information for mapping and monitoring coastal environments. Different wavelengths of the solar light penetrate the water column to different depths and are routinely sensed by EO satellites. A large selection of multispectral imagery (MS) from many platforms were examined, as well as from small aircrafts and drones. A number of bays representing very different coastal environments were explored in turn. The project's workflow is created by building a catalogue of satellite and field bathymetric data to assess the suitability of imagery captured at a range of spatial, spectral and temporal resolutions. Turbidity indices are derived from the multispectral information. Finally, a number of spatial regression models using water-leaving radiance parameters and field calibration data are examined. Our assessment reveals that spatial regression algorithms have the potential to significantly improve the accuracy of the predictions up to 10m WD and offer a better handle on the error and uncertainty budget. The four spatial models investigated show better adjustments than the basic non-spatial model. Accuracy of the predictions is better than 10% WD at 95% confidence. Future work will focus on improving the accuracy of the predictions incorporating an analytical model in conjunction with improved empirical methods. The recently launched ESA Sentinel 2 will become the

  4. Coral Bleaching Products - Office of Satellite and Product Operations

    Science.gov (United States)

    satellite remotely sensed global sea surface temperature (SST) measurements and derived indices of coral HotSpots, Degree Heating Weeks, Time Series, SST Contour Charts, Ocean Surface Winds, and On-site Buoys as the product, are derived from Coral Bleaching HotSpots and Degree Heating Weeks (DHW) values measured

  5. Validation of Satellite Derived Cloud Properties Over the Southeastern Pacific

    Science.gov (United States)

    Ayers, J.; Minnis, P.; Zuidema, P.; Sun-Mack, S.; Palikonda, R.; Nguyen, L.; Fairall, C.

    2005-12-01

    Satellite measurements of cloud properties and the radiation budget are essential for understanding meso- and large-scale processes that determine the variability in climate over the southeastern Pacific. Of particular interest in this region is the prevalent stratocumulus cloud deck. The stratocumulus albedos are directly related to cloud microphysical properties that need to be accurately characterized in Global Climate Models (GCMs) to properly estimate the Earth's radiation budget. Meteorological observations in this region are sparse causing large uncertainties in initialized model fields. Remote sensing from satellites can provide a wealth of information about the clouds in this region, but it is vital to validate the remotely sensed parameters and to understand their relationship to other parameters that are not directly observed by the satellites. The variety of measurements from the R/V Roger Revelle during the 2003 STRATUS cruise and from the R/V Ron Brown during EPIC 2001 and the 2004 STRATUS cruises are suitable for validating and improving the interpretation of the satellite derived cloud properties. In this study, satellite-derived cloud properties including coverage, height, optical depth, and liquid water path are compared with in situ measurements taken during the EPIC and STRATUS cruises. The remotely sensed values are derived from Geostationary Operational Environmental Satellite (GOES) imager data, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites, and from the Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The products from this study will include regional monthly cloud climatologies derived from the GOES data for the 2003 and 2004 cruises as well as micro and macro physical cloud property retrievals centered over the ship tracks from MODIS and VIRS.

  6. Potentials of satellite derived SIF products to constrain GPP simulated by the new ORCHIDEE-FluOR terrestrial model at the global scale

    Science.gov (United States)

    Bacour, C.; Maignan, F.; Porcar-Castell, A.; MacBean, N.; Goulas, Y.; Flexas, J.; Guanter, L.; Joiner, J.; Peylin, P.

    2016-12-01

    A new era for improving our knowledge of the terrestrial carbon cycle at the global scale has begun with recent studies on the relationships between remotely sensed Sun Induce Fluorescence (SIF) and plant photosynthetic activity (GPP), and the availability of such satellite-derived products now "routinely" produced from GOSAT, GOME-2, or OCO-2 observations. Assimilating SIF data into terrestrial ecosystem models (TEMs) represents a novel opportunity to reduce the uncertainty of their prediction with respect to carbon-climate feedbacks, in particular the uncertainties resulting from inaccurate parameter values. A prerequisite is a correct representation in TEMs of the several drivers of plant fluorescence from the leaf to the canopy scale, and in particular the competing processes of photochemistry and non photochemical quenching (NPQ).In this study, we present the first results of a global scale assimilation of GOME-2 SIF products within a new version of the ORCHIDEE land surface model including a physical module of plant fluorescence. At the leaf level, the regulation of fluorescence yield is simulated both by the photosynthesis module of ORCHIDEE to calculate the photochemical yield and by a parametric model to estimate NPQ. The latter has been calibrated on leaf fluorescence measurements performed for boreal coniferous and Mediterranean vegetation species. A parametric representation of the SCOPE radiative transfer model is used to model the plant fluorescence fluxes for PSI and PSII and the scaling up to the canopy level. The ORCHIDEE-FluOR model is firstly evaluated with respect to in situ measurements of plant fluorescence flux and photochemical yield for scots pine and wheat. The potentials of SIF data to constrain the modelled GPP are evaluated by assimilating one year of GOME-2-SIF products within ORCHIDEE-FluOR. We investigate in particular the changes in the spatial patterns of GPP following the optimization of the photosynthesis and phenology parameters

  7. Global Navigation Satellite System (GNSS) Final Clock Product (5 minute resolution, daily files, generated weekly) from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This derived product set consists of Global Navigation Satellite System Final Satellite and Receiver Clock Product (5-minute granularity, daily files, generated...

  8. Integrating global satellite-derived data products as a pre-analysis for hydrological modelling studies : a case study for the Red River Basin

    NARCIS (Netherlands)

    Simons, G.W.H.; Bastiaanssen, W.G.M.; Ngô, L.A.; Hain, C.R.; Anderson, M.; Senay, G.

    2016-01-01

    With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P) and land use/land cover (LULC) is

  9. Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

    Science.gov (United States)

    Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

    2017-10-01

    the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

  10. Evaluation of satellite derived spectral diffuse attenuation coefficients

    Digital Repository Service at National Institute of Oceanography (India)

    Suresh, T.; Talaulikar, M.; Desa, E.; Mascarenhas, A.A.M.Q.; Matondkar, S.G.P.

    , 443, 490, 510, 555 and 670 nm derived from the ocean color satellite sensor, SeaWiFS with the in-situ measured values from the Arabian Sea is compared. The satellite derived values are found to be comparable to the measured values in the lower...

  11. MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

    Science.gov (United States)

    Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

    2016-12-01

    Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and

  12. Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

    Science.gov (United States)

    Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

    2009-01-01

    In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

  13. Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

    Directory of Open Access Journals (Sweden)

    Guenther Seufert

    2009-02-01

    Full Text Available In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC with the aims of i improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

  14. Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables

    Science.gov (United States)

    Guillevic, P. C.; Nickeson, J. E.; Roman, M. O.; camacho De Coca, F.; Wang, Z.; Schaepman-Strub, G.

    2016-12-01

    The Global Climate Observing System (GCOS) has specified the need to systematically produce and validate Essential Climate Variables (ECVs). The Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and in particular its subgroup on Land Product Validation (LPV) is playing a key coordination role leveraging the international expertise required to address actions related to the validation of global land ECVs. The primary objective of the LPV subgroup is to set standards for validation methods and reporting in order to provide traceable and reliable uncertainty estimates for scientists and stakeholders. The Subgroup is comprised of 9 focus areas that encompass 10 land surface variables. The activities of each focus area are coordinated by two international co-leads and currently include leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR), vegetation phenology, surface albedo, fire disturbance, snow cover, land cover and land use change, soil moisture, land surface temperature (LST) and emissivity. Recent additions to the focus areas include vegetation indices and biomass. The development of best practice validation protocols is a core activity of CEOS LPV with the objective to standardize the evaluation of land surface products. LPV has identified four validation levels corresponding to increasing spatial and temporal representativeness of reference samples used to perform validation. Best practice validation protocols (1) provide the definition of variables, ancillary information and uncertainty metrics, (2) describe available data sources and methods to establish reference validation datasets with SI traceability, and (3) describe evaluation methods and reporting. An overview on validation best practice components will be presented based on the LAI and LST protocol efforts to date.

  15. Investigating the Relationship between the Inter-Annual Variability of Satellite-Derived Vegetation Phenology and a Proxy of Biomass Production in the Sahel

    Directory of Open Access Journals (Sweden)

    Michele Meroni

    2014-06-01

    Full Text Available In the Sahel region, moderate to coarse spatial resolution remote sensing time series are used in early warning monitoring systems with the aim of detecting unfavorable crop and pasture conditions and informing stakeholders about impending food security risks. Despite growing evidence that vegetation productivity is directly related to phenology, most approaches to estimate such risks do not explicitly take into account the actual timing of vegetation growth and development. The date of the start of the season (SOS or of the peak canopy density can be assessed by remote sensing techniques in a timely manner during the growing season. However, there is limited knowledge about the relationship between vegetation biomass production and these variables at the regional scale. This study describes the first attempt to increase our understanding of such a relationship through the analysis of phenological variables retrieved from SPOT-VEGETATION time series of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR. Two key phenological variables (growing season length (GSL; timing of SOS and the maximum value of FAPAR attained during the growing season (Peak are analyzed as potentially related to a proxy of biomass production (CFAPAR, the cumulative value of FAPAR during the growing season. GSL, SOS and Peak all show different spatial patterns of correlation with CFAPAR. In particular, GSL shows a high and positive correlation with CFAPAR over the whole Sahel (mean r = 0.78. The negative correlation between delays in SOS and CFAPAR is stronger (mean r = −0.71 in the southern agricultural band of the Sahel, while the positive correlation between Peak FAPAR and CFAPAR is higher in the northern and more arid grassland region (mean r = 0.75. The consistency of the results and the actual link between remote sensing-derived phenological parameters and biomass production were evaluated using field measurements of aboveground herbaceous biomass

  16. Global Navigation Satellite System (GNSS) Rapid Clock Product Summary from NASA CDDIS

    Data.gov (United States)

    National Aeronautics and Space Administration — This derived product set consists of Global Navigation Satellite System Rapid Clock Product Summary from the NASA Crustal Dynamics Data Information System (CDDIS)....

  17. Sorghum yield and associated satellite-derived meteorological ...

    African Journals Online (AJOL)

    Sorghum yield and associated satellite-derived meteorological parameters in semi-arid Botswana. ... African Crop Science Journal ... Sorghum (Sorghum bicolor) yield for five seasons (2005/6 to 2009/10) from the Botswana Department of Crop ... Key Words: Coefficient of determination, NDVI, Pearson correlation ...

  18. Application of a chlorophyll index derived from satellite data to ...

    African Journals Online (AJOL)

    Application of a chlorophyll index derived from satellite data to investigate the variability of phytoplankton in the Benguela ecosystem. H Demarcq, R Barlow, L Hutchings. Abstract. No Abstract. African Journal of Marine Science Vol.29(2) 2007: pp. 271-282. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD ...

  19. Regional and monthly and clear-sky aerosol direct radiative effect (and forcing derived from the GlobAEROSOL-AATSR satellite aerosol product

    Directory of Open Access Journals (Sweden)

    G. E. Thomas

    2013-01-01

    Full Text Available Using the GlobAEROSOL-AATSR dataset, estimates of the instantaneous, clear-sky, direct aerosol radiative effect and radiative forcing have been produced for the year 2006. Aerosol Robotic Network sun-photometer measurements have been used to characterise the random and systematic error in the GlobAEROSOL product for 22 regions covering the globe. Representative aerosol properties for each region were derived from the results of a wide range of literature sources and, along with the de-biased GlobAEROSOL AODs, were used to drive an offline version of the Met Office unified model radiation scheme. In addition to the mean AOD, best-estimate run of the radiation scheme, a range of additional calculations were done to propagate uncertainty estimates in the AOD, optical properties, surface albedo and errors due to the temporal and spatial averaging of the AOD fields. This analysis produced monthly, regional estimates of the clear-sky aerosol radiative effect and its uncertainty, which were combined to produce annual, global mean values of (−6.7 ± 3.9 W m−2 at the top of atmosphere (TOA and (−12 ± 6 W m−2 at the surface. These results were then used to give estimates of regional, clear-sky aerosol direct radiative forcing, using modelled pre-industrial AOD fields for the year 1750 calculated for the AEROCOM PRE experiment. However, as it was not possible to quantify the uncertainty in the pre-industrial aerosol loading, these figures can only be taken as indicative and their uncertainties as lower bounds on the likely errors. Although the uncertainty on aerosol radiative effect presented here is considerably larger than most previous estimates, the explicit inclusion of the major sources of error in the calculations suggest that they are closer to the true constraint on this figure from similar methodologies, and point to the need for more, improved estimates of both global aerosol loading and aerosol optical properties.

  20. Analysis of satellite-derived solar irradiance over the Netherlands

    Science.gov (United States)

    Dirksen, Marieke; Fokke Meirink, Jan; Sluiter, Raymond

    2017-04-01

    Measurements from geostationary satellites allow the retrieval of surface solar irradiance homogeneously over large areas, thereby providing essential information for the solar energy sector. In this paper, the SICCS solar irradiance data record derived from 12 years of Meteosat Second Generation satellite measurements is analysed with a focus on the Netherlands, where the spatial resolution is about 6 by 3 km2. Extensive validation of the SICCS data with pyranometer observations is performed, indicating a bias of approximately 3 W/m2 and RMSE of 11 W/m2 for daily data. Long term averages and seasonal variations of solar irradiance show regional patterns related to the surface type (e.g., coastal waters, forests, cities). The inter-annual variability over the time frame of the data record is quantified. Methods to merge satellite and surface observations into an optimized data record are explored.

  1. Assessment and Applications of NASA Ozone Data Products Derived from Aura OMI-MLS Satellite Measurements in Context of the GMI Chemical Transport Model

    Science.gov (United States)

    Ziemke, J. R.; Olsen, M. A.; Witte, J. C.; Douglass, A. R.; Strahan, S. E.; Wargan, K.; Liu, X.; Schoeberl, M. R.; Yang, K.; Kaplan, T. B.; hide

    2013-01-01

    Measurements from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS), both onboard the Aura spacecraft, have been used to produce daily global maps of column and profile ozone since August 2004. Here we compare and evaluate three strategies to obtain daily maps of tropospheric and stratospheric ozone from OMI and MLS measurements: trajectory mapping, direct profile retrieval, and data assimilation. Evaluation is based upon an assessment that includes validation using ozonesondes and comparisons with the Global Modeling Initiative (GMI) chemical transport model (CTM). We investigate applications of the three ozone data products from near-decadal and inter-annual timescales to day-to-day case studies. Zonally averaged inter-annual changes in tropospheric ozone from all of the products in any latitude range are of the order 1-2 Dobson Units while changes (increases) over the 8-year Aura record investigated http://eospso.gsfc.nasa.gov/atbd-category/49 vary approximately 2-4 Dobson Units. It is demonstrated that all of the ozone products can measure and monitor exceptional tropospheric ozone events including major forest fire and pollution transport events. Stratospheric ozone during the Aura record has several anomalous inter-annual events including stratospheric warming split events in the Northern Hemisphere extra-tropics that are well captured using the data assimilation ozone profile product. Data assimilation with continuous daily global coverage and vertical ozone profile information is the best of the three strategies at generating a global tropospheric and stratospheric ozone product for science applications.

  2. Merging Satellite Precipitation Products for Improved Streamflow Simulations

    Science.gov (United States)

    Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

    2017-12-01

    Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

  3. New satellite altimetry products for coastal oceans

    Science.gov (United States)

    Dufau, Claire; Mercier, F.; Ablain, M.; Dibarboure, G.; Carrere, L.; Labroue, S.; Obligis, E.; Sicard, P.; Thibaut, P.; Birol, F.; Bronner, E.; Lombard, A.; Picot, N.

    Since the launch of Topex-Poseidon in 1992, satellite altimetry has become one of the most essential elements of the Earth's observing system. Its global view of the ocean state has permitted numerous improvements in the environment understanding, particularly in the global monitoring of climate changes and ocean circulation. Near the coastlines where human activities have a major impact on the ocean, satellite altimeter techniques are unfortunately limited by a growth of their error budget. This quality loss is due to land contamination in the altimetric and radiometric footprints but also to inaccurate geophysical corrections (tides, high-frequency processes linked to atmospheric forcing).Despite instrumental perturbations by emerged lands until 10 km (altimeter) and 50 km (radiometer) off the coasts, measurements are made and may contain useful information for coastal studies. In order to recover these data close to the coast, the French Spatial Agency (CNES) has funded the development of the PISTACH prototype dedicated to Jason-2 altimeter processing in coastal ocean. Since November 2008, these new satellite altimeter products have been providing new retracking solutions, several state-of-the-art or with higher resolution corrections in addition to standard fields. This presentation will present and illustrate this new set of satellite data for the coastal oceans.

  4. A Land Product Characterization System for Comparative Analysis of Satellite Data and Products

    Directory of Open Access Journals (Sweden)

    Kevin Gallo

    2017-12-01

    Full Text Available A Land Product Characterization System (LPCS has been developed to provide land data and products to the community of individuals interested in validating space-based land products by comparing them with similar products available from other sensors or surface-based observations. The LPCS facilitates the application of global multi-satellite and in situ data for characterization and validation of higher-level, satellite-derived, land surface products (e.g., surface reflectance, normalized difference vegetation index, and land surface temperature. The LPCS includes data search, inventory, access, and analysis functions that will permit data to be easily identified, retrieved, co-registered, and compared statistically through a single interface. The system currently includes data and products available from Landsat 4 through 8, Moderate Resolution Imaging Spectroradiometer (MODIS Terra and Aqua, Suomi National Polar-Orbiting Partnership (S-NPP/Joint Polar Satellite System (JPSS Visible Infrared Imaging Radiometer Suite (VIIRS, and simulated data for the Geostationary Operational Environmental Satellite (GOES-16 Advanced Baseline Imager (ABI. In addition to the future inclusion of in situ data, higher-level land products from the European Space Agency (ESA Sentinel-2 and -3 series of satellites, and other high and medium resolution spatial sensors, will be included as available. When fully implemented, any of the sensor data or products included in the LPCS would be available for comparative analysis.

  5. Intercomparison of IRS-P4-MSMR derived geophysical products ...

    Indian Academy of Sciences (India)

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

    In this paper, MSMR geophysical products like Integrated Water Vapour (IWV), Ocean Surface. Wind Speed (OWS) and Cloud Liquid Water (CLW) in different grids of 50, 75 and 150kms are compared with similar products available from other satellites like DMSP-SSM/I and TRMM-. TMI. MSMR derived IWV, OWS and CLW ...

  6. Migratory herbivorous waterfowl track satellite-derived green wave index.

    Directory of Open Access Journals (Sweden)

    Mitra Shariatinajafabadi

    Full Text Available Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI, has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7. Data were collected over three years (2008-2010. Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%, while the Greenland geese followed an earlier stage (GWI 20-40%. Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration, thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

  7. Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

    Directory of Open Access Journals (Sweden)

    C. Albergel

    2017-10-01

    comprehensive evaluation of the assimilation impact is conducted using (i agricultural statistics over France, (ii river discharge observations, (iii satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM project and (iv spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.

  8. Maritime NOx Emissions Over Chinese Seas Derived From Satellite Observations

    Science.gov (United States)

    Ding, J.; van der A, R. J.; Mijling, B.; Jalkanen, J.-P.; Johansson, L.; Levelt, P. F.

    2018-02-01

    By applying an inversion algorithm to NOx satellite observations from Ozone Monitoring Instrument, monthly NOx emissions for a 10 year period (2007 to 2016) over Chinese seas are presented for the first time. No effective regulations on NOx emissions have been implemented for ships in China, which is reflected in the trend analysis of maritime emissions. The maritime emissions display a continuous increase rate of about 20% per year until 2012 and slow down to 3% after that. The seasonal cycle of shipping emissions has regional variations, but all regions show lower emissions during winter. Simulations by an atmospheric chemistry transport model show a notable influence of maritime emissions on air pollution over coastal areas, especially in summer. The satellite-derived spatial distribution and the magnitude of maritime emissions over Chinese seas are in good agreement with bottom-up studies based on the Automatic Identification System of ships.

  9. Theoretical algorithms for satellite-derived sea surface temperatures

    Science.gov (United States)

    Barton, I. J.; Zavody, A. M.; O'Brien, D. M.; Cutten, D. R.; Saunders, R. W.; Llewellyn-Jones, D. T.

    1989-03-01

    Reliable climate forecasting using numerical models of the ocean-atmosphere system requires accurate data sets of sea surface temperature (SST) and surface wind stress. Global sets of these data will be supplied by the instruments to fly on the ERS 1 satellite in 1990. One of these instruments, the Along-Track Scanning Radiometer (ATSR), has been specifically designed to provide SST in cloud-free areas with an accuracy of 0.3 K. The expected capabilities of the ATSR can be assessed using transmission models of infrared radiative transfer through the atmosphere. The performances of several different models are compared by estimating the infrared brightness temperatures measured by the NOAA 9 AVHRR for three standard atmospheres. Of these, a computationally quick spectral band model is used to derive typical AVHRR and ATSR SST algorithms in the form of linear equations. These algorithms show that a low-noise 3.7-μm channel is required to give the best satellite-derived SST and that the design accuracy of the ATSR is likely to be achievable. The inclusion of extra water vapor information in the analysis did not improve the accuracy of multiwavelength SST algorithms, but some improvement was noted with the multiangle technique. Further modeling is required with atmospheric data that include both aerosol variations and abnormal vertical profiles of water vapor and temperature.

  10. Short Communication Validation of aerosol products derived from ...

    African Journals Online (AJOL)

    The aerosol products derived from the ocean colour missions SeaWiFS and MODIS (Aqua and Terra) were assessed with AERONET field measurements collected at sites in Mozambique (Inhaca) and Kenya (Malindi). The median of absolute relative differences between satellite and AERONET aerosol optical thickness τa ...

  11. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  12. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

    2017-04-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

  13. Satellite-derived SIF and CO2 Observations Show Coherent Responses to Interannual Climate Variations

    Science.gov (United States)

    Butterfield, Z.; Hogikyan, A.; Kulawik, S. S.; Keppel-Aleks, G.

    2017-12-01

    Gross primary production (GPP) is the single largest carbon flux in the Earth system, but its sensitivity to changes in climate is subject to significant uncertainty. Satellite measurements of solar-induced chlorophyll fluorescence (SIF) offer insight into spatial and temporal patterns in GPP at a global scale and, combined with other satellite-derived datasets, provide unprecedented opportunity to explore interactions between atmospheric CO2, GPP, and climate variability. To explore potential drivers of GPP in the Northern Hemisphere (NH), we compare monthly-averaged SIF data from the Global Ozone Monitoring Experiment 2 (GOME-2) with observed anomalies in temperature (T; CRU-TS), liquid water equivalent (LWE) from the Gravity Recovery and Climate Experiment (GRACE), and photosynthetically active radiation (PAR; CERES SYN1deg). Using observations from 2007 through 2015 for several NH regions, we calculate month-specific sensitivities of SIF to variability in T, LWE, and PAR. These sensitivities provide insight into the seasonal progression of how productivity is affected by climate variability and can be used to effectively model the observed SIF signal. In general, we find that high temperatures are beneficial to productivity in the spring, but detrimental in the summer. The influences of PAR and LWE are more heterogeneous between regions; for example, higher LWE in North American temperate forest leads to decreased springtime productivity, while exhibiting a contrasting effect in water-limited regions. Lastly, we assess the influence of variations in terrestrial productivity on atmospheric carbon using a new lower tropospheric CO2 product derived from the Greenhouse Gases Observing Satellite (GOSAT). Together, these data shed light on the drivers of interannual variability in the annual cycle of NH atmospheric CO2, and may provide improved constraints on projections of long-term carbon cycle responses to climate change.

  14. Estimating Next Primary Productivity using Satellite and Ancillary Data

    Science.gov (United States)

    Choudhury, B. J.

    The net primary productivity (C) or annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of the rate of gross photosynthesis (Ag) and autotrophic respiration (R) per unit ground area. Although available observations show that R is a large and variable fraction of Ag, viz., 0.3 to 0.7, it is generally recognized that much uncertainties exist in this fraction due to difficulties associated with the needed measurements. Additional uncertainties arise when these measurements are extrapolated to regional or global land surface using empirical equations, for example, using regression equations relating C to mean annual precipitation and air temperature. Here, a process- based approach has been taken to calculate Ag and R using satellite and ancillary data. Ag has been expressed as a product of radiation use efficiency, magnitude of intercepted photosynthetically active radiation (PAR), and normalized by stresses due to soil water shortage and air temperature away from the optimum range. A biophysical model has been used to determine the radiation use efficiency from the maximum rate of carbon assimilation by a leaf, foliage temperature, and the fraction of diffuse PAR incident on a canopy. All meteorological data (PAR, air temperature, precipitation, etc.) needed for the calculation are derived from satellite observations, while a land use, land cover data (based on satellite and ground measurements) have been used to assess the maximum rate of carbon assimilation by a leaf of varied cover type based on field measurements. R has been calculated as the sum of maintenance and growth components. The maintenance respiration of foliage and live fine roots at a standard temperature of different land cover has been determined from their nitrogen content using field and satellite measurements, while that of living fraction of woody stem (viz., sapwood) from the seasonal maximum leaf area index as determined from satellite

  15. Satellite-Derived Bathymetry: Accuracy Assessment on Depths Derivation Algorithm for Shallow Water Area

    Science.gov (United States)

    Said, N. M.; Mahmud, M. R.; Hasan, R. C.

    2017-10-01

    Over the years, the acquisition technique of bathymetric data has evolved from a shipborne platform to airborne and presently, utilising space-borne acquisition. The extensive development of remote sensing technology has brought in the new revolution to the hydrographic surveying. Satellite-Derived Bathymetry (SDB), a space-borne acquisition technique which derives bathymetric data from high-resolution multispectral satellite imagery for various purposes recently considered as a new promising technology in the hydrographic surveying industry. Inspiring by this latest developments, a comprehensive study was initiated by National Hydrographic Centre (NHC) and Universiti Teknologi Malaysia (UTM) to analyse SDB as a means for shallow water area acquisition. By adopting additional adjustment in calibration stage, a marginal improvement discovered on the outcomes from both Stumpf and Lyzenga algorithms where the RMSE values for the derived (predicted) depths were 1.432 meters and 1.728 meters respectively. This paper would deliberate in detail the findings from the study especially on the accuracy level and practicality of SDB over the tropical environmental setting in Malaysia.

  16. Office of Satellite and Product Operations

    Science.gov (United States)

    ; Strategy » International Agreements » POES Current » GOES Current History » History in Images » POES History » GOES History OSPO Information » Access and Distribution Policy » Organization Chart  Branch utilizes interactive processing technology to integrate multiple satellite sensor data streams

  17. Gravity Anomalies and Estimated Topography Derived from Satellite Altimetry

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In many areas of the global ocean, the depth of the seafloor is not well known because survey lines by ships are hundreds of kilometers apart. Satellites carrying...

  18. SACRA - global data sets of satellite-derived crop calendars for agricultural simulations: an estimation of a high-resolution crop calendar using satellite-sensed NDVI

    Science.gov (United States)

    Kotsuki, S.; Tanaka, K.

    2015-01-01

    To date, many studies have performed numerical estimations of food production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC) is an essential input datum to estimate food production and agricultural water demand accurately with the numerical estimations. CC defines the date or month when farmers plant and harvest in cropland. This study aims to develop a new global data set of a satellite-derived crop calendar for agricultural simulations (SACRA) and reveal advantages and disadvantages of the satellite-derived CC compared to other global products. We estimate global CC at a spatial resolution of 5 min (≈10 km) using the satellite-sensed NDVI data, which corresponds well to vegetation growth and death on the land surface. We first demonstrate that SACRA shows similar spatial pattern in planting date compared to a census-based product. Moreover, SACRA reflects a variety of CC in the same administrative unit, since it uses high-resolution satellite data. However, a disadvantage is that the mixture of several crops in a grid is not considered in SACRA. We also address that the cultivation period of SACRA clearly corresponds to the time series of NDVI. Therefore, accuracy of SACRA depends on the accuracy of NDVI used for the CC estimation. Although SACRA shows different CC from a census-based product in some regions, multiple usages of the two products are useful to take into consideration the uncertainty of the CC. An advantage of SACRA compared to the census-based products is that SACRA provides not only planting/harvesting dates but also a peak date from the time series of NDVI data.

  19. Bio-Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

    Science.gov (United States)

    Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter

    2018-03-01

    An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.

  20. Volcanic SO2 fluxes derived from satellite data: a survey using OMI, GOME-2, IASI and MODIS

    Directory of Open Access Journals (Sweden)

    N. Theys

    2013-06-01

    Full Text Available Sulphur dioxide (SO2 fluxes of active degassing volcanoes are routinely measured with ground-based equipment to characterize and monitor volcanic activity. SO2 of unmonitored volcanoes or from explosive volcanic eruptions, can be measured with satellites. However, remote-sensing methods based on absorption spectroscopy generally provide integrated amounts of already dispersed plumes of SO2 and satellite derived flux estimates are rarely reported. Here we review a number of different techniques to derive volcanic SO2 fluxes using satellite measurements of plumes of SO2 and investigate the temporal evolution of the total emissions of SO2 for three very different volcanic events in 2011: Puyehue-Cordón Caulle (Chile, Nyamulagira (DR Congo and Nabro (Eritrea. High spectral resolution satellite instruments operating both in the ultraviolet-visible (OMI/Aura and GOME-2/MetOp-A and thermal infrared (IASI/MetOp-A spectral ranges, and multispectral satellite instruments operating in the thermal infrared (MODIS/Terra-Aqua are used. We show that satellite data can provide fluxes with a sampling of a day or less (few hours in the best case. Generally the flux results from the different methods are consistent, and we discuss the advantages and weaknesses of each technique. Although the primary objective of this study is the calculation of SO2 fluxes, it also enables us to assess the consistency of the SO2 products from the different sensors used.

  1. Nearshore Benthic Habitats of Timor-Leste Derived from WorldView-2 Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Benthic habitat classes were derived for nearshore waters (< 20 m depths) around Timor-Leste from DigitalGlobe WorldView-2 satellite imagery, acquired from Jan 26...

  2. Level-2 product generation for the Swarm satellite constellation mission

    DEFF Research Database (Denmark)

    Olsen, Poul Erik Holmdahl; Tøffner-Clausen, Lars; Olsen, Nils

    In order to take advantage of the unique constellation aspect of ESA's Swarm constellation mission, considerably advanced data analysis tools have been developed. The Swarm ESL/SCARF (Satellite Constellation Application and Research Facility), a consortium of several research institutions, derives...

  3. Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

    Science.gov (United States)

    Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

    2017-04-01

    In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

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

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

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

  5. Are satellite products good proxies for gauge precipitation over Singapore?

    Science.gov (United States)

    Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

    2018-05-01

    The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate

  6. Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling

    Science.gov (United States)

    Tang, W.; Cohan, D. S.; Pour-Biazar, A.; Lamsal, L. N.; White, A. T.; Xiao, X.; Zhou, W.; Henderson, B. H.; Lash, B. F.

    2015-02-01

    Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O3) regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NOx emissions to identify and reduce uncertainties in bottom-up NOx emissions. However, the joint application of multiple satellite-derived model inputs to improve O3 state implementation plan (SIP) modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES) observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O3 concentrations by up to 80 ppb and improves O3 simulations by reducing modeled normalized mean bias (NMB) and normalized mean error (NME) by up to 0.1. A sector-based discrete Kalman filter (DKF) inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-decoupled direct method (DDM) model to adjust Texas NOx emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO2 product. The discrepancy between OMI and CAMx NO2 vertical column densities (VCDs) is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The region-based DKF inversion suggests increasing NOx emissions by 10-50% in most regions, deteriorating the model performance in predicting ground NO2 and O3, while the sector-based DKF inversion tends to scale down area and nonroad NOx emissions by 50%, leading to a 2-5 ppb decrease in ground 8 h O3 predictions. Model performance in simulating ground NO2 and O3 are improved using sector-based inversion-constrained NOx emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together reduces modeled NMB and NME by 0.05, increases the model

  7. Satellites

    International Nuclear Information System (INIS)

    Burns, J.A.; Matthews, M.S.

    1986-01-01

    The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

  8. Assessment of global precipitation measurement satellite products over Saudi Arabia

    Science.gov (United States)

    Mahmoud, Mohammed T.; Al-Zahrani, Muhammad A.; Sharif, Hatim O.

    2018-04-01

    Most hydrological analysis and modeling studies require reliable and accurate precipitation data for successful simulations. However, precipitation measurements should be more representative of the true precipitation distribution. Many approaches and techniques are used to collect precipitation data. Recently, hydrometeorological and climatological applications of satellite precipitation products have experienced a significant improvement with the emergence of the latest satellite products, namely, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) products, which can be utilized to estimate and analyze precipitation data. This study focuses on the validation of the IMERG early, late and final run rainfall products using ground-based rain gauge observations throughout Saudi Arabia for the period from October 2015 to April 2016. The accuracy of each IMERG product is assessed using six statistical performance measures to conduct three main evaluations, namely, regional, event-based and station-based evaluations. The results indicate that the early run product performed well in the middle and eastern parts as well as some of the western parts of the country; meanwhile, the satellite estimates for the other parts fluctuated between an overestimation and an underestimation. The late run product showed an improved accuracy over the southern and western parts; however, over the northern and middle parts, it showed relatively high errors. The final run product revealed significantly improved precipitation estimations and successfully obtained higher accuracies over most parts of the country. This study provides an early assessment of the performance of the GPM satellite products over the Middle East. The study findings can be used as a beneficial reference for the future development of the IMERG algorithms.

  9. Hydrological Utility and Uncertainty of Multi-Satellite Precipitation Products in the Mountainous Region of South Korea

    Directory of Open Access Journals (Sweden)

    Jong Pil Kim

    2016-07-01

    Full Text Available Satellite-derived precipitation can be a potential source of forcing data for assessing water availability and managing water supply in mountainous regions of East Asia. This study investigates the hydrological utility of satellite-derived precipitation and uncertainties attributed to error propagation of satellite products in hydrological modeling. To this end, four satellite precipitation products (tropical rainfall measuring mission (TRMM multi-satellite precipitation analysis (TMPA version 6 (TMPAv6 and version 7 (TMPAv7, the global satellite mapping of precipitation (GSMaP, and the climate prediction center (CPC morphing technique (CMORPH were integrated into a physically-based hydrologic model for the mountainous region of South Korea. The satellite precipitation products displayed different levels of accuracy when compared to the intra- and inter-annual variations of ground-gauged precipitation. As compared to the GSMaP and CMORPH products, superior performances were seen when the TMPA products were used within streamflow simulations. Significant dry (negative biases in the GSMaP and CMORPH products led to large underestimates of streamflow during wet-summer seasons. Although the TMPA products displayed a good level of performance for hydrologic modeling, there were some over/underestimates of precipitation by satellites during the winter season that were induced by snow accumulation and snowmelt processes. These differences resulted in streamflow simulation uncertainties during the winter and spring seasons. This study highlights the crucial need to understand hydrological uncertainties from satellite-derived precipitation for improved water resource management and planning in mountainous basins. Furthermore, it is suggested that a reliable snowfall detection algorithm is necessary for the new global precipitation measurement (GPM mission.

  10. Particle production in higher derivative theory

    Indian Academy of Sciences (India)

    Lemaitre–Robertson–Walker cosmological model during the early stages of the universe is analysed in the framework of higher derivative theory. The universe has been considered as an open thermodynamic system where particle production ...

  11. Evaluating Terra MODIS Satellite Sensor Data Products for Maize ...

    African Journals Online (AJOL)

    Evaluating Terra MODIS Satellite Sensor Data Products for Maize Yield Estimation in South Africa. C Frost, N Thiebaut, T Newby. Abstract. The Free State Province of the Republic of South Africa contains some of the most important maize-producing areas in South Africa. For this reason this province has also been selected ...

  12. Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

    Directory of Open Access Journals (Sweden)

    Hao Guo

    2015-06-01

    Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.

  13. Resolving traceability issues of product derivation for software product lines

    OpenAIRE

    Abid, Saad bin

    2009-01-01

    peer-reviewed Dealing with traceability management issues during model based product derivation in large complex industrial SPL is error prone due to the lack of tool support. As a result traceability management between connected models emerges as an important research topic. In this position paper, we discuss research challenges as scenarios from developed example product line and give recommendations on resolving traceability issues during product derivation. We also discuss initial idea...

  14. Evaluation of the Precision of Satellite-Derived Sea Surface Temperature Fields

    Science.gov (United States)

    Wu, F.; Cornillon, P. C.; Guan, L.

    2016-02-01

    A great deal of attention has been focused on the temporal accuracy of satellite-derived sea surface temperature (SST) fields with little attention being given to their spatial precision. Specifically, the primary measure of the quality of SST fields has been the bias and variance of selected values minus co-located (in space and time) in situ values. Contributing values, determined by the location of the in situ values and the necessity that the satellite-derived values be cloud free, are generally widely separated in space and time hence provide little information related to the pixel-to-pixel uncertainty in the retrievals. But the main contribution to the uncertainty in satellite-derived SST retrievals relates to atmospheric contamination and because the spatial scales of atmospheric features are, in general, large compared with the pixel separation of modern infra-red sensors, the pixel-to-pixel uncertainty is often smaller than the accuracy determined from in situ match-ups. This makes selection of satellite-derived datasets for the study of submesoscale processes, for which the spatial structure of the upper ocean is significant, problematic. In this presentation we present a methodology to characterize the spatial precision of satellite-derived SST fields. The method is based on an examination of the high wavenumber tail of the 2-D spectrum of SST fields in the Sargasso Sea, a low energy region of the ocean close to the track of the MV Oleander, a container ship making weekly roundtrips between New York and Bermuda, with engine intake temperatures sampled every 75 m along track. Important spectral characteristics are the point at which the satellite-derived spectra separate from the Oleander spectra and the spectral slope following separation. In this presentation a number of high resolution 375 m to 10 km SST datasets are evaluated based on this approach.

  15. sorghum yield and associated satellite-derived meteorological

    African Journals Online (AJOL)

    ACSS

    1Department of Crop Science and Production, Botswana College of Agriculture, Private ... Although the NDVI and RFEs data were available for 2005 to 2011 (6 seasons), the limiting factor was ..... ISPRS Commission VII Mid-term Symposium.

  16. Object-Based Assessment of Satellite Precipitation Products

    Directory of Open Access Journals (Sweden)

    Jingjing Li

    2016-06-01

    Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

  17. Combining satellite derived phenology with climate data for climate change impact assessment

    Science.gov (United States)

    Ivits, E.; Cherlet, M.; Tóth, G.; Sommer, S.; Mehl, W.; Vogt, J.; Micale, F.

    2012-05-01

    The projected influence of climate change on the timing and volume of phytomass production is expected to affect a number of ecosystem services. In order to develop coherent and locally effective adaptation and mitigation strategies, spatially explicit information on the observed changes is needed. Long-term variations of the vegetative growing season in different environmental zones of Europe for 1982-2006 have been derived by analysing time series of GIMMS NDVI data. The associations of phenologically homogenous spatial clusters to time series of temperature and precipitation data were evaluated. North-east Europe showed a trend to an earlier and longer growing season, particularly in the northern Baltic areas. Despite the earlier greening up large areas of Europe exhibited rather stable season length indicating the shift of the entire growing season to an earlier period. The northern Mediterranean displayed a growing season shift towards later dates while some agglomerations of earlier and shorter growing season were also seen. The correlation of phenological time series with climate data shows a cause-and-effect relationship over the semi natural areas consistent with results in literature. Managed ecosystems however appear to have heterogeneous change pattern with less or no correlation to climatic trends. Over these areas climatic trends seemed to overlap in a complex manner with more pronounced effects of local biophysical conditions and/or land management practices. Our results underline the importance of satellite derived phenological observations to explain local nonconformities to climatic trends for climate change impact assessment.

  18. Identifying individual fires from satellite-derived burned area data

    CSIR Research Space (South Africa)

    Archibald, S

    2009-07-01

    Full Text Available An algorithm for identifying individual fires from the Modis burned area data product is introduced for southern Africa. This algorithm gives the date of burning, size of fire, and location of the centroid for all fires identified over 8 years...

  19. Production process for advanced space satellite system cables/interconnects.

    Energy Technology Data Exchange (ETDEWEB)

    Mendoza, Luis A.

    2007-12-01

    This production process was generated for the satellite system program cables/interconnects group, which in essences had no well defined production process. The driver for the development of a formalized process was based on the set backs, problem areas, challenges, and need improvements faced from within the program at Sandia National Laboratories. In addition, the formal production process was developed from the Master's program of Engineering Management for New Mexico Institute of Mining and Technology in Socorro New Mexico and submitted as a thesis to meet the institute's graduating requirements.

  20. Algorithm Development and Validation for Satellite-Derived Distributions of DOC and CDOM in the US Middle Atlantic Bight

    Science.gov (United States)

    Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.

    2007-01-01

    In coastal ocean waters, distributions of dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) vary seasonally and interannually due to multiple source inputs and removal processes. We conducted several oceanographic cruises within the continental margin of the U.S. Middle Atlantic Bight (MAB) to collect field measurements in order to develop algorithms to retrieve CDOM and DOC from NASA's MODIS-Aqua and SeaWiFS satellite sensors. In order to develop empirical algorithms for CDOM and DOC, we correlated the CDOM absorption coefficient (a(sub cdom)) with in situ radiometry (remote sensing reflectance, Rrs, band ratios) and then correlated DOC to Rrs band ratios through the CDOM to DOC relationships. Our validation analyses demonstrate successful retrieval of DOC and CDOM from coastal ocean waters using the MODIS-Aqua and SeaWiFS satellite sensors with mean absolute percent differences from field measurements of cdom)(355)1,6 % for a(sub cdom)(443), and 12% for the CDOM spectral slope. To our knowledge, the algorithms presented here represent the first validated algorithms for satellite retrieval of a(sub cdom) DOC, and CDOM spectral slope in the coastal ocean. The satellite-derived DOC and a(sub cdom) products demonstrate the seasonal net ecosystem production of DOC and photooxidation of CDOM from spring to fall. With accurate satellite retrievals of CDOM and DOC, we will be able to apply satellite observations to investigate interannual and decadal-scale variability in surface CDOM and DOC within continental margins and monitor impacts of climate change and anthropogenic activities on coastal ecosystems.

  1. Near-real-time global biomass burning emissions product from geostationary satellite constellation

    Science.gov (United States)

    Zhang, Xiaoyang; Kondragunta, Shobha; Ram, Jessica; Schmidt, Christopher; Huang, Ho-Chun

    2012-07-01

    Near-real-time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near-real-time global biomass burning emission product from geostationary satellites (GBBEP-Geo) produced from satellite-derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second-generation satellites (Meteosat-09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport Satellite (MTSAT) operated by the Japan Meteorological Agency. These satellites observe wildfires at an interval of 15-30 min. Because of the impacts from sensor saturation, cloud cover, and background surface, the FRP values are generally not continuously observed. The missing observations are simulated by combining the available instantaneous FRP observations within a day and a set of representative climatological diurnal patterns of FRP for various ecosystems. Finally, the simulated diurnal variation in FRP is applied to quantify biomass combustion and emissions in individual fire pixels with a latency of 1 day. By analyzing global patterns in hourly biomass burning emissions in 2010, we find that peak fire season varied greatly and that annual wildfires burned 1.33 × 1012 kg dry mass, released 1.27 × 1010 kg of PM2.5 (particulate mass for particles with diameter forest and savanna fires in Africa, South America, and North America. Evaluation of emission result reveals that the GBBEP-Geo estimates are comparable with other FRP-derived estimates in Africa, while the results are generally smaller than most of the other global products that were derived from burned

  2. Scale up of proteoliposome derived Cochleate production.

    Science.gov (United States)

    Zayas, Caridad; Bracho, Gustavo; Lastre, Miriam; González, Domingo; Gil, Danay; Acevedo, Reinaldo; del Campo, Judith; Taboada, Carlos; Solís, Rosa L; Barberá, Ramón; Pérez, Oliver

    2006-04-12

    Cochleate are highly stable structures with promising immunological features. Cochleate structures are usually obtaining from commercial lipids. Proteoliposome derived Cochleate are derived from an outer membrane vesicles of Neisseria meningitidis B. Previously, we obtained Cochleates using dialysis procedures. In order to increase the production process, we used a crossflow system (CFS) that allows easy scale up to obtain large batches in an aseptic environment. The raw material and solutions used in the production process are already approved for human application. This work demonstrates that CFS is very efficient process to obtain Cochleate structures with a yield of more than 80% and the immunogenicity comparable to that obtained by dialysis membrane.

  3. Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes

    Science.gov (United States)

    Gallant, Alisa L.; Sadinski, Walter J.; Brown, Jesslyn F.; Senay, Gabriel B.; Roth, Mark F.

    2018-01-01

    Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.

  4. Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity

    Directory of Open Access Journals (Sweden)

    S. A. Henson

    2010-02-01

    Full Text Available Global climate change is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR. We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of ~40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (~20–30 years. Analysis of modelled chlorophyll and primary production from 2001–2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

  5. Assessment of Satellite Precipitation Products in the Philippine Archipelago

    Science.gov (United States)

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

    2016-06-01

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

  6. Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

    Directory of Open Access Journals (Sweden)

    Ying Qu

    2015-01-01

    Full Text Available Surface albedo is one of the key controlling geophysical parameters in the surface energy budget studies, and its temporal and spatial variation is closely related to the global climate change and regional weather system due to the albedo feedback mechanism. As an efficient tool for monitoring the surfaces of the Earth, remote sensing is widely used for deriving long-term surface broadband albedo with various geostationary and polar-orbit satellite platforms in recent decades. Moreover, the algorithms for estimating surface broadband albedo from satellite observations, including narrow-to-broadband conversions, bidirectional reflectance distribution function (BRDF angular modeling, direct-estimation algorithm and the algorithms for estimating albedo from geostationary satellite data, are developed and improved. In this paper, we present a comprehensive literature review on algorithms and products for mapping surface broadband albedo with satellite observations and provide a discussion of different algorithms and products in a historical perspective based on citation analysis of the published literature. This paper shows that the observation technologies and accuracy requirement of applications are important, and long-term, global fully-covered (including land, ocean, and sea-ice surfaces, gap-free, surface broadband albedo products with higher spatial and temporal resolution are required for climate change, surface energy budget, and hydrological studies.

  7. 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.

  8. Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland

    Directory of Open Access Journals (Sweden)

    Sheng Chang

    2017-06-01

    Full Text Available In Mongolia, drought is a major natural disaster that can influence and devastate large regions, reduce livestock production, cause economic damage, and accelerate desertification in association with destructive human activities. The objective of this article is to determine the optimal satellite-derived drought indices for accurate and real-time expression of grassland drought in Mongolia. Firstly, an adaptability analysis was performed by comparing nine remote sensing-derived drought indices with reference indicators obtained from field observations using several methods (correlation, consistency percentage (CP, and time-space analysis. The reference information included environmental data, vegetation growth status, and region drought-affected (RDA information at diverse scales (pixel, county, and region for three types of land cover (forest steppe, steppe, and desert steppe. Second, a meteorological index (PED, a normalized biomass (NorBio reference indicator, and the RDA-based drought CP method were adopted for describing Mongolian drought. Our results show that in forest steppe regions the normalized difference water index (NDWI is most sensitive to NorBio (maximum correlation coefficient (MAX_R: up to 0.92 and RDA (maximum CP is 87%, and is most consistent with RDA spatial distribution. The vegetation health index (VHI and temperature condition index (TCI are most correlated with the PED index (MAX_R: 0.75 and soil moisture (MAX_R: 0.58, respectively. In steppe regions, the NDWI is most closely related to soil moisture (MAX_R: 0.69 and the VHI is most related to the PED (MAX_R: 0.76, NorBio (MCC: 0.95, and RDA data (maximum CP is 89%, exhibiting the most consistency with RDA spatial distribution. In desert steppe areas, the vegetation condition index (VCI correlates best with NorBio (MAX_R: 0.92, soil moisture (MAX_R: 0.61, and RDA spatial distribution, while TCI correlates best with the PED (MAX_R: 0.75 and the RDA data (maximum CP is 79

  9. Particle production in higher derivative theory

    Indian Academy of Sciences (India)

    Cosmological models; particle production; higher derivative theory of gravitation. PACS No. 98.80. 1. ... is of singular models where the cosmic expansion is driven by the big-bang impulse; all ... According to Gibbs integrability condition, one cannot independently specify an equa- .... [3] B Hartle and S W Hawking Phys. Rev.

  10. Minding the gaps: new insights into R&D management and operational transitions of NOAA satellite products

    Science.gov (United States)

    Colton, Marie C.; Powell, Alfred M.; Jordan, Gretchen; Mote, Jonathon; Hage, Jerald; Frank, Donald

    2004-10-01

    The NESDIS Center for Satellite Applications and Research (STAR), formerly ORA, Office of Research and Applications, consists of three research and applications divisions that encompass satellite meteorology, oceanography, climatology, and cooperative research with academic institutions. With such a wide background of talent, and a charter to develop operational algorithms and applications, STAR scientists develop satellite-derived land, ice, ocean, and atmospheric environmental data products in support of all of NOAA"s mission goals. In addition, in close association with the Joint Center for Satellite Data Assimilation, STAR scientists actively work with the numerical modeling communities of NOAA, NASA, and DOD to support the development of new methods for assimilation of satellite data. In this new era of observations from many new satellite instruments, STAR aims to effectively integrate these data into multi-platform data products for utilization by the forecast and applications communities. Much of our work is conducted in close partnerships with other agencies, academic institutes, and industry. In order to support the nearly 400 current satellite-derived products for various users on a routine basis from our sister operations office, and to evolve to future systems requires an ongoing strategic planning approach that maps research and development activities from NOAA goals to user requirements. Since R&D accomplishments are not necessarily amenable to precise schedules, appropriate motivators and measures of scientific progress must be developed to assure that the product development cycle remains aligned with the other engineering segments of a satellite program. This article presents the status and results of this comprehensive effort to chart a course from the present set of operational satellites to the future.

  11. Using GIS data and satellite derived irradiance to optimize siting of PV installations in Switzerland

    Science.gov (United States)

    Kahl, Annelen; Nguyen, Viet-Anh; Bartlett, Stuart; Sossan, Fabrizio; Lehning, Michael

    2016-04-01

    For a successful distribution strategy of PV installations, it does not suffice to choose the locations with highest annual total irradiance. Attention needs to be given to spatial correlation patterns of insolation to avoid large system-wide variations, which can cause extended deficits in supply or might even damage the electrical network. One alternative goal instead is to seek configurations that provide the smoothest energy production, with the most reliable and predictable supply. Our work investigates several scenarios, each pursuing a different strategy for a future renewable Switzerland without nuclear power. Based on an estimate for necessary installed capacity for solar power [Bartlett, 2015] we first use heuristics to pre-select realistic placements for PV installations. Then we apply optimization methods to find a subset of locations that provides the best possible combined electricity production. For the first part of the selection process, we use a DEM to exclude high elevation zones which would be difficult to access and which are prone to natural hazards. Then we use land surface cover information to find all zones with potential roof area, deemed suitable for installation of solar panels. The optimization employs Principal Component Analysis of satellite derived irradiance data (Surface Incoming Shortwave Radiation (SIS), based on Meteosat Second Generation sensors) to incorporate a spatial aspect into the selection process that does not simply maximize annual total production but rather provides the most robust supply, by combining regions with anti-correlated cloud cover patterns. Depending on the initial assumptions and constraints, the resulting distribution schemes for PV installations vary with respect to required surface area, annual total and lowest short-term production, and illustrate how important it is to clearly define priorities and policies for a future renewable Switzerland.

  12. Satellite Imagery Production and Processing Using Apache Hadoop

    Science.gov (United States)

    Hill, D. V.; Werpy, J.

    2011-12-01

    The United States Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center Land Science Research and Development (LSRD) project has devised a method to fulfill its processing needs for Essential Climate Variable (ECV) production from the Landsat archive using Apache Hadoop. Apache Hadoop is the distributed processing technology at the heart of many large-scale, processing solutions implemented at well-known companies such as Yahoo, Amazon, and Facebook. It is a proven framework and can be used to process petabytes of data on thousands of processors concurrently. It is a natural fit for producing satellite imagery and requires only a few simple modifications to serve the needs of science data processing. This presentation provides an invaluable learning opportunity and should be heard by anyone doing large scale image processing today. The session will cover a description of the problem space, evaluation of alternatives, feature set overview, configuration of Hadoop for satellite image processing, real-world performance results, tuning recommendations and finally challenges and ongoing activities. It will also present how the LSRD project built a 102 core processing cluster with no financial hardware investment and achieved ten times the initial daily throughput requirements with a full time staff of only one engineer. Satellite Imagery Production and Processing Using Apache Hadoop is presented by David V. Hill, Principal Software Architect for USGS LSRD.

  13. Product derivation in software product families : a case study

    NARCIS (Netherlands)

    Deelstra, S; Sinnema, M; Bosch, J

    2005-01-01

    From our experience with several organizations that employ software product families, we have learned that, contrary to popular belief, deriving individual products from shared software assets is a time-consuming and expensive activity. In this paper we therefore present a study that investigated

  14. The International Satellite Cloud Climatology Project H-Series climate data record product

    Science.gov (United States)

    Young, Alisa H.; Knapp, Kenneth R.; Inamdar, Anand; Hankins, William; Rossow, William B.

    2018-03-01

    This paper describes the new global long-term International Satellite Cloud Climatology Project (ISCCP) H-series climate data record (CDR). The H-series data contain a suite of level 2 and 3 products for monitoring the distribution and variation of cloud and surface properties to better understand the effects of clouds on climate, the radiation budget, and the global hydrologic cycle. This product is currently available for public use and is derived from both geostationary and polar-orbiting satellite imaging radiometers with common visible and infrared (IR) channels. The H-series data currently span July 1983 to December 2009 with plans for continued production to extend the record to the present with regular updates. The H-series data are the longest combined geostationary and polar orbiter satellite-based CDR of cloud properties. Access to the data is provided in network common data form (netCDF) and archived by NOAA's National Centers for Environmental Information (NCEI) under the satellite Climate Data Record Program (https://doi.org/10.7289/V5QZ281S" target="_blank">https://doi.org/10.7289/V5QZ281S). The basic characteristics, history, and evolution of the dataset are presented herein with particular emphasis on and discussion of product changes between the H-series and the widely used predecessor D-series product which also spans from July 1983 through December 2009. Key refinements included in the ISCCP H-series CDR are based on improved quality control measures, modified ancillary inputs, higher spatial resolution input and output products, calibration refinements, and updated documentation and metadata to bring the H-series product into compliance with existing standards for climate data records.

  15. Next-Generation Satellite Precipitation Products for Understanding Global and Regional Water Variability

    Science.gov (United States)

    Hou, Arthur Y.

    2011-01-01

    A major challenge in understanding the space-time variability of continental water fluxes is the lack of accurate precipitation estimates over complex terrains. While satellite precipitation observations can be used to complement ground-based data to obtain improved estimates, space-based and ground-based estimates come with their own sets of uncertainties, which must be understood and characterized. Quantitative estimation of uncertainties in these products also provides a necessary foundation for merging satellite and ground-based precipitation measurements within a rigorous statistical framework. Global Precipitation Measurement (GPM) is an international satellite mission that will provide next-generation global precipitation data products for research and applications. It consists of a constellation of microwave sensors provided by NASA, JAXA, CNES, ISRO, EUMETSAT, DOD, NOAA, NPP, and JPSS. At the heart of the mission is the GPM Core Observatory provided by NASA and JAXA to be launched in 2013. The GPM Core, which will carry the first space-borne dual-frequency radar and a state-of-the-art multi-frequency radiometer, is designed to set new reference standards for precipitation measurements from space, which can then be used to unify and refine precipitation retrievals from all constellation sensors. The next-generation constellation-based satellite precipitation estimates will be characterized by intercalibrated radiometric measurements and physical-based retrievals using a common observation-derived hydrometeor database. For pre-launch algorithm development and post-launch product evaluation, NASA supports an extensive ground validation (GV) program in cooperation with domestic and international partners to improve (1) physics of remote-sensing algorithms through a series of focused field campaigns, (2) characterization of uncertainties in satellite and ground-based precipitation products over selected GV testbeds, and (3) modeling of atmospheric processes and

  16. Evaluation of Satellite and Model Precipitation Products Over Turkey

    Science.gov (United States)

    Yilmaz, M. T.; Amjad, M.

    2017-12-01

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

  17. ASSESSMENT OF SATELLITE PRECIPITATION PRODUCTS IN THE PHILIPPINE ARCHIPELAGO

    Directory of Open Access Journals (Sweden)

    M. D. Ramos

    2016-06-01

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

  18. The remote sensing of ocean primary productivity - Use of a new data compilation to test satellite algorithms

    Science.gov (United States)

    Balch, William; Evans, Robert; Brown, Jim; Feldman, Gene; Mcclain, Charles; Esaias, Wayne

    1992-01-01

    Global pigment and primary productivity algorithms based on a new data compilation of over 12,000 stations occupied mostly in the Northern Hemisphere, from the late 1950s to 1988, were tested. The results showed high variability of the fraction of total pigment contributed by chlorophyll, which is required for subsequent predictions of primary productivity. Two models, which predict pigment concentration normalized to an attenuation length of euphotic depth, were checked against 2,800 vertical profiles of pigments. Phaeopigments consistently showed maxima at about one optical depth below the chlorophyll maxima. CZCS data coincident with the sea truth data were also checked. A regression of satellite-derived pigment vs ship-derived pigment had a coefficient of determination. The satellite underestimated the true pigment concentration in mesotrophic and oligotrophic waters and overestimated the pigment concentration in eutrophic waters. The error in the satellite estimate showed no trends with time between 1978 and 1986.

  19. Moisture convergence using satellite-derived wind fields - A severe local storm case study

    Science.gov (United States)

    Negri, A. J.; Vonder Haar, T. H.

    1980-01-01

    Five-minute interval 1-km resolution SMS visible channel data were used to derive low-level wind fields by tracking small cumulus clouds on NASA's Atmospheric and Oceanographic Information Processing System. The satellite-derived wind fields were combined with surface mixing ratios to derive horizontal moisture convergence in the prestorm environment of April 24, 1975. Storms began developing in an area extending from southwest Oklahoma to eastern Tennessee 2 h subsequent to the time of the derived fields. The maximum moisture convergence was computed to be 0.0022 g/kg per sec and areas of low-level convergence of moisture were in general indicative of regions of severe storm genesis. The resultant moisture convergence fields derived from two wind sets 20 min apart were spatially consistent and reflected the mesoscale forcing of ensuing storm development. Results are discussed with regard to possible limitations in quantifying the relationship between low-level flow and between low-level flow and satellite-derived cumulus motion in an antecedent storm environment.

  20. Arctic sea ice albedo - A comparison of two satellite-derived data sets

    Science.gov (United States)

    Schweiger, Axel J.; Serreze, Mark C.; Key, Jeffrey R.

    1993-01-01

    Spatial patterns of mean monthly surface albedo for May, June, and July, derived from DMSP Operational Line Scan (OLS) satellite imagery are compared with surface albedos derived from the International Satellite Cloud Climatology Program (ISCCP) monthly data set. Spatial patterns obtained by the two techniques are in general agreement, especially for June and July. Nevertheless, systematic differences in albedo of 0.05 - 0.10 are noted which are most likely related to uncertainties in the simple parameterizations used in the DMSP analyses, problems in the ISCCP cloud-clearing algorithm and other modeling simplifications. However, with respect to the eventual goal of developing a reliable automated retrieval algorithm for compiling a long-term albedo data base, these initial comparisons are very encouraging.

  1. Global detailed gravimetric geoid. [based on gravity model derived from satellite tracking and surface gravity data

    Science.gov (United States)

    Vincent, S.; Marsh, J. G.

    1973-01-01

    A global detailed gravimetric geoid has been computed by combining the Goddard Space Flight Center GEM-4 gravity model derived from satellite and surface gravity data and surface 1 deg-by-1 deg mean free air gravity anomaly data. The accuracy of the geoid is + or - 2 meters on continents, 5 to 7 meters in areas where surface gravity data are sparse, and 10 to 15 meters in areas where no surface gravity data are available. Comparisons have been made with the astrogeodetic data provided by Rice (United States), Bomford (Europe), and Mather (Australia). Comparisons have also been carried out with geoid heights derived from satellite solutions for geocentric station coordinates in North America, the Caribbean, Europe, and Australia.

  2. Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

    Science.gov (United States)

    Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

    2009-01-01

    We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

  3. Merged/integrated Bathymetric Data Derived from Multibeam Sonar, LiDAR, and Satellite-derived Bathymetry

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with derived bathymetry from alternate sources to provide a GIS layer with expanded spatial coverage. Integrated products...

  4. Estimation of PV energy production based on satellite data

    Science.gov (United States)

    Mazurek, G.

    2015-09-01

    Photovoltaic (PV) technology is an attractive source of power for systems without connection to power grid. Because of seasonal variations of solar radiation, design of such a power system requires careful analysis in order to provide required reliability. In this paper we present results of three-year measurements of experimental PV system located in Poland and based on polycrystalline silicon module. Irradiation values calculated from results of ground measurements have been compared with data from solar radiation databases employ calculations from of satellite observations. Good convergence level of both data sources has been shown, especially during summer. When satellite data from the same time period is available, yearly and monthly production of PV energy can be calculated with 2% and 5% accuracy, respectively. However, monthly production during winter seems to be overestimated, especially in January. Results of this work may be helpful in forecasting performance of similar PV systems in Central Europe and allow to make more precise forecasts of PV system performance than based only on tables with long time averaged values.

  5. A diagnostic approach to obtaining planetary boundary layer winds using satellite-derived thermal data

    Science.gov (United States)

    Belt, Carol L.; Fuelberg, Henry E.

    1984-01-01

    The feasibility of using satellite derived thermal data to generate realistic synoptic scale winds within the planetary boundary layer (PBL) is examined. Diagnostic modified Ekman wind equations from the Air Force Global Weather Central (AFGWC) Boundary Layer Model are used to compute winds at seven levels within the PBL transition layer (50 m to 1600 m AGL). Satellite derived winds based on 62 predawn TIROS-N soundings are compared to similarly derived wind fields based on 39 AVE-SESAME II rawinsonde (RAOB) soundings taken 2 h later. Actual wind fields are also used as a basis for comparison. Qualitative and statistical comparisons show that the Ekman winds from both sources are in very close agreement, with an average vector correlation coefficient of 0.815. Best results are obtained at 300 m AGL. Satellite winds tend to be slightly weaker than their RAOB counterparts and exhibit a greater degree of cross-isobaric flow. The modified Ekman winds show a significant improvement over geostrophic values at levels nearest the surface.

  6. Estimates of lightning NOx production from GOME satellite observations

    Directory of Open Access Journals (Sweden)

    K. F. Boersma

    2005-01-01

    Full Text Available Tropospheric NO2 column retrievals from the Global Ozone Monitoring Experiment (GOME satellite spectrometer are used to quantify the source strength and 3-D distribution of lightning produced nitrogen oxides (NOx=NO+NO2. A sharp increase of NO2 is observed at convective cloud tops with increasing cloud top height, consistent with a power-law behaviour with power 5±2. Convective production of clouds with the same cloud height are found to produce NO2 with a ratio 1.6/1 for continents compared to oceans. This relation between cloud properties and NO2 is used to construct a 10:30 local time global lightning NO2 production map for 1997. An extensive statistical comparison is conducted to investigate the capability of the TM3 chemistry transport model to reproduce observed patterns of lightning NO2 in time and space. This comparison uses the averaging kernel to relate modelled profiles of NO2 to observed NO2 columns. It exploits a masking scheme to minimise the interference of other NOx sources on the observed total columns. Simulations are performed with two lightning parameterizations, one relating convective preciptation (CP scheme to lightning flash distributions, and the other relating the fifth power of the cloud top height (H5 scheme to lightning distributions. The satellite-retrieved NO2 fields show significant correlations with the simulated lightning contribution to the NO2 concentrations for both parameterizations. Over tropical continents modelled lightning NO2 shows remarkable quantitative agreement with observations. Over the oceans however, the two model lightning parameterizations overestimate the retrieved NO2 attributed to lightning. Possible explanations for these overestimations are discussed. The ratio between satellite-retrieved NO2 and modelled lightning NO2 is used to rescale the original modelled lightning NOx production. Eight estimates of the lightning NOx production in 1997 are obtained from spatial and temporal

  7. CHAOS-2-a geomagnetic field model derived from one decade of continuous satellite data

    DEFF Research Database (Denmark)

    Olsen, Nils; Mandea, M.; Sabaka, T.J.

    2009-01-01

    We have derived a model of the near-Earth's magnetic field using more than 10 yr of high-precision geomagnetic measurements from the three satellites Orsted, CHAMP and SAC-C. This model is an update of the two previous models, CHAOS (Olsen et al. 2006) and xCHAOS (Olsen & Mandea 2008). Data...... by minimizing the second time derivative of the squared magnetic field intensity at the core-mantle boundary. The CHAOS-2 model describes rapid time changes, as monitored by the ground magnetic observatories, much better than its predecessors....

  8. 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...

  9. A machine learning approach to estimation of downward solar radiation from satellite-derived data products: An application over a semi-arid ecosystem in the U.S.

    Science.gov (United States)

    Zhou, Qingtao; Flores, Alejandro; Glenn, Nancy F; Walters, Reggie; Han, Bangshuai

    2017-01-01

    Shortwave solar radiation is an important component of the surface energy balance and provides the principal source of energy for terrestrial ecosystems. This paper presents a machine learning approach in the form of a random forest (RF) model for estimating daily downward solar radiation flux at the land surface over complex terrain using MODIS (MODerate Resolution Imaging Spectroradiometer) remote sensing data. The model-building technique makes use of a unique network of 16 solar flux measurements in the semi-arid Reynolds Creek Experimental Watershed and Critical Zone Observatory, in southwest Idaho, USA. Based on a composite RF model built on daily observations from all 16 sites in the watershed, the model simulation of downward solar radiation matches well with the observation data (r2 = 0.96). To evaluate model performance, RF models were built from 12 of 16 sites selected at random and validated against the observations at the remaining four sites. Overall root mean square errors (RMSE), bias, and mean absolute error (MAE) are small (range: 37.17 W/m2-81.27 W/m2, -48.31 W/m2-15.67 W/m2, and 26.56 W/m2-63.77 W/m2, respectively). When extrapolated to the entire watershed, spatiotemporal patterns of solar flux are largely consistent with expected trends in this watershed. We also explored significant predictors of downward solar flux in order to reveal important properties and processes controlling downward solar radiation. Based on the composite RF model built on all 16 sites, the three most important predictors to estimate downward solar radiation include the black sky albedo (BSA) near infrared band (0.858 μm), BSA visible band (0.3-0.7 μm), and clear day coverage. This study has important implications for improving the ability to derive downward solar radiation through a fusion of multiple remote sensing datasets and can potentially capture spatiotemporally varying trends in solar radiation that is useful for land surface hydrologic and terrestrial

  10. Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

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

    2013-12-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, 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), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme

  11. A Satellite-Based Surface Radiation Climatology Derived by Combining Climate Data Records and Near-Real-Time Data

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-09-01

    Full Text Available This study presents a method for adjusting long-term climate data records (CDRs for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS. Recently, a 23-year long (1983–2005 continuous SIS CDR has been generated based on the visible channel (0.45–1 μm of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF. Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005 and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present was applied that combines the Standard Normal Homogeneity Test (SNHT and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN and about 50 stations of the Global Energy Balance Archive (GEBA over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of

  12. Vegetable milks and their fermented derivative products

    Directory of Open Access Journals (Sweden)

    Neus Bernat

    2014-04-01

    Full Text Available The so-called vegetable milks are in the spotlight thanks to their lactose-free, animal protein-free and cholesterol-free features which fit well with the current demand for healthy food products. Nevertheless, and with the exception of soya, little information is available about these types of milks and their derivatives. The aims of this review, therefore, are to: highlight the main nutritional benefits of the nut and cereal vegetable milks available on the market, fermented or not; describe the basic processing steps involved in their manufacturing process; and analyze the major problems affecting their overall quality, together with the current feasible solutions. On the basis of the information gathered, vegetable milks and their derivatives have excellent nutritional properties which provide them a high potential and positive market expectation. Nevertheless, optimal processing conditions for each raw material or the application of new technologies have to be researched in order to improve the quality of the products. Hence, further studies need to be developed to ensure the physical stability of the products throughout their whole shelf-life. These studies would also allow for a reduction in the amount of additives (hydrocolloids and/or emulsifiers and thus reduce the cost of the products. In the particular case of fermented products, the use of starters which are able to both improve the quality (by synthesizing enhanced flavors and providing optimal textures and exert health benefits for consumers (i.e. probiotics is the main challenge to be faced in future studies.

  13. Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

    Science.gov (United States)

    Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

    2014-08-01

    The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

  14. Assessment of satellite rainfall products over the Andean plateau

    Science.gov (United States)

    Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

    2016-01-01

    Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a

  15. Rainfall frequency analysis for ungauged sites using satellite precipitation products

    Science.gov (United States)

    Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh

    2017-11-01

    The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

  16. Assessing water availability over peninsular Malaysia using public domain satellite data products

    International Nuclear Information System (INIS)

    Ali, M I; Hashim, M; Zin, H S M

    2014-01-01

    Water availability monitoring is an essential task for water resource sustainability and security. In this paper, the assessment of satellite remote sensing technique for determining water availability is reported. The water-balance analysis is used to compute the spatio-temporal water availability with main inputs; the precipitation and actual evapotranspiration rate (AET), both fully derived from public-domain satellite products of Tropical Rainfall Measurement Mission (TRMM) and MODIS, respectively. Both these satellite products were first subjected to calibration to suit corresponding selected local precipitation and AET samples. Multi-temporal data sets acquired 2000-2010 were used in this study. The results of study, indicated strong agreement of monthly water availability with the basin flow rate (r 2 = 0.5, p < 0.001). Similar agreements were also noted between the estimated annual average water availability with the in-situ measurement. It is therefore concluded that the method devised in this study provide a new alternative for water availability mapping over large area, hence offers the only timely and cost-effective method apart from providing comprehensive spatio-temporal patterns, crucial in water resource planning to ensure water security

  17. A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data

    Science.gov (United States)

    Leng, Pei; Li, Zhao-Liang; Duan, Si-Bo; Gao, Mao-Fang; Huo, Hong-Yuan

    2017-09-01

    Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images and gridded meteorological products. In this approach, soil moisture over the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky pixels are estimated from the Vegetation Index/Temperature (VIT) trapezoid scheme in which theoretical dry and wet edges were determined pixel to pixel by China Meteorological Administration Land Data Assimilation System (CLDAS) meteorological products, including air temperature, solar radiation, wind speed and specific humidity. For cloudy pixels, soil moisture values are derived by the calculation of surface and aerodynamic resistances from wind speed. The approach is capable of filling the soil moisture gaps over remaining cloudy pixels by traditional optical/thermal infrared methods, allowing for a spatially complete soil moisture map over large areas. Evaluation over agricultural fields indicates that the proposed approach can produce an overall generally reasonable distribution of all-weather soil moisture. An acceptable accuracy between the estimated all-weather soil moisture and in-situ measurements at different depths could be found with an Root Mean Square Error (RMSE) varying from 0.067 m3/m3 to 0.079 m3/m3 and a slight bias ranging from 0.004 m3/m3 to -0.011 m3/m3. The proposed approach reveals significant potential to derive all-weather soil moisture using currently available satellite images and meteorological products at a regional or global scale in future developments.

  18. Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm

    Directory of Open Access Journals (Sweden)

    Waseem Muhammad

    2018-04-01

    Full Text Available Satellite-based precipitation products (e.g., Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG and its predecessor, Tropical Rainfall Measuring Mission (TRMM are a critical source of precipitation estimation, particularly for a region with less, or no, hydrometric networking. However, the inconsistency in the performance of these products has been observed in different climatic and topographic diverse regions, timescales, and precipitation intensities and there is still room for improvement. Hence, using a projected ensemble algorithm, the regional precipitation estimate (RP is introduced here. The RP concept is mainly based on the regional performance weights derived from the Mean Square Error (MSE and the precipitation estimate from the TRMM product, that is, TRMM 3B42 (TR, real-time (late (IT and the research (post-real-time (IR products of IMERG. The overall results of the selected contingency table (e.g., Probability of detection (POD and statistical indices (e.g., Correlation Coefficient (CC signposted that the proposed RP product has shown an overall better potential to capture the gauge observations compared with the TR, IR, and IT in five different climatic regions of Pakistan from January 2015 to December 2016, at a diurnal time scale. The current study could be the first research providing preliminary feedback from Pakistan for global precipitation measurement researchers by highlighting the need for refinement in the IMERG.

  19. A climate index derived from satellite measured spectral infrared radiation. Ph.D. Thesis

    Science.gov (United States)

    Abel, M. D.; Fox, S. K.

    1982-01-01

    The vertical infrared radiative emitting structure (VIRES) climate index, based on radiative transfer theory and derived from the spectral radiances typically used to retrieve temperature profiles, is introduced. It is assumed that clouds and climate are closely related and a change in one will result in a change in the other. The index is a function of the cloud, temperature, and moisture distributions. It is more accurately retrieved from satellite data than is cloudiness per se. The VIRES index is based upon the shape and relative magnitude of the broadband weighting function of the infrared radiative transfer equation. The broadband weighting curves are retrieved from simulated satellite infrared sounder data (spectral radiances). The retrieval procedure is described and the error error sensitivities of the method investigated. Index measuring options and possible applications of the VIRES index are proposed.

  20. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  1. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

  2. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  3. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multispectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  4. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  5. Validation of satellite-derived tropical cyclone heat potential with in situ observations in the North Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Nagamani, P.V.; Ali, M.M.; Goni, G.J.; Dinezio, P.N.; Pezzullo, J.C.; UdayaBhaskar, T.V.S.; Gopalakrishna, V.V.; Nisha, K.

    validation with in situ estimations for quantification of their reliability and consistency. Once the validation has been carried out, the satellite-derived TCHP values with their improved tempo- ral and spatial properties can be conveniently used...

  6. Migration to Earth Observation Satellite Product Dissemination System at JAXA

    Science.gov (United States)

    Ikehata, Y.; Matsunaga, M.

    2017-12-01

    JAXA released "G-Portal" as a portal web site for search and deliver data of Earth observation satellites in February 2013. G-Portal handles ten satellites data; GPM, TRMM, Aqua, ADEOS-II, ALOS (search only), ALOS-2 (search only), MOS-1, MOS-1b, ERS-1 and JERS-1 and archives 5.17 million products and 14 million catalogues in total. Users can search those products/catalogues in GUI web search and catalogue interface(CSW/Opensearch). In this fiscal year, we will replace this to "Next G-Portal" and has been doing integration, test and migrations. New G-Portal will treat data of satellites planned to be launched in the future in addition to those handled by G - Portal. At system architecture perspective, G-Portal adopted "cluster system" for its redundancy, so we must replace the servers into those with higher specifications when we improve its performance ("scale up approach"). This requests a lot of cost in every improvement. To avoid this, Next G-Portal adopts "scale out" system: load balancing interfaces, distributed file system, distributed data bases. (We reported in AGU fall meeting 2015(IN23D-1748).) At customer usability perspective, G-Portal provides complicated interface: "step by step" web design, randomly generated URLs, sftp (needs anomaly tcp port). Customers complained about the interfaces and the support team had been tired from answering them. To solve this problem, Next G-Portal adopts simple interfaces: "1 page" web design, RESTful URL, and Normal FTP. (We reported in AGU fall meeting 2016(IN23B-1778).) Furthermore, Next G-Portal must merge GCOM-W data dissemination system to be terminated in the next March as well as the current G-Portal. This might arrise some difficulties, since the current G-Portal and GCOM-W data dissemination systems are quite different from Next G-Portal. The presentation reports the knowledge obtained from the process of merging those systems.

  7. Quantifying the clear-sky bias of satellite-derived infrared LST

    Science.gov (United States)

    Ermida, S. L.; Trigo, I. F.; DaCamara, C.

    2017-12-01

    Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

  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. Antarctic and Greenland ice sheet mass balance products from satellite gravimetry

    Science.gov (United States)

    Horwath, Martin; Groh, Andreas; Horvath, Alexander; Forsberg, René; Meister, Rakia; Barletta, Valentina R.; Shepherd, Andrew

    2017-04-01

    Because of their important role in the Earth's climate system, ESA's Climate Change Initiative (CCI) has identified both the Antarctic Ice Sheet (AIS) and the Greenland Ice Sheet (GIS) as Essential Climate Variables (ECV). Since respondents of a user survey indicated that the ice sheet mass balance is one of the most important ECV data products needed to better understand climate change, the AIS_cci and the GIS_cci project provide Gravimetric Mass Balance (GMB) products based on satellite gravimetry data. The GMB products are derived from GRACE (Gravity Recovery and Climate Experiment) monthly solutions of release ITSG-Grace2016 produced at TU Graz. GMB basin products (i.e. time series of monthly mass changes for the entire ice sheets and selected drainage basins) and GMB gridded products (e.g. mass balance estimates with a formal resolution of about 50km, covering the entire ice sheets) are generated for the period from 2002 until present. The first GMB product was released in mid 2016. Here we present an extended and updated version of the ESA CCI GMB products, which are freely available through data portals hosted by the projects (https://data1.geo.tu-dresden.de/ais_gmb, http://products.esa-icesheets-cci.org/products/downloadlist/GMB). Since the initial product release, the applied processing strategies have been improved in order to further reduce GRACE errors and to enhance the separation of signals super-imposed to the ice mass changes. While a regional integration approach is used by the AIS_cci project, the GMB products of the GIS_cci project are derived using a point mass inversion. The differences between both approaches are investigated through the example of the GIS, where an alternative GMB product was generated using the regional integration approach implemented by the AIS_cci. Finally, we present the latest mass balance estimates for both ice sheets as well as their corresponding contributions to global sea level rise.

  10. Potential for a biogenic influence on cloud microphysics over the ocean: a correlation study with satellite-derived data

    Directory of Open Access Journals (Sweden)

    A. Lana

    2012-09-01

    Full Text Available Aerosols have a large potential to influence climate through their effects on the microphysics and optical properties of clouds and, hence, on the Earth's radiation budget. Aerosol–cloud interactions have been intensively studied in polluted air, but the possibility that the marine biosphere plays an important role in regulating cloud brightness in the pristine oceanic atmosphere remains largely unexplored. We used 9 yr of global satellite data and ocean climatologies to derive parameterizations of the temporal variability of (a production fluxes of sulfur aerosols formed by the oxidation of the biogenic gas dimethylsulfide emitted from the sea surface; (b production fluxes of secondary organic aerosols from biogenic organic volatiles; (c emission fluxes of biogenic primary organic aerosols ejected by wind action on sea surface; and (d emission fluxes of sea salt also lifted by the wind upon bubble bursting. Series of global monthly estimates of these fluxes were correlated to series of potential cloud condensation nuclei (CCN numbers derived from satellite (MODIS. More detailed comparisons among weekly series of estimated fluxes and satellite-derived cloud droplet effective radius (re data were conducted at locations spread among polluted and clean regions of the oceanic atmosphere. The outcome of the statistical analysis was that positive correlation to CCN numbers and negative correlation to re were common at mid and high latitude for sulfur and organic secondary aerosols, indicating both might be important in seeding cloud droplet activation. Conversely, primary aerosols (organic and sea salt showed widespread positive correlations to CCN only at low latitudes. Correlations to re were more variable, non-significant or positive, suggesting that, despite contributing to large shares of the marine aerosol mass, primary aerosols are not widespread major drivers of the variability of cloud

  11. Land-atmosphere interaction patterns in southeastern South America using satellite products and climate models

    Science.gov (United States)

    Spennemann, P. C.; Salvia, M.; Ruscica, R. C.; Sörensson, A. A.; Grings, F.; Karszenbaum, H.

    2018-02-01

    In regions of strong Land-Atmosphere (L-A) interaction, soil moisture (SM) conditions can impact the atmosphere through modulating the land surface fluxes. The importance of the identification of L-A interaction regions lies in the potential improvement of the weather/seasonal forecast and the better understanding of the physical mechanisms involved. This study aims to compare the terrestrial segment of the L-A interaction from satellite products and climate models, motivated by previous modeling studies pointing out southeastern South America (SESA) as a L-A hotspot during austral summer. In addition, the L-A interaction under dry or wet anomalous conditions over SESA is analyzed. To identify L-A hotspots the AMSRE-LPRM SM and MODIS land surface temperature products; coupled climate models and uncoupled land surface models were used. SESA highlights as a strong L-A interaction hotspot when employing different metrics, temporal scales and independent datasets, showing consistency between models and satellite estimations. Both AMSRE-LPRM bands (X and C) are consistent showing a strong L-A interaction hotspot over the Pampas ecoregion. Intensification and a larger spatial extent of the L-A interaction for dry summers was observed in both satellite products and models compared to wet summers. These results, which were derived from measured physical variables, are encouraging and promising for future studies analyzing L-A interactions. L-A interaction analysis is proposed here as a meeting point between remote sensing and climate modelling communities of Argentina, within a region with the highest agricultural and livestock production of the continent, but with an important lack of in-situ SM observations.

  12. Classification of Dust Days by Satellite Remotely Sensed Aerosol Products

    Science.gov (United States)

    Sorek-Hammer, M.; Cohen, A.; Levy, Robert C.; Ziv, B.; Broday, D. M.

    2013-01-01

    Considerable progress in satellite remote sensing (SRS) of dust particles has been seen in the last decade. From an environmental health perspective, such an event detection, after linking it to ground particulate matter (PM) concentrations, can proxy acute exposure to respirable particles of certain properties (i.e. size, composition, and toxicity). Being affected considerably by atmospheric dust, previous studies in the Eastern Mediterranean, and in Israel in particular, have focused on mechanistic and synoptic prediction, classification, and characterization of dust events. In particular, a scheme for identifying dust days (DD) in Israel based on ground PM10 (particulate matter of size smaller than 10 nm) measurements has been suggested, which has been validated by compositional analysis. This scheme requires information regarding ground PM10 levels, which is naturally limited in places with sparse ground-monitoring coverage. In such cases, SRS may be an efficient and cost-effective alternative to ground measurements. This work demonstrates a new model for identifying DD and non-DD (NDD) over Israel based on an integration of aerosol products from different satellite platforms (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)). Analysis of ground-monitoring data from 2007 to 2008 in southern Israel revealed 67 DD, with more than 88 percent occurring during winter and spring. A Classification and Regression Tree (CART) model that was applied to a database containing ground monitoring (the dependent variable) and SRS aerosol product (the independent variables) records revealed an optimal set of binary variables for the identification of DD. These variables are combinations of the following primary variables: the calendar month, ground-level relative humidity (RH), the aerosol optical depth (AOD) from MODIS, and the aerosol absorbing index (AAI) from OMI. A logistic regression that uses these variables, coded as binary

  13. Estimating Net Primary Productivity Using Satellite and Ancillary Data

    Science.gov (United States)

    Choudhury, Bhaskar J.

    2002-01-01

    The net primary productivity (C) or the annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of gross photosynthesis (A(sub g)) and respiration (R) per unit ground area. Available field observations show that R is a large and variable fraction of A(sub g), although it is generally recognized that there are considerable difficulties in determining these fluxes, and thus pose challenge in assessing the accuracy. Further uncertainties arise in extrapolating field measurements (which are acquired over a hectare or so area) to regional scale. Here, an approach is presented for determining these fluxes using satellite and ancillary data to be representative of regional scale and allow assessment of interannual variation. A, has been expressed as the product of radiation use efficiency for gross photosynthesis by an unstressed canopy and intercepted photosynthetically active radiation, which is then adjusted for stresses due to soil water shortage and temperature away from optimum. R has been calculated as the sum of growth and maintenance components (respectively, R(sub g) and R(sub m)).The R(sub m) has been determined from nitrogen content of plant tissue per unit ground area, while R(sub g) has been obtained as a fraction of the difference of A(sub g) and R(sub m). Results for five consecutive years (1986-1990) are presented for the Amazon-Tocontins, Mississippi, and Ob River basins.

  14. Assessment of Satellite-Derived Surface Reflectances by NASA's CAR Airborne Radiometer over Railroad Valley, Nevada

    Science.gov (United States)

    Kharbouche, Said; Muller, Jan-Peter; Gatebe, Charles K.; Scanlon, Tracy; Banks, Andrew C.

    2017-01-01

    CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada (38.504 deg N, 115.692 deg W).The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CARs land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol

  15. Modeling UV-B Effects on Primary Production Throughout the Southern Ocean Using Multi-Sensor Satellite Data

    Science.gov (United States)

    Lubin, Dan

    2001-01-01

    This study has used a combination of ocean color, backscattered ultraviolet, and passive microwave satellite data to investigate the impact of the springtime Antarctic ozone depletion on the base of the Antarctic marine food web - primary production by phytoplankton. Spectral ultraviolet (UV) radiation fields derived from the satellite data are propagated into the water column where they force physiologically-based numerical models of phytoplankton growth. This large-scale study has been divided into two components: (1) the use of Total Ozone Mapping Spectrometer (TOMS) and Special Sensor Microwave Imager (SSM/I) data in conjunction with radiative transfer theory to derive the surface spectral UV irradiance throughout the Southern Ocean; and (2) the merging of these UV irradiances with the climatology of chlorophyll derived from SeaWiFS data to specify the input data for the physiological models.

  16. A new CM SAF Solar Surface Radiation Climate Data Set derived from Meteosat Satellite Observations

    Science.gov (United States)

    Trentmann, J.; Mueller, R. W.; Pfeifroth, U.; Träger-Chatterjee, C.; Cremer, R.

    2014-12-01

    The incoming surface solar radiation has been defined as an essential climate variable by GCOS. It is mandatory to monitor this part of the earth's energy balance, and thus gain insights on the state and variability of the climate system. In addition, data sets of the surface solar radiation have received increased attention over the recent years as an important source of information for the planning of solar energy applications. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving surface solar radiation from geostationary and polar-orbiting satellite instruments. While CM SAF is focusing on the generation of high-quality long-term climate data records, also operationally data is provided in short time latency within 8 weeks. Here we present SARAH (Solar Surface Radiation Dataset - Heliosat), i.e. the new CM SAF Solar Surface Radiation data set based on Meteosat satellite observations. SARAH provides instantaneous, daily- and monthly-averaged data of the effective cloud albedo (CAL), the direct normalized solar radiation (DNI) and the solar irradiance (SIS) from 1983 to 2013 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05 deg allowing for detailed regional studies, and are available in netcdf-format at no cost without restrictions at www.cmsaf.eu. We provide an overview of the data sets, including a validation against reference measurements from the BSRN and GEBA surface station networks.

  17. Applications of Satellite Remote Sensing Products to Enhance and Evaluate the AIRPACT Regional Air Quality Modeling System

    Science.gov (United States)

    Herron-Thorpe, F. L.; Mount, G. H.; Emmons, L. K.; Lamb, B. K.; Jaffe, D. A.; Wigder, N. L.; Chung, S. H.; Zhang, R.; Woelfle, M.; Vaughan, J. K.; Leung, F. T.

    2013-12-01

    The WSU AIRPACT air quality modeling system for the Pacific Northwest forecasts hourly levels of aerosols and atmospheric trace gases for use in determining potential health and ecosystem impacts by air quality managers. AIRPACT uses the WRF/SMOKE/CMAQ modeling framework, derives dynamic boundary conditions from MOZART-4 forecast simulations with assimilated MOPITT CO, and uses the BlueSky framework to derive fire emissions. A suite of surface measurements and satellite-based remote sensing data products across the AIRPACT domain are used to evaluate and improve model performance. Specific investigations include anthropogenic emissions, wildfire simulations, and the effects of long-range transport on surface ozone. In this work we synthesize results for multiple comparisons of AIRPACT with satellite products such as IASI ammonia, AIRS carbon monoxide, MODIS AOD, OMI tropospheric ozone and nitrogen dioxide, and MISR plume height. Features and benefits of the newest version of AIRPACT's web-interface are also presented.

  18. Satellite Derived Bathymetry as a Coastal Geo-Intelligence Tool for Alaska

    Science.gov (United States)

    Ventura, D. C.

    2017-12-01

    What do marine rescue, navigation safety, resource management, coastal infrastructure management, climate adaptation and resilience, economic investment, habitat protection agencies and institutions all have in common? They all benefit from accurate coastal bathymetric data As Arctic-Related Incidents of National Significance (IoNS) workshop points out, reducing time and cost of collecting coastal bathymetry in the Arctic is fundamental to addressing needs of a multitude of stakeholders. Until recently, high resolution coastal data acquisition involved field mobilization of planes, vessels, and people. Given limited resources, short season and remoteness, this approach results in very modest progress toward filling the Alaska's coastal bathymetry data gap and updating vintage data from circa Captain Cook.After successfully executing Satellite Derived Bathymetry (SDB) projects in other more environmentally suitable locations, Fugro and its partner EOMAP are now assessing suitability SDB technique along the Alaska coast. This includes aaccessing archived satellite data and understanding best environmental conditions for the mapping and defining maximum mapping depth as an initial action to understand potentials for Alaska. Here we leverage the physics-based approach to satellite imagery data extraction to derive water depth and complimentary intelligence such as seafloor habitat mapping and certain water quality parameters, such as clarity, turbidity, sediment and chlorophyll-a concentrations, and seasonal changes. Both new and archive imagery are utilized as part of the process. If successful, the benefits and cost savings of this approach are enormous as repeat rate for data collects like this can be measured in months/years as opposed to decades/centuries. Arctic coasts have multiple vulnerabilities and the rate of change will continue to outpace the budgets. As innovative and learning organizations, Fugro and EOMAP strive to not only share the results of this

  19. Characterization of the variability of the South Pacific Convergence Zone using satellite and reanalysis wind products

    Science.gov (United States)

    Kidwell, Autumn; Lee, Tong; Jo, Young-Heon; Yan, Xiao-hai

    2016-04-01

    The South Pacific Convergence Zone (SPCZ), the largest rain band worldwide during austral summer, is important to atmospheric circulation (including cyclone genesis) and ocean circulation. Previous studies of the SPCZ have focused on parameters such as outgoing longwave radiation or precipitation. However, wind convergence is fundamental causing the variations of these parameters. In this study, the SPCZ variability is examined using ocean surface wind products derived from NASA's QuickSCAT (1999-2009) and ESA's ASCAT (2007 onward) satellite scatterometers and ERA-Interim atmospheric reanalysis (1981 onward). From these products, indices were developed to characterize the SPCZ strength, area, and centroid location. Excellent agreement is found in terms of the temporal variations of the indices derived from the satellites and reanalysis wind products, despite some small differences in the time-mean SPCZ strength. The SPCZ strength, area, and centroid latitude have a dominant seasonal cycle. In contrast, the SPCZ centroid longitude is dominated by intraseasonal variability due to the influence by the Madden-Julian Oscillation. The SPCZ indices are all correlated with El Niño-Southern Oscillation indices. Interannual and intraseasonal variations of SPCZ strength during strong El Niño are approximately twice as large as the respective seasonal variations. SPCZ strength depends more on the intensity of El Niño rather than the central- vs. eastern-Pacific type. The longer ERA-Interim product is also used to examine decadal variations of the SPCZ indices. The change from positive to negative Pacific Decadal Oscillation phase around 1999 resulted in a westward shift of the SPCZ centroid longitude, much smaller interannual swing in centroid latitude, and a decrease in SPCZ area. This study improves the understanding of the variations of the SPCZ on multiple time scales and reveals the variations of SPCZ strength not reported previously. The diagnostics analyses can be

  20. Capabilities and uncertainties of aircraft measurements for the validation of satellite precipitation products – a virtual case study

    Directory of Open Access Journals (Sweden)

    Andrea Lammert

    2015-08-01

    Full Text Available Remote sensing sensors on board of research aircraft provide detailed measurements of clouds and precipitation which can be used as reference data to validate satellite products. Such satellite derived precipitation data using passive microwave radiometers with a resolution of typically 50×50km2$50\\times50\\,\\text{km}^2$ stands against high spatial and temporal resolved airborne measurements, but only along a chosen line. This paper focuses on analysis on the uncertainty arising from the different spatial resolution and coverage. Therefore we use a perfect model approach, with a high resolved forecast model yielding perfect virtual aircraft and satellite observations. The mean precipitation and standard deviation per satellite box were estimated with a Gaussian approach. The comparison of the mean values shows a high correlation of 0.92, but a very wide spread. As criterion to define good agreement between satellite mean and reference, we choose a deviation of one standard deviation of the virtual aircraft as threshold. Considering flight tracks in the range of 50 km (one overflight, the perfect agreement of satellite and aircraft observations is only detected in 65 % of the cases. To increase this low reliability the precipitation distributions of the virtual aircraft were fitted by a gamma density function. Using the same quality criterion, the usage of gamma density fit yields an improvement of the Aircraft reliability up to 80 %.

  1. Data Analysis of GPM Constellation Satellites-IMERG and ERA-Interim precipitation products over West of Iran

    Science.gov (United States)

    Sharifi, Ehsan; Steinacker, Reinhold; Saghafian, Bahram

    2016-04-01

    Precipitation is a critical component of the Earth's hydrological cycle. The primary requirement in precipitation measurement is to know where and how much precipitation is falling at any given time. Especially in data sparse regions with insufficient radar coverage, satellite information can provide a spatial and temporal context. Nonetheless, evaluation of satellite precipitation is essential prior to operational use. This is why many previous studies are devoted to the validation of satellite estimation. Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to hazards. In situ observations over mountainous areas are mostly limited, but currently available satellite precipitation products can potentially provide the precipitation estimation needed for meteorological and hydrological applications. One of the newest and blended methods that use multi-satellites and multi-sensors has been developed for estimating global precipitation. The considered data set known as Integrated Multi-satellitE Retrievals (IMERG) for GPM (Global Precipitation Measurement) is routinely produced by the GPM constellation satellites. Moreover, recent efforts have been put into the improvement of the precipitation products derived from reanalysis systems, which has led to significant progress. One of the best and a worldwide used model is developed by the European Centre for Medium Range Weather Forecasts (ECMWF). They have produced global reanalysis daily precipitation, known as ERA-Interim. This study has evaluated one year of precipitation data from the GPM-IMERG and ERA-Interim reanalysis daily time series over West of Iran. IMERG and ERA-Interim yield underestimate the observed values while IMERG underestimated slightly and performed better when precipitation is greater than 10mm. Furthermore, with respect to evaluation of probability of detection (POD), threat score (TS), false alarm ratio (FAR) and probability

  2. Risk management and lessons learned solutions for satellite product assurance

    Science.gov (United States)

    Larrère, Jean-Luc

    2004-08-01

    The historic trend of the space industry towards lower cost programmes and more generally a better economic efficiency raises a difficult question to the quality assurance community: how to achieve the same—or better—mission success rate while drastically reducing the cost of programmes, hence the cost and level of quality assurance activities. EADS Astrium Earth Observation and Science (France) Business Unit have experimented Risk Management and Lessons Learned on their satellite programmes to achieve this goal. Risk analysis and management are deployed from the programme proposal phase through the development and operations phases. Results of the analysis and the corresponding risk mitigation actions are used to tailor the product assurance programme and activities. Lessons learned have been deployed as a systematic process to collect positive and negative experience from past and on-going programmes and feed them into new programmes. Monitoring and justification of their implementation in programmes is done under supervision from the BU quality assurance function. Control of the system is ensured by the company internal review system. Deployment of these methods has shown that the quality assurance function becomes more integrated in the programme team and development process and that its tasks gain focus and efficiency while minimising the risks associated with new space programmes.

  3. Satellite Driven Estimation of Primary Productivity of Agroecosystems in India

    Science.gov (United States)

    Patel, N. R.; Dadhwal, V. K.; Agrawal, S.; Saha, S. K.

    2011-08-01

    Earth observation driven ecosystem modeling have played a major role in estimation of carbon budget components such as gross primary productivity (GPP) and net primary production (NPP) over terrestrial ecosystems, including agriculture. The present study therefore evaluate satellite-driven vegetation photosynthesis (VPM) model for GPP estimation over agro-ecosystems in India by using time series of the Normalized Difference Vegetation Index (NDVI) from SPOT-VEGETATION, cloud cover observation from MODIS, coarse-grid C3/C4 crop fraction and decadal grided databases of maximum and minimum temperatures. Parameterization of VPM parameters e.g. maximum light use efficiency (ɛ*) and Tscalar was done based on eddy-covariance measurements and literature survey. Incorporation of C3/C4 crop fraction is a modification to commonly used constant maximum LUE. Modeling results from VPM captured very well the geographical pattern of GPP and NPP over cropland in India. Well managed agro-ecosystems in Trans-Gangetic and upper Indo-Gangetic plains had the highest magnitude of GPP with peak GPP during kharif occurs in sugarcane-wheat system (western UP) and it occurs in rice-wheat system (Punjab) during Rabi season. Overall, croplands in these plains had more annual GPP (> 1000 g C m-2) and NPP (> 600 g C m-2) due to input-intensive cultivation. Desertic tracts of western Rajasthan showed the least GPP and NPP values. Country-level contribution of croplands to national GPP and NPP amounts to1.34 Pg C year-1 and 0.859 Pg C year-1, respectively. Modeled estimates of cropland NPP agrees well with ground-based estimates for north-western India (R2 = 0.63 and RMSE = 108 g C m-2). Future research will focus on evaluating the VPM model with medium resolution sensors such as AWiFS and MODIS for rice-wheat system and validating with eddy-covariance measurements.

  4. Satellite-derived land covers for runoff estimation using SCS-CN method in Chen-You-Lan Watershed, Taiwan

    Science.gov (United States)

    Zhang, Wen-Yan; Lin, Chao-Yuan

    2017-04-01

    The Soil Conservation Service Curve Number (SCS-CN) method, which was originally developed by the USDA Natural Resources Conservation Service, is widely used to estimate direct runoff volume from rainfall. The runoff Curve Number (CN) parameter is based on the hydrologic soil group and land use factors. In Taiwan, the national land use maps were interpreted from aerial photos in 1995 and 2008. Rapid updating of post-disaster land use map is limited due to the high cost of production, so the classification of satellite images is the alternative method to obtain the land use map. In this study, Normalized Difference Vegetation Index (NDVI) in Chen-You-Lan Watershed was derived from dry and wet season of Landsat imageries during 2003 - 2008. Land covers were interpreted from mean value and standard deviation of NDVI and were categorized into 4 groups i.e. forest, grassland, agriculture and bare land. Then, the runoff volume of typhoon events during 2005 - 2009 were estimated using SCS-CN method and verified with the measured runoff data. The result showed that the model efficiency coefficient is 90.77%. Therefore, estimating runoff by using the land cover map classified from satellite images is practicable.

  5. Streamlining On-Demand Access to Joint Polar Satellite System (JPSS) Data Products for Weather Forecasting

    Science.gov (United States)

    Evans, J. D.; Tislin, D.

    2017-12-01

    Observations from the Joint Polar Satellite System (JPSS) support National Weather Service (NWS) forecasters, whose Advanced Weather Interactive Processing System (AWIPS) Data Delivery (DD) will access JPSS data products on demand from the National Environmental Satellite, Data, and Information Service (NESDIS) Product Distribution and Access (PDA) service. Based on the Open Geospatial Consortium (OGC) Web Coverage Service, this on-demand service promises broad interoperability and frugal use of data networks by serving only the data that a user needs. But the volume, velocity, and variety of JPSS data products impose several challenges to such a service. It must be efficient to handle large volumes of complex, frequently updated data, and to fulfill many concurrent requests. It must offer flexible data handling and delivery, to work with a diverse and changing collection of data, and to tailor its outputs into products that users need, with minimal coordination between provider and user communities. It must support 24x7 operation, with no pauses in incoming data or user demand; and it must scale to rapid changes in data volume, variety, and demand as new satellites launch, more products come online, and users rely increasingly on the service. We are addressing these challenges in order to build an efficient and effective on-demand JPSS data service. For example, on-demand subsetting by many users at once may overload a server's processing capacity or its disk bandwidth - unless alleviated by spatial indexing, geolocation transforms, or pre-tiling and caching. Filtering by variable (/ band / layer) may also alleviate network loads, and provide fine-grained variable selection; to that end we are investigating how best to provide random access into the variety of spatiotemporal JPSS data products. Finally, producing tailored products (derivatives, aggregations) can boost flexibility for end users; but some tailoring operations may impose significant server loads

  6. On the assimilation of satellite derived soil moisture in numerical weather prediction models

    Science.gov (United States)

    Drusch, M.

    2006-12-01

    Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

  7. Comparison of precision orbit derived density estimates for CHAMP and GRACE satellites

    Science.gov (United States)

    Fattig, Eric Dale

    Current atmospheric density models cannot adequately represent the density variations observed by satellites in Low Earth Orbit (LEO). Using an optimal orbit determination process, precision orbit ephemerides (POE) are used as measurement data to generate corrections to density values obtained from existing atmospheric models. Densities obtained using these corrections are then compared to density data derived from the onboard accelerometers of satellites, specifically the CHAMP and GRACE satellites. This comparison takes two forms, cross correlation analysis and root mean square analysis. The densities obtained from the POE method are nearly always superior to the empirical models, both in matching the trends observed by the accelerometer (cross correlation), and the magnitudes of the accelerometer derived density (root mean square). In addition, this method consistently produces better results than those achieved by the High Accuracy Satellite Drag Model (HASDM). For satellites orbiting Earth that pass through Earth's upper atmosphere, drag is the primary source of uncertainty in orbit determination and prediction. Variations in density, which are often not modeled or are inaccurately modeled, cause difficulty in properly calculating the drag acting on a satellite. These density variations are the result of many factors; however, the Sun is the main driver in upper atmospheric density changes. The Sun influences the densities in Earth's atmosphere through solar heating of the atmosphere, as well as through geomagnetic heating resulting from the solar wind. Data are examined for fourteen hour time spans between November 2004 and July 2009 for both the CHAMP and GRACE satellites. This data spans all available levels of solar and geomagnetic activity, which does not include data in the elevated and high solar activity bins due to the nature of the solar cycle. Density solutions are generated from corrections to five different baseline atmospheric models, as well as

  8. Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

    Science.gov (United States)

    Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

    2016-01-01

    Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

  9. Estimation of absorbed photosynthetically active radiation and vegetation net production efficiency using satellite data

    International Nuclear Information System (INIS)

    Hanan, N.P.; Prince, S.D.; Begue, A.

    1995-01-01

    The amount of photosynthetically active radiation (PAR) absorbed by green vegetation is an important determinant of photosynthesis and growth. Methods for the estimation of fractional absorption of PAR (iff PAR ) for areas greater than 1 km 2 using satellite data are discussed, and are applied to sites in the Sahel that have a sparse herb layer and tree cover of less than 5%. Using harvest measurements of seasonal net production, net production efficiencies are calculated. Variation in estimates of seasonal PAR absorption (APAR) caused by the atmospheric correction method and relationship between surface reflectances and iff PAR is considered. The use of maximum value composites of satellite NDVI to reduce the effect of the atmosphere is shown to produce inaccurate APAR estimates. In this data set, however, atmospheric correction using average optical depths was found to give good approximations of the fully corrected data. A simulation of canopy radiative transfer using the SAIL model was used to derive a relationship between canopy NDVI and iff PAR . Seasonal APAR estimates assuming a 1:1 relationship between iff PAR and NDVI overestimated the SAIL modeled results by up to 260%. The use of a modified 1:1 relationship, where iff PAR was assumed to be linearly related to NDVI scaled between minimum (soil) and maximum (infinite canopy) values, underestimated the SAIL modeled results by up to 35%. Estimated net production efficiencies (ϵ n , dry matter per unit APAR) fell in the range 0.12–1.61 g MJ −1 for above ground production, and in the range 0.16–1.88 g MJ −1 for total production. Sites with lower rainfall had reduced efficiencies, probably caused by physiological constraints on photosynthesis during dry conditions. (author)

  10. Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

    Science.gov (United States)

    Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

    2015-01-01

    Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

  11. Satellite-Based Derivation of High-Resolution Forest Information Layers for Operational Forest Management

    Directory of Open Access Journals (Sweden)

    Johannes Stoffels

    2015-06-01

    Full Text Available A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.

  12. Exploring Machine Learning to Correct Satellite-Derived Sea Surface Temperatures

    Directory of Open Access Journals (Sweden)

    Stéphane Saux Picart

    2018-02-01

    Full Text Available Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work is an attempt at using advanced statistical methods of machine learning to predict the bias between Sea Surface Temperature (SST derived from infrared remote sensing and ground “truth” from drifting buoy measurements. A large dataset of collocation between satellite SST and in situ SST is explored. Four regression models are used: Simple multi-linear regression, Least Square Shrinkage and Selection Operator (LASSO, Generalised Additive Model (GAM and random forest. In the case of geostationary satellites for which a large number of collocations is available, results show that the random forest model is the best model to predict the systematic errors and it is computationally fast, making it a good candidate for operational processing. It is able to explain nearly 31% of the total variance of the bias (in comparison to about 24% for the multi-linear regression model.

  13. A European satellite-derived UV climatology available for impact studies

    International Nuclear Information System (INIS)

    Verdebout, J.

    2004-01-01

    This paper presents a satellite-derived climatology of the surface UV radiation, intended to support impact studies on the environment and human health. As of today, the dataset covers the period from 1 January 1984 to 31 August 2003, with daily dose maps covering Europe with a spatial resolution of 0.05 deg.. A comparison between the modelled erythemal daily dose and measurements in Ispra yields an r.m.s value with a relative difference of 29% and a bias of 3%. The seemingly large dispersion is, however, due to a restricted number of days for which the relative difference is very high. The climatological dataset documents systematic patterns in the geographical distribution of the surface UV radiation due to cloudiness, altitude and snow. It also shows a large year-to-year variability in monthly doses of up to ±50% in spring and ±30% in summer. (authors)

  14. Analysis of Satellite AIS Data to Derive Weather Judging Criteria for Voyage Route Selection

    Directory of Open Access Journals (Sweden)

    Michio Fujii

    2017-06-01

    Full Text Available The operational limitations are discussed at the IMO as a part of the second generation intact stability criteria. Since it is a first attempt to introduce operational efforts into safety regulations, comprehensive discussions are necessary to realize practically acceptable ones. Therefore this study investigates actual navigation routes of container ships and pure car carriers in the trans-North Pacific Ocean in winter, because they are prone to suffer significant parametric roll which is one of stability failure modes. Firstly, interviews are made to shipmasters who have experiences to have operated the subject ships to identify major elements for route selection in the North Pacific Ocean. Secondly, sufficient number of actual navigation records is collected from Satellite AIS data to derive the weather criteria for the route selection in severe weather condition. Finally, shipmaster’s on-board decision-making criteria are discussed by analysing the ship tracking data and weather data.

  15. Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

    Science.gov (United States)

    Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

  16. Use of Real Time Satellite Infrared and Ocean Color to Produce Ocean Products

    Science.gov (United States)

    Roffer, M. A.; Muller-Karger, F. E.; Westhaver, D.; Gawlikowski, G.; Upton, M.; Hall, C.

    2014-12-01

    Real-time data products derived from infrared and ocean color satellites are useful for several types of users around the world. Highly relevant applications include recreational and commercial fisheries, commercial towing vessel and other maritime and navigation operations, and other scientific and applied marine research. Uses of the data include developing sampling strategies for research programs, tracking of water masses and ocean fronts, optimizing ship routes, evaluating water quality conditions (coastal, estuarine, oceanic), and developing fisheries and essential fish habitat indices. Important considerations for users are data access and delivery mechanisms, and data formats. At this time, the data are being generated in formats increasingly available on mobile computing platforms, and are delivered through popular interfaces including social media (Facebook, Linkedin, Twitter and others), Google Earth and other online Geographical Information Systems, or are simply distributed via subscription by email. We review 30 years of applications and describe how we develop customized products and delivery mechanisms working directly with users. We review benefits and issues of access to government databases (NOAA, NASA, ESA), standard data products, and the conversion to tailored products for our users. We discuss advantages of different product formats and of the platforms used to display and to manipulate the data.

  17. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

    Science.gov (United States)

    Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

    2016-06-01

    The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

  18. Assessment of satellite and model derived long term solar radiation for spatial crop models: A case study using DSSAT in Andhra Pradesh

    Directory of Open Access Journals (Sweden)

    Anima Biswal

    2014-09-01

    Full Text Available Crop Simulation models are mathematical representations of the soil plant-atmosphere system that calculate crop growth and yield, as well as the soil and plant water and nutrient balances, as a function of environmental conditions and crop management practices on daily time scale. Crop simulation models require meteorological data as inputs, but data availability and quality are often problematic particularly in spatialising the model for a regional studies. Among these weather variables, daily total solar radiation and air temperature (Tmax and Tmin have the greatest influence on crop phenology and yield potential. The scarcity of good quality solar radiation data can be a major limitation to the use of crop models. Satellite-sensed weather data have been proposed as an alternative when weather station data are not available. These satellite and modeled based products are global and, in general, contiguous in time and also been shown to be accurate enough to provide reliable solar and meteorological resource data over large regions where surface measurements are sparse or nonexistent. In the present study, an attempt was made to evaluate the satellite and model derived daily solar radiation for simulating groundnut crop growth in the rainfed distrcits of Andhra Pradesh. From our preliminary investigation, we propose that satellite derived daily solar radiation data could be used along with ground observed temperature and rainfall data for regional crop simulation studies where the information on ground observed solar radiation is missing or not available.

  19. Towards a merged satellite and in situ fluorescence ocean chlorophyll product

    Directory of Open Access Journals (Sweden)

    H. Lavigne

    2012-06-01

    Full Text Available Understanding the ocean carbon cycle requires a precise assessment of phytoplankton biomass in the oceans. In terms of numbers of observations, satellite data represent the largest available data set. However, as they are limited to surface waters, they have to be merged with in situ observations. Amongst the in situ data, fluorescence profiles constitute the greatest data set available, because fluorometers have operated routinely on oceanographic cruises since the 1970s. Nevertheless, fluorescence is only a proxy of the total chlorophyll a concentration and a data calibration is required. Calibration issues are, however, sources of uncertainty, and they have prevented a systematic and wide range exploitation of the fluorescence data set. In particular, very few attempts to standardize the fluorescence databases have been made. Consequently, merged estimations with other data sources (e.g. satellite are lacking.

    We propose a merging method to fill this gap. It consists firstly in adjusting the fluorescence profile to impose a zero chlorophyll a concentration at depth. Secondly, each point of the fluorescence profile is then multiplied by a correction coefficient, which forces the chlorophyll a integrated content measured on the fluorescence profile to be consistent with the concomitant ocean colour observation. The method is close to the approach proposed by Boss et al. (2008 to correct fluorescence data of a profiling float, although important differences do exist. To develop and test our approach, in situ data from three open ocean stations (BATS, HOT and DYFAMED were used. Comparison of the so-called "satellite-corrected" fluorescence profiles with concomitant bottle-derived estimations of chlorophyll a concentration was performed to evaluate the final error (estimated at 31%. Comparison with the Boss et al. (2008 method, using a subset of the DYFAMED data set, demonstrated that the methods have similar

  20. A calibrated, high-resolution goes satellite solar insolation product for a climatology of Florida evapotranspiration

    Science.gov (United States)

    Paech, S.J.; Mecikalski, J.R.; Sumner, D.M.; Pathak, C.S.; Wu, Q.; Islam, S.; Sangoyomi, T.

    2009-01-01

    Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m-2/day (13%). Calibration reduced errors to 1.7 MJ m -2/day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.

  1. A lithospheric magnetic field model derived from the Swarm satellite magnetic field measurements

    Science.gov (United States)

    Hulot, G.; Thebault, E.; Vigneron, P.

    2015-12-01

    The Swarm constellation of satellites was launched in November 2013 and has since then delivered high quality scalar and vector magnetic field measurements. A consortium of several research institutions was selected by the European Space Agency (ESA) to provide a number of scientific products which will be made available to the scientific community. Within this framework, specific tools were tailor-made to better extract the magnetic signal emanating from Earth's the lithospheric. These tools rely on the scalar gradient measured by the lower pair of Swarm satellites and rely on a regional modeling scheme that is more sensitive to small spatial scales and weak signals than the standard spherical harmonic modeling. In this presentation, we report on various activities related to data analysis and processing. We assess the efficiency of this dedicated chain for modeling the lithospheric magnetic field using more than one year of measurements, and finally discuss refinements that are continuously implemented in order to further improve the robustness and the spatial resolution of the lithospheric field model.

  2. Towards a Cloud Computing Environment: Near Real-time Cloud Product Processing and Distribution for Next Generation Satellites

    Science.gov (United States)

    Nguyen, L.; Chee, T.; Minnis, P.; Palikonda, R.; Smith, W. L., Jr.; Spangenberg, D.

    2016-12-01

    The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) processes and derives near real-time (NRT) global cloud products from operational geostationary satellite imager datasets. These products are being used in NRT to improve forecast model, aircraft icing warnings, and support aircraft field campaigns. Next generation satellites, such as the Japanese Himawari-8 and the upcoming NOAA GOES-R, present challenges for NRT data processing and product dissemination due to the increase in temporal and spatial resolution. The volume of data is expected to increase to approximately 10 folds. This increase in data volume will require additional IT resources to keep up with the processing demands to satisfy NRT requirements. In addition, these resources are not readily available due to cost and other technical limitations. To anticipate and meet these computing resource requirements, we have employed a hybrid cloud computing environment to augment the generation of SatCORPS products. This paper will describe the workflow to ingest, process, and distribute SatCORPS products and the technologies used. Lessons learn from working on both AWS Clouds and GovCloud will be discussed: benefits, similarities, and differences that could impact decision to use cloud computing and storage. A detail cost analysis will be presented. In addition, future cloud utilization, parallelization, and architecture layout will be discussed for GOES-R.

  3. Validation of Satellite-Derived Sea Surface Temperatures for Waters around Taiwan

    Directory of Open Access Journals (Sweden)

    Ming-An Lee

    2005-01-01

    Full Text Available In order to validate the Advanced Very High Resolution Radiometer (AVHRR-derived sea surface temperatures (SST of the waters around Taiwan, we generated a match-up data set of 961 pairs, which included in situ SSTs and concurrent AVHRR measurements for the period of 1998 to 2002. Availability of cloud-free images, i.e., images with more than 85% of cloud-free area in their coverage, was about 2.23% of all AVHRR images during the study period. The range of in situ SSTs was from _ to _ The satellite derived-SSTs through MCSST and NLSST algorithms were linearly related to the in situ SSTs with correlation coefficients of 0.985 and 0.98, respectively. The MCSSTs and NLSSTs had small biases of 0.009 _ and 0.256 _ with root mean square deviations of 0.64 _ and 0.801 _ respectively, therefore the AVHRR-based MCSSTs and NLSSTs had high accuracy in the seas around Taiwan.

  4. Integration of Synthetic Aperture Radar (SAR) Imagery and Derived Products into Severe Weather Disaster Response

    Science.gov (United States)

    Schultz, L. A.; Molthan, A.; Nicoll, J. B.; Bell, J. R.; Gens, R.; Meyer, F. J.

    2017-12-01

    Disaster response efforts leveraging imagery from NASA, USGS, NOAA, and the European Space Agency (ESA) have continued to expand as satellite imagery and derived products offer an enhanced overview of the affected areas, especially in remote areas where terrain and the scale of the damage can inhibit response efforts. NASA's Short-term Prediction Research and Transition (SPoRT) Center has been supporting the NASA Earth Science Disaster Response Program by providing both optical and SAR imagery products to the NWS and FEMA to assist during domestic response efforts. Although optical imagery has dominated, the availability of ESA's Synthetic Aperture Radar (SAR) data from the Sentinel 1-A/B satellites offers a unique perspective to the damage response community as SAR imagery can be collected regardless of the time of day or the presence of clouds, two major hindrances to the use of satellite optical imagery. Through a partnership with the University of Alaska Fairbanks (UAF) and the collocated Alaska Satellite Facility (ASF), NASA's SAR Distributed Active Archive Center (DAAC), SPoRT has been investigating the use of SAR imagery products to support storm damage surveys conducted by the National Weather Service after any severe weather event. Additionally, products are also being developed and tested for FEMA and the National Guard Bureau. This presentation will describe how SAR data from the Sentinel 1A/B satellites are processed and developed into products. Examples from multiple tornado and hail events will be presented highlighting both the strengths and weaknesses of SAR imagery and how it integrates and compliments more traditional optical imagery collected post-event. Specific case study information from a large hail event in South Dakota and a long track tornado near Clear Lake, Wisconsin will be discussed as well as an overview of the work being done to support FEMA and the National Guard.

  5. Estimates of lightning NOx production from GOME satellite observations

    NARCIS (Netherlands)

    Boersma, K.F.; Eskes, H.J.; Meijer, E.W.; Kelder, H.M.

    2005-01-01

    Tropospheric NO2 column retreivals from the Global Ozone Monitoring Expeiment (GOME) satellite spectrometer are used to quantify the source strength and 3-D distribution of lightning produced nitrogen oxides (NOx=NO+NO2). A sharp increase of NO2 is observed at convective cloud tops with increasing

  6. Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

    Science.gov (United States)

    Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

    2016-12-01

    Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

  7. A Novel Approach for Forecasting Crop Production and Yield Using Remotely Sensed Satellite Images

    Science.gov (United States)

    Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.

    2017-12-01

    Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.

  8. A Regional-Scale Assessment of Satellite Derived Precipitable Water Vapor Across The Amazon Basin

    Science.gov (United States)

    DeLiberty, Tracy; Callahan, John; Guillory, Anthony R.; Jedlovec, Gary

    2000-01-01

    Atmospheric water vapor is widely recognized as a key climate variable, linking an assortment of poorly understood and complex processes. It is a major element of the hydrological cycle and provides a mechanism for energy exchange among many of the Earth system components. Reducing uncertainty in our current knowledge of water vapor and its role in the climate system requires accurate measurement, improved modeling techniques, and long-term prediction. Satellites have the potential to satisfy these criteria, as well as provide high resolution measurements that are not available from conventional sources. The focus of this paper is to examine the temporal and mesoscale variations of satellite derived precipitable water vapor (PW) across the Amazon Basin. This region is pivotal in the functioning of the global climate system through its abundant release of latent heat associated with heavy precipitation events. In addition, anthropogenic deforestation and biomass burning activities in recent decades are altering the conditions of the atmosphere, especially in the planetary boundary layer. A physical split-window (PSW) algorithm estimates PW using images from the GOES satellites along with the NCEP/NCAR Reanalysis data that provides the first guess information. Retrievals are made at a three-hourly time step during daylight hours in the Amazon Basin and surrounding areas for the months of June and October in 1988 (dry year) and 1995 (wet year). Spatially continuous fields are generated 5 times daily at 12Z, 15Z, 18Z, 21Z, and 00Z. These fields are then averaged to create monthly and 3 hourly monthly grids. Overall, the PSW estimates PW reasonable well in the Amazon with MAE ranging from 3.0 - 9.0 mm and MAE/observed mean around 20% in comparison to radiosonde observations. The distribution of PW generally mimics that of precipitation. Maximum values (42 - 52 mm) are located in the Northwest whereas minimum values (18 - 27 mm) are found along Brazil's East coast. Aside

  9. 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.

  10. A new model of Earth's radial conductivity structure derived from over 10 yr of satellite and observatory magnetic data

    DEFF Research Database (Denmark)

    Püthe, Christoph; Kuvshinov, Alexey; Khan, Amir

    2015-01-01

    We present a newmodel of the radial (1-D) conductivity structure of Earth's mantle. This model is derived frommore than 10 yr of magnetic measurements from the satellites ørsted, CHAMP, SAC-C and the Swarm trio as well as the global network of geomagnetic observatories. After removal of core...

  11. "Using Satellite Remote Sensing to Derive Numeric Criteria in Coastal and Inland Waters of the United States"

    Science.gov (United States)

    Crawford, T. N.; Schaeffer, B. A.

    2016-12-01

    Anthropogenic nutrient pollution is a major stressor of aquatic ecosystems around the world. In the United States, states and tribes can adopt numeric water quality values (i.e. criteria) into their water quality management standards to protect aquatic life from eutrophication impacts. However, budget and resource constraints have limited the ability of many states and tribes to collect the water quality monitoring data needed to derive numeric criteria. Over the last few decades, satellite technology has provided water quality measurements on a global scale over long time periods. Water quality managers are finding the data provided by satellite technology useful in managing eutrophication impacts in coastal waters, estuaries, lakes, and reservoirs. In recent years EPA has worked with states and tribes to derive remotely sensed numeric Chl-a criteria for coastal waters with limited field-based data. This approach is now being expanded and used to derive Chl-a criteria in freshwater systems across the United States. This presentation will cover EPA's approach to derive numeric Chl-a criteria using satellite remote sensing, recommendations to improve satellite sensors to expand applications, potential areas of interest, and the challenges of using remote sensing to establish water quality management goals, as well as provide a case in which this approach has been applied.

  12. Error estimates for near-Real-Time Satellite Soil Moisture as Derived from the Land Parameter Retrieval Model

    NARCIS (Netherlands)

    Parinussa, R.M.; Meesters, A.G.C.A.; Liu, Y.Y.; Dorigo, W.; Wagner, W.; de Jeu, R.A.M.

    2011-01-01

    A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from

  13. The relationship of field burn severity measures to satellite-derived Burned Area Reflectance Classification (BARC) maps

    Science.gov (United States)

    Andrew Hudak; Penelope Morgan; Carter Stone; Pete Robichaud; Terrie Jain; Jess Clark

    2004-01-01

    Preliminary results are presented from ongoing research on spatial variability of fire effects on soils and vegetation from the Black Mountain Two and Cooney Ridge wildfires, which burned in western Montana during the 2003 fire season. Extensive field fractional cover data were sampled to assess the efficacy of quantitative satellite image-derived indicators of burn...

  14. How to Get Data from NOAA Environmental Satellites: An Overview of Operations, Products, Access and Archive

    Science.gov (United States)

    Donoho, N.; Graumann, A.; McNamara, D. P.

    2015-12-01

    In this presentation we will highlight access and availability of NOAA satellite data for near real time (NRT) and retrospective product users. The presentation includes an overview of the current fleet of NOAA satellites and methods of data distribution and access to hundreds of imagery and products offered by the Environmental Satellite Processing Center (ESPC) and the Comprehensive Large Array-data Stewardship System (CLASS). In particular, emphasis on the various levels of services for current and past observations will be presented. The National Environmental Satellite, Data, and Information Service (NESDIS) is dedicated to providing timely access to global environmental data from satellites and other sources. In special cases, users are authorized direct access to NESDIS data distribution systems for environmental satellite data and products. Other means of access include publicly available distribution services such as the Global Telecommunication System (GTS), NOAA satellite direct broadcast services and various NOAA websites and ftp servers, including CLASS. CLASS is NOAA's information technology system designed to support long-term, secure preservation and standards-based access to environmental data collections and information. The National Centers for Environmental Information (NCEI) is responsible for the ingest, quality control, stewardship, archival and access to data and science information. This work will also show the latest technology improvements, enterprise approach and future plans for distribution of exponentially increasing data volumes from future NOAA missions. A primer on access to NOAA operational satellite products and services is available at http://www.ospo.noaa.gov/Organization/About/access.html. Access to post-operational satellite data and assorted products is available at http://www.class.noaa.gov

  15. Characterization of the variability of the South Pacific Convergence Zone using satellite and reanalysis wind product

    Science.gov (United States)

    Lee, T.; Kidwell, A. N.; Jo, Y. H.; Yan, X. H.

    2016-02-01

    The variability of the South Pacific Convergence Zone (SPCZ) is evaluated using ocean surface wind products derived from the QuickSCAT satellite scatterometer for the period of 1999-2009and ERA-Interim atmospheric reanalysis for the period of 1981-2014. From these products, indices were developed to represent the SPCZ strength, area, and centroid location. Excellent agreement is found between the indices derived from the two wind products during the QuikSCAT period in terms of the spatio-temporal structures of the SPCZ. The longer ERA-Interim product is then used to study the variations of SPCZ properties on intraseasonal, seasonal, interannual, and decadal time scales. The SPCZ strength, area, and centroid latitude have a dominant seasonal cycle. In contrast, the SPCZ centroid longitude is dominated by intraseasonal variability due to the influence by the Madden-Julian Oscillation. The SPCZ indices are all correlated with El Niño-Southern Oscillation indices. Interannual and intraseasonal variations of SPCZ strength during strong El Niño are approximately twice as large as the respective seasonal variations. SPCZ strength depends more on the intensity of El Niño rather than the central- vs. eastern-Pacific type. The change from positive to negative Pacific Decadal Oscillation phase around 1999 results in a westward shift of the SPCZ centroid longitude, much smaller interannual swing in centroid latitude, and a decrease in SPCZ area. This study improves the understanding of the variations of the SPCZ on multiple time scales and reveals the variations of SPCZ strength not reported previously. The diagnostics analyses can be used to evaluate climate models.

  16. Preparing for Automated Derivation of Products in a Software Product Line

    National Research Council Canada - National Science Library

    McGregor, John D

    2005-01-01

    ... to bring a product to market, or through other production improvements. Business goals such as these make automated product derivation an appealing strategy to a software product line organization...

  17. Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring.

    Science.gov (United States)

    David P. Turner; William D. Ritts; Warren B. Cohen; Thomas K. Maeirsperger; Stith T. Gower; Al A. Kirschbaum; Steve W. Runnings; Maosheng Zhaos; Steven C. Wofsy; Allison L. Dunn; Beverly E. Law; John L. Campbell; Walter C. Oechel; Hyo Jung Kwon; Tilden P. Meyers; Eric E. Small; Shirley A. Kurc; John A. Gamon

    2005-01-01

    Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling...

  18. A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data

    International Nuclear Information System (INIS)

    Elvidge, Ch. D.; Erwin, E. H.; Ziskin, D.; Baugh, K. E.; Tuttle, B. T.; Ghosh, T.; Tuttle, B. T.; Ghosh, T.; Pack, D. W.; Zhizhin, M.

    2009-01-01

    We have produced annual estimates of national and global gas flaring and gas flaring efficiency from 1994 through 2008 using low light imaging data acquired by the Defense Meteorological Satellite Program (DMSP). Gas flaring is a widely used practice for the disposal of associated gas in oil production and processing facilities where there is insufficient infrastructure for utilization of the gas (primarily methane). Improved utilization of the gas is key to reducing global carbon emissions to the atmosphere. The DMSP estimates of flared gas volume are based on a calibration developed with a pooled set of reported national gas flaring volumes and data from individual flares. Flaring efficiency was calculated as the volume of flared gas per barrel of crude oil produced. Global gas flaring has remained largely stable over the past fifteen years, in the range of 140 to 170 billion cubic meters (BCM). Global flaring efficiency was in the seven to eight cubic meters per barrel from 1994 to 2005 and declined to 5.6 m 3 per barrel by 2008. The 2008 gas flaring estimate of 139 BCM represents 21% of the natural gas consumption of the USA with a potential retail market value of 68 billions USD. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO 2e ) into the atmosphere. The DMSP estimated gas flaring volumes indicate that global gas flaring has declined by 19% since 2005, led by gas flaring reductions in Russia and Nigeria, the two countries with the highest gas flaring levels. The flaring efficiency of both Russia and Nigeria improved from 2005 to 2008, suggesting that the reductions in gas flaring are likely the result of either improved utilization of the gas, reinjection, or direct venting of gas into the atmosphere, although the effect of uncertainties in the satellite data cannot be ruled out. It is anticipated that the capability to estimate gas flaring volumes based on satellite data will spur improved utilization of gas that

  19. Quality Improvement of the Satellite Soil Moisture Products by Fusing In Situ and GNSS-R Observation

    Science.gov (United States)

    Yuan, Q.; Xu, H.; Li, T.; Shen, H.; Zhang, L.

    2017-12-01

    Soil moisture plays a fundamental role in the hydrological cycle as well as in the energy partitioning. On this basis, it is of great concern to derive a long-term soil moisture time series on a global scale and monitor its temporal and spatial variations for practical applications. Although passive and active microwave satellites have been shown to provide useful retrievals of near-surface soil moisture at regional and global scales, the limitations in retrieval accuracy prevent them from high-quality applications in specific areas. On the other hand, measuring soil moisture straightly through in situdevices, such as soil moisture probes, is high accuracy, but is not able to derive global soil moisture maps. Recently, the ground-based GNSS-R method is emerging in monitoring near-surface soil moisture variations but still over limited spatial scales. In this paper, a multi-source data fusion method was applied to synthesize regional high-quality soil moisture products from 2015 to 2017 in western parts of the continental United States. Firstly, we put all the three soil moisture datasets into the generalized regression neural network (GRNN) model. The input signals of the model are SMOS and SMAP satellite-derived passive level 3 soil moisture daily products combined with date and latitude and longitude information, while the in situ measured and GNSS-R retrieved soil moisture are used as target. Finally, we apply the model to all the soil moisture time series in the experiment area and obtain two high-quality regional soil moisture products for SMOS and SMAP, respectively. The results before fusion show that the correlation coefficients between site-specific soil moisture and satellite-derived soil moisture are 0.39 for SMOS and 0.27 for SMAP and that unbiased root-mean-square errors (ubRMSE) are 0.113 for SMOS and 0.128 for SMAP, respectively. After applying the GRNN-R, the model fitted correlation coefficients have reached 0.72 for SMOS and 0.75 for SMAP and the

  20. The Stackelberg Model for a Leader of Production and Many Satellites

    Directory of Open Access Journals (Sweden)

    Catalin Angelo Ioan

    2015-05-01

    Full Text Available Oligopoly is a market situation where there are a small number of bidders (at least two of a good non-substituent and a sufficient number of consumers. The paper analyses the Stackelberg model for a leader of production and many satellites. There are obtained the equilibrium productions, maximum profits and sales price where one of the company is the leader of quantity, and other satellites. There are also survey the situations where the firm based on its marginal cost of production can effectively take the lead of production.

  1. A corotation electric field model of the Earth derived from Swarm satellite magnetic field measurements

    Science.gov (United States)

    Maus, Stefan

    2017-08-01

    Rotation of the Earth in its own geomagnetic field sets up a primary corotation electric field, compensated by a secondary electric field of induced electrical charges. For the geomagnetic field measured by the Swarm constellation of satellites, a derivation of the global corotation electric field inside and outside of the corotation region is provided here, in both inertial and corotating reference frames. The Earth is assumed an electrical conductor, the lower atmosphere an insulator, followed by the corotating ionospheric E region again as a conductor. Outside of the Earth's core, the induced charge is immediately accessible from the spherical harmonic Gauss coefficients of the geomagnetic field. The charge density is positive at high northern and southern latitudes, negative at midlatitudes, and increases strongly toward the Earth's center. Small vertical electric fields of about 0.3 mV/m in the insulating atmospheric gap are caused by the corotation charges located in the ionosphere above and the Earth below. The corotation charges also flow outward into the region of closed magnetic field lines, forcing the plasmasphere to corotate. The electric field of the corotation charges further extends outside of the corotating regions, contributing radial outward electric fields of about 10 mV/m in the northern and southern polar caps. Depending on how the magnetosphere responds to these fields, the Earth may carry a net electric charge.

  2. Urban thermal environment and its biophysical parameters derived from satellite remote sensing imagery

    Science.gov (United States)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

    2013-10-01

    In frame of global warming, the field of urbanization and urban thermal environment are important issues among scientists all over the world. This paper investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Bucharest metropolitan area of Romania based on satellite remote sensing imagery Landsat TM/ETM+, time series MODIS Terra/Aqua data and IKONOS acquired during 1990 - 2012 period. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also retrieved from thermal infrared band of Landsat TM/ETM+, from MODIS Terra/Aqua datasets. Based on these parameters, the urban growth, urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results indicated that the metropolitan area ratio of impervious surface in Bucharest increased significantly during two decades investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

  3. Oceanic geoid and tides derived from GEOS 3 satellite data in the Northwestern Atlantic Ocean

    Science.gov (United States)

    Won, I. J.; Miller, L. S.

    1979-01-01

    Two sets of GEOS 3 altimeter data which fall within about a 2.5-deg width are analyzed for ocean geoid and tides. One set covers a path from Newfoundland to Cuba, and the other a path from Puerto Rico to the North Carolina coast. Forty different analyses using various parameters are performed in order to investigate convergence. Profiles of the geoid and four tides, M2, O1, S2, and K1, are derived along the two strips. While the analyses produced convergent solutions for all 40 cases, the uncertainty caused by the linear orbital bias error of the satellite is too large to claim that the solutions represent the true ocean tides in the area. A spot check of the result with the Mode deep-sea tide gauge data shows poor agreement. A positive conclusion of this study is that despite the uncertain orbital error the oceanic geoid obtained through this analysis can improve significantly the short-wavelength structure over existing spherical harmonic geoid models.

  4. Statistical Characteristics of Mesoscale Eddies in the North Pacific Derived from Satellite Altimetry

    Directory of Open Access Journals (Sweden)

    Yu-Hsin Cheng

    2014-06-01

    Full Text Available The sea level anomaly data derived from satellite altimetry are analyzed to investigate statistical characteristics of mesoscale eddies in the North Pacific. Eddies are detected by a free-threshold eddy identification algorithm. The results show that the distributions of size, amplitude, propagation speed, and eddy kinetic energy of eddy follow the Rayleigh distribution. The most active regions of eddies are the Kuroshio Extension region, the Subtropical Counter Current zone, and the Northeastern Tropical Pacific region. By contrast, eddies are seldom observed around the center of the eastern part of the North Pacific Subarctic Gyre. The propagation speed and kinetic energy of cyclonic and anticyclonic eddies are almost the same, but anticyclonic eddies possess greater lifespans, sizes, and amplitudes than those of cyclonic eddies. Most eddies in the North Pacific propagate westward except in the Oyashio region. Around the northeastern tropical Pacific and the California currents, cyclonic and anticyclonic eddies propagate westward with slightly equatorward (197° average azimuth relative to east and poleward (165° deflection, respectively. This implies that the background current may play an important role in formation of the eddy pathway patterns.

  5. Water Level Fluctuations in the Congo Basin Derived from ENVISAT Satellite Altimetry

    Directory of Open Access Journals (Sweden)

    Mélanie Becker

    2014-09-01

    Full Text Available In the Congo Basin, the elevated vulnerability of food security and the water supply implies that sustainable development strategies must incorporate the effects of climate change on hydrological regimes. However, the lack of observational hydro-climatic data over the past decades strongly limits the number of studies investigating the effects of climate change in the Congo Basin. We present the largest altimetry-based dataset of water levels ever constituted over the entire Congo Basin. This dataset of water levels illuminates the hydrological regimes of various tributaries of the Congo River. A total of 140 water level time series are extracted using ENVISAT altimetry over the period of 2003 to 2009. To improve the understanding of the physical phenomena dominating the region, we perform a K-means cluster analysis of the altimeter-derived river level height variations to identify groups of hydrologically similar catchments. This analysis reveals nine distinct hydrological regions. The proposed regionalization scheme is validated and therefore considered reliable for estimating monthly water level variations in the Congo Basin. This result confirms the potential of satellite altimetry in monitoring spatio-temporal water level variations as a promising and unprecedented means for improved representation of the hydrologic characteristics in large ungauged river basins.

  6. Northern South China Sea Surface Circulation and its Variability Derived by Combining Satellite Altimetry and Surface Drifter Data

    Directory of Open Access Journals (Sweden)

    N. Peter Benny

    2015-01-01

    Full Text Available The present study analyses the mean and seasonal mesoscale surface circulation of the Northern South China Sea (NSCS and determines the influence of El Niño/SouthernNiño/Southern Oscillation (ENSO. High resolution Eulerian velocity field is derived by combining the available satellite tracked surface drifter data with satellite altimetry during 1993 - 2012. The wind driven current is computed employing the weekly ocean surface mean wind fields derived from the scatterometers on board ERS 1/2, QuikSCAT and ASCAT. The derived mean velocity field exhibits strong boundary currents and broad zonal flow across NSCS. The anomalous field is quite strong in the southern part and the Seasonal circulation clearly depicts the monsoonal forcing. Eddy Kinetic Energy (EKE distribution and its spatial and temporal structures are determined employing Empirical Orthogonal Function (EOF analysis. The ENSO influence on NSCS surface circulation has been analyzed using monthly absolute geostrophic velocity fields during 1996 - 1999.

  7. Data Filtering and Assimilation of Satellite Derived Aerosol Optical Depth, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Satellite observations of the Earth often contain excessive noise and extensive data voids. Aerosol measurements, for instance, are obscured and contaminated by...

  8. 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.

  9. Estimation of time-series properties of gourd observed solar irradiance data using cloud properties derived from satellite observations

    Science.gov (United States)

    Watanabe, T.; Nohara, D.

    2017-12-01

    The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.

  10. Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China

    Directory of Open Access Journals (Sweden)

    Lei Bai

    2018-02-01

    Full Text Available Precipitation is the main component of global water cycle. At present, satellite quantitative precipitation estimates (QPEs are widely applied in the scientific community. However, the evaluations of satellite QPEs have some limitations in terms of the deficiency in observation, evaluation methodology, the selection of time windows for evaluation and short periods for evaluation. The objective of this work is to make some improvements by evaluating the spatio-temporal pattern of the long-terms Climate Hazard Group InfraRed Precipitation Satellite’s (CHIRPS’s QPEs over mainland China. In this study, we compared the daily precipitation estimates from CHIRPS with 2480 rain gauges across China and gridded observation using several statistical metrics in the long-term period of 1981–2014. The results show that there is significant difference between point evaluation and grid evaluation for CHIRPS. CHIRPS has better performance for a large amount of precipitation than it does for arid and semi-arid land. The change in good performance zones has strong relationship with monsoon’s movement. Therefore, CHIRPS performs better in river basins of southern China and exhibits poor performance in river basins in northwestern and northern China. Moreover, CHIRPS exhibits better in warm season than in Winter, owing to its limited ability to detect snowfall. Nevertheless, CHIRPS is moderately sensitive to the precipitation from typhoon weather systems. The limitations for CHIRPS result from the Tropical Rainfall Measuring Mission (TRMM 3B42 estimates’ accuracy and valid spatial coverage.

  11. Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

    OpenAIRE

    Ayehu, Getachew Tesfaye; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

    2018-01-01

    Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through...

  12. Deriving the effect of wind speed on clean marine aerosol optical properties using the A-Train satellites

    Directory of Open Access Journals (Sweden)

    V. P. Kiliyanpilakkil

    2011-11-01

    showed a tendency toward leveling off, asymptotically approaching value of 0.15. The conclusions of this study regarding the aerosol extinction vs. wind speed relationship may have been influenced by the constant lidar ratio used for CALIPSO-derived AOD532. Nevertheless, active satellite sensor used in this study that allows separation of maritime wind induced component of AOD from the total AOD over the ocean could lead to improvements in optical properties of sea spray aerosols and their production mechanisms.

  13. Validating GPM-based Multi-satellite IMERG Products Over South Korea

    Science.gov (United States)

    Wang, J.; Petersen, W. A.; Wolff, D. B.; Ryu, G. H.

    2017-12-01

    Accurate precipitation estimates derived from space-borne satellite measurements are critical for a wide variety of applications such as water budget studies, and prevention or mitigation of natural hazards caused by extreme precipitation events. This study validates the near-real-time Early Run, Late Run and the research-quality Final Run Integrated Multi-Satellite Retrievals for GPM (IMERG) using Korean Quantitative Precipitation Estimation (QPE). The Korean QPE data are at a 1-hour temporal resolution and 1-km by 1-km spatial resolution, and were developed by Korea Meteorological Administration (KMA) from a Real-time ADjusted Radar-AWS (Automatic Weather Station) Rainrate (RAD-RAR) system utilizing eleven radars over the Republic of Korea. The validation is conducted by comparing Version-04A IMERG (Early, Late and Final Runs) with Korean QPE over the area (124.5E-130.5E, 32.5N-39N) at various spatial and temporal scales during March 2014 through November 2016. The comparisons demonstrate the reasonably good ability of Version-04A IMERG products in estimating precipitation over South Korea's complex topography that consists mainly of hills and mountains, as well as large coastal plains. Based on this data, the Early Run, Late Run and Final Run IMERG precipitation estimates higher than 0.1mm h-1 are about 20.1%, 7.5% and 6.1% higher than Korean QPE at 0.1o and 1-hour resolutions. Detailed comparison results are available at https://wallops-prf.gsfc.nasa.gov/KoreanQPE.V04/index.html

  14. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  15. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  16. Satellite Monitoring of Ash and Sulphur Dioxide for the mitigation of Aviation Hazards: Part II. Validation of satellite-derived Volcanic Sulphur Dioxide Levels.

    Science.gov (United States)

    Koukouli, MariLiza; Balis, Dimitris; Dimopoulos, Spiros; Clarisse, Lieven; Carboni, Elisa; Hedelt, Pascal; Spinetti, Claudia; Theys, Nicolas; Tampellini, Lucia; Zehner, Claus

    2014-05-01

    The eruption of the Icelandic volcano Eyjafjallajökull in the spring of 2010 turned the attention of both the public and the scientific community to the susceptibility of the European airspace to the outflows of large volcanic eruptions. The ash-rich plume from Eyjafjallajökull drifted towards Europe and caused major disruptions of European air traffic for several weeks affecting the everyday life of millions of people and with a strong economic impact. This unparalleled situation revealed limitations in the decision making process due to the lack of information on the tolerance to ash of commercial aircraft engines as well as limitations in the ash monitoring and prediction capabilities. The European Space Agency project Satellite Monitoring of Ash and Sulphur Dioxide for the mitigation of Aviation Hazards, was introduced to facilitate the development of an optimal End-to-End System for Volcanic Ash Plume Monitoring and Prediction. This system is based on comprehensive satellite-derived ash plume and sulphur dioxide [SO2] level estimates, as well as a widespread validation using supplementary satellite, aircraft and ground-based measurements. The validation of volcanic SO2 levels extracted from the sensors GOME-2/MetopA and IASI/MetopA are shown here with emphasis on the total column observed right before, during and after the Eyjafjallajökull 2010 eruptions. Co-located ground-based Brewer Spectrophotometer data extracted from the World Ozone and Ultraviolet Radiation Data Centre, WOUDC, were compared to the different satellite estimates. The findings are presented at length, alongside a comprehensive discussion of future scenarios.

  17. Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts

    Science.gov (United States)

    Alcaraz-Segura, Domingo; Lomba, Angela; Sousa-Silva, Rita; Nieto-Lugilde, Diego; Alves, Paulo; Georges, Damien; Vicente, Joana R.; Honrado, João P.

    2017-05-01

    In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001-2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species.

  18. Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

    Science.gov (United States)

    Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

    2013-01-01

    The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case

  19. Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets

    Directory of Open Access Journals (Sweden)

    V. Pedinotti

    2012-06-01

    Full Text Available During the 1970s and 1980s, West Africa has faced extreme climate variations with extended drought conditions. Of particular importance is the Niger basin, since it traverses a large part of the Sahel and is thus a critical source of water for an ever-increasing local population in this semi arid region. However, the understanding of the hydrological processes over this basin is currently limited by the lack of spatially distributed surface water and discharge measurements. The purpose of this study is to evaluate the ability of the ISBA-TRIP continental hydrologic system to represent key processes related to the hydrological cycle of the Niger basin. ISBA-TRIP is currently used within a coupled global climate model, so that the scheme must represent the first order processes which are critical for representing the water cycle while retaining a limited number of parameters and a simple representation of the physics. To this end, the scheme uses first-order approximations to account explicitly for the surface river routing, the floodplain dynamics, and the water storage using a deep aquifer reservoir. In the current study, simulations are done at a 0.5 by 0.5° spatial resolution over the 2002–2007 period (in order to take advantage of the recent satellite record and data from the African Monsoon Multidisciplinary Analyses project, AMMA. Four configurations of the model are compared to evaluate the separate impacts of the flooding scheme and the aquifer on the water cycle. Moreover, the model is forced by two different rainfall datasets to consider the sensitivity of the model to rainfall input uncertainties. The model is evaluated using in situ discharge measurements as well as satellite derived flood extent, total continental water storage changes and river height changes. The basic analysis of in situ discharges confirms the impact of the inner delta area, known as a significant flooded area, on the discharge, characterized by a strong

  20. Animal derived products may conflict with religious patients' beliefs.

    Science.gov (United States)

    Eriksson, Axelina; Burcharth, Jakob; Rosenberg, Jacob

    2013-12-01

    Implants and drugs with animal and human derived content are widely used in medicine and surgery, but information regarding ingredients is rarely obtainable by health practitioners. A religious perspective concerning the use of animal and human derived drug ingredients has not thoroughly been investigated. The purpose of this study was to clarify which parts of the medical and surgical treatments offered in western world-hospitals that conflicts with believers of major religions. Religious and spiritual leaders of the six largest religions worldwide (18 branches) were contacted. A standardised questionnaire was sent out regarding their position on the use of human and animal derived products in medical and surgical treatments. Of the 18 contacted religious branches, 10 replied representing the 6 largest religions worldwide. Hindus and Sikhs did not approve of the use of bovine or porcine derived products, and Muslims did not accept the use of porcine derived drugs, dressings or implants. Christians (including Jehovah's Witnesses), Jews and Buddhists accepted the use of all animal and human derived products. However, all religions accepted the use of all these products in case of an emergency and only if alternatives were not available. The views here suggest that religious codes conflict with some treatment regimens. It is crucial to obtain informed consent from patients for the use of drugs and implants with animal or human derived content. However, information on the origin of ingredients in drugs is not always available to health practitioners.

  1. Satellite-based Flood Modeling Using TRMM-based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Greg Easson

    2007-12-01

    Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

  2. Evaluating Terra MODIS Satellite Sensor Data Products for Maize ...

    African Journals Online (AJOL)

    Celeste

    Maize plants mature on average from 120 to 165 days after planting. ... is a maize yield estimation timing model, developed using data from the ... The objective yields were surveyed and randomly selected from results of the stratified point ... are used in formulae (Frost, 2006) to derive plant population and a predicted ...

  3. Satellite Derived Water Quality Observations Are Related to River Discharge and Nitrogen Loads in Pensacola Bay, Florida

    OpenAIRE

    John C. Lehrter; John C. Lehrter; Chengfeng Le

    2017-01-01

    Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011) in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging ...

  4. Distribution and Variability of Satellite-Derived Signals of Isolated Convection Initiation Events Over Central Eastern China

    Science.gov (United States)

    Huang, Yipeng; Meng, Zhiyong; Li, Jing; Li, Wanbiao; Bai, Lanqiang; Zhang, Murong; Wang, Xi

    2017-11-01

    This study combined measurements from the Chinese operational geostationary satellite Fengyun-2E (FY-2E) and ground-based weather radars to conduct a statistical survey of isolated convection initiation (CI) over central eastern China (CEC). The convective environment in CEC is modulated by the complex topography and monsoon climate. From May to August 2010, a total of 1,630 isolated CI signals were derived from FY-2E using a semiautomated method. The formation of these satellite-derived CI signals peaks in the early afternoon and occurs with high frequency in areas with remarkable terrain inhomogeneity (e.g., mountain, water, and mountain-water areas). The high signal frequency areas shift from northwest CEC (dry, high altitude) in early summer to southeast CEC (humid, low altitude) in midsummer along with an increasing monthly mean frequency. The satellite-derived CI signals tend to have longer lead times (the time difference between satellite-derived signal formation and radar-based CI) in the late morning and afternoon than in the early morning and night. During the early morning and night, the distinction between cloud top signatures and background terrestrial radiation becomes less apparent, resulting in delayed identification of the signals and thus short and even negative lead times. A decline in the lead time is observed from May to August, likely due to the increasing cloud growth rate and warm-rain processes. Results show increasing lead times with increasing landscape elevation, likely due to more warm-rain processes over the coastal sea and plain, along with a decreasing cloud growth rate from hill and mountain to the plateau.

  5. Electricity derivative markets: Investment valuation, production planning and hedging

    Energy Technology Data Exchange (ETDEWEB)

    Naesaekkaelae, E.

    2005-07-01

    This thesis studies electricity derivative markets from a view point of an electricity producer. The traditionally used asset pricing methods, based on the no arbitrage principle, are extended to take into account electricity specific features: the non storability of electricity and the variability in the load process. The sources of uncertainty include electricity forward curve, prices of resources used to generate electricity, and the size of the future production. Also the effects of competitors' actions are considered. The thesis illustrates how the information in the derivative prices can be used in investment and production planning. In addition, the use of derivatives as a tool to stabilize electricity dependent cash flows is considered. The results indicate that the information about future electricity prices and their uncertainty, obtained from derivative markets, is important in investment analysis and production planning. (orig.)

  6. Electricity derivative markets: Investment valuation, production planning and hedging

    International Nuclear Information System (INIS)

    Naesaekkaelae, E.

    2005-01-01

    This thesis studies electricity derivative markets from a view point of an electricity producer. The traditionally used asset pricing methods, based on the no arbitrage principle, are extended to take into account electricity specific features: the non storability of electricity and the variability in the load process. The sources of uncertainty include electricity forward curve, prices of resources used to generate electricity, and the size of the future production. Also the effects of competitors' actions are considered. The thesis illustrates how the information in the derivative prices can be used in investment and production planning. In addition, the use of derivatives as a tool to stabilize electricity dependent cash flows is considered. The results indicate that the information about future electricity prices and their uncertainty, obtained from derivative markets, is important in investment analysis and production planning. (orig.)

  7. Thematic mapping from satellite imagery

    CERN Document Server

    Denègre, J

    2013-01-01

    Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

  8. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery (Draft)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Estimated shallow-water, depth maps were produced using rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations in the...

  9. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    Energy Technology Data Exchange (ETDEWEB)

    Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

    2005-07-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

  10. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    International Nuclear Information System (INIS)

    Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

    2005-01-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

  11. Statistical properties of entropy production derived from fluctuation theorems

    International Nuclear Information System (INIS)

    Merhav, Neri; Kafri, Yariv

    2010-01-01

    Several implications of well-known fluctuation theorems, on the statistical properties of entropy production, are studied using various approaches. We begin by deriving a tight lower bound on the variance of the entropy production for a given mean of this random variable. It is shown that the Evans–Searles fluctuation theorem alone imposes a significant lower bound on the variance only when the mean entropy production is very small. It is then nonetheless demonstrated that upon incorporating additional information concerning the entropy production, this lower bound can be significantly improved, so as to capture extensivity properties. Another important aspect of the fluctuation properties of the entropy production is the relationship between the mean and the variance, on the one hand, and the probability of the event where the entropy production is negative, on the other hand. Accordingly, we derive upper and lower bounds on this probability in terms of the mean and the variance. These bounds are tighter than previous bounds that can be found in the literature. Moreover, they are tight in the sense that there exist probability distributions, satisfying the Evans–Searles fluctuation theorem, that achieve them with equality. Finally, we present a general method for generating a wide class of inequalities that must be satisfied by the entropy production. We use this method to derive several new inequalities that go beyond the standard derivation of the second law

  12. Long-term changes of tropospheric NO2 over megacities derived from multiple satellite instruments

    Directory of Open Access Journals (Sweden)

    A. Hilboll

    2013-04-01

    Full Text Available Tropospheric NO2, a key pollutant in particular in cities, has been measured from space since the mid-1990s by the GOME, SCIAMACHY, OMI, and GOME-2 instruments. These data provide a unique global long-term dataset of tropospheric pollution. However, the observations differ in spatial resolution, local time of measurement, viewing geometry, and other details. All these factors can severely impact the retrieved NO2 columns. In this study, we present three ways to account for instrumental differences in trend analyses of the NO2 columns derived from satellite measurements, while preserving the individual instruments' spatial resolutions. For combining measurements from GOME and SCIAMACHY into one consistent time series, we develop a method to explicitly account for the instruments' difference in ground pixel size (40 × 320 km2 vs. 30 × 60 km2. This is especially important when analysing NO2 changes over small, localised sources like, e.g. megacities. The method is based on spatial averaging of the measured earthshine spectra and extraction of a spatial pattern of the resolution effect. Furthermore, two empirical corrections, which summarise all instrumental differences by including instrument-dependent offsets in a fitted trend function, are developed. These methods are applied to data from GOME and SCIAMACHY separately, to the combined time series, and to an extended dataset comprising also GOME-2 and OMI measurements. All approaches show consistent trends of tropospheric NO2 for a selection of areas on both regional and city scales, for the first time allowing consistent trend analysis of the full time series at high spatial resolution. Compared to previous studies, the longer study period leads to significantly reduced uncertainties. We show that measured tropospheric NO2 columns have been strongly increasing over China, the Middle East, and India, with values over east-central China tripling from 1996 to 2011. All parts of the developed world

  13. Modernized Techniques for Dealing with Quality Data and Derived Products

    Science.gov (United States)

    Neiswender, C.; Miller, S. P.; Clark, D.

    2008-12-01

    "I just want a picture of the ocean floor in this area" is expressed all too often by researchers, educators, and students in the marine geosciences. As more sophisticated systems are developed to handle data collection and processing, the demand for quality data, and standardized products continues to grow. Data management is an invisible bridge between science and researchers/educators. The SIOExplorer digital library presents more than 50 years of ocean-going research. Prior to publication, all data is checked for quality using standardized criterion developed for each data stream. Despite the evolution of data formats and processing systems, SIOExplorer continues to present derived products in well- established formats. Standardized products are published for each cruise, and include a cruise report, MGD77 merged data, multi-beam flipbook, and underway profiles. Creation of these products is made possible by processing scripts, which continue to change with ever-evolving data formats. We continue to explore the potential of database-enabled creation of standardized products, such as the metadata-rich MGD77 header file. Database-enabled, automated processing produces standards-compliant metadata for each data and derived product. Metadata facilitates discovery and interpretation of published products. This descriptive information is stored both in an ASCII file, and a searchable digital library database. SIOExplorer's underlying technology allows focused search and retrieval of data and products. For example, users can initiate a search of only multi-beam data, which includes data-specific parameters. This customization is made possible with a synthesis of database, XML, and PHP technology. The combination of standardized products and digital library technology puts quality data and derived products in the hands of scientists. Interoperable systems enable distribution these published resources using technology such as web services. By developing modernized

  14. Evaluation of multiple satellite evaporation products in two dryland regions using GRACE

    KAUST Repository

    Lopez, Oliver

    2015-12-01

    Remote sensing has become a valuable tool for monitoring the water cycle variables in areas that lack the availability of ground-based measurements. Integrating multiple remote sensing-based estimates of evaporation, precipitation, and the terrestrial water storage changes with local measurements of streamflow into a consistent estimate of the regional water budget is a challenge, due to the scale mismatch among the retrieved variables. Evapotranspiration, including soil evaporation, interception losses and canopy transpiration, has received special focus in a number of recent studies that aim to provide global or regional estimates of evaporation at regular time intervals using a variety of remote sensing input. In arid and semi-arid regions, modeling of evaporation is particularly challenging due to the relatively high role of the soil evaporation component in these regions and the variable nature of rainfall events that drive the evaporation process. In this study, we explore the hydrological consistency of remote sensing products in terms of water budget closure and the correlation among spatial patterns of precipitation (P), evaporation (E) and terrestrial water storage, using P-E as a surrogate of water storage changes, with special attention to the evaporation component. The analysis is undertaken within two dryland regions that have presented recent significant changes in climatology (Murray-Darling Basin in Australia) and water storage (the Saq aquifer in northern Saudi Arabia). Water storage changes were derived from the Gravity Recovery and Climate Experiment (GRACE) spherical harmonic (SH) coefficients. Six remote sensing-based evaporation estimates were subtracted from the Global Precipitation Climatology Project (GPCP)-based precipitation estimates and were compared with GRACE-derived water storage changes. Our results suggest that it is not possible to close the water balance by using satellite data alone, even when adopting a spherical harmonic

  15. 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

  16. Improving spatio-temporal model estimation of satellite-derived PM2.5 concentrations: Implications for public health

    Science.gov (United States)

    Barik, M. G.; Al-Hamdan, M. Z.; Crosson, W. L.; Yang, C. A.; Coffield, S. R.

    2017-12-01

    Satellite-derived environmental data, available in a range of spatio-temporal scales, are contributing to the growing use of health impact assessments of air pollution in the public health sector. Models developed using correlation of Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD) with ground measurements of fine particulate matter less than 2.5 microns (PM2.5) are widely applied to measure PM2.5 spatial and temporal variability. In the public health sector, associations of PM2.5 with respiratory and cardiovascular diseases are often investigated to quantify air quality impacts on these health concerns. In order to improve predictability of PM2.5 estimation using correlation models, we have included meteorological variables, higher-resolution AOD products and instantaneous PM2.5 observations into statistical estimation models. Our results showed that incorporation of high-resolution (1-km) Multi-Angle Implementation of Atmospheric Correction (MAIAC)-generated MODIS AOD, meteorological variables and instantaneous PM2.5 observations improved model performance in various parts of California (CA), USA, where single variable AOD-based models showed relatively weak performance. In this study, we further asked whether these improved models actually would be more successful for exploring associations of public health outcomes with estimated PM2.5. To answer this question, we geospatially investigated model-estimated PM2.5's relationship with respiratory and cardiovascular diseases such as asthma, high blood pressure, coronary heart disease, heart attack and stroke in CA using health data from the Centers for Disease Control and Prevention (CDC)'s Wide-ranging Online Data for Epidemiologic Research (WONDER) and the Behavioral Risk Factor Surveillance System (BRFSS). PM2.5 estimation from these improved models have the potential to improve our understanding of associations between public health concerns and air quality.

  17. 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

  18. Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

    Energy Technology Data Exchange (ETDEWEB)

    Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

    2004-03-01

    Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

  19. Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

    International Nuclear Information System (INIS)

    Boresjoe Bronge, Laine

    2004-03-01

    Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given

  20. Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

    Science.gov (United States)

    Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

    2006-01-01

    We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

  1. SeaWiFS Technical Report Series. Volume 42; Satellite Primary Productivity Data and Algorithm Development: A Science Plan for Mission to Planet Earth

    Science.gov (United States)

    Falkowski, Paul G.; Behrenfeld, Michael J.; Esaias, Wayne E.; Balch, William; Campbell, Janet W.; Iverson, Richard L.; Kiefer, Dale A.; Morel, Andre; Yoder, James A.; Hooker, Stanford B. (Editor); hide

    1998-01-01

    Two issues regarding primary productivity, as it pertains to the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Program and the National Aeronautics and Space Administration (NASA) Mission to Planet Earth (MTPE) are presented in this volume. Chapter 1 describes the development of a science plan for deriving primary production for the world ocean using satellite measurements, by the Ocean Primary Productivity Working Group (OPPWG). Chapter 2 presents discussions by the same group, of algorithm classification, algorithm parameterization and data availability, algorithm testing and validation, and the benefits of a consensus primary productivity algorithm.

  2. Merging of airborne gravity and gravity derived from satellite altimetry: Test cases along the coast of greenland

    DEFF Research Database (Denmark)

    Olesen, Arne Vestergaard; Andersen, Ole Baltazar; Tscherning, C.C.

    2002-01-01

    for the use of gravity data especially, when computing geoid models in coastal regions. The presence of reliable marine gravity data for independent control offers an opportunity to study procedures for the merging of airborne and satellite data around Greenland. Two different merging techniques, both based......The National Survey and Cadastre - Denmark (KMS) has for several years produced gravity anomaly maps over the oceans derived from satellite altimetry. During the last four years, KMS has also conducted airborne gravity surveys along the coast of Greenland dedicated to complement the existing...... onshore gravity coverage and fill in new data in the very-near coastal area, where altimetry data may contain gross errors. The airborne surveys extend from the coastline to approximately 100 km offshore, along 6000 km of coastline. An adequate merging of these different data sources is important...

  3. A model of Earth’s magnetic field derived from 2 years of Swarm satellite constellation data

    DEFF Research Database (Denmark)

    Olsen, Nils; Finlay, Chris; Kotsiaros, Stavros

    2016-01-01

    More than 2 years of magnetic field data taken by the three-satellite constellation mission Swarm are used to derive a model of Earth’s magnetic field and its time variation. This model is called SIFMplus. In addition to the magnetic field observations provided by each of the three Swarm satellites...... the North–South gradient. The SIFMplus model provides a description of the static lithospheric field that is very similar to models determined from CHAMP data, up to at least spherical harmonic degree n=75. Also the core field part of SIFMplus, with a quadratic time dependence for n≤6 and a linear time...... with the model of the core, lithospheric and large-scale magnetospheric fields, a magnetic potential that depends on quasi-dipole latitude and magnetic local time....

  4. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  5. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  6. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  7. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  8. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  9. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  10. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  11. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  12. Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  13. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  14. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of the Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  15. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  16. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Rota Island, Territory of Mariana, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  17. Mosaic of 2m bathymetry derived from multispectral IKONOS World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  18. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  19. Accuracy assessment of satellite Ocean colour products in coastal waters.

    Science.gov (United States)

    Tilstone, G.; Lotliker, A.; Groom, S.

    2012-04-01

    The use of Ocean Colour Remote Sensing to monitor phytoplankton blooms in coastal waters is hampered by the absorption and scattering from substances in the water that vary independently of phytoplankton. In this paper we compare different ocean colour algorithms available for SeaWiFS, MODIS and MERIS with in situ observations of Remote Sensing Reflectance, Chlorophyll-a (Chla), Total Suspended Material and Coloured Dissolved Organic Material in coastal waters of the Arabian Sea, Bay of Bengal, North Sea and Western English Channel, which have contrasting inherent optical properties. We demonstrate a clustering method on specific-Inherent Optical Properties (sIOP) that gives accurate water quality products from MERIS data (HYDROPT) and also test the recently developed ESA CoastColour MERIS products. We found that for coastal waters of the Bay of Bengal, OC5 gave the most accurate Chla, for the Arabian Sea GSM and OC3M Chla were more accurate and for the North Sea and Western English Channel, MERIS HYDROPT were more accurate than standard algorithms. The reasons for these differences will be discussed. A Chla time series from 2002-2011 will be presented to illustrate differences in algorithms between coastal regions and inter- and intra-annual variability in phytoplankton blooms

  20. Towards Improving Satellite Tropospheric NO2 Retrieval Products: Impacts of the spatial resolution and lighting NOx production from the a priori chemical transport model

    Science.gov (United States)

    Smeltzer, C. D.; Wang, Y.; Zhao, C.; Boersma, F.

    2009-12-01

    Polar orbiting satellite retrievals of tropospheric nitrogen dioxide (NO2) columns are important to a variety of scientific applications. These NO2 retrievals rely on a priori profiles from chemical transport models and radiative transfer models to derive the vertical columns (VCs) from slant columns measurements. In this work, we compare the retrieval results using a priori profiles from a global model (TM4) and a higher resolution regional model (REAM) at the OMI overpass hour of 1330 local time, implementing the Dutch OMI NO2 (DOMINO) retrieval. We also compare the retrieval results using a priori profiles from REAM model simulations with and without lightning NOx (NO + NO2) production. A priori model resolution and lightning NOx production are both found to have large impact on satellite retrievals by altering the satellite sensitivity to a particular observation by shifting the NO2 vertical distribution interpreted by the radiation model. The retrieved tropospheric NO2 VCs may increase by 25-100% in urban regions and be reduced by 50% in rural regions if the a priori profiles from REAM simulations are used during the retrievals instead of the profiles from TM4 simulations. The a priori profiles with lightning NOx may result in a 25-50% reduction of the retrieved tropospheric NO2 VCs compared to the a priori profiles without lightning. As first priority, a priori vertical NO2 profiles from a chemical transport model with a high resolution, which can better simulate urban-rural NO2 gradients in the boundary layer and make use of observation-based parameterizations of lightning NOx production, should be first implemented to obtain more accurate NO2 retrievals over the United States, where NOx source regions are spatially separated and lightning NOx production is significant. Then as consequence of a priori NO2 profile variabilities resulting from lightning and model resolution dynamics, geostationary satellite, daylight observations would further promote the next

  1. High-resolution Monthly Satellite Precipitation Product over the Conterminous United States

    Science.gov (United States)

    Hashemi, H.; Fayne, J.; Knight, R. J.; Lakshmi, V.

    2017-12-01

    We present a data set that enhanced the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) monthly product 3B43 in its accuracy and spatial resolution. For this, we developed a correction function to improve the accuracy of TRMM 3B43, spatial resolution of 25 km, by estimating and removing the bias in the satellite data using a ground-based precipitation data set. We observed a strong relationship between the bias and land surface elevation; TRMM 3B43 tends to underestimate the ground-based product at elevations above 1500 m above mean sea level (m.amsl) over the conterminous United States. A relationship was developed between satellite bias and elevation. We then resampled TRMM 3B43 to the Digital Elevation Model (DEM) data set at a spatial resolution of 30 arc second ( 1 km on the ground). The produced high-resolution satellite-based data set was corrected using the developed correction function based on the bias-elevation relationship. Assuming that each rain gauge represents an area of 1 km2, we verified our product against 9,200 rain gauges across the conterminous United States. The new product was compared with the gauges, which have 50, 60, 70, 80, 90, and 100% temporal coverage within the TRMM period of 1998 to 2015. Comparisons between the high-resolution corrected satellite-based data and gauges showed an excellent agreement. The new product captured more detail in the changes in precipitation over the mountainous region than the original TRMM 3B43.

  2. Comparison of cloud top heights derived from FY-2 meteorological satellites with heights derived from ground-based millimeter wavelength cloud radar

    Science.gov (United States)

    Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa

    2018-01-01

    Clouds are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic cloud measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their cloud top temperature product can be processed to retrieve the cloud top height (CTH). The ground-based millimeter wavelength cloud radar can acquire information about the vertical structure of clouds-such as the cloud base height (CBH), CTH and the cloud thickness-and can continuously monitor changes in the vertical profiles of clouds. The CTHs were retrieved using both cloud top temperature data from the FY-2 satellites and the cloud radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of cloud detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker clouds with larger echo intensity and for more continuous clouds. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level clouds was less than that for high-level clouds. An attenuation threshold of the cloud radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the cloud radar data.

  3. Plantago lagopus B Chromosome Is Enriched in 5S rDNA-Derived Satellite DNA

    Czech Academy of Sciences Publication Activity Database

    Kumke, K.; Macas, Jiří; Fuchs, J.; Altschmied, L.; Kour, J.; Dhar, M.K.; Houben, A.

    2016-01-01

    Roč. 148, č. 1 (2016), s. 68-73 ISSN 1424-8581 R&D Projects: GA ČR GBP501/12/G090 Institutional support: RVO:60077344 Keywords : Polymorhpic A chromosome segment * Satellite repeat * Supernumerary chromosome * 5S rDNA Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.354, year: 2016

  4. Will the aerosol derived from the OCM satellite sensor be representative of the aerosol over Goa?

    Digital Repository Service at National Institute of Oceanography (India)

    Talaulikar, M.; Suresh, T.; Rodrigues, A.; Desa, E.; Chauhan, P.

    Most of the ocean color satellite sensors such as IRS-P4 OCM, SeaWiFS and MODIS are sun synchronous and have pass over the regions during noon. From our measurements of aerosol optical properties using five-channel sunphotometer over the coastal...

  5. How consistent is the satellite derived SST-LHF relationship in comparison with observed values ?

    Digital Repository Service at National Institute of Oceanography (India)

    Muraleedharan, P.M.; Pankajakshan, T.

    Arabian Sea was generally above 27 degrees C, the satellite underestimation often produced SSTs less than 27 degrees C, thereby supporting a linear relationship with LHF, as suggested by Zhang and McPhaden. Similarly for SSTs higher than 28 degrees C...

  6. Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area

    DEFF Research Database (Denmark)

    Westergaard-Nielsen, Andreas; Lund, Magnus; Hansen, Birger Ulf

    2013-01-01

    vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid...... and GPP (R-2 = 0.85, p remote Arctic regions....... (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved....

  7. Systematical estimation of GPM-based global satellite mapping of precipitation products over China

    Science.gov (United States)

    Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

    2018-03-01

    As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

  8. The annual cycle of satellite derived sea surface temperature on the western South Atlantic shelf

    Directory of Open Access Journals (Sweden)

    Carlos A. D. Lentini

    2000-01-01

    Full Text Available In this article, thirteen years of weekly sea surface temperature (SST fields derived from NOAA Advanced Very High Resolution Radiometer global area coverage infrared satellite data, from January 1982 to December 1994, are used to investigate spatial and temporal variabilities of SST seasonal cycle in the Southwest Atlantic Oceano This work addresses large scale variations over the eastem South American continental shelf and slope regions limited offshore by the 1000-m isobath, between 42° and 22°S. SST time series are fit with annual and semi-annual harmonics to describe the annual variation of sea surface temperatures. The annual harmonic explains a large proportion of the SST variability. The coefficient of determination is highest (> 90% on the continental shelf, decreasing offshore. The estimated amplitude of the seasonal cycle ranges between 4° and 13°e throughout the study area, with minima in August­September and maxima in February-March. After the identification and removal of the dominant annual components ofSST variability, models such as the one presented here are an attractive tool to study interannual SST variability.Neste artigo, treze anos de imagens semanais da temperatura da superfície do mar (TSM obtidas através do sensor infravermelho Advanced Very High Resolution Radiometer a bordo dos satélites NOAA, de janeiro de 1982 a dezembro de 1994, são utlilizadas para investigar as variabilidades espacial e temporal do cicIo sazonal de TSM no Oceano Atlântico Sudoeste. Este trabalho objetiva as variações de larga escala sobre a plataforma continental e o talude leste da América do Sul limitados ao largo pela isóbata de 1000 metros, entre 42°5 e 22°S. As séries temporais de TSM são ajustadas aos .harmônicos anual e sem i-anual para descrever a variação anual das temperaturas da superfície do mar. O harmônico anual explica a maior parte da variabilidade da TSM. O coeficiente de determinação é alto (> 90

  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. Time-Series Similarity Analysis of Satellite Derived Data to Understand Changes in Forest Biomass.

    Science.gov (United States)

    Singh, N.; Fritz, B.

    2017-12-01

    One of the goals of promoting bioenergy is reducing green-house gas emissions by replacing fossil fuels. However, there are concerns that carbon emissions due to changes in land use resulting from crop production for ethanol will negate the impact of biofuels on the environment. So, the current focus is to use lignocellulose feedstocks also referred to as second generation biofuels as the new source of bioenergy. Wood based pellets derived from the forests of southeastern United States are one such source which is being exported to Europe as a carbon-neutral fuel. These wood-pellets meet the EU standard for carbon emissions and are being used to replace coal for energy generation and heating. As a result US exports of wood-based pellets have increased from nearly zero to over 6 million metric tons over the past 8 years. Wood-based pellets are traditionally produced from softwood trees which have a relatively shorter life-cycle and propagate easily, and thus are expected to provide a sustainable source of wood chips used for pellet production. However, there are concerns that as the demand and price of wood pellets increases, lumber mills will seek wood chips from other sources as well, particularly from hardwood trees resulting in higher carbon emissions as well as loss of biodiversity. In this study we use annual stacks of normalized difference vegetation index (NDVI) data at a 16-day temporal resolution to monitor biomass around pellet mills in southeastern United States. We use a combination of time series similarity technique and supervised learning to understand if there have been significant changes in biomass around pellet mills in the southeastern US. We also demonstrate how our method can be used to monitor biomass over large geographic regions using phenological properties of growing vegetation.

  11. Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

  12. Space transportation. [user needs met by information derived from satellites and the interface with space transportation systems

    Science.gov (United States)

    1975-01-01

    User-oriented panels were formed to examine practical applications of information or services derived from earth orbiting satellites. Topics discussed include: weather and climate; uses of communication; land use planning; agriculture, forest, and range; inland water resources; retractable resources; environmental quality; marine and maritime uses; and materials processing in space. Emphasis was placed on the interface of the space transportation system (STS) with the applications envisioned by the user panels. User requirements were compared with expected STS capabilities in terms of availability, carrying payload to orbit, and estimated costs per launch. Conclusions and recommendations were reported.

  13. A satellite digital controller or 'play that PID tune again, Sam'. [Position, Integral, Derivative feedback control algorithm for design strategy

    Science.gov (United States)

    Seltzer, S. M.

    1976-01-01

    The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.

  14. Natural product derived insecticides: discovery and development of spinetoram.

    Science.gov (United States)

    Galm, Ute; Sparks, Thomas C

    2016-03-01

    This review highlights the importance of natural product research and industrial microbiology for product development in the agricultural industry, based on examples from Dow AgroSciences. It provides an overview of the discovery and development of spinetoram, a semisynthetic insecticide derived by a combination of a genetic block in a specific O-methylation of the rhamnose moiety of spinosad coupled with neural network-based QSAR and synthetic chemistry. It also emphasizes the key role that new technologies and multidisciplinary approaches play in the development of current spinetoram production strains.

  15. Stem-cell-derived products: an FDA update.

    Science.gov (United States)

    Moos, Malcolm

    2008-12-01

    The therapeutic potential of products derived from stem cells of various types has prompted increasing research and development and public attention. Initiation of human clinical trials in the not-too-distant future is now a realistic possibility. It is, therefore, important to weigh the potential benefits against known, theoretical and totally unsuspected risks in light of current knowledge to ensure that subjects participating in these trials are afforded the most reasonable balance possible between potential risks and potential benefits. There are no apparent differences in fundamental, qualitative biological characteristics between stem-cell-derived products and other cellular therapies regulated by the United States Food and Drug Administration (FDA). Existing authorities can, therefore, be applied. Nevertheless, these products do have properties that require careful evaluation.

  16. Nutritional value of milk and meat products derived from cloning.

    Science.gov (United States)

    Tomé, Daniel; Dubarry, Michel; Fromentin, Gilles

    2004-01-01

    The development and use of milk and meat products derived from cloning depends on their safety and on the nutritional advantages they can confer to the products as perceived by consumers. The development of such products thus implies (i) to demonstrate their safety and security, (ii) to show that their nutritional value is equivalent to the traditional products, and (iii) to identify the conditions under which cloning could allow additional nutritional and health benefit in comparison to traditional products for the consumers. Both milk and meat products are a source of high quality protein as determined from their protein content and essential amino acid profile. Milk is a source of calcium, phosphorus, zinc, magnesium and vitamin B2 and B12. Meat is a source of iron, zinc and vitamin B12. An important issue regarding the nutritional quality of meat and milk is the level and quality of fat which usually present a high content in saturated fat and some modification of the fat fraction could improve the nutritional quality of the products. The role of the dietary proteins as potential allergens has to be taken into account and an important aspect regarding this question is to evaluate whether the cloning does not produce the appearance of novel allergenic structures. The presence of bio-activities associated to specific components of milk (lactoferrin, immunoglobulins, growth factors, anti-microbial components) also represents a promising development. Preliminary results obtained in rats fed cow's milk or meat-based diets prepared from control animals or from animals derived from cloning did not show any difference between control and cloning-derived products.

  17. The long-term Global LAnd Surface Satellite (GLASS) product suite and applications

    Science.gov (United States)

    Liang, S.

    2015-12-01

    Our Earth's environment is experiencing rapid changes due to natural variability and human activities. To monitor, understand and predict environment changes to meet the economic, social and environmental needs, use of long-term high-quality satellite data products is critical. The Global LAnd Surface Satellite (GLASS) product suite, generated at Beijing Normal University, currently includes 12 products, including leaf area index (LAI), broadband shortwave albedo, broadband longwave emissivity, downwelling shortwave radiation and photosynthetically active radiation, land surface skin temperature, longwave net radiation, daytime all-wave net radiation, fraction of absorbed photosynetically active radiation absorbed by green vegetation (FAPAR), fraction of green vegetation coverage, gross primary productivity (GPP), and evapotranspiration (ET). Most products span from 1981-2014. The algorithms for producing these products have been published in the top remote sensing related journals and books. More and more applications have being reported in the scientific literature. The GLASS products are freely available at the Center for Global Change Data Processing and Analysis of Beijing Normal University (http://www.bnu-datacenter.com/), and the University of Maryland Global Land Cover Facility (http://glcf.umd.edu). After briefly introducing the basic characteristics of GLASS products, we will present some applications on the long-term environmental changes detected from GLASS products at both global and local scales. Detailed analysis of regional hotspots, such as Greenland, Tibetan plateau, and northern China, will be emphasized, where environmental changes have been mainly associated with climate warming, drought, land-atmosphere interactions, and human activities.

  18. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Science.gov (United States)

    Fita, L.; Romero, R.; Luque, A.; Ramis, C.

    2009-08-01

    The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

  19. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Directory of Open Access Journals (Sweden)

    L. Fita

    2009-08-01

    Full Text Available The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA. An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity

  20. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Energy Technology Data Exchange (ETDEWEB)

    Fita, L.; Romero, R.; Luque, A.; Ramis, C. [Univ. de les Illes Balears, Palma de Mallorca (Spain). Grup de Meteorologia

    2009-07-01

    The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

  1. Tumorigenicity studies for human pluripotent stem cell-derived products.

    Science.gov (United States)

    Kuroda, Takuya; Yasuda, Satoshi; Sato, Yoji

    2013-01-01

    Human pluripotent stem cells (hPSCs), i.e. human embryonic stem cells and human induced pluripotent stem cells, are able to self-renew and differentiate into multiple cell types. Because of these abilities, numerous attempts have been made to utilize hPSCs in regenerative medicine/cell therapy. hPSCs are, however, also tumorigenic, that is, they can give rise to the progressive growth of tumor nodules in immunologically unresponsive animals. Therefore, assessing and managing the tumorigenicity of all final products is essential in order to prevent ectopic tissue formation, tumor development, and/or malignant transformation elicited by residual pluripotent stem cells after implantation. No detailed guideline for the tumorigenicity testing of hPSC-derived products has yet been issued for regenerative medicine/cell therapy, despite the urgent necessity. Here, we describe the current situations and issues related to the tumorigenicity testing of hPSC-derived products and we review the advantages and disadvantages of several types of tumorigenicity-associated tests. We also refer to important considerations in the execution and design of specific studies to monitor the tumorigenicity of hPSC-derived products.

  2. Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

    Directory of Open Access Journals (Sweden)

    Adam Milewski

    2015-05-01

    Full Text Available TRMM Multi-satellite Precipitation Analysis (TMPA satellite precipitation products have been utilized to quantify, forecast, or understand precipitation patterns, climate change, hydrologic models, and drought in numerous scientific investigations. The TMPA products recently went through a series of algorithm developments to enhance the accuracy and reliability of high-quality precipitation measurements, particularly in low rainfall environments and complex terrain. In this study, we evaluated four TMPA products (3B42: V6, V7temp, V7, RTV7 against 125 rain gauges in Northern Morocco to assess the accuracy of TMPA products in various regimes, examine the performance metrics of new algorithm developments, and assess the impact of the processing error in 2012. Results show that the research products outperform the real-time products in all environments within Morocco, and the newest algorithm development (3B42 V7 outperforms the previous version (V6, particularly in low rainfall and high-elevation environments. TMPA products continue to overestimate precipitation in arid environments and underestimate it in high-elevation areas. Lastly, the temporary processing error resulted in little bias except in arid environments. These results corroborate findings from previous studies, provide scientific data for the Middle East, highlight the difficulty of using TMPA products in varying conditions, and present preliminary research for future algorithm development for the GPM mission.

  3. Solar resources and power potential mapping in Vietnam using satellite-derived and GIS-based information

    International Nuclear Information System (INIS)

    Polo, J.; Bernardos, A.; Navarro, A.A.; Fernandez-Peruchena, C.M.; Ramírez, L.; Guisado, María V.; Martínez, S.

    2015-01-01

    Highlights: • Satellite-based, reanalysis data and measurements are combined for solar mapping. • Plant output modeling for PV and CSP results in simple expressions of solar potential. • Solar resource, solar potential are used in a GIS for determine technical solar potential. • Solar resource and potential maps of Vietnam are presented. - Abstract: The present paper presents maps of the solar resources in Vietnam and of the solar potential for concentrating solar power (CSP) and for grid-connected photovoltaic (PV) technology. The mapping of solar radiation components has been calculated from satellite-derived data combined with solar radiation derived from sunshine duration and other additional sources of information based on reanalysis for several atmospheric and meteorological parameters involved. Two scenarios have been selected for the study of the solar potential: CSP Parabolic Trough of 50 MWe and grid-connected Flat Plate PV plant of around 1 MWe. For each selected scenario plant performance simulations have been computed for developing simple expressions that allow the estimation of the solar potential from the annual solar irradiation and the latitude of every site in Vietnam. Finally, Geographic Information Systems (GIS) have been used for combining the solar potential with the land availability according each scenario to deliver the technical solar potential maps of Vietnam

  4. Impact analysis of satellite rainfall products on flow simulations in the Magdalena River Basin, Colombia

    Directory of Open Access Journals (Sweden)

    Amr Elgamal

    2017-02-01

    Full Text Available The Magdalena River is the most important river in Colombia in terms of economic activities and is home to about 77% of the country’s population. The river faces water resources allocation challenges, which require reliable hydrological assessments. However, hydrological analysis and model simulations are hampered by insufficient and uncertain knowledge of the actual rainfall fields. In this research the reliability of groundbased measurements, different satellite products of rainfall and their combinations are tested for their impact on the discharge simulations of the Magdalena River. Two different satellite rainfall products from the Tropical Rainfall Measuring Mission (TRMM, have been compared and merged with the ground-based measurements and their impact on the Magdalena river flows quantified using the Representative Elementary Watershed (REW distributed hydrological model.

  5. Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

    Science.gov (United States)

    Drusch, M.

    2007-02-01

    Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

  6. Crust-mantle density distribution in the eastern Qinghai-Tibet Plateau revealed by satellite-derived gravity gradients

    Science.gov (United States)

    LI, Honglei; Fang, Jian; Braitenberg, Carla; Wang, Xinsheng

    2015-04-01

    As the highest, largest and most active plateau on Earth, the Qinghai-Tibet Plateau has a complex crust-mantle structure, especially in its eastern part. In response to the subduction of the lithospheric mantle of the Indian plate, large-scale crustal motion occurs in this area. Despite the many previous studies, geodynamic processes at depth remain unclear. Knowledge of crust and upper mantle density distribution allows a better definition of the deeper geological structure and thus provides critically needed information for understanding of the underlying geodynamic processes. With an unprecedented precision of 1-2 mGal and a spatial resolution better than 100 km, GOCE (Gravity field and steady-state Ocean Circulation Explorer) mission products can be used to constrain the crust-mantle density distribution. Here we used GOCE gravitational gradients at an altitude of 10km after reducing the effects of terrain, sediment thickness variations, and Moho undulations to image the density structures of eastern Tibet up to 200 km depths. We inverted the residual satellite gravitational gradients using a least square approach. The initial density model for the inversion is based on seismic velocities from the tomography. The model is composed of rectangular blocks, having a uniform density, with widths of about 100 km and variable thickness and depths. The thickness of the rectangular cells changes from10 to 60km in accordance with the seismic model. Our results reveal some large-scale, structurally controlled density variations at depths. The lithospheric root defined by higher-density contrast features from southwest to northeast, with shallowing in the central part: base of lithosphere reaches a depth of180 km, less than 100km, and 200 km underneath the Lhasa, Songpan-Ganzi, and Ordos crustal blocks, respectively. However, these depth values only represent a first-order parameterization because they depend on model discretization inherited from the original seismic

  7. Whey-derived valuable products obtained by microbial fermentation.

    Science.gov (United States)

    Pescuma, Micaela; de Valdez, Graciela Font; Mozzi, Fernanda

    2015-08-01

    Whey, the main by-product of the cheese industry, is considered as an important pollutant due to its high chemical and biological oxygen demand. Whey, often considered as waste, has high nutritional value and can be used to obtain value-added products, although some of them need expensive enzymatic synthesis. An economical alternative to transform whey into valuable products is through bacterial or yeast fermentations and by accumulation during algae growth. Fermentative processes can be applied either to produce individual compounds or to formulate new foods and beverages. In the first case, a considerable amount of research has been directed to obtain biofuels able to replace those derived from petrol. In addition, the possibility of replacing petrol-derived plastics by biodegradable polymers synthesized during bacterial fermentation of whey has been sought. Further, the ability of different organisms to produce metabolites commonly used in the food and pharmaceutical industries (i.e., lactic acid, lactobionic acid, polysaccharides, etc.) using whey as growth substrate has been studied. On the other hand, new low-cost functional whey-based foods and beverages leveraging the high nutritional quality of whey have been formulated, highlighting the health-promoting effects of fermented whey-derived products. This review aims to gather the multiple uses of whey as sustainable raw material for the production of individual compounds, foods, and beverages by microbial fermentation. This is the first work to give an overview on the microbial transformation of whey as raw material into a large repertoire of industrially relevant foods and products.

  8. Evaluation of Satellite Precipitation Products with Rain Gauge Data at Different Scales: Implications for Hydrological Applications

    Directory of Open Access Journals (Sweden)

    Ruifang Guo

    2016-07-01

    Full Text Available Rain gauge and satellite-retrieved data have been widely used in basin-scale hydrological applications. While rain gauges provide accurate measurements that are generally unevenly distributed in space, satellites offer spatially regular observations and common error prone retrieval. Comparative evaluation of gauge-based and satellite-based data is necessary in hydrological studies, as precipitation is the most important input in basin-scale water balance. This study uses quality-controlled rain gauge data and prevailing satellite products (Tropical Rainfall Measuring Mission (TRMM 3B43, 3B42 and 3B42RT to examine the consistency and discrepancies between them at different scales. Rain gauges and TRMM products were available in the Poyang Lake Basin, China, from 1998 to 2007 (3B42RT: 2000–2007. Our results show that the performance of TRMM products generally increases with increasing spatial scale. At both the monthly and annual scales, the accuracy is highest for TRMM 3B43, with 3B42 second and 3B42RT third. TRMM products generally overestimate precipitation because of a high frequency and degree of overestimation in light and moderate rain cases. At the daily scale, the accuracy is relatively low between TRMM 3B42 and 3B42RT. Meanwhile, the performances of TRMM 3B42 and 3B42RT are highly variable in different seasons. At both the basin and pixel scales, TRMM 3B43 and 3B42 exhibit significant discrepancies from July to September, performing worst in September. For TRMM 3B42RT, all statistical indices fluctuate and are low throughout the year, performing worst in July at the pixel scale and January at the basin scale. Furthermore, the spatial distributions of the statistical indices of TRMM 3B43 and 3B42 performed well, while TRMM 3B42RT displayed a poor performance.

  9. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

    Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

  10. Life Cycle Assessment in the Cereal and Derived Products Sector

    DEFF Research Database (Denmark)

    Renzulli, Pietro A.; Bacenetti, Jacopo; Benedetto, Graziella

    2015-01-01

    environmental improvement in such systems. Following a brief introduction to the cereal sector and supply chain, this chapter reviews some of the current cereal-based life cycle thinking literature, with a particular emphasis on LCA. Next, an analysis of the LCA methodological issues emerging from......This chapter discusses the application of life cycle assessment methodologies to rice, wheat, corn and some of their derived products. Cereal product systems are vital for the production of commodities of worldwide importance that entail particular environmental hot spots originating from...... their widespread use and from their particular nature. It is thus important for tools such as life cycle assessment (LCA) to be tailored to such cereal systems in order to be used as a means of identifying the negative environmental effects of cereal products and highlighting possible pathways to overall...

  11. New efficient hydrogen process production from organosilane hydrogen carriers derivatives

    Energy Technology Data Exchange (ETDEWEB)

    Brunel, Jean Michel [Unite URMITE, UMR 6236 CNRS, Faculte de Medecine et de Pharmacie, Universite de la Mediterranee, 27 boulevard Jean Moulin, 13385 Marseille 05 (France)

    2010-04-15

    While the source of hydrogen constitutes a significant scientific challenge, addressing issues of hydrogen storage, transport, and delivery is equally important. None of the current hydrogen storage options, liquefied or high pressure H{sub 2} gas, metal hydrides, etc.. satisfy criteria of size, costs, kinetics, and safety for use in transportation. In this context, we have discovered a methodology for the production of hydrogen on demand, in high yield, under kinetic control, from organosilane hydrogen carriers derivatives and methanol as co-reagent under mild conditions catalyzed by a cheap ammonium fluoride salt. Finally, the silicon by-products can be efficiently recycle leading to an environmentally friendly source of energy. (author)

  12. Cytotoxic Natural Products from Marine Sponge-Derived Microorganisms

    Directory of Open Access Journals (Sweden)

    Huawei Zhang

    2017-03-01

    Full Text Available A growing body of evidence indicates that marine sponge-derived microbes possess the potential ability to make prolific natural products with therapeutic effects. This review for the first time provides a comprehensive overview of new cytotoxic agents from these marine microbes over the last 62 years from 1955 to 2016, which are assorted into seven types: terpenes, alkaloids, peptides, aromatics, lactones, steroids, and miscellaneous compounds.

  13. Evaluation of the Performance of Three Satellite Precipitation Products over Africa

    Directory of Open Access Journals (Sweden)

    Aleix Serrat-Capdevila

    2016-10-01

    Full Text Available We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM Multi-satellite Precipitation Analysis (TMPA, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, and Climate Prediction Center (CPC Morphing Technique (CMORPH—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.

  14. Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

    Science.gov (United States)

    Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

    2015-12-01

    Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

  15. A first map of tropical Africa's above-ground biomass derived from satellite imagery

    International Nuclear Information System (INIS)

    Baccini, A; Laporte, N; Goetz, S J; Sun, M; Dong, H

    2008-01-01

    Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha -1 for a range of biomass between 0 and 454 Mg ha -1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R 2 = 0.90) between the GLAS height metrics and predicted AGB.

  16. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed...... by the sensor. This is further complicated by temperature differences between the sunlit and shaded parts of each of the components, controlled by the exposure of the components to direct sunlight. As the SEVIRI sensor is onboard a geostationary platform, the viewing geometry is fixed (for each pixel), while...

  17. Lunar tidal acceleration obtained from satellite-derived ocean tide parameters

    Science.gov (United States)

    Goad, C. C.; Douglas, B. C.

    1978-01-01

    One hundred sets of mean elements of GEOS-3 computed at 2-day intervals yielded observation equations for the M sub 2 ocean tide from the long periodic variations of the inclination and node of the orbit. The 2nd degree Love number was given the value k sub 2 = 0.30 and the solid tide phase angle was taken to be zero. Combining obtained equations with results for the satellite 1967-92A gives the M sub 2 ocean tide parameter values. Under the same assumption of zero solid tide phase lag, the lunar tidal acceleration was found mostly due to the C sub 22 term in the expansion of the M sub 2 tide with additional small contributions from the 0 sub 1 and N sub 2 tides. Using Lambeck's (1975) estimates for the latter, the obtained acceleration in lunar longitudal in excellent agreement with the most recent determinations from ancient and modern astronomical data.

  18. Estuarine Suspended Sediment Dynamics: Observations Derived from over a Decade of Satellite Data

    Directory of Open Access Journals (Sweden)

    Anthony Reisinger

    2017-12-01

    Full Text Available Suspended sediment dynamics of Corpus Christi Bay, Texas, USA, a shallow-water wind-driven estuary, were investigated by combining field and satellite measurements of total suspended solids (TSS. An algorithm was developed to transform 500-m Moderate Resolution Imaging Spectroradiometer (MODIS Aqua satellite reflectance data into estimated TSS values. The algorithm was developed using a reflectance ratio regression of MODIS Band 1 (red and Band 3 (green with TSS measurements (n = 54 collected by the Texas Commission on Environmental Quality for Corpus Christi Bay and other Texas estuaries. The algorithm was validated by independently collected TSS measurements during the period of 2011–2014 with an uncertainty estimate of 13%. The algorithm was applied to the period of 2002–2014 to create a synoptic time series of TSS for Corpus Christi Bay. Potential drivers of long-term variability in suspended sediment were investigated. Median and IQR composites of suspended sediments were generated for seasonal wind regimes. From this analysis it was determined that long-term, spatial patterns of suspended sediment in the estuary are related to wind-wave resuspension during the predominant northerly and prevalent southeasterly seasonal wind regimes. The impact of dredging is also apparent in long-term patterns of Corpus Christi Bay as concentrations of suspended sediments over dredge spoil disposal sites are higher and more variable than surrounding areas, which is most likely due to their less consolidated sediments and shallower depths requiring less wave energy for sediment resuspension. This study highlights the advantage of how long-synoptic time series of TSS can be used to elucidate the major drivers of suspended sediments in estuaries.

  19. Underway Sampling of Marine Inherent Optical Properties on the Tara Oceans Expedition as a Novel Resource for Ocean Color Satellite Data Product Validation

    Science.gov (United States)

    Werdell, P. Jeremy; Proctor, Christopher W.; Boss, Emmanuel; Leeuw, Thomas; Ouhssain, Mustapha

    2013-01-01

    Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate-the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

  20. Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Heo, Gil

    2015-01-01

    Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

  1. Priority pollutant analysis of MHD-derived combustion products

    Science.gov (United States)

    Parks, Katherine D.

    An important factor in developing Magnetohydrodynamics (MHD) for commercial applications is environmental impact. Consequently, an effort was initiated to identify and quantify any possible undesirable minute chemical constituents in MHD waste streams, with special emphasis on the priority pollutant species. This paper discusses how priority pollutant analyses were used to accomplish the following goals at the University of Tennessee Space Institute (UTSI): comparison of the composition of solid combustion products collected from various locations along a prototypical MHD flow train during the firing of Illinois No. 6 and Montana Rosebud coals; comparison of solid waste products generated from MHD and conventional power plant technologies; and identification of a suitable disposal option for various MHD derived combustion products. Results from our ongoing research plans for gas phase sampling and analysis of priority pollutant volatiles, semi-volatiles, and metals are discussed.

  2. Advanced Satellite-Derived Wind Observations, Assimilation, and Targeting Strategies during TCS-08 for Developing Improved Operational Analysis and Prediction of Western Pacific Tropical Cyclones

    Science.gov (United States)

    2013-09-30

    TC structure evolve up to landfall or extratropical transition. In particular, winds derived from geostationary satellites have been shown to be an... extratropical transition, it is clear that a dedicated research effort is needed to optimize the satellite data processing strategies, assimilation, and...applications to better understand the behavior of the near- storm environmental flow fields during these evolutionary TC stages. To our knowledge, this

  3. A metabolic derivation of tritium transfer factors in animal products

    International Nuclear Information System (INIS)

    Galeriu, D.; Melintescu, A.; Crout, N. M. J.; Bersford, N. A.; Peterson, S. R.; Hess, M. van

    2001-01-01

    Tritium is a potentially important environmental contaminant arising from the nuclear industry. Because tritium is an isotope of hydrogen, its behaviour in the environment is controlled by the behaviour of hydrogen. Chronic releases of tritium to the atmosphere, in particular, will result in tritium-to-hydrogen (T/H) ratios in plants and animals that are more or less in equilibrium with T/H ratios in the air moisture. Tritium is thus a potentially important contaminant of plant and animal food products. The transfer of tritium from air moisture to plants is quite well understood. In contrast, although a number of regulatory agencies have published transfer coefficient values for diet tritium transfer for a limited number of animal products, a fresh evaluation of these transfers needs to be made In this paper we present an approach for the derivation of tritium transfer coefficients which is based on the metabolism of hydrogen in animals in conjunction with experimental data on tritium transfer. The derived transfer coefficients separately account for transfer to and from free (i.e. water) and organically bound tritium. The predicted transfer coefficients are compared to available data independent of model development. Agreement is good, with the exception of the transfer coefficient for transfer from tritiated water to organically bound tritium in ruminants, which may be attributable to the particular characteristics of ruminant digestion. We show that transfer coefficients will vary in response to the metabolic status of an animal (e.g. stage of lactation, digestibility of diet, etc.) and that the use of a single transfer coefficient from diet to animal product is not appropriate for tritium. It is possible to derive concentration ratio values which relate the concentration of tritiated water and organically bound tritium in an animal product to the corresponding concentrations in the animals diet. These concentration ratios are shown to be less subject to

  4. On the performance of satellite precipitation products in riverine flood modeling: A review

    Science.gov (United States)

    Maggioni, Viviana; Massari, Christian

    2018-03-01

    This work is meant to summarize lessons learned on using satellite precipitation products for riverine flood modeling and to propose future directions in this field of research. Firstly, the most common satellite precipitation products (SPPs) during the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) eras are reviewed. Secondly, we discuss the main errors and uncertainty sources in these datasets that have the potential to affect streamflow and runoff model simulations. Thirdly, past studies that focused on using SPPs for predicting streamflow and runoff are analyzed. As the impact of floods depends not only on the characteristics of the flood itself, but also on the characteristics of the region (population density, land use, geophysical and climatic factors), a regional analysis is required to assess the performance of hydrologic models in monitoring and predicting floods. The performance of SPP-forced hydrological models was shown to largely depend on several factors, including precipitation type, seasonality, hydrological model formulation, topography. Across several basins around the world, the bias in SPPs was recognized as a major issue and bias correction methods of different complexity were shown to significantly reduce streamflow errors. Model re-calibration was also raised as a viable option to improve SPP-forced streamflow simulations, but caution is necessary when recalibrating models with SPP, which may result in unrealistic parameter values. From a general standpoint, there is significant potential for using satellite observations in flood forecasting, but the performance of SPP in hydrological modeling is still inadequate for operational purposes.

  5. GeoComp-n, an advanced system for the processing of coarse and medium resolution satellite data. Part 2: biophysical products for Northern ecosystems

    Energy Technology Data Exchange (ETDEWEB)

    Cihlar, J. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Chen, J. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Univ. of Toronto, Dept. of Geography, Toronto, Ontario (Canada); Li, Z. [Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ontario (Canada); Univ. of Maryland, Dept of Meteorology, College Park, MD (United States)] [and others

    2002-02-01

    Effective use of satellite data for environmental monitoring requires consistent, high-throughput processing of large volumes of data as it is transformed from raw measurements to useful higher level products. 'GeoComp-n', the next generation of the Geocoding and Compositing System developed at the Canada Centre for Remote Sensing, Natural Resources Canada, was developed as a software solution to this challenge, for use with satellites that provide daily data for the landmass of Canada or comparably large areas. In this paper, the authors discuss the characteristics of the algorithms and methods used in the generation of GeoComp-n products. The theoretical basis and assumptions in the algorithms are described, and the quality of the products is discussed based on validation studies. Examples of a suite of products for Canada during one 10-day period illustrate the diversity and quality of observations for the terrestrial biosphere that may be derived frequently and over large areas from satellites. Issues related to quality assessment in a production environment are also discussed. (author)

  6. GeoComp-n, an advanced system for the processing of coarse and medium resolution satellite data. Part 2: biophysical products for Northern ecosystems

    International Nuclear Information System (INIS)

    Cihlar, J.; Chen, J.; Li, Z.

    2002-01-01

    Effective use of satellite data for environmental monitoring requires consistent, high-throughput processing of large volumes of data as it is transformed from raw measurements to useful higher level products. 'GeoComp-n', the next generation of the Geocoding and Compositing System developed at the Canada Centre for Remote Sensing, Natural Resources Canada, was developed as a software solution to this challenge, for use with satellites that provide daily data for the landmass of Canada or comparably large areas. In this paper, the authors discuss the characteristics of the algorithms and methods used in the generation of GeoComp-n products. The theoretical basis and assumptions in the algorithms are described, and the quality of the products is discussed based on validation studies. Examples of a suite of products for Canada during one 10-day period illustrate the diversity and quality of observations for the terrestrial biosphere that may be derived frequently and over large areas from satellites. Issues related to quality assessment in a production environment are also discussed. (author)

  7. Comparison of measured and satellite-derived spectral diffuse attenuation coefficients for the Arabian Sea

    Digital Repository Service at National Institute of Oceanography (India)

    Suresh, T.; Talaulikar, M.; Desa, E.; Matondkar, S.G.P.; Mascarenhas, A.

    The results of study comparing the spectral diffuse attenuation coefficients Kd(Lambda) measured in the Arabian Sea with those derived from the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) using three algorithms, of which two are empirical...

  8. Seasonal and nonseasonal variability of satellite-derived chlorophyll and colored dissolved organic matter concentration in the California Current

    Science.gov (United States)

    Kahru, Mati; Mitchell, B. Greg

    2001-02-01

    Time series of surface chlorophyll a concentration (Chl) and colored dissolved organic matter (CDOM) derived from the Ocean Color and Temperature Sensor and Sea-Viewing Wide Field-of-View Sensor were evaluated for the California Current area using regional algorithms. Satellite data composited for 8-day periods provide the ability to describe large-scale changes in surface parameters. These changes are difficult to detect based on in situ observations alone that suffer from undersampling the large temporal and spatial variability, especially in Chl. We detected no significant bias in satellite Chl estimates compared with ship-based measurements. The variability in CDOM concentration was significantly smaller than that in Chl, both spatially and temporally. While being subject to large interannual and short-term variations, offshore waters (100-1000 km from the shore) have an annual cycle of Chl and CDOM with a maximum in winter-spring (December-March) and a minimum in late summer. For inshore waters the maximum is more likely in spring (April-May). We detect significant increase in both Chl and CDOM off central and southern California during the La Niña year of 1999. The trend of increasing Chl and CDOM from October 1996 to June 2000 is statistically significant in many areas.

  9. Satellite-Derived Photic Depth on the Great Barrier Reef: Spatio-Temporal Patterns of Water Clarity

    Directory of Open Access Journals (Sweden)

    Scarla Weeks

    2012-11-01

    Full Text Available Detecting changes to the transparency of the water column is critical for understanding the responses of marine organisms, such as corals, to light availability. Long-term patterns in water transparency determine geographical and depth distributions, while acute reductions cause short-term stress, potentially mortality and may increase the organisms’ vulnerability to other environmental stressors. Here, we investigated the optimal, operational algorithm for light attenuation through the water column across the scale of the Great Barrier Reef (GBR, Australia. We implemented and tested a quasi-analytical algorithm to determine the photic depth in GBR waters and matched regional Secchi depth (ZSD data to MODIS-Aqua (2002–2010 and SeaWiFS (1997–2010 satellite data. The results of the in situ ZSD/satellite data matchup showed a simple bias offset between the in situ and satellite retrievals. Using a Type II linear regression of log-transformed satellite and in situ data, we estimated ZSD and implemented the validated ZSD algorithm to generate a decadal satellite time series (2002–2012 for the GBR. Water clarity varied significantly in space and time. Seasonal effects were distinct, with lower values during the austral summer, most likely due to river runoff and increased vertical mixing, and a decline in water clarity between 2008–2012, reflecting a prevailing La Niña weather pattern. The decline in water clarity was most pronounced in the inshore area, where a significant decrease in mean inner shelf ZSD of 2.1 m (from 8.3 m to 6.2 m occurred over the decade. Empirical Orthogonal Function Analysis determined the dominance of Mode 1 (51.3%, with the greatest variation in water clarity along the mid-shelf, reflecting the strong influence of oceanic intrusions on the spatio-temporal patterns of water clarity. The newly developed photic depth product has many potential applications for the GBR from water quality monitoring to analyses of

  10. Determining the Pixel-to-Pixel Uncertainty in Satellite-Derived SST Fields

    Directory of Open Access Journals (Sweden)

    Fan Wu

    2017-08-01

    Full Text Available The primary measure of the quality of sea surface temperature (SST fields obtained from satellite-borne infrared sensors has been the bias and variance of matchups with co-located in-situ values. Because such matchups tend to be widely separated, these bias and variance estimates are not necessarily a good measure of small scale (several pixels gradients in these fields because one of the primary contributors to the uncertainty in satellite retrievals is atmospheric contamination, which tends to have large spatial scales compared with the pixel separation of infrared sensors. Hence, there is not a good measure to use in selecting SST fields appropriate for the study of submesoscale processes and, in particular, of processes associated with near-surface fronts, both of which have recently seen a rapid increase in interest. In this study, two methods are examined to address this problem, one based on spectra of the SST data and the other on their variograms. To evaluate the methods, instrument noise was estimated in Level-2 Visible-Infrared Imager-Radiometer Suite (VIIRS and Advanced Very High Resolution Radiometer (AVHRR SST fields of the Sargasso Sea. The two methods provided very nearly identical results for AVHRR: along-scan values of approximately 0.18 K for both day and night and along-track values of 0.21 K for day and night. By contrast, the instrument noise estimated for VIIRS varied by method, scan geometry and day-night. Specifically, daytime, along-scan (along-track, spectral estimates were found to be approximately 0.05 K (0.08 K and the corresponding nighttime values of 0.02 K (0.03 K. Daytime estimates based on the variogram were found to be 0.08 K (0.10 K with the corresponding nighttime values of 0.04 K (0.06 K. Taken together, AVHRR instrument noise is significantly larger than VIIRS instrument noise, along-track noise is larger than along-scan noise and daytime levels are higher than nighttime levels. Given the similarity of

  11. Improvement of global and regional mean sea level derived from satellite altimetry multi missions

    Science.gov (United States)

    Ablain, M.; Faugere, Y.; Larnicol, G.; Picot, N.; Cazenave, A.; Benveniste, J.

    2012-04-01

    With the satellite altimetry missions, the global mean sea level (GMSL) has been calculated on a continual basis since January 1993. 'Verification' phases, during which the satellites follow each other in close succession (Topex/Poseidon--Jason-1, then Jason-1--Jason-2), help to link up these different missions by precisely determining any bias between them. Envisat, ERS-1 and ERS-2 are also used, after being adjusted on these reference missions, in order to compute Mean Sea Level at high latitudes (higher than 66°N and S), and also to improve spatial resolution by combining all these missions together. The global mean sea level (MSL) deduced from TOPEX/Poseidon, Jason-1 and Jason-2 provide a global rate of 3.2 mm from 1993 to 2010 applying the post glacial rebound (MSL aviso website http://www.jason.oceanobs.com/msl). Besides, the regional sea level trends bring out an inhomogeneous repartition of the ocean elevation with local MSL slopes ranging from + 8 mm/yr to - 8 mm/year. A study published in 2009 [Ablain et al., 2009] has shown that the global MSL trend unceratainty was estimated at +/-0.6 mm/year with a confidence interval of 90%. The main sources of errors at global and regional scales are due to the orbit calculation and the wet troposphere correction. But others sea-level components have also a significant impact on the long-term stability of MSL as for instance the stability of instrumental parameters and the atmospheric corrections. Thanks to recent studies performed in the frame of the SALP project (supported by CNES) and Sea-level Climate Change Initiative project (supported by ESA), strong improvements have been provided for the estimation of the global and regional MSL trends. In this paper, we propose to describe them; they concern the orbit calculation thanks to new gravity fields, the atmospheric corrections thanks to ERA-interim reanalyses, the wet troposphere corrections thanks to the stability improvement, and also empirical corrections

  12. 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.

  13. The Effects of Climate Variability on Phytoplankton Composition in the Equatorial Pacific Ocean using a Model and a Satellite-Derived Approach

    Science.gov (United States)

    Rousseaux, C. S.; Gregg, W. W.

    2012-01-01

    Compared the interannual variation in diatoms, cyanobacteria, coccolithophores and chlorophytes from the NASA Ocean Biogeochemical Model with those derived from satellite data (Hirata et al. 2011) between 1998 and 2006 in the Equatorial Pacific. Using NOBM, La Ni a events were characterized by an increase in diatoms (correlation with MEI, r=-0.81, Pphytoplankton community in response to climate variability. However, satellite-derived phytoplankton groups were all negatively correlated with climate variability (r ranged from -0.39 for diatoms to -0.64 for coccolithophores, Pphytoplankton groups except diatoms than NOBM. However, the different responses of phytoplankton to intense interannual events in the Equatorial Pacific raises questions about the representation of phytoplankton dynamics in models and algorithms: is a phytoplankton community shift as in the model or an across-the-board change in abundances of all phytoplankton as in the satellite-derived approach.

  14. Climatology 2011: An MLS and Sonde Derived Ozone Climatology for Satellite Retrieval Algorithms

    Science.gov (United States)

    McPeters, Richard D.; Labow, Gordon J.

    2012-01-01

    The ozone climatology used as the a priori for the version 8 Solar Backscatter Ultraviolet (SBUV) retrieval algorithms has been updated. The Microwave Limb Sounder (MLS) instrument on Aura has excellent latitude coverage and measures ozone daily from the upper troposphere to the lower mesosphere. The new climatology consists of monthly average ozone profiles for ten degree latitude zones covering pressure altitudes from 0 to 65 km. The climatology was formed by combining data from Aura MLS (2004-2010) with data from balloon sondes (1988-2010). Ozone below 8 km (below 12 km at high latitudes) is based on balloons sondes, while ozone above 16 km (21 km at high latitudes) is based on MLS measurements. Sonde and MLS data are blended in the transition region. Ozone accuracy in the upper troposphere is greatly improved because of the near uniform coverage by Aura MLS, while the addition of a large number of balloon sonde measurements improves the accuracy in the lower troposphere, in the tropics and southern hemisphere in particular. The addition of MLS data also improves the accuracy of climatology in the upper stratosphere and lower mesosphere. The revised climatology has been used for the latest reprocessing of SBUV and TOMS satellite ozone data.

  15. Global Electric Circuit Diurnal Variation Derived from Storm Overflight and Satellite Optical Lightning Datasets

    Science.gov (United States)

    Mach, Douglas M.; Blakeslee, R. J.; Bateman, M. J.; Bailey, J. C.

    2011-01-01

    We have combined analyses of over 1000 high altitude aircraft observations of electrified clouds with diurnal lightning statistics from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to produce an estimate of the diurnal variation in the global electric circuit. Using basic assumptions about the mean storm currents as a function of flash rate and location, and the global electric circuit, our estimate of the current in the global electric circuit matches the Carnegie curve diurnal variation 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. Mean contributions to the global electric circuit from land and ocean thunderstorms are 1.1 kA (land) and 0.7 kA (ocean). Contributions to the global electric circuit from ESCs are 0.22 kA for ocean storms and 0.04 kA for land storms. Using our analysis, the mean total conduction current for the global electric circuit is 2.0 kA.

  16. Satellite-derived land surface parameters for mesoscale modelling of the Mexico City basin

    Directory of Open Access Journals (Sweden)

    B. de Foy

    2006-01-01

    Full Text Available Mesoscale meteorological modelling is an important tool to help understand air pollution and heat island effects in urban areas. Accurate wind simulations are difficult to obtain in areas of weak synoptic forcing. Local factors have a dominant role in the circulation and include land surface parameters and their interaction with the atmosphere. This paper examines an episode during the MCMA-2003 field campaign held in the Mexico City Metropolitan Area (MCMA in April of 2003. Because the episode has weak synoptic forcing, there is the potential for the surface heat budget to influence the local meteorology. High resolution satellite observations are used to specify the land use, vegetation fraction, albedo and surface temperature in the MM5 model. Making use of these readily available data leads to improved meteorological simulations in the MCMA, both for the wind circulation patterns and the urban heat island. Replacing values previously obtained from land-use tables with actual measurements removes the number of unknowns in the model and increases the accuracy of the energy budget. In addition to improving the understanding of local meteorology, this sets the stage for the use of advanced urban modules.

  17. Snowmelt on the Greenland Ice Sheet as Derived From Passive Microwave Satellite Data

    Science.gov (United States)

    Abdalati, Waleed; Steffen, Konrad

    1997-01-01

    The melt extent of the snow on the Greenland ice sheet is of considerable importance to the ice sheet's mass and energy balance, as well as Arctic and global climates. By comparing passive microwave satellite data to field observations, variations in melt extent have been detected by establishing melt thresholds in the cross-polarized gradient ratio (XPGR). The XPGR, defined as the normalized difference between the 19-GHz horizontal channel and the 37-GHz vertical channel of the Special Sensor Microwave/Imager (SSM/I), exploits the different effects of snow wetness on different frequencies and polarizations and establishes a distinct melt signal. Using this XPGR melt signal, seasonal and interannual variations in snowmelt extent of the ice sheet are studied. The melt is found to be most extensive on the western side of the ice sheet and peaks in late July. Moreover, there is a notable increasing trend in melt area between the years 1979 and 1991 of 4.4% per year, which came to an abrupt halt in 1992 after the eruption of Mt. Pinatubo. A similar trend is observed in the temperatures at six coastal stations. The relationship between the warming trend and increasing melt trend between 1979 and 1991 suggests that a 1 C temperature rise corresponds to an increase in melt area of 73000 sq km, which in general exceeds one standard deviation of the natural melt area variability.

  18. Systematic Derivation of Static Analyses for Software Product Lines

    DEFF Research Database (Denmark)

    Midtgaard, Jan; Brabrand, Claus; Wasowski, Andrzej

    2014-01-01

    A recent line of work lifts particular verification and analysis methods to Software Product Lines (SPL). In an effort to generalize such case-by-case approaches, we develop a systematic methodology for lifting program analyses to SPLs using abstract interpretation. Abstract interpretation...... for lifting analyses and Galois connections. We prove that for analyses developed using our method, the soundness of lifting follows by construction. Finally, we discuss approximating variability in an analysis and we derive variational data-flow equations for an example analysis, a constant propagation...

  19. NESDIS Blended Rain Rate (RR) Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The blended Rain Rate (RR) product is derived from multiple sensors/satellites. The blended products were merged from polar-orbiting and geostationary satellite...

  20. Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

    Science.gov (United States)

    Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

    2018-04-01

    Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by

  1. Validation of satellite derived LHF using coare_3.0 scheme and time series data over north-east Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Muraleedharan, P.M.; Pankajakshan, T.; Sathe, P.V.

    to the scientific community as it call for near perfect observational platforms and sensors to Page 1 of 10Gayana (Concepción) - VALIDATION OF SATELLITE DERIVED LHF USING C... 8/11/2006http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717...>VALIDATION OF SATELLITE DERIVED LHF USING C... 8/11/2006http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-65382004000300019&lng=... Day and night passes of SSMI (wind speed and columnar water vapor) and TMI (sea surface temperature) data for the period July...

  2. Land-ocean contrast on electrical characteristics of lightning discharge derived from satellite optical measurements

    Science.gov (United States)

    Adachi, T.; Said, R.; Cummer, S. A.; Li, J.; Takahashi, Y.; Hsu, R.; Su, H.; Chen, A. B.; Mende, S. B.; Frey, H. U.

    2010-12-01

    Comparative studies on the electrical properties of oceanic and continental lightning are crucial to elucidate air discharge processes occurring under different conditions. Past studies however have primarily focused on continental lightning because of the limited coverage of ground-based instruments. Recent satellite measurements by FORMOSAT-2/ISUAL provided a new way to survey the global characteristics of lightning and transient luminous events regardless of land and ocean. In this study, we analyze ISUAL/spectrophotometer data to clarify the electrical properties of lightning on a global level. Based on the results obtained by Cummer et al. [2006] and Adachi et al. [2009], the OI-777.4nm emission intensity is used to infer lightning electrical parameters. Results show a clear land-ocean contrast on the parameters of lightning discharge: in oceanic lightning, peak luminosity is 60 % higher and the time scale of return stroke is 30 % shorter. These results suggest higher peak current in oceanic lightning, which is consistent with the fact that elves, EMP-driven phenomena, also tend to occur over the ocean [Chen et al., 2008]. Further analysis of lightning events occurring around the Caribbean Sea shows that the transition-line of lightning electrical properties is precisely located along the coastline. We suggest that the differences in these electrical properties may be due to the boundary conditions (conductivity, surface terrain, etc). In this talk, based on the calibration with NLDN and Duke magnetometer data, current moment change and charge moment change will be globally evaluated using a complete set of the ISUAL-observed lightning events.

  3. A Satellite-Derived Climatological Analysis of Urban Heat Island over Shanghai during 2000–2013

    Directory of Open Access Journals (Sweden)

    Weijiao Huang

    2017-06-01

    Full Text Available The urban heat island is generally conducted based on ground observations of air temperature and remotely sensing of land surface temperature (LST. Satellite remotely sensed LST has the advantages of global coverage and consistent periodicity, which overcomes the weakness of ground observations related to sparse distributions and costs. For human related studies and urban climatology, canopy layer urban heat island (CUHI based on air temperatures is extremely important. This study has employed remote sensing methodology to produce monthly CUHI climatology maps during the period 2000–2013, revealing the spatiotemporal characteristics of daytime and nighttime CUHI during this period of rapid urbanization in Shanghai. Using stepwise linear regression, daytime and nighttime air temperatures at the four overpass times of Terra/Aqua were estimated based on time series of Terra/Aqua-MODIS LST and other auxiliary variables including enhanced vegetation index, normalized difference water index, solar zenith angle and distance to coast. The validation results indicate that the models produced an accuracy of 1.6–2.6 °C RMSE for the four overpass times of Terra/Aqua. The models based on Terra LST showed higher accuracy than those based on Aqua LST, and nighttime air temperature estimation had higher accuracy than daytime. The seasonal analysis shows daytime CUHI is strongest in summer and weakest in winter, while nighttime CUHI is weakest in summer and strongest in autumn. The annual mean daytime CUHI during 2000–2013 is 1.0 and 2.2 °C for Terra and Aqua overpass, respectively. The annual mean nighttime CUHI is about 1.0 °C for both Terra and Aqua overpass. The resultant CUHI climatology maps provide a spatiotemporal quantification of CUHI with emphasis on temperature gradients. This study has provided information of relevance to urban planners and environmental managers for assessing and monitoring urban thermal environments which are constantly

  4. Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

    Science.gov (United States)

    Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

    2016-04-01

    Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

  5. Production and Structural Characterization of Lactobacillus helveticus Derived Biosurfactant

    Science.gov (United States)

    Sharma, Deepansh; Saharan, Baljeet Singh; Chauhan, Nikhil; Bansal, Anshul; Procha, Suresh

    2014-01-01

    A probiotic strain of lactobacilli was isolated from traditional soft Churpi cheese of Yak milk and found positive for biosurfactant production. Lactobacilli reduced the surface tension of phosphate buffer saline (PBS) from 72.0 to 39.5 mNm−1 pH 7.2 and its critical micelle concentration (CMC) was found to be 2.5 mg mL−1. Low cost production of Lactobacilli derived biosurfactant was carried out at lab scale fermenter which yields 0.8 mg mL−1 biosurfactant. The biosurfactant was found least phytotoxic and cytotoxic as compared to the rhamnolipid and sodium dodecyl sulphate (SDS) at different concentration. Structural attributes of biosurfactant were determined by FTIR, NMR (1H and 13C), UPLC-MS, and fatty acid analysis by GCMS which confirmed the presence of glycolipid type of biosurfactant closely similar to xylolipids. Biosurfactant is mainly constituted by lipid and sugar fractions. The present study outcomes provide valuable information on structural characterization of the biosurfactant produced by L. helveticus MRTL91. These findings are encouraging for the application of Lactobacilli derived biosurfactant as nontoxic surface active agents in the emerging field of biomedical applications. PMID:25506070

  6. Evaluation of cloud properties in the NOAA/NCEP global forecast system using multiple satellite products

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Hyelim [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Li, Zhanqing [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Beijing Normal University, State Key Laboratory of Earth Surface Processes and Resource Ecology, GCESS, Beijing (China)

    2012-12-15

    Knowledge of cloud properties and their vertical structure is important for meteorological studies due to their impact on both the Earth's radiation budget and adiabatic heating within the atmosphere. The objective of this study is to evaluate bulk cloud properties and vertical distribution simulated by the US National Oceanic and Atmospheric Administration National Centers for Environmental Prediction Global Forecast System (GFS) using three global satellite products. Cloud variables evaluated include the occurrence and fraction of clouds in up to three layers, cloud optical depth, liquid water path, and ice water path. Cloud vertical structure data are retrieved from both active (CloudSat/CALIPSO) and passive sensors and are subsequently compared with GFS model results. In general, the GFS model captures the spatial patterns of hydrometeors reasonably well and follows the general features seen in satellite measurements, but large discrepancies exist in low-level cloud properties. More boundary layer clouds over the interior continents were generated by the GFS model whereas satellite retrievals showed more low-level clouds over oceans. Although the frequencies of global multi-layer clouds from observations are similar to those from the model, latitudinal variations show discrepancies in terms of structure and pattern. The modeled cloud optical depth over storm track region and subtropical region is less than that from the passive sensor and is overestimated for deep convective clouds. The distributions of ice water path (IWP) agree better with satellite observations than do liquid water path (LWP) distributions. Discrepancies in LWP/IWP distributions between observations and the model are attributed to differences in cloud water mixing ratio and mean relative humidity fields, which are major control variables determining the formation of clouds. (orig.)

  7. Satellite-derived vertical profiles of temperature and dew point for mesoscale weather forecast

    Science.gov (United States)

    Masselink, Thomas; Schluessel, P.

    1995-12-01

    Weather forecast-models need spatially high resolutioned vertical profiles of temperature and dewpoint for their initialisation. These profiles can be supplied by a combination of data from the Tiros-N Operational Vertical Sounder (TOVS) and the imaging Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbiting sate!- lites. In cloudy cases the profiles derived from TOVS data only are of insufficient accuracy. The stanthrd deviations from radiosonde ascents or numerical weather analyses likely exceed 2 K in temperature and 5Kin dewpoint profiles. It will be shown that additional cloud information as retrieved from AVHIRR allows a significant improvement in theaccuracy of vertical profiles. The International TOVS Processing Package (ITPP) is coupled to an algorithm package called AVHRR Processing scheme Over cLouds, Land and Ocean (APOLLO) where parameters like cloud fraction and cloud-top temperature are determined with higher accuracy than obtained from TOVS retrieval alone. Furthermore, a split-window technique is applied to the cloud-free AVHRR imagery in order to derive more accurate surface temperatures than can be obtained from the pure TOVS retrieval. First results of the impact of AVHRR cloud detection on the quality of the profiles are presented. The temperature and humidity profiles of different retrieval approaches are validated against analyses of the European Centre for Medium-Range Weatherforecasts.

  8. Satellite-derived aerosol radiative forcing from the 2004 British Columbia wildfires

    Science.gov (United States)

    Guo, Song; Leighton, H.

    2008-01-01

    The British Columbia wildfires of 2004 was one of the largest wildfire events in the last ten years in Canada. Both the shortwave and longwave smoke aerosol radiative forcing at the top-of-atmosphere (TOA) are investigated using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Clouds and the Earth's Radiant Energy System (CERES) instruments. Relationships between the radiative forcing fluxes (??F) and wildfire aerosol optical thickness (AOT) at 0.55 ??m (??0.55) are deduced for both noontime instantaneous forcing and diurnally averaged forcing. The noontime averaged instantaneous shortwave and longwave smoke aerosol radiative forcing at the TOA are 45.8??27.5 W m-2 and -12.6??6.9 W m-2, respectively for a selected study area between 62??N and 68??N in latitude and 125??W and 145??W in longitude over three mainly clear-sky days (23-25 June). The derived diurnally averaged smoke aerosol shortwave radiative forcing is 19.9??12.1 W m-2 for a mean ??0.55 of 1.88??0.71 over the same time period. The derived ??F-?? relationship can be implemented in the radiation scheme used in regional climate models to assess the effect of wildfire aerosols.

  9. A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data

    Science.gov (United States)

    Pengra, Bruce; Long, Jordan; Dahal, Devendra; Stehman, Stephen V.; Loveland, Thomas R.

    2015-01-01

    The methodology for selection, creation, and application of a global remote sensing validation dataset using high resolution commercial satellite data is presented. High resolution data are obtained for a stratified random sample of 500 primary sampling units (5 km  ×  5 km sample blocks), where the stratification based on Köppen climate classes is used to distribute the sample globally among biomes. The high resolution data are classified to categorical land cover maps using an analyst mediated classification workflow. Our initial application of these data is to evaluate a global 30 m Landsat-derived, continuous field tree cover product. For this application, the categorical reference classification produced at 2 m resolution is converted to percent tree cover per 30 m pixel (secondary sampling unit)for comparison to Landsat-derived estimates of tree cover. We provide example results (based on a subsample of 25 sample blocks in South America) illustrating basic analyses of agreement that can be produced from these reference data. Commercial high resolution data availability and data quality are shown to provide a viable means of validating continuous field tree cover. When completed, the reference classifications for the full sample of 500 blocks will be released for public use.

  10. Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

    Directory of Open Access Journals (Sweden)

    Tao Yu

    2018-02-01

    Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

  11. Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea

    Directory of Open Access Journals (Sweden)

    Shuibo Hu

    2018-03-01

    Full Text Available Ocean colour remote sensing is used as a tool to detect phytoplankton size classes (PSCs. In this study, the Medium Resolution Imaging Spectrometer (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS, and Sea-viewing Wide Field-of-view Sensor (SeaWiFS phytoplankton size classes (PSCs products were compared with in-situ High Performance Liquid Chromatography (HPLC data for the South China Sea (SCS, collected from August 2006 to September 2011. Four algorithms were evaluated to determine their ability to detect three phytoplankton size classes. Chlorophyll-a (Chl-a and absorption spectra of phytoplankton (aph(λ were also measured to help understand PSC’s algorithm performance. Results show that the three abundance-based approaches performed better than the inherent optical property (IOP-based approach in the SCS. The size detection of microplankton and picoplankton was generally better than that of nanoplankton. A three-component model was recommended to produce maps of surface PSCs in the SCS. For the IOP-based approach, satellite retrievals of inherent optical properties and the PSCs algorithm both have impacts on inversion accuracy. However, for abundance-based approaches, the selection of the PSCs algorithm seems to be more critical, owing to low uncertainty in satellite Chl-a input data

  12. Satellite-derived temperature data for monitoring water status in a floodplain forest of the Upper Sabine River, Texas

    Science.gov (United States)

    Lemon, Mary Grace T.; Allen, Scott T.; Edwards, Brandon L.; King, Sammy L.; Keim, Richard F.

    2016-01-01

    Decreased water availability due to hydrologic modifications, groundwater withdrawal, and climate change threaten bottomland hardwood (BLH) forest communities. We used satellite-derived (MODIS) land-surface temperature (LST) data to investigate spatial heterogeneity of canopy temperature (an indicator of plant-water status) in a floodplain forest of the upper Sabine River for 2008–2014. High LST pixels were generally further from the river and at higher topographic locations, indicating lower water-availability. Increasing rainfall-derived soil moisture corresponded with decreased heterogeneity of LST between pixels but there was weaker association between Sabine River stage and heterogeneity. Stronger dependence of LST convergence on rainfall rather than river flow suggests that some regions are less hydrologically connected to the river, and vegetation may rely on local precipitation and other contributions to the riparian aquifer to replenish soil moisture. Observed LST variations associated with hydrology encourage further investigation of the utility of this approach for monitoring forest stress, especially with considerations of climate change and continued river management.

  13. A New ENSO Index Derived from Satellite Measurements of Column Ozone

    Science.gov (United States)

    Ziemke, J. R.; Chandra, S.; Oman, L. D.; Bhartia, P. K.

    2010-01-01

    Column Ozone measured in tropical latitudes from Nimbus 7 total ozone mapping spectrometer (TOMS), Earth Probe TOMS, solar backscatter ultraviolet (SBUV), and Aura ozone monitoring instrument (OMI) are used to derive an El Nino-Southern Oscillation (ENSO) index. This index, which covers a time period from 1979 to the present, is defined as the Ozone ENSO Index (OEI) and is the first developed from atmospheric trace gas measurements. The OEI is constructed by first averaging monthly mean column ozone over two broad regions in the western and eastern Pacific and then taking their difference. This differencing yields a self-calibrating ENSO index which is independent of individual instrument calibration offsets and drifts in measurements over the long record. The combined Aura OMI and MLS ozone data confirm that zonal variability in total column ozone in the tropics caused by ENSO events lies almost entirely in the troposphere. As a result, the OEI can be derived directly from total column ozone instead of tropospheric column ozone. For clear-sky ozone measurements a +1K change in Nino 3.4 index corresponds to +2.9 Dobson Unit (DU) change in the OEI, while a +1 hPa change in SOI coincides with a -1.7DU change in the OEI. For ozone measurements under all cloud conditions these numbers are +2.4DU and -1.4 DU, respectively. As an ENSO index based upon ozone, it is potentially useful in evaluating climate models predicting long term changes in ozone and other trace gases.

  14. Correlation between Satellite-Derived Aerosol Characteristics and Oceanic Dimethylsulfide (DMS)

    Science.gov (United States)

    1988-12-01

    intensity gained by multiple scattering into the beam from all directions and the beam addition term accounting for single scattering events. The physical...the extinction and scattering coefficients are the integracion over radius of the product of the cross sectional area of aerosol particles, the...the same photon more than once is small. Therefore, the multiple interaction term can be neglected and a single scattering approximation is made. The

  15. Nature of the Venus thermosphere derived from satellite drag measurements (solicited paper)

    Science.gov (United States)

    Keating, G.; Theriot, M.; Bougher, S.

    2008-09-01

    From drag measurements obtained by Pioneer Venus and Magellan, the Venus upper atmosphere was discovered to be much colder than Earth's, even though Venus is much closer to the Sun than the Earth. On the dayside, exospheric temperatures are near 300K compared to Earth's of near 1200K [1]. This is thought to result principally from 15 micron excitation of carbon dioxide by atomic oxygen resulting in very strong 15 micron emission to space, cooling off the upper atmosphere [2]. On the nightside the Venus upper atmosphere is near 100K [3], compared to Earth where temperatures are near 900K. The nightside Venus temperatures drop with altitude contrary to a thermosphere where temperatures rise with altitude. As a result, the very cold nightside is called a "cryosphere" rather than a thermosphere. This is the first cryosphere discovered in the solar system [1]. Temperatures sharply drop near the terminator. Apparently, heat is somehow blocked near the terminator from being significantly transported to the nightside [4]. Recently, drag studies were performed on a number of Earth satellites to establish whether the rise of carbon dioxide on Earth was cooling the Earth's thermosphere similar to the dayside of Venus. Keating et al. [5] discovered that a 10 percent drop in density near 350km at solar minimum occurred globally over a period of 20 years with a 10 per cent rise in carbon dioxide. This should result in about a factor of 2 decline in density from 1976 values, by the end of the 21st century brought on by thermospheric cooling. Subsequent studies have confirmed these results. Thus we are beginning to see the cooling of Earth's upper atmosphere apparently from the same process cooling the Venus thermosphere. Fig. 1 VIRA Exospheric Temperatures Atmospheric drag data from the Pioneer Venus Orbiter and Magellan were combined to generate an improved version of the Venus International Reference Atmosphere (VIRA) [6], [7]. A "fountain effect" was discovered where the

  16. Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

    Directory of Open Access Journals (Sweden)

    Shimelis B. Gebere

    2015-09-01

    Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

  17. Hydrological differentiation and spatial distribution of high altitude wetlands in a semi-arid Andean region derived from satellite data

    Science.gov (United States)

    Otto, M.; Scherer, D.; Richters, J.

    2011-05-01

    High Altitude Wetlands of the Andes (HAWA) belong to a unique type of wetland within the semi-arid high Andean region. Knowledge about HAWA has been derived mainly from studies at single sites within different parts of the Andes at only small time scales. On the one hand, HAWA depend on water provided by glacier streams, snow melt or precipitation. On the other hand, they are suspected to influence hydrology through water retention and vegetation growth altering stream flow velocity. We derived HAWA land cover from satellite data at regional scale and analysed changes in connection with precipitation over the last decade. Perennial and temporal HAWA subtypes can be distinguished by seasonal changes of photosynthetically active vegetation (PAV) indicating the perennial or temporal availability of water during the year. HAWA have been delineated within a region of 12 800 km2 situated in the Northwest of Lake Titicaca. The multi-temporal classification method used Normalized Differenced Vegetation Index (NDVI) and Normalized Differenced Infrared Index (NDII) data derived from two Landsat ETM+ scenes at the end of austral winter (September 2000) and at the end of austral summer (May 2001). The mapping result indicates an unexpected high abundance of HAWA covering about 800 km2 of the study region (6 %). Annual HAWA mapping was computed using NDVI 16-day composites of Moderate Resolution Imaging Spectroradiometer (MODIS). Analyses on the relation between HAWA and precipitation was based on monthly precipitation data of the Tropical Rain Measurement Mission (TRMM 3B43) and MODIS Eight Day Maximum Snow Extent data (MOD10A2) from 2000 to 2010. We found HAWA subtype specific dependencies on precipitation conditions. A strong relation exists between perennial HAWA and snow fall (r2: 0.82) in dry austral winter months (June to August) and between temporal HAWA and precipitation (r2: 0.75) during austral summer (March to May). Annual changes in spatial extend of perennial HAWA

  18. Estimates of biomass burning emissions in tropical Asia based on satellite-derived data

    OpenAIRE

    D. Chang; Y. Song

    2009-01-01

    Biomass burning in tropical Asia emits large amounts of trace gases and particulate matter into the atmosphere, which has significant implications for atmospheric chemistry and climatic change. In this study, emissions from open biomass burning over tropical Asia were evaluated during seven fire years from 2000 to 2006 (1 March 2000–31 February 2007). The size of the burned areas was estimated from newly published 1-km L3JRC and 500-m MODIS burned area products (MCD45A1). Available fuel loads...

  19. Large Scale Production of Stem Cells and Their Derivatives

    Science.gov (United States)

    Zweigerdt, Robert

    Stem cells have been envisioned to become an unlimited cell source for regenerative medicine. Notably, the interest in stem cells lies beyond direct therapeutic applications. They might also provide a previously unavailable source of valuable human cell types for screening platforms, which might facilitate the development of more efficient and safer drugs. The heterogeneity of stem cell types as well as the numerous areas of application suggests that differential processes are mandatory for their in vitro culture. Many of the envisioned applications would require the production of a high number of stem cells and their derivatives in scalable, well-defined and potentially clinical compliant manner under current good manufacturing practice (cGMP). In this review we provide an overview on recent strategies to develop bioprocesses for the expansion, differentiation and enrichment of stem cells and their progenies, presenting examples for adult and embryonic stem cells alike.

  20. Naturally Efficient Emitters: Luminescent Organometallic Complexes Derived from Natural Products

    Science.gov (United States)

    Zhang, Wen-Hua; Young, David J.

    2013-08-01

    Naturally occurring molecules offer intricate structures and functionality that are the basis of modern medicinal chemistry, but are under-represented in materials science. Herein, we review recent literature describing the use of abundant and relatively inexpensive, natural products for the synthesis of ligands for luminescent organometallic complexes used for organic light emitting diodes (OLEDs) and related technologies. These ligands are prepared from the renewable starting materials caffeine, camphor, pinene and cinchonine and, with the exception of caffeine, impart performance improvements to the emissive metal complexes and resulting OLED devices, with emission wavelengths that span the visible spectrum from blue to red. The advantages of these biologically-derived molecules include improved solution processibility and phase homogeneity, brighter luminescence, higher quantum efficiencies and lower turn-on voltages. While nature has evolved these carbon-skeletons for specific purposes, they also offer some intriguing benefits in materials science and technology.

  1. Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data

    NARCIS (Netherlands)

    de Hoogh, Kees; Gulliver, John; Donkelaar, Aaron van; Martin, Randall V; Marshall, Julian D; Bechle, Matthew J; Cesaroni, Giulia; Pradas, Marta Cirach; Dedele, Audrius; Eeftens, Marloes|info:eu-repo/dai/nl/315028300; Forsberg, Bertil; Galassi, Claudia; Heinrich, Joachim; Hoffmann, Barbara; Jacquemin, Bénédicte; Katsouyanni, Klea; Korek, Michal; Künzli, Nino; Lindley, Sarah J; Lepeule, Johanna; Meleux, Frederik; de Nazelle, Audrey; Nieuwenhuijsen, Mark; Nystad, Wenche; Raaschou-Nielsen, Ole; Peters, Annette; Peuch, Vincent-Henri; Rouil, Laurence; Udvardy, Orsolya; Slama, Rémy; Stempfelet, Morgane; Stephanou, Euripides G; Tsai, Ming Y; Yli-Tuomi, Tarja; Weinmayr, Gudrun; Brunekreef, Bert|info:eu-repo/dai/nl/067548180; Vienneau, Danielle; Hoek, Gerard|info:eu-repo/dai/nl/069553475

    2016-01-01

    Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models,

  2. On the use of satellite-derived CH4 : CO2 columns in a joint inversion of CH4 and CO2 fluxes

    NARCIS (Netherlands)

    Pandey, S.

    2015-01-01

    We present a method for assimilating total column CH4 : CO2 ratio measurements from satellites for inverse modeling of CH4 and CO2 fluxes using the variational approach. Unlike conventional approaches, in which retrieved CH4 : CO2 are multiplied by model-derived total column CO2 and only the

  3. Catalytic Production of Ethanol from Biomass-Derived Synthesis Gas

    Energy Technology Data Exchange (ETDEWEB)

    Trewyn, Brian G. [Colorado School of Mines, Golden, CO (United States); Smith, Ryan G. [Iowa State Univ., Ames, IA (United States)

    2016-06-01

    Heterogeneous catalysts have been developed for the conversion of biomass-derived synthetic gas (syngas) to ethanol. The objectives of this project were to develop a clean synthesis gas from biomass and develop robust catalysts with high selectivity and lifetime for C2 oxygenate production from biomass-derived syngas and surrogate syngas. During the timeframe for this project, we have made research progress on the four tasks: (1) Produce clean bio-oil generated from biomass, such as corn stover or switchgrass, by using fast pyrolysis system, (2) Produce clean, high pressure synthetic gas (syngas: carbon monoxide, CO, and hydrogen, H2) from bio-oil generated from biomass by gasification, (3) Develop and characterize mesoporous mixed oxide-supported metal catalysts for the selective production of ethanol and other alcohols, such as butanol, from synthesis gas, and (4) Design and build a laboratory scale synthesis gas to ethanol reactor system evaluation of the process. In this final report, detailed explanations of the research challenges associated with this project are given. Progress of the syngas production from various biomass feedstocks and catalyst synthesis for upgrading the syngas to C2-oxygenates is included. Reaction properties of the catalyst systems under different reaction conditions and different reactor set-ups are also presented and discussed. Specifically, the development and application of mesoporous silica and mesoporous carbon supports with rhodium nanoparticle catalysts and rhodium nanoparticle with manganese catalysts are described along with the significant material characterizations we completed. In addition to the synthesis and characterization, we described the activity and selectivity of catalysts in our micro-tubular reactor (small scale) and fixed bed reactor (larger scale). After years of hard work, we are proud of the work done on this project, and do believe that this work will provide a solid

  4. Satellite microwave remote sensing of North Eurasian inundation dynamics: development of coarse-resolution products and comparison with high-resolution synthetic aperture radar data

    International Nuclear Information System (INIS)

    Schroeder, R; Rawlins, M A; McDonald, K C; Podest, E; Zimmermann, R; Kueppers, M

    2010-01-01

    Wetlands are not only primary producers of atmospheric greenhouse gases but also possess unique features that are favourable for application of satellite microwave remote sensing to monitoring their status and trend. In this study we apply combined passive and active microwave remote sensing data sets from the NASA sensors AMSR-E and QuikSCAT to map surface water dynamics over Northern Eurasia. We demonstrate our method on the evolution of large wetland complexes for two consecutive years from January 2006 to December 2007. We apply river discharge measurements from the Ob River along with land surface runoff simulations derived from the Pan-Arctic Water Balance Model during and after snowmelt in 2006 and 2007 to interpret the abundance of widespread flooding along the River Ob in early summer of 2007 observed in the remote sensing products. The coarse-resolution, 25 km, surface water product is compared to a high-resolution, 30 m, inundation map derived from ALOS PALSAR (Advanced Land Observation Satellite phased array L-band synthetic aperture radar) imagery acquired for 11 July 2006, and extending along a transect in the central Western Siberian Plain. We found that the surface water fraction derived from the combined AMSR-E/QuikSCAT data sets closely tracks the inundation mapped using higher-resolution ALOS PALSAR data.

  5. Satellite Derived Water Quality Observations Are Related to River Discharge and Nitrogen Loads in Pensacola Bay, Florida

    Directory of Open Access Journals (Sweden)

    John C. Lehrter

    2017-09-01

    Full Text Available Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011 in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging Spectrometer (MERIS and used to calculate monthly and annual estuarine time-series of chlorophyll a (Chla, colored dissolved organic matter (CDOM, and total suspended sediments (TSS. Monthly MERIS Chla varied from 2.0 mg m−3 in the lower region of the bay to 17.2 mg m−3 in the upper bay. MERIS CDOM and TSS exhibited similar patterns with ranges of 0.51–2.67 (m−1 and 0.11–8.9 (g m−3. Variations in the MERIS-derived monthly and annual Chla, CDOM, and TSS time-series were significantly related to monthly and annual river discharge and loads of nitrogen, organic carbon, and suspended sediments from the Escambia and Yellow rivers. Multiple regression models based on river loads (independent variables and MERIS Chla, CDOM, or TSS (dependent variables explained significant fractions of the variability (up to 62% at monthly and annual scales. The most significant independent variables in the regressions were river nitrogen loads, which were associated with increased MERIS Chla, CDOM, and TSS concentrations, and river suspended sediment loads, which were associated with decreased concentrations. In contrast, MERIS water quality variations were not significantly related to river total phosphorus loads. The spatially synoptic, nine-year satellite record expanded upon the spatial extent of past field studies to reveal previously unseen system-wide responses to river discharge and loading variation. The results indicated that variations in Pensacola Bay Chla

  6. Catalytic amino acid production from biomass-derived intermediates

    KAUST Repository

    Deng, Weiping

    2018-04-30

    Amino acids are the building blocks for protein biosynthesis and find use in myriad industrial applications including in food for humans, in animal feed, and as precursors for bio-based plastics, among others. However, the development of efficient chemical methods to convert abundant and renewable feedstocks into amino acids has been largely unsuccessful to date. To that end, here we report a heterogeneous catalyst that directly transforms lignocellulosic biomass-derived α-hydroxyl acids into α-amino acids, including alanine, leucine, valine, aspartic acid, and phenylalanine in high yields. The reaction follows a dehydrogenation-reductive amination pathway, with dehydrogenation as the rate-determining step. Ruthenium nanoparticles supported on carbon nanotubes (Ru/CNT) exhibit exceptional efficiency compared with catalysts based on other metals, due to the unique, reversible enhancement effect of NH3 on Ru in dehydrogenation. Based on the catalytic system, a two-step chemical process was designed to convert glucose into alanine in 43% yield, comparable with the well-established microbial cultivation process, and therefore, the present strategy enables a route for the production of amino acids from renewable feedstocks. Moreover, a conceptual process design employing membrane distillation to facilitate product purification is proposed and validated. Overall, this study offers a rapid and potentially more efficient chemical method to produce amino acids from woody biomass components.

  7. Production, quality and quality assurance of Refuse Derived Fuels (RDFs).

    Science.gov (United States)

    Sarc, R; Lorber, K E

    2013-09-01

    This contribution describes characterization, classification, production, application and quality assurance of Refuse Derived Fuels (RDFs) that are increasingly used in a wide range of co-incineration plants. It is shown in this paper, that the fuel-parameter, i.e. net calorific value [MJ/kg(OS)], particle size d(90) or d(95) [mm], impurities [w%], chlorine content [w%], sulfur content [w%], fluorine content [w%], ash content [w%], moisture [w%] and heavy metals content [mg/kg(DM)], can be preferentially used for the classification of different types of RDF applied for co-incineration and substitution of fossil-fuel in different industial sectors. Describing the external production of RDF by processing and confectioning of wastes as well as internal processing of waste at the incineration plant, a case study is reported on the application of RDF made out of different household waste fractions in a 120,000t/yr Waste to Energy (WtE) circulating fluidized bed (CFB) incinerator. For that purpose, delivered wastes, as well as incinerator feedstock material (i.e. after internal waste processing) are extensively investigated. Starting with elaboration of sampling plan in accordance with the relevant guidelines and standards, waste from different suppliers was sampled. Moreover, manual sorting analyses and chemical analyses were carried out. Finally, results of investigations are presented and discussed in the paper. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. 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.

  9. Trend shifts in satellite-derived vegetation growth in Central Eurasia, 1982-2013.

    Science.gov (United States)

    Xu, Hao-Jie; Wang, Xin-Ping; Yang, Tai-Bao

    2017-02-01

    Central Eurasian vegetation is critical for the regional ecological security and the global carbon cycle. However, climatic impacts on vegetation growth in Central Eurasia are uncertain. The reason for this uncertainty lies in the fact that the response of vegetation to climate change showed nonlinearity, seasonality and differences among plant functional types. Based on remotely sensed vegetation index and in-situ meteorological data for the years 1982-2013, in conjunction with the latest land cover type product, we analyzed how vegetation growth trend varied across different seasons and evaluated vegetation response to climate variables at regional, biome and pixel scales. We found a persistent increase in the growing season NDVI over Central Eurasia during 1982-1994, whereas this greening trend has stalled since the mid-1990s in response to increased water deficit. The stalled trend in the growing season NDVI was largely attributed by summer and autumn NDVI changes. Enhanced spring vegetation growth after 2002 was caused by rapid spring warming. The response of vegetation to climatic factors varied in different seasons. Precipitation was the main climate driver for the growing season and summer vegetation growth. Changes in temperature and precipitation during winter and spring controlled the spring vegetation growth. Autumn vegetation growth was mainly dependent on the vegetation growth in summer. We found diverse responses of different vegetation types to climate drivers in Central Eurasia. Forests were more responsive to temperature than to precipitation. Grassland and desert vegetation responded more strongly to precipitation than to temperature in summer but more strongly to temperature than to precipitation in spring. In addition, the growth of desert vegetation was more dependent on winter precipitation than that of grasslands. This study has important implications for improving the performance of terrestrial ecosystem models to predict future vegetation

  10. Improving User Access to the Integrated Multi-Satellite Retrievals for GPM (IMERG) Products

    Science.gov (United States)

    Huffman, George; Bolvin, David; Nelkin, Eric; Kidd, Christopher

    2016-04-01

    The U.S. Global Precipitation Measurement mission (GPM) team has developed the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm to take advantage of the international constellation of precipitation-relevant satellites and the Global Precipitation Climatology Centre surface precipitation gauge analysis. The goal is to provide a long record of homogeneous, high-resolution quasi-global estimates of precipitation. While expert scientific researchers are major users of the IMERG products, it is clear that many other user communities and disciplines also desire access to the data for wide-ranging applications. Lessons learned during the Tropical Rainfall Measuring Mission, the predecessor to GPM, led to some basic design choices that provided the framework for supporting multiple user bases. For example, two near-real-time "runs" are computed, the Early and Late (currently 5 and 15 hours after observation time, respectively), then the Final Run about 3 months later. The datasets contain multiple fields that provide insight into the computation of the complete precipitation data field, as well as diagnostic (currently) estimates of the precipitation's phase. In parallel with this, the archive sites are working to provide the IMERG data in a variety of formats, and with subsetting and simple interactive analysis to make the data more easily available to non-expert users. The various options for accessing the data are summarized under the pmm.nasa.gov data access page. The talk will end by considering the feasibility of major user requests, including polar coverage, a simplified Data Quality Index, and reduced data latency for the Early Run. In brief, the first two are challenging, but under the team's control. The last requires significant action by some of the satellite data providers.

  11. A review of the PERSIANN family global satellite precipitation data products

    Science.gov (United States)

    Nguyen, P.; Ombadi, M.; Ashouri, H.; Thorstensen, A.; Hsu, K. L.; Braithwaite, D.; Sorooshian, S.; William, L.

    2017-12-01

    Precipitation is an integral part of the hydrologic cycle and plays an important role in the water and energy balance of the Earth. Careful and consistent observation of precipitation is important for several reasons. Over the last two decades, the PERSIANN system of precipitation products have been developed at the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine in collaboration with NASA, NOAA and the UNESCO G-WADI program. The PERSIANN family includes three main satellite-based precipitation estimation products namely PERSIANN, PERSIANN-CCS, and PERSIANN-CDR. They are accessible through several web-based interfaces maintained by CHRS to serve the needs of researchers, professionals and general public. These interfaces are CHRS iRain, Data Portal and RainSphere, which can be accessed at http://irain.eng.uci.edu, http://chrsdata.eng.uci.edu, and http://rainsphere.eng.uci.edu respectively and can be used for visualization, analysis or download of the data. The main objective of this presentation is to provide a concise and clear summary of the similarities and differences between the three products in terms of attributes and algorithm structure. Moreover, the presentation aims to provide an evaluation of the performance of the products over the Contiguous United States (CONUS) using Climate Prediction Center (CPC) precipitation dataset as a baseline of comparison. Also, an assessment of the behavior of PERSIANN family products over the globe (60°S - 60°N) is performed.

  12. LAI, FAPAR and FCOVER products derived from AVHRR long time series: principles and evaluation

    Science.gov (United States)

    Verger, A.; Baret, F.; Weiss, M.; Lacaze, R.; Makhmara, H.; Pacholczyk, P.; Smets, B.; Kandasamy, S.; Vermote, E.

    2012-04-01

    Continuous and long term global monitoring of the terrestrial biosphere has draught an intense interest in the recent years in the context of climate and global change. Developing methodologies for generating historical data records from data collected with different satellite sensors over the past three decades by taking benefits from the improvements identified in the processing of the new generation sensors is a new central issue in remote sensing community. In this context, the Bio-geophysical Parameters (BioPar) service within Geoland2 project (http://www.geoland2.eu) aims at developing pre-operational infrastructures for providing global land products both in near real time and off-line mode with long time series. In this contribution, we describe the principles of the GEOLAND algorithm for generating long term datasets of three key biophysical variables, leaf area index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) and cover fraction (FCOVER), that play a key role in several processes, including photosynthesis, respiration and transpiration. LAI, FAPAR and FCOVER are produced globally from AVHRR Long Term Data Record (LTDR) for the 1981-2000 period at 0.05° spatial resolution and 10 days temporal sampling frequency. The proposed algorithm aims to ensure robustness of the derived long time series and consistency with the ones developed in the recent years, and particularly with GEOLAND products derived from VEGETATION sensor. The approach is based on the capacity of neural networks to learn a particular biophysical product (GEOLAND) from reflectances from another sensor (AVHRR normalized reflectances in the red and near infrared bands). Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated. Prior information based on the climatology is used to get more robust estimates. A specific gap filing and smoothing procedure was applied to generate continuous and smooth time series of decadal

  13. Producing a satellite-derived map and modelling Spartina alterniflora expansion for Willapa Bay in Washington State

    Science.gov (United States)

    Berlin, Cynthia Jane

    1998-12-01

    This research addresses the identification of the areal extent of the intertidal wetlands of Willapa Bay, Washington, and the evaluation of the potential for exotic Spartina alterniflora (smooth cordgrass) expansion in the bay using a spatial geographic approach. It is hoped that the results will address not only the management needs of the study area but provide a research design that may be applied to studies of other coastal wetlands. Four satellite images, three Landsat Multi-Spectral (MSS) and one Thematic Mapper (TM), are used to derive a map showing areas of water, low, middle and high intertidal, and upland. Two multi-date remote sensing mapping techniques are assessed: a supervised classification using density-slicing and an unsupervised classification using an ISODATA algorithm. Statistical comparisons are made between the resultant derived maps and the U.S.G.S. topographic maps for the Willapa Bay area. The potential for Spartina expansion in the bay is assessed using a sigmoidal (logistic) growth model and a spatial modelling procedure for four possible growth scenarios: without management controls (Business-as-Usual), with moderate management controls (e.g. harvesting to eliminate seed setting), under a hypothetical increase in the growth rate that may reflect favorable environmental changes, and under a hypothetical decrease in the growth rate that may reflect aggressive management controls. Comparisons for the statistics of the two mapping techniques suggest that although the unsupervised classification method performed satisfactorily, the supervised classification (density-slicing) method provided more satisfactory results. Results from the modelling of potential Spartina expansion suggest that Spartina expansion will proceed rapidly for the Business-as-Usual and hypothetical increase in the growth rate scenario, and at a slower rate for the elimination of seed setting and hypothetical decrease in the growth rate scenarios, until all potential

  14. 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.

  15. 4SM: A Novel Self-Calibrated Algebraic Ratio Method for Satellite-Derived Bathymetry and Water Column Correction.

    Science.gov (United States)

    Morel, Yann G; Favoretto, Fabio

    2017-07-21

    All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions; (ii) in order to specify and operate the simplified radiative transfer equation (RTE); (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need for (i) formal atmospheric correction; (ii) conversion of relative radiance into calibrated reflectance; or (iii) existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a "near-nadir" view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

  16. Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements

    Science.gov (United States)

    Ocko, Ilissa B.; Ginoux, Paul A.

    2017-04-01

    Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud-Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.

  17. Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

    Directory of Open Access Journals (Sweden)

    MARIA IOANA VLAD

    2011-01-01

    Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

  18. A cloud-ozone data product from Aura OMI and MLS satellite measurements

    Directory of Open Access Journals (Sweden)

    J. R. Ziemke

    2017-11-01

    Full Text Available Ozone within deep convective clouds is controlled by several factors involving photochemical reactions and transport. Gas-phase photochemical reactions and heterogeneous surface chemical reactions involving ice, water particles, and aerosols inside the clouds all contribute to the distribution and net production and loss of ozone. Ozone in clouds is also dependent on convective transport that carries low-troposphere/boundary-layer ozone and ozone precursors upward into the clouds. Characterizing ozone in thick clouds is an important step for quantifying relationships of ozone with tropospheric H2O, OH production, and cloud microphysics/transport properties. Although measuring ozone in deep convective clouds from either aircraft or balloon ozonesondes is largely impossible due to extreme meteorological conditions associated with these clouds, it is possible to estimate ozone in thick clouds using backscattered solar UV radiation measured by satellite instruments. Our study combines Aura Ozone Monitoring Instrument (OMI and Microwave Limb Sounder (MLS satellite measurements to generate a new research product of monthly-mean ozone concentrations in deep convective clouds between 30° S and 30° N for October 2004–April 2016. These measurements represent mean ozone concentration primarily in the upper levels of thick clouds and reveal key features of cloud ozone including: persistent low ozone concentrations in the tropical Pacific of  ∼ 10 ppbv or less; concentrations of up to 60 pphv or greater over landmass regions of South America, southern Africa, Australia, and India/east Asia; connections with tropical ENSO events; and intraseasonal/Madden–Julian oscillation variability. Analysis of OMI aerosol measurements suggests a cause and effect relation between boundary-layer pollution and elevated ozone inside thick clouds over landmass regions including southern Africa and India/east Asia.

  19. CALIBRATION/VALIDATION OF LANDSAT-DERIVED OCEAN COLOUR PRODUCTS IN BOSTON HARBOUR

    Directory of Open Access Journals (Sweden)

    N. Pahlevan

    2016-06-01

    Full Text Available The Landsat data archive provides a unique opportunity to investigate the long-term evolution of coastal ecosystems at fine spatial scales that cannot be resolved by ocean colour (OC satellite sensors. Recognizing Landsat’s limitations in applications over coastal waters, we have launched a series of field campaigns in Boston Harbor and Massachusetts Bay (MA, USA to validate OC products derived from Landsat-8. We will provide a preliminary demonstration on the calibration/validation of the existing OC algorithms (atmospheric correction and in-water optical properties to enhance monitoring efforts in Boston Harbor. To do so, Landsat optical images were first compared against ocean colour products over high-latitude regions. The in situ cruise data, including optical data (remote sensing reflectance and water samples were analyzed to obtain insights into the optical and biogeochemical properties of near-surface waters. Along with the cruise data, three buoys were deployed in three locations across the Harbor to complement our database of concentrations of chlorophyll a, total suspended solids (TSS, and absorption of colour dissolved organic matter (CDOM. The data collected during the first year of the project are used to develop and/or tune OC algorithms. The data will be combined with historic field data to map in-water constituents back to the early 1990’s. This paper presents preliminary analysis of some of the data collected under Landsat-8 overpasses.

  20. Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

    Directory of Open Access Journals (Sweden)

    G. T. Ayehu

    2018-04-01

    Full Text Available Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor ground observations or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3 and the African Rainfall Climatology (ARC 2 products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD  =  0.99, 1.00 and measure of volumetric rainfall (VHI  =  1.00, 1.00, the highest correlation coefficients (r =  0.81, 0.88, better bias values (0.96, 0.96, and the lowest RMSE (28.45 mm dekad−1, 59.03 mm month−1 than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale, although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance

  1. Determining Optimal New Generation Satellite Derived Metrics for Accurate C3 and C4 Grass Species Aboveground Biomass Estimation in South Africa

    Directory of Open Access Journals (Sweden)

    Cletah Shoko

    2018-04-01

    Full Text Available While satellite data has proved to be a powerful tool in estimating C3 and C4 grass species Aboveground Biomass (AGB, finding an appropriate sensor that can accurately characterize the inherent variations remains a challenge. This limitation has hampered the remote sensing community from continuously and precisely monitoring their productivity. This study assessed the potential of a Sentinel 2 MultiSpectral Instrument, Landsat 8 Operational Land Imager, and WorldView-2 sensors, with improved earth imaging characteristics, in estimating C3 and C4 grasses AGB in the Cathedral Peak, South Africa. Overall, all sensors have shown considerable potential in estimating species AGB; with the use of different combinations of the derived spectral bands and vegetation indices producing better accuracies. However, WorldView-2 derived variables yielded better predictive accuracies (R2 ranging between 0.71 and 0.83; RMSEs between 6.92% and 9.84%, followed by Sentinel 2, with R2 between 0.60 and 0.79; and an RMSE 7.66% and 14.66%. Comparatively, Landsat 8 yielded weaker estimates, with R2 ranging between 0.52 and 0.71 and high RMSEs ranging between 9.07% and 19.88%. In addition, spectral bands located within the red edge (e.g., centered at 0.705 and 0.745 µm for Sentinel 2, SWIR, and NIR, as well as the derived indices, were found to be very important in predicting C3 and C4 AGB from the three sensors. The competence of these bands, especially of the free-available Landsat 8 and Sentinel 2 dataset, was also confirmed from the fusion of the datasets. Most importantly, the three sensors managed to capture and show the spatial variations in AGB for the target C3 and C4 grassland area. This work therefore provides a new horizon and a fundamental step towards C3 and C4 grass productivity monitoring for carbon accounting, forage mapping, and modelling the influence of environmental changes on their productivity.

  2. Satellite observed salinity distributions at high latitudes in the Northern Hemisphere: A comparison of four products

    Science.gov (United States)

    Garcia-Eidell, Cynthia; Comiso, Josefino C.; Dinnat, Emmanuel; Brucker, Ludovic

    2017-09-01

    Global surface ocean salinity measurements have been available since the launch of SMOS in 2009 and coverage was further enhanced with the launch of Aquarius in 2011. In the polar regions where spatial and temporal changes in sea surface salinity (SSS) are deemed important, the data have not been as robustly validated because of the paucity of in situ measurements. This study presents a comparison of four SSS products in the ice-free Arctic region, three using Aquarius data and one using SMOS data. The accuracy of each product is assessed through comparative analysis with ship and other in situ measurements. Results indicate RMS errors ranging between 0.33 and 0.89 psu. Overall, the four products show generally good consistency in spatial distribution with the Atlantic side being more saline than the Pacific side. A good agreement between the ship and satellite measurements was also observed in the low salinity regions in the Arctic Ocean, where SSS in situ measurements are usually sparse, at the end of summer melt seasons. Some discrepancies including biases of about 1 psu between the products in spatial and temporal distribution are observed. These are due in part to differences in retrieval techniques, geophysical filtering, and sea ice and land masks. The monthly SSS retrievals in the Arctic from 2011 to 2015 showed variations (within ˜1 psu) consistent with effects of sea ice seasonal cycles. This study indicates that spaceborne observations capture the seasonality and interannual variability of SSS in the Arctic with reasonably good accuracy.

  3. 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

  4. Hydrological differentiation and spatial distribution of high altitude wetlands in a semi-arid Andean region derived from satellite data

    Directory of Open Access Journals (Sweden)

    M. Otto

    2011-05-01

    Full Text Available High Altitude Wetlands of the Andes (HAWA belong to a unique type of wetland within the semi-arid high Andean region. Knowledge about HAWA has been derived mainly from studies at single sites within different parts of the Andes at only small time scales. On the one hand, HAWA depend on water provided by glacier streams, snow melt or precipitation. On the other hand, they are suspected to influence hydrology through water retention and vegetation growth altering stream flow velocity. We derived HAWA land cover from satellite data at regional scale and analysed changes in connection with precipitation over the last decade. Perennial and temporal HAWA subtypes can be distinguished by seasonal changes of photosynthetically active vegetation (PAV indicating the perennial or temporal availability of water during the year. HAWA have been delineated within a region of 12 800 km2 situated in the Northwest of Lake Titicaca. The multi-temporal classification method used Normalized Differenced Vegetation Index (NDVI and Normalized Differenced Infrared Index (NDII data derived from two Landsat ETM+ scenes at the end of austral winter (September 2000 and at the end of austral summer (May 2001. The mapping result indicates an unexpected high abundance of HAWA covering about 800 km2 of the study region (6 %. Annual HAWA mapping was computed using NDVI 16-day composites of Moderate Resolution Imaging Spectroradiometer (MODIS. Analyses on the relation between HAWA and precipitation was based on monthly precipitation data of the Tropical Rain Measurement Mission (TRMM 3B43 and MODIS Eight Day Maximum Snow Extent data (MOD10A2 from 2000 to 2010. We found HAWA subtype specific dependencies on precipitation conditions. A strong relation exists between perennial HAWA and snow fall (r2: 0.82 in dry austral winter months (June to August and between temporal HAWA and precipitation (r2: 0.75 during austral summer

  5. PROCEDURES FOR ACCURATE PRODUCTION OF COLOR IMAGES FROM SATELLITE OR AIRCRAFT MULTISPECTRAL DIGITAL DATA.

    Science.gov (United States)

    Duval, Joseph S.

    1985-01-01

    Because the display and interpretation of satellite and aircraft remote-sensing data make extensive use of color film products, accurate reproduction of the color images is important. To achieve accurate color reproduction, the exposure and chemical processing of the film must be monitored and controlled. By using a combination of sensitometry, densitometry, and transfer functions that control film response curves, all of the different steps in the making of film images can be monitored and controlled. Because a sensitometer produces a calibrated exposure, the resulting step wedge can be used to monitor the chemical processing of the film. Step wedges put on film by image recording machines provide a means of monitoring the film exposure and color balance of the machines.

  6. Towards a Quantitative Use of Satellite Remote Sensing in Crop Growth Models for Large Scale Agricultural Production Estimate (Invited)

    Science.gov (United States)

    Defourny, P.

    2013-12-01

    The development of better agricultural monitoring capabilities is clearly considered as a critical step for strengthening food production information and market transparency thanks to timely information about crop status, crop area and yield forecasts. The documentation of global production will contribute to tackle price volatility by allowing local, national and international operators to make decisions and anticipate market trends with reduced uncertainty. Several operational agricultural monitoring systems are currently operating at national and international scales. Most are based on the methods derived from the pioneering experiences completed some decades ago, and use remote sensing to qualitatively compare one year to the others to estimate the risks of deviation from a normal year. The GEO Agricultural Monitoring Community of Practice described the current monitoring capabilities at the national and global levels. An overall diagram summarized the diverse relationships between satellite EO and agriculture information. There is now a large gap between the current operational large scale systems and the scientific state of the art in crop remote sensing, probably because the latter mainly focused on local studies. The poor availability of suitable in-situ and satellite data over extended areas hampers large scale demonstrations preventing the much needed up scaling research effort. For the cropland extent, this paper reports a recent research achievement using the full ENVISAT MERIS 300 m archive in the context of the ESA Climate Change Initiative. A flexible combination of classification methods depending to the region of the world allows mapping the land cover as well as the global croplands at 300 m for the period 2008 2012. This wall to wall product is then compared with regards to the FP 7-Geoland 2 results obtained using as Landsat-based sampling strategy over the IGADD countries. On the other hand, the vegetation indices and the biophysical variables

  7. IR-BASED SATELLITE PRODUCTS FOR THE MONITORING OF ATMOSPHERIC WATER VAPOR OVER THE BLACK SEA

    Directory of Open Access Journals (Sweden)

    VELEA LILIANA

    2016-03-01

    Full Text Available The amount of precipitable water (TPW in the atmospheric column is one of the important information used weather forecasting. Some of the studies involving the use of TPW relate to issues like lightning warning system in airports, tornadic events, data assimilation in numerical weather prediction models for short-range forecast, TPW associated with intense rain episodes. Most of the available studies on TPW focus on properties and products at global scale, with the drawback that regional characteristics – due to local processes acting as modulating factors - may be lost. For the Black Sea area, studies on the climatological features of atmospheric moisture are available from sparse or not readily available observational databases or from global reanalysis. These studies show that, although a basin of relatively small dimensions, the Black Sea presents features that may significantly impact on the atmospheric circulation and its general characteristics. Satellite observations provide new opportunities for extending the knowledge on this area and for monitoring atmospheric properties at various scales. In particular, observations in infrared (IR spectrum are suitable for studies on small-scale basins, due to the finer spatial sampling and reliable information in the coastal areas. As a first step toward the characterization of atmospheric moisture over the Black Sea from satellite-based information, we investigate three datasets of IR-based products which contain information on the total amount of moisture and on its vertical distribution, available in the area of interest. The aim is to provide a comparison of these data with regard to main climatological features of moisture in this area and to highlight particular strengths and limits of each of them, which may be helpful in the choice of the most suitable dataset for a certain application.

  8. Satellite-derived NO

    NARCIS (Netherlands)

    Ding, J.

    2018-01-01

    Nitrogen oxides (NOx) are important air pollutants and play a crucial role in climate change. NOx emissions are important for chemical transport models to simulate and forecast air quality. Up-to-date emission information also helps policymakers to mitigate air pollution. In this thesis, we have

  9. A simple model for yield prediction of rice based on vegetation index derived from satellite and AMeDAS data during ripening period

    International Nuclear Information System (INIS)

    Wakiyama, Y.; Inoue, K.; Nakazono, K.

    2003-01-01

    The present study was conducted to show a simple model for rice yield predicting by using a vegetation index (NDVI) derived from satellite and meteorological data. In a field experiment, the relationship between the vegetation index and radiation absorbed by the rice canopy was investigated from transplanting to maturity. Their correlation held. This result revealed that the vegetation index could be used as a measure of absorptance of solar radiation by rice canopy. NDVI multiplied by solar radiation (SR) every day was accumulated (Σ(SR·NDVI)) from the field experiment. Σ(SR·NDVI) was plotted against above ground dry matter. It was obvious that they had a strong relationship. Rice yield largely depends on solar radiation and air temperature during the ripening period. Air temperature affects dry matter production. Relationships between Y SR -1 (Y: rice yield, SR: solar radiation) and mean air temperature were investigated from meteorological data and statistical data on rice yield. There was an optimum air temperature, 21.3°C, for ripening. When it was near 21.3°C in the ripening period, the rice yield was higher. We proposed a simple model for yield prediction of rice based on these results. The model is composed with SR·NDVI and the optimum air temperature. Vegetation index was derived from 3 years, LANDSAT TM data in Toyama, Ishikawa, Fukui and Nagano prefectures at heading. The meteorological data was used from AMeDAS data. The model was described as follows: Y = 0.728 SR·NDVI−2.04(T−21.3) 2 + 282 (r 2 = 0.65, n = 43) where Y is rice yield (kg 10a -1 ), SR is solar radiation (MJ m -2 ) during the ripening period (from 10 days before heading to 30 days after heading), T is mean air temperature (°C) during the ripening period. RMSE was 33.7kg 10a -1 . The model revealed good precision. (author)

  10. Combined Aircraft and Satellite-Derived Storm Electric Current and Lightning Rates Measurements and Implications for the Global Electric Circuit

    Science.gov (United States)

    Mach, Douglas M.; Blakeslee, Richard J.; Bateman, Monte G.

    2010-01-01

    Using rotating vane electric field mills and Gerdien capacitors, we measured the electric field profile and conductivity during 850 overflights of electrified shower clouds and thunderstorms 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, with and without lightning, and with positive and negative fields above the storms. The measurements were made with the NASA ER-2 and the Altus-II high altitude aircrafts. Peak electric fields, with lightning transients removed, ranged from -1.0 kV/m to 16 kV/m, with a mean value of 0.9 kV/m. The median peak field was 0.29 kV/m. 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 storms with lightning is 1.6 A while the mean current for land storms with lightning is 1.0 A. The mean current for oceanic storms without lightning (i.e., electrified shower clouds) is 0.39 A and the mean current for land storms without lightning is 0.13 A. Thus, on average, land storms with or without lightning have about half the mean current as their corresponding oceanic storm counterparts. Over three-quarters (78%) of the land storms had detectable lightning, while less than half (43%) of the oceanic storms had lightning. 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 lightning 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

  11. 4SM: A Novel Self-Calibrated Algebraic Ratio Method for Satellite-Derived Bathymetry and Water Column Correction

    Directory of Open Access Journals (Sweden)

    Yann G. Morel

    2017-07-01

    Full Text Available All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i use only the relative radiance data in the image along with published data, and several new assumptions; (ii in order to specify and operate the simplified radiative transfer equation (RTE; (iii for the purpose of retrieving both the satellite derived bathymetry (SDB and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need for (i formal atmospheric correction; (ii conversion of relative radiance into calibrated reflectance; or (iii existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM. This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

  12. Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational ℓ1-Norm Regularization in the Derivative Domain

    Science.gov (United States)

    Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

    2014-05-01

    The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ℓ1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case

  13. Validation of a global satellite rainfall product for real time monitoring of meteorological extremes

    Science.gov (United States)

    Cánovas-García, Fulgencio; García-Galiano, Sandra; Karbalaee, Negar

    2017-10-01

    The real time monitoring of storms is important for the management and prevention of flood risks. However, in the southeast of Spain, it seems that the density of the rain gauge network may not be sufficient to adequately characterize the rainfall spatial distribution or the high rainfall intensities that are reached during storms. Satellite precipitation products such as PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System) could be used to complement the automatic rain gauge networks and so help solve this problem. However, the PERSIANN-CCS product has only recently become available, so its operational validity for areas such as south-eastern Spain is not yet known. In this work, a methodology for the hourly validation of PERSIANN-CCS is presented. We used the rain gauge stations of the SIAM (Sistema de Información Agraria de Murcia) network to study three storms with a very high return period. These storms hit the east and southeast of the Iberian Peninsula and resulted in the loss of human life, major damage to agricultural crops and a strong impact on many different types of infrastructure. The study area is the province of Murcia (Region of Murcia), located in the southeast of the Iberian Peninsula, covering an area of more than 11,000 km2 and with a population of almost 1.5 million. In order to validate the PERSIANN-CCS product for these three storms, contrasts were made with the hyetographs registered by the automatic rain gauges, analyzing statistics such as bias, mean square difference and Pearson's correlation coefficient. Although in some cases the temporal distribution of rainfall was well captured by PERSIANN-CCS, in several rain gauges high intensities were not properly represented. The differences were strongly correlated with the rain gauge precipitation, but not with satellite-obtained rainfall. The main conclusion concerns the need for specific local calibration

  14. How consistent are global long-term satellite LAI products in terms of interannual variability and trend?

    Science.gov (United States)

    Jiang, C.; Ryu, Y.; Fang, H.

    2016-12-01

    Proper usage of global satellite LAI products requires comprehensive evaluation. To address this issue, the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup proposed a four-stage validation hierarchy. During the past decade, great efforts have been made following this validation framework, mainly focused on absolute magnitude, seasonal trajectory, and spatial pattern of those global satellite LAI products. However, interannual variability and trends of global satellite LAI products have been investigated marginally. Targeting on this gap, we made an intercomparison between seven global satellite LAI datasets, including four short-term ones: MODIS C5, MODIS C6, GEOV1, MERIS, and three long-term products ones: LAI3g, GLASS, and GLOBMAP. We calculated global annual LAI time series for each dataset, among which we found substantial differences. During the overlapped period (2003 - 2011), MODIS C5, GLASS and GLOBMAP have positive correlation (r > 0.6) between each other, while MODIS C6, GEOV1, MERIS, and LAI3g are highly consistent (r > 0.7) in interannual variations. However, the previous three datasets show negative trends, all of which use MODIS C5 reflectance data, whereas the latter four show positive trends, using MODIS C6, SPOT/VGT, ENVISAT/MERIS, and NOAA/AVHRR, respectively. During the pre-MODIS era (1982 - 1999), the three AVHRR-based datasets (LAI3g, GLASS and GLOBMAP) agree well (r > 0.7), yet all of them show oscillation related with NOAA platform changes. In addition, both GLASS and GLOBMAP show clear cut-points around 2000 when they move from AVHRR to MODIS. Such inconsistency is also visible for GEOV1, which uses SPOT-4 and SPOT-5 before and after 2002. We further investigate the map-to-map deviations among these products. This study highlights that continuous sensor calibration and cross calibration are essential to obtain reliable global LAI time series.

  15. High spatial resolution satellite observations for validation of MODIS land products: IKONOS observations acquired under the NASA scientific data purchase.

    Science.gov (United States)

    Jeffrey T. Morisette; Jaime E. Nickeson; Paul Davis; Yujie Wang; Yuhong Tian; Curtis E. Woodcock; Nikolay Shabanov; Matthew Hansen; Warren B. Cohen; Doug R. Oetter; Robert E. Kennedy

    2003-01-01

    Phase 1I of the Scientific Data Purchase (SDP) has provided NASA investigators access to data from four different satellite and airborne data sources. The Moderate Resolution Imaging Spectrometer (MODIS) land discipline team (MODLAND) sought to utilize these data in support of land product validation activities with a lbcus on tile EOS Land Validation Core Sites. These...

  16. Use of satellite erythemal UV products in analysing the global UV changes

    Directory of Open Access Journals (Sweden)

    I. Ialongo

    2011-09-01

    Full Text Available Long term changes in solar UV radiation affect global bio-geochemistry and climate. The satellite-based dataset of TOMS (Total Ozone Monitoring System and OMI (Ozone Monitoring Instrument of erythemal UV product was applied for the first time to estimate the long-term ultraviolet (UV changes at the global scale. The analysis of the uncertainty related to the different input information is presented. OMI and GOME-2 (Global Ozone Monitoring Experiment-2 products were compared in order to analyse the differences in the global UV distribution and their effect on the linear trend estimation.

    The results showed that the differences in the inputs (mainly surface albedo and aerosol information used in the retrieval, affect significantly the UV change calculation, pointing out the importance of using a consistent dataset when calculating long term UV changes. The areas where these differences played a major role were identified using global maps of monthly UV changes. Despite the uncertainties, significant positive UV changes (ranging from 0 to about 5 %/decade were observed, with higher values in the Southern Hemisphere at mid-latitudes during spring-summer, where the largest ozone decrease was observed.

  17. A biophysical process based approach for estimating net primary production using satellite and ground observations

    Science.gov (United States)

    Choudhury, Bhaskar J.

    An approach is presented for calculating interannual variation of net primary production (C) of terrestrial plant communities at regional scale using satellite and ground measurements. C has been calculated as the difference of gross photosynthesis (A g) and respiration (R), recognizing that different biophysical factors exert major control on these two processes. A g has been expressed as the product of radiation use efficiency for gross photosynthesis by an unstressed canopy and intercepted photosynthetically active radiation, which is then adjusted for stresses due to soil water shortage and temperature away from optimum. R has been calculated as the sum of growth and maintenance components (respectively, R g and R m. The R m has been determined from nitrogen content of plant tissue per unit ground area, while R g has been obtained as a fraction of the difference of A g and R m. Model parameters have not been determined by matching the calculated fluxes against observations at any location. Results are presented for cultivated and temperate deciduous forest areas over North America for five consecutive years (1986-1990) and compared with observations.

  18. Can Airborne Laser Scanning (ALS and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest?

    Directory of Open Access Journals (Sweden)

    Eva Lindberg

    2015-04-01

    Full Text Available In managed landscapes, conservation planning requires effective methods to identify high-biodiversity areas. The objective of this study was to evaluate the potential of airborne laser scanning (ALS and forest estimates derived from satellite images extracted at two spatial scales for predicting the stand-scale abundance and species richness of birds and beetles in a managed boreal forest landscape. Multiple regression models based on forest data from a 50-m radius (i.e., corresponding to a homogenous forest stand had better explanatory power than those based on a 200-m radius (i.e., including also parts of adjacent stands. Bird abundance and species richness were best explained by the ALS variables “maximum vegetation height” and “vegetation cover between 0.5 and 3 m” (both positive. Flying beetle abundance and species richness, as well as epigaeic (i.e., ground-living beetle richness were best explained by a model including the ALS variable “maximum vegetation height” (positive and the satellite-derived variable “proportion of pine” (negative. Epigaeic beetle abundance was best explained by “maximum vegetation height” at 50 m (positive and “stem volume” at 200 m (positive. Our results show that forest estimates derived from satellite images and ALS data provide complementary information for explaining forest biodiversity patterns. We conclude that these types of remote sensing data may provide an efficient tool for conservation planning in managed boreal landscapes.

  19. Intercomparison of Satellite Derived Gravity Time Series with Inferred Gravity Time Series from TOPEX/POSEIDON Sea Surface Heights and Climatological Model Output

    Science.gov (United States)

    Cox, C.; Au, A.; Klosko, S.; Chao, B.; Smith, David E. (Technical Monitor)

    2001-01-01

    The upcoming GRACE mission promises to open a window on details of the global mass budget that will have remarkable clarity, but it will not directly answer the question of what the state of the Earth's mass budget is over the critical last quarter of the 20th century. To address that problem we must draw upon existing technologies such as SLR, DORIS, and GPS, and climate modeling runs in order to improve our understanding. Analysis of long-period geopotential changes based on SLR and DORIS tracking has shown that addition of post 1996 satellite tracking data has a significant impact on the recovered zonal rates and long-period tides. Interannual effects such as those causing the post 1996 anomalies must be better characterized before refined estimates of the decadal period changes in the geopotential can be derived from the historical database of satellite tracking. A possible cause of this anomaly is variations in ocean mass distribution, perhaps associated with the recent large El Nino/La Nina. In this study, a low-degree spherical harmonic gravity time series derived from satellite tracking is compared with a TOPEX/POSEIDON-derived sea surface height time series. Corrections for atmospheric mass effects, continental hydrology, snowfall accumulation, and ocean steric model predictions will be considered.

  20. Satellite Derived Seafloor Bathymetry and Habitat Mapping on a Shallow Carbonate Platform: Campeche Bank, México.

    Science.gov (United States)

    Garza-Perez, J. R.; Rankey, E. C.; Rodriguez-Vázquez, R. A.; Naranjo-Garcia, M. J.

    2017-12-01

    Extensive and consistent high-resolution seafloor mapping is a difficult task involving important financial resources, intensive field work and careful planning; thus there is a paucity of this type of mapping products both in spatial distribution and through time. Remote sensed imagery has supported continuous mapping efforts elsewhere, but extensive seafloor mapping, even in shallow regions keeps being elusive. Challenges to this effort include cloud cover, surface sun-glint, and water turbidity caused by sediment resuspension and primary productivity. Nevertheless, using high-quality satellite imagery (Landsat-8 OLI -30x30m/pixel- and GeoEye-1 -2x2m/pixel) and rigorous pre-processing (atmospheric correction, de-glinting and water-column light extinction compensation), resulting data contribute towards the advancement of seafloor mapping. The Yucatan Peninsula in México is a carbonate ramp devoid of significant orographic features and surface water bodies. Its submerged portion is the Campeche Bank, gently sloping towards the Gulf of Mexico. The bottom features several distinct blankets composed by medium-fine sediment (dominated by pelecypods, gastropods, foraminifera, lithoclasts, calcareous peloids and algal nodules, Halimeda plaques and coralline algae fragments), and a reef unit with several bank-type coral reefs. Outside the coral reefs, biotic cover down to 20 m deep is dominated by macroalgae (red, brown, green), coralline and filamentous algae with sharp seasonal changes in abundance, from almost nil during north-winds (Oct. - Jan.) to high during dry (Feb.- May) and rainy seasons (Jun. - Sept.), with changes of dominance by algae groups between dry and rainy seasons. This bloom is favored by increases in sunlight and nutrients carried by the Caribbean current upwelling washing the Campeche Bank. Beyond 20 m depth, sandy plains dominate the seascape. Corals, octocorals, sponges and tunicates are spatially restricted to bottoms with thin layers of

  1. Heterogeneous benefits of precision nitrogen management over the Midwestern US: evidence from 1,000 fields derived by satellite imagery and crop modeling

    Science.gov (United States)

    Jin, Z.; Archontoulis, S.; Lobell, D. B.

    2017-12-01

    The wise management of nitrogen (N) fertilizer is important for both economic and environmental considerations. The variable rate technology (VRT) that applies different rates of N fertilizer by fully taking account of the spatial heterogeneity within fields has gained popularity with the recent advent of high-resolution satellites and spectrometers, but its profitability is still uncertain given the dependence of corn-nitrogen responses to soil and climate. To our knowledge, the benefits of adopting VRT in the vast Midwestern US agricultural zones have only been assessed at a very limited number of fields based on labor-costing on-farm samplings. Here we present a study that integrates a range of geospatial tools and data to quantifying the economic benefit of VRT versus uniform N application over 1,000 randomly selected corn fields in the US Midwest. We employed the Google Earth Engine (GEE) and Landsat-5, 7 and 8 collections to derive 30m-resolution yield map for years 2007-2015, and used the multi-year averaged yields to characterize the yield variation and hence the management zones for each field and zone-specific yield goal. The yield goals as well as the Soil Survey Geographic Database (SSURGO) data were then used to calibrate the Agricultural Production Systems sIMulator (APSIM) model, which generated a range of variables such as yields, N balance and leaching. Our preliminary results showed that the calibrated APSIM model was able to capture about 60% of the variation in the satellite-based yield estimates, and more than 70% of the yield spread (i.e. maximum - minimum yield). Regardless of the overall environmental benefits of less N loss through leaching, the economic difference between adopting VRT and uniform application ranged from -50 to 200 per acre, with the majority lay between -10 and 40 per acre. Fields with a wider range of yield spread benefited more from adopting VRT, yet the conclusion varies upon weather, especially the precipitation. Our

  2. Detection and variability of the Congo River plume from satellite derived sea surface temperature, salinity, ocean colour and sea level

    Science.gov (United States)

    Hopkins, Jo; Lucas, Marc; Dufau, Claire; Sutton, Marion; Lauret, Olivier

    2013-04-01

    The Congo River in Africa has the world's second highest annual mean daily freshwater discharge and is the second largest exporter of terrestrial organic carbon into the oceans. It annually discharges an average of 1,250 × 109 m3 of freshwater into the southeast Atlantic producing a vast fresh water plume, whose signature can be traced hundreds of kilometres from the river mouth. Large river plumes such as this play important roles in the ocean carbon cycle, often functioning as carbon sinks. An understanding of their extent and seasonality is therefore essential if they are to be realistically accounted for in global assessments of the carbon cycle. Despite its size, the variability and dynamics of the Congo plume are minimally documented. In this paper we analyse satellite derived sea surface temperature, salinity, ocean colour and sea level anomaly to describe and quantify the extent, strength and variability of the far-field plume and to explain its behaviour in relation to winds, ocean currents and fresh water discharge. Empirical Orthogonal Function analysis reveals strong seasonal and coastal upwelling signals, potential bimodal seasonality of the Angola Current and responses to fresh water discharge peaks in all data sets. The strongest plume-like signatures however were found in the salinity and ocean colour where the dominant sources of variability come from the Congo River itself, rather than from the wider atmosphere and ocean. These two data sets are then analysed using a statistically based water mass detection technique to isolate the behaviour of the plume. The Congo's close proximity to the equator means that the influence of the earth's rotation on the fresh water inflow is relatively small and the plume tends not to form a distinct coastal current. Instead, its behaviour is determined by wind and surface circulation patterns. The main axis of the plume between November and February, following peak river discharge, is oriented northwest, driven

  3. PPARγ and MyoD are differentially regulated by myostatin in adipose-derived stem cells and muscle satellite cells

    International Nuclear Information System (INIS)

    Zhang, Feng; Deng, Bing; Wen, Jianghui; Chen, Kun; Liu, Wu; Ye, Shengqiang; Huang, Haijun; Jiang, Siwen; Xiong, Yuanzhu

    2015-01-01

    Myostatin (MSTN) is a secreted protein belonging to the transforming growth factor-β (TGF-β) family that is primarily expressed in skeletal muscle and also functions in adipocyte maturation. Studies have shown that MSTN can inhibit adipogenesis in muscle satellite cells (MSCs) but not in adipose-derived stem cells (ADSCs). However, the mechanism by which MSTN differently regulates adipogenesis in these two cell types remains unknown. Peroxisome proliferator-activated receptor-γ (PPARγ) and myogenic differentiation factor (MyoD) are two key transcription factors in fat and muscle cell development that influence adipogenesis. To investigate whether MSTN differentially regulates PPARγ and MyoD, we analyzed PPARγ and MyoD expression by assessing mRNA, protein and methylation levels in ADSCs and MSCs after treatment with 100 ng/mL MSTN for 0, 24, and 48 h. PPARγ mRNA levels were downregulated after 24 h and upregulated after 48 h of treatment in ADSCs, whereas in MSCs, PPARγ levels were downregulated at both time points. MyoD expression was significantly increased in ADSCs and decreased in MSCs. PPARγ and MyoD protein levels were upregulated in ADSCs and downregulated in MSCs. The CpG methylation levels of the PPARγ and MyoD promoters were decreased in ADSCs and increased in MSCs. Therefore, this study demonstrated that the different regulatory adipogenic roles of MSTN in ADSCs and MSCs act by differentially regulating PPARγ and MyoD expression. - Highlights: • PPARγ and MyoD mRNA and protein levels are upregulated by myostatin in ADSCs. • PPARγ and MyoD mRNA and protein levels are downregulated by myostatin in MSCs. • PPARγ exhibited different methylation levels in myostatin-treated ADSCs and MSCs. • MyoD exhibited different methylation levels in myostatin-treated ADSCs and MSCs. • PPARγ and MyoD are differentially regulated by myostatin in ADSCs and MSCs

  4. PPARγ and MyoD are differentially regulated by myostatin in adipose-derived stem cells and muscle satellite cells

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Feng [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China); Deng, Bing [Wuhan Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Science and Technology, Wuhan, Hubei, 430208 (China); Wen, Jianghui [Wu Han University of Technology, Wuhan 430074 (China); Chen, Kun [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China); Liu, Wu; Ye, Shengqiang; Huang, Haijun [Wuhan Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Science and Technology, Wuhan, Hubei, 430208 (China); Jiang, Siwen, E-mail: jiangsiwen@mail.hzau.edu.cn [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China); Xiong, Yuanzhu, E-mail: xiongyzhu@163.com [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China)

    2015-03-06

    Myostatin (MSTN) is a secreted protein belonging to the transforming growth factor-β (TGF-β) family that is primarily expressed in skeletal muscle and also functions in adipocyte maturation. Studies have shown that MSTN can inhibit adipogenesis in muscle satellite cells (MSCs) but not in adipose-derived stem cells (ADSCs). However, the mechanism by which MSTN differently regulates adipogenesis in these two cell types remains unknown. Peroxisome proliferator-activated receptor-γ (PPARγ) and myogenic differentiation factor (MyoD) are two key transcription factors in fat and muscle cell development that influence adipogenesis. To investigate whether MSTN differentially regulates PPARγ and MyoD, we analyzed PPARγ and MyoD expression by assessing mRNA, protein and methylation levels in ADSCs and MSCs after treatment with 100 ng/mL MSTN for 0, 24, and 48 h. PPARγ mRNA levels were downregulated after 24 h and upregulated after 48 h of treatment in ADSCs, whereas in MSCs, PPARγ levels were downregulated at both time points. MyoD expression was significantly increased in ADSCs and decreased in MSCs. PPARγ and MyoD protein levels were upregulated in ADSCs and downregulated in MSCs. The CpG methylation levels of the PPARγ and MyoD promoters were decreased in ADSCs and increased in MSCs. Therefore, this study demonstrated that the different regulatory adipogenic roles of MSTN in ADSCs and MSCs act by differentially regulating PPARγ and MyoD expression. - Highlights: • PPARγ and MyoD mRNA and protein levels are upregulated by myostatin in ADSCs. • PPARγ and MyoD mRNA and protein levels are downregulated by myostatin in MSCs. • PPARγ exhibited different methylation levels in myostatin-treated ADSCs and MSCs. • MyoD exhibited different methylation levels in myostatin-treated ADSCs and MSCs. • PPARγ and MyoD are differentially regulated by myostatin in ADSCs and MSCs.

  5. 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

  6. Evaluation of Land Surface Models in Reproducing Satellite-Derived LAI over the High-Latitude Northern Hemisphere. Part I: Uncoupled DGVMs

    Directory of Open Access Journals (Sweden)

    Ning Zeng

    2013-10-01

    Full Text Available Leaf Area Index (LAI represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades. This provides a unique opportunity to validate LAI estimates from multiple vegetation models. The objective of this paper is to compare new, satellite-derived LAI measurements with modeled output for the Northern Hemisphere. We compare monthly LAI output from eight land surface models from the TRENDY compendium with satellite data from an Artificial Neural Network (ANN from the latest version (third generation of GIMMS AVHRR NDVI data over the period 1986–2005. Our results show that all the models overestimate the mean LAI, particularly over the boreal forest. We also find that seven out of the eight models overestimate the length of the active vegetation-growing season, mostly due to a late dormancy as a result of a late summer phenology. Finally, we find that the models report a much larger positive trend in LAI over this period than the satellite observations suggest, which translates into a higher trend in the growing season length. These results highlight the need to incorporate a larger number of more accurate plant functional types in all models and, in particular, to improve the phenology of deciduous trees.

  7. Global Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

    Science.gov (United States)

    Smith, M.; Slayback, D. A.; Policelli, F.; Brakenridge, G. R.; Tokay, M.

    2012-12-01

    Flooding is among the most destructive, frequent, and costly natural disasters faced by modern society, with several major events occurring each year. In the past few years, major floods have devastated parts of China, Thailand, Pakistan, Australia, and the Philippines, among others. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we have developed, and are now operating, a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours after flooding events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard. The LANCE system typically processes imagery in less than 3 hours after satellite overpass, and our flood mapping system can output flood products within ½ hour of acquiring the LANCE products. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial assessment of flooding extent by late afternoon, every day, and more robust assessments after accumulating imagery over a longer period; the MODIS sensors are optical, so cloud cover remains an issue, which is partly overcome by using multiple looks over one or more days. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extents. We have made progress on some of these issues

  8. Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003-2013

    Science.gov (United States)

    Anderson, Martha C.; Zolin, Cornelio A.; Hain, Christopher R.; Semmens, Kathryn; Tugrul Yilmaz, M.; Gao, Feng

    2015-07-01

    Shortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and functioning have been attributed to cloud and aerosol contamination of shortwave reflectance composites, particularly over the rainforested regions of the Amazon basin which are subject to prolonged periods of cloud cover and episodes of intense biomass burning. This study compares timeseries of satellite-derived maps of LAI from the Moderate Resolution Imaging Spectroradiometer (MODIS) and precipitation from the Tropical Rainfall Mapping Mission (TRMM) with a diagnostic Evaporative Stress Index (ESI) retrieved using thermal infrared remote sensing over South America for the period 2003-2013. This period includes several severe droughts and floods that occurred both over the Amazon and over unforested savanna and agricultural areas in Brazil. Cross-correlations between absolute values and standardized anomalies in monthly LAI and precipitation composites as well as the actual-to-reference evapotranspiration (ET) ratio used in the ESI were computed for representative forested and agricultural regions. The correlation analyses reveal strong apparent anticorrelation between MODIS LAI and TRMM precipitation anomalies over the Amazon, but better coupling over regions vegetated with shorter grass and crop canopies. The ESI was more consistently correlated with precipitation patterns over both landcover types. Temporal comparisons between ESI and TRMM anomalies suggest longer moisture buffering timescales in the deeper rooted rainforest systems. Diagnostic thermal-based retrievals of ET and ET anomalies, such as used in the ESI, provide independent information on the impacts of extreme hydrologic events on vegetation health in comparison with VI and precipitation-based drought

  9. An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

    NARCIS (Netherlands)

    Kimani, M.W.; Hoedjes, Johannes Cornelis Bernardus; Su, Z.

    2017-01-01

    Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks.

  10. How robust are in situ observations for validating satellite-derived albedo over the dark zone of the Greenland Ice Sheet?

    Science.gov (United States)

    Ryan, J.; Hubbard, A., II; Irvine-Fynn, T. D.; Doyle, S. H.; Cook, J.; Stibal, M.; Smith, L. C.; Box, J. E.

    2017-12-01

    Calibration and validation of satellite-derived ice sheet albedo data require high-quality, in situ measurements commonly acquired by up and down facing pyranometers mounted on automated weather stations (AWS). However, direct comparison between ground and satellite-derived albedo can only be justified when the measured surface is homogeneous at the length-scale of both satellite pixel and in situ footprint. We used digital imagery acquired by an unmanned aerial vehicle to evaluate point-to-pixel albedo comparisons across the western, ablating margin of the Greenland Ice Sheet. Our results reveal that in situ measurements overestimate albedo by up to 0.10 at the end of the melt season because the ground footprints of AWS-mounted pyranometers are insufficient to capture the spatial heterogeneity of the ice surface as it progressively ablates and darkens. Statistical analysis of 21 AWS across the entire Greenland Ice Sheet reveals that almost half suffer from this bias, including some AWS located within the wet snow zone.

  11. Using infrared spectroscopy and satellite data to accurately monitor remote volcanoes and map their eruptive products

    Science.gov (United States)

    Ramsey, M. S.

    2011-12-01

    The ability to detect the onset of new activity at a remote volcano commonly relies on high temporal resolution thermal infrared (TIR) satellite-based observations. These observations from sensors such as AVHRR and MODIS are being used in innovative ways to produce trends of activity, which are critical for hazard response planning and scientific modeling. Such data are excellent for detection of new thermal features, volcanic plumes, and tracking changes over the hour time scale, for example. For some remote volcanoes, the lack of ground-based monitoring typically means that these sensors provide the first and only confirmation of renewed activity. However, what is lacking is the context of the higher spatial scale, which provides the volcanologist with meter-scale information on specific temperatures and changes in the composition and texture of the eruptive products. For the past eleven years, the joint US-Japanese ASTER instrument has been acquiring image-based data of volcanic eruptions around the world, including in the remote northern Pacific region. There have been more ASTER observations of Kamchatka volcanoes than any other location on the globe due mainly to an operational program put into place in 2004. Automated hot spot alarms from AVHRR data trigger ASTER acquisitions using the instrument's "rapid response" mode. Specifically for Kamchatka, this program has resulted in more than 700 additional ASTER images of the most thermally-active volcanoes (e.g., Shiveluch, Kliuchevskoi, Karymsky, Bezymianny). The scientific results from this program at these volcanoes will be highlighted. These results were strengthened by several field seasons used to map new products, collect samples for laboratory-based spectroscopy, and acquire TIR camera data. The fusion of ground, laboratory and space-based spectroscopy provided the most accurate interpretation of the eruptions and laid the ground work for future VSWIR/TIR sensors such as HyspIRI, which are a critically

  12. Derivation of economic values for production traits in aquaculture species

    NARCIS (Netherlands)

    Janssen, K.P.E.; Berentsen, P.B.M.; Besson, M.B.; Komen, J.

    2017-01-01

    Background:
    In breeding programs for aquaculture species, breeding goal traits are often weighted based on the desired gains but economic gain would be higher if economic values were used instead. The objectives of this study were: (1) to develop a bio-economic model to derive economic values

  13. MODIS-derived terrestrial primary production [chapter 28

    Science.gov (United States)

    Maosheng Zhao; Steven Running; Faith Ann Heinsch; Ramakrishna Nemani

    2011-01-01

    Temporal and spatial changes in terrestrial biological productivity have a large impact on humankind because terrestrial ecosystems not only create environments suitable for human habitation, but also provide materials essential for survival, such as food, fiber and fuel. A recent study estimated that consumption of terrestrial net primary production (NPP; a list of...

  14. Global, Daily, Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

    Science.gov (United States)

    Slayback, D. A.; Policelli, F. S.; Brakenridge, G. R.; Tokay, M. M.; Smith, M. M.; Kettner, A. J.

    2013-12-01

    Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is expected to increase in frequency and damage with climate change and population growth. Some of 2013's major floods have impacted the New York City region, the Midwest, Alberta, Australia, various parts of China, Thailand, Pakistan, and central Europe. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours of events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial daily assessment of flooding extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extents. We have made progress on many of these issues, and are working to develop higher resolution flood detection using alternate sensors, including Landsat and various radar sensors. Although these

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

    Science.gov (United States)

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

    2017-12-01

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

  16. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA from 2003-08-26 to 2012-05-03 (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  17. Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China

    Directory of Open Access Journals (Sweden)

    Shan-hu Jiang

    2010-12-01

    Full Text Available Three high-resolution satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM standard precipitation products 3B42V6 and 3B42RT and the Climate Precipitation Center's (CPC morphing technique precipitation product (CMORPH, were evaluated against surface rain gauge observations from the Laohahe Basin in northern China. Widely used statistical validation indices and categorical statistics were adopted. The evaluations were performed at multiple time scales, ranging from daily to yearly, for the years from 2003 to 2008. The results show that all three satellite precipitation products perform very well in detecting the occurrence of precipitation events, but there are some different biases in the amount of precipitation. 3B42V6, which has a bias of 21%, fits best with the surface rain gauge observations at both daily and monthly scales, while the biases of 3B42RT and CMORPH, with values of 81% and 67%, respectively, are much higher than a normal receivable threshold. The quality of the satellite precipitation products also shows monthly and yearly variation: 3B42RT has a large positive bias in the cold season from September to April, while CMORPH has a large positive bias in the warm season from May to August, and they all attained their best values in 2006 (with 10%, 50%, and −5% biases for 3B42V6, 3B42RT, and CMORPH, respectively. Our evaluation shows that, for the Laohahe Basin, 3B42V6 has the best correspondence with the surface observations, and CMORPH performs much better than 3B42RT. The large errors of 3B42RT and CMORPH remind us of the need for new improvements to satellite precipitation retrieval algorithms or feasible bias adjusting methods.

  18. Recent history of large-scale ecosystem disturbances in North America derived from the AVHRR satellite record.

    Science.gov (United States)

    Christopher Potter; Tan Pang-Ning; Vipin Kumar; Chris Kucharik; Steven Klooster; Vanessa Genovese; Warren Cohen; Sean. Healey

    2005-01-01

    Ecosystem structure and function are strongly affected by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the advanced very high resolution radiometer (AVHRR...

  19. Performance metrics for the assessment of satellite data products: an ocean color case study

    Science.gov (United States)

    Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coeffic...

  20. Engineered Nanoscale Materials and Derivative Products: Regulatory Challenges

    National Research Council Canada - National Science Library

    Schierow, Linda-Jo

    2008-01-01

    .... government has invested billions of dollars to ensure that American industry remains a global leader in the field, because the products of nanotechnology are seen to have great economic potential...

  1. Initial biochar effects on plant productivity derive from N fertilization

    NARCIS (Netherlands)

    Jeffery, Simon; Memelink, Ilse; Hodgson, Edward; Jones, Sian; van de Voorde, Tess F. J.; Bezemer, T. Martijn; Mommer, Liesje; van Groenigen, Jan Willem

    2017-01-01

    Biochar application to soil is widely claimed to increase plant productivity. However, the underlying mechanisms are still not conclusively described. Here, we aim to elucidate these mechanisms using stable isotope probing.

  2. Fate of ivermectin residues in ewes' milk and derived products.

    Science.gov (United States)

    Cerkvenik, Vesna; Perko, Bogdan; Rogelj, Irena; Doganoc, Darinka Z; Skubic, Valentin; Beek, Wim M J; Keukens, Henk J

    2004-02-01

    The fate of ivermectin (IVM) residues was studied throughout the processing of daily bulk milk from 30 ewes (taken up to 33 d following subcutaneous administration of 0.2 mg IVM/kg b.w.) in the following milk products: yoghurt made from raw and pasteurized milk; cheese after pressing; 30- and 60-day ripened cheese; and whey, secondary whey and whey proteins obtained after cheese-making (albumin cheese). The concentration of the H2B1a component of IVM was analysed in these dairy products using an HPLC method with fluorescence detection. The mean recovery of the method was, depending on the matrix, between 87 and 100%. Limits of detection in the order of only 0.1 microg H2B1a/kg of product were achieved. Maximum concentrations of IVM were detected mostly at 2 d after drug administration to the ewes. The highest concentration of IVM was found on day 2 in 60-day ripened cheese (96 microg H2B1a/kg cheese). Secondary whey was the matrix with the lowest concentration of IVM (milk fat and solid content were evident. During yoghurt production, fermentation and thermal stability of IVM was observed. During cheese production, approximately 35% of the IVM, present in the raw (bulk) milk samples, was lost. From the results it was concluded that the processing of ewes' milk did not eliminate the drug residues under investigation. The consequences of IVM in the human diet were discussed. Milk from treated animals should be excluded from production of fat products like cheese for longer after treatment with IVM than for lower fat products.

  3. Validation of Satellite Precipitation Products Using Local Rain Gauges to Support Water Assessment in Cochabamba, Bolivia

    Science.gov (United States)

    Saavedra, O.

    2017-12-01

    The metropolitan region of Cochabamba has been struggling for a consistent water supply master plan for years. The limited precipitation intensities and growing water demand have led to severe water conflicts since 2000 when the fight for water had international visibility. A new dam has just placed into operation, located at the mountain range north of the city, which is the hope to fulfill partially water demand in the region. Looking for feasible water sources and projects are essential to fulfill demand. However, the limited monitoring network composed by conventional rain gauges are not enough to come up with the proper aerial precipitation patterns. This study explores the capabilities of GSMaP-GPM satellite products combined with local rain gauge network to obtain an enhanced product with spatial and temporal resolution. A simple methodology based on penalty factors is proposed to adjust GSMaP-GPM intensities on grid-by-grid basis. The distance of an evaluated grid to the surrounding rain gauges was taken into account. The final correcting factors were obtained by iteration, at this particular case of study four iterations were enough to reduce the relative error. A distributed hydrological model was forced with the enhanced precipitation product to simulate the inflow to the new operating dam. Once the model parameters were calibrated and validated, forecast simulations were run. For the short term, the precipitation trend was projected using exponential equation. As for the long term projection, precipitation and temperature from the hadGEM2 and MIROC global circulation model outputs were used where the last one was found in closer agreement of predictions in the past. Overall, we found out that the amount of 1000 l/s for water supply to the region should be possible to fulfill till 2030. Beyond this year, the intake of two neighboring basins should be constructed to increase the stored volume. This is study was found particularly useful to forecast river

  4. Estimating Net Primary Productivity Beneath Snowpack Using Snowpack Radiative Transfer Modeling and Global Satellite Data

    Science.gov (United States)

    Barber, D. E.; Peterson, M. C.

    2002-05-01

    Sufficient photosynthetically active radiation (PAR) penetrates snow for plants to grow beneath snowpack during late winter or early spring in tundra ecosystems. During the spring in this ecosystem, the snowpack creates an environment with higher humidity and less variable and milder temperatures than on the snow-free land. Under these conditions, the amount of PAR available is likely to be the limiting factor for plant growth. Current methods for determining net primary productivity (NPP) of tundra ecosystems do not account for this plant growth beneath snowpack, apparently resulting in underestimating plant production there. We are currently in the process of estimating the magnitude of this early growth beneath snow for tundra ecosystems. Our method includes a radiative transfer model that simulates diffuse and direct PAR penetrating snowpack based on downwelling PAR values and snow depth data from global satellite databases. These PAR levels are convolved with plant growth for vegetation that thrives beneath snowpacks, such as lichen. We expect to present the net primary production for Cladonia species (a common Arctic lichen) that has the capability of photosynthesizing at low temperatures beneath snowpack. This method may also be used to study photosynthesis beneath snowpacks in other hardy plants. Lichens are used here as they are common in snow-covered regions, flourish under snowpack, and provide an important food source for tundra herbivores (e.g. caribou). In addition, lichens are common in arctic-alpine environments and our results can be applied to these ecosystems as well. Finally, the NPP of lichen beneath snowpack is relatively well understood compared to other plants, making it ideal vegetation for this first effort at estimating the potential importance of photosynthesis at large scales. We are examining other candidate plants for their photosynthetic potential beneath snowpack at this time; however, little research has been done on this topic. We

  5. Integrating hydrodynamic models and COSMO-SkyMed derived products for flood damage assessment

    Science.gov (United States)

    Giuffra, Flavio; Boni, Giorgio; Pulvirenti, Luca; Pierdicca, Nazzareno; Rudari, Roberto; Fiorini, Mattia

    2015-04-01

    Floods are the most frequent weather disasters in the world and probably the most costly in terms of social and economic losses. They may have a strong impact on infrastructures and health because the range of possible damages includes casualties, loss of housing and destruction of crops. Presently, the most common approach for remotely sensing floods is the use of synthetic aperture radar (SAR) images. Key features of SAR data for inundation mapping are the synoptic view, the capability to operate even in cloudy conditions and during both day and night time and the sensitivity of the microwave radiation to water. The launch of a new generation of instruments, such as TerraSAR-X and COSMO-SkyMed (CSK) allows producing near real time flood maps having a spatial resolution in the order of 1-5 m. Moreover, the present (CSK) and upcoming (Sentinel-1) constellations permit the acquisition of radar data characterized by a short revisit time (in the order of some hours for CSK), so that the production of frequent inundation maps can be envisaged. Nonetheless, gaps might be present in the SAR-derived flood maps because of the limited area imaged by SAR; moreover, the detection of floodwater may be complicated by the presence of very dense vegetation or urban settlements. Hence the need to complement SAR-derived flood maps with the outputs of physical models. Physical models allow delivering to end users very useful information for a complete flood damage assessment, such as data on water depths and flow directions, which cannot be directly derived from satellite remote sensing images. In addition, the flood extent predictions of hydraulic models can be compared to SAR-derived inundation maps to calibrate the models, or to fill the aforementioned gaps that can be present in the SAR-derived maps. Finally, physical models enable the construction of risk scenarios useful for emergency managers to take their decisions and for programming additional SAR acquisitions in order to

  6. Temporal variatiions of Sea ice cover in the Baltic Sea derived from operational sea ice products used in NWP.

    Science.gov (United States)

    Lange, Martin; Paul, Gerhard; Potthast, Roland

    2014-05-01

    Sea ice cover is a crucial parameter for surface fluxes of heat and moisture over water areas. The isolating effect and the much higher albedo strongly reduces the turbulent exchange of heat and moisture from the surface to the atmosphere and allows for cold and dry air mass flow with strong impact on the stability of the whole boundary layer and consequently cloud formation as well as precipitation in the downstream regions. Numerical weather centers as, ECMWF, MetoFrance or DWD use external products to initialize SST and sea ice cover in their NWP models. To the knowledge of the author there are mainly two global sea ice products well established with operational availability, one from NOAA NCEP that combines measurements with satellite data, and the other from OSI-SAF derived from SSMI/S sensors. The latter one is used in the Ostia product. DWD additionally uses a regional product for the Baltic Sea provided by the national center for shipping and hydrografie which combines observations from ships (and icebreakers) for the German part of the Baltic Sea and model analysis from the hydrodynamic HIROMB model of the Swedish meteorological service for the rest of the domain. The temporal evolution of the three different products are compared for a cold period in Februar 2012. Goods and bads will be presented and suggestions for a harmonization of strong day to day jumps over large areas are suggested.

  7. Assessing variability and long-term trends in burned area by merging multiple satellite fire products

    Directory of Open Access Journals (Sweden)

    L. Giglio

    2010-03-01

    Full Text Available Long term, high quality estimates of burned area are needed for improving both prognostic and diagnostic fire emissions models and for assessing feedbacks between fire and the climate system. We developed global, monthly burned area estimates aggregated to 0.5° spatial resolution for the time period July 1996 through mid-2009 using four satellite data sets. From 2001–2009, our primary data source was 500-m burned area maps produced using Moderate Resolution Imaging Spectroradiometer (MODIS surface reflectance imagery; more than 90% of the global area burned during this time period was mapped in this fashion. During times when the 500-m MODIS data were not available, we used a combination of local regression and regional regression trees developed over periods when burned area and Terra MODIS active fire data were available to indirectly estimate burned area. Cross-calibration with fire observations from the Tropical Rainfall Measuring Mission (TRMM Visible and Infrared Scanner (VIRS and the Along-Track Scanning Radiometer (ATSR allowed the data set to be extended prior to the MODIS era. With our data set we estimated that the global annual area burned for the years 1997–2008 varied between 330 and 431 Mha, with the maximum occurring in 1998. We compared our data set to the recent GFED2, L3JRC, GLOBCARBON, and MODIS MCD45A1 global burned area products and found substantial differences in many regions. Lastly, we assessed the interannual variability and long-term trends in global burned area over the past 13 years. This burned area time series serves as the basis for the third version of the Global Fire Emissions Database (GFED3 estimates of trace gas and aerosol emissions.

  8. Comparison of ground based indices (API and AQI) with satellite based aerosol products.

    Science.gov (United States)

    Zheng, Sheng; Cao, Chun-Xiang; Singh, Ramesh P

    2014-08-01

    Air quality in mega cities is one of the major concerns due to serious health issues and its indirect impact to the climate. Among mega cities, Beijing city is considered as one of the densely populated cities with extremely poor air quality. The meteorological parameters (wind, surface temperature, air temperature and relative humidity) control the dynamics and dispersion of air pollution. China National Environmental Monitoring Centre (CNEMC) started air pollution index (API) as of 2000 to evaluate air quality, but over the years, it was felt that the air quality is not well represented by API. Recently, the Ministry of Environmental Protection (MEP) of the People's Republic of China (PRC) started using a new index "air quality index (AQI)" from January 2013. We have compared API and AQI with three different MODIS (MODIS - Moderate Resolution Imaging SpectroRadiometer, onboard the Terra/Aqua satellites) AOD (aerosol optical depth) products for ten months, January-October, 2013. The correlation between AQI and Aqua Deep Blue AOD was found to be reasonably good as compared with API, mainly due to inclusion of PM2.5 in the calculation of AQI. In addition, for every month, the correlation coefficient between AQI and Aqua Deep Blue AOD was found to be relatively higher in the month of February to May. According to the monthly average distribution of precipitation, temperature, and PM10, the air quality in the months of June-September was better as compared to those in the months of February-May. AQI and Aqua Deep Blue AOD show highly polluted days associated with dust event, representing true air quality of Beijing. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. Chemistry and biology of natural product derived protease inhibitors

    OpenAIRE

    Stolze, Sara Christina

    2012-01-01

    Im Rahmen dieser Dissertation sollten Naturstoffe und davon abgeleitete Derivate synthetisiert und im Hinblick auf ihre biologische Aktivität als Protease-Inhibitoren untersucht werden. Für die Naturstoffklasse der 3-Amino-6-Hydroxy-2-piperidon(Ahp)-Cyclodepsipeptide, die als nicht-kovalente Serin-Protease-Inhibitoren bekannt sind, konnte eine Festphasensynthese basierend auf einem allgemeinen Ahp-Vorläufermolekül entwickelt werden. Für den Ahp-Vorläufer wurde eine Lösungssynthese entwicke...

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

    Science.gov (United States)

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

    2015-12-01

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

  11. Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Realtime and Research Products and Applications

    Science.gov (United States)

    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guojon

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25 deg latitude-longitude resolution over the latitude range from 50 deg N-50 deg S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  12. Precipitation Analysis at Fine Time Scales Using Multiple Satellites: Real-time and Research Products and Applications

    Science.gov (United States)

    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) in 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O"N-5O0S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  13. Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Real-time and Research Products and Applications

    Science.gov (United States)

    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guo-Jon

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O0N-50"S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, includmg: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  14. A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

    Science.gov (United States)

    Chen, Jung-Chieh

    This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

  15. Fate of ivermectin residues in ewes' milk and derived products

    NARCIS (Netherlands)

    Cerkvenik, V.; Perko, B.; Rogelj, I.; Doganoc, D.Z.; Skubic, V.; Beek, W.M.J.; Keukens, H.J.

    2004-01-01

    The fate of ivermectin (IVM) residues was studied throughout the processing of daily bulk milk from 30 ewes (taken up to 33 d following subcutaneous administration of 0·2 mg IVM/kg b.w.) in the following milk products: yoghurt made from raw and pasteurized milk; cheese after pressing; 30- and 60-day

  16. Photoelectrochemical Hydrogen Production Using New Combinatorial Chemistry Derived Materials

    Energy Technology Data Exchange (ETDEWEB)

    Jaramillo, Thomas F.; Baeck, Sung-Hyeon; Kleiman-Shwarsctein, Alan; Stucky, Galen D. (PI); McFarland, Eric W. (PI)

    2004-10-25

    Solar photoelectrochemical water-splitting has long been viewed as one of the “holy grails” of chemistry because of its potential impact as a clean, renewable method of fuel production. Several known photocatalytic semiconductors can be used; however, the fundamental mechanisms of the process remain poorly understood and no known material has the required properties for cost effective hydrogen production. In order to investigate morphological and compositional variations in metal oxides as they relate to opto-electrochemical properties, we have employed a combinatorial methodology using automated, high-throughput, electrochemical synthesis and screening together with conventional solid-state methods. This report discusses a number of novel, high-throughput instruments developed during this project for the expeditious discovery of improved materials for photoelectrochemical hydrogen production. Also described within this report are results from a variety of materials (primarily tungsten oxide, zinc oxide, molybdenum oxide, copper oxide and titanium dioxide) whose properties were modified and improved by either layering, inter-mixing, or doping with one or more transition metals. Furthermore, the morphologies of certain materials were also modified through the use of structure directing agents (SDA) during synthesis to create mesostructures (features 2-50 nm) that increased surface area and improved rates of hydrogen production.

  17. Deriving heat production from gaseous exchange: validity of the approach

    NARCIS (Netherlands)

    Gerrits, W.J.J.; Borne, van den J.J.G.C.; Labussière, E.

    2015-01-01

    The use of indirect calorimetry as a means to quantify heat production (Q) and net substrate oxidation has increased rapidly since the pioneering work of Lavoisier, and today, indirect calorimetry is often used as a reference for other measures of Q. Simple equations were developed and widely

  18. Understanding Financial Innovation: An Introduction to Derivative Financial Products.

    Science.gov (United States)

    Robinson, J. N.

    1992-01-01

    Explains the use of forwards, futures, swaps, and options in international currency trading. Argues that pricing options are based on the same basic principles as pricing other financial instruments. Concludes that, although financial markets have developed several new products, hedging and speculation involve similar processes. (CFR)

  19. Profitability of sweet potato production in derived savannah zone of ...

    African Journals Online (AJOL)

    This study examined profitability of sweet potato production in Odeda Local Government Area, Ogun State, Nigeria. The study was based on primary data collected from 82 sweet potato farmers through multistage sampling technique; analysed using descriptive statistics and budgetary techniques. The result revealed that ...

  20. Initial biochar effects on plant productivity derive from N fertilization

    NARCIS (Netherlands)

    Jeffery, S.L.; Memelink, Ilse; Hodgson, Edward; Jones, S.; Voorde, van de T.F.J.; Bezemer, T.M.; Mommer, L.; Groenigen, van J.W.

    2017-01-01

    Background and aim
    Biochar application to soil is widely claimed to increase plant productivity. However, the underlying mechanisms are still not conclusively described. Here, we aim to elucidate these mechanisms using stable isotope probing.
    Methods
    We conducted two experiments with

  1. Deriving Forest Harvesting Machine Productivity from Positional Data

    Science.gov (United States)

    T.P. McDonald; S.E. Taylor; R.B. Rummer

    2000-01-01

    Automated production study systems will provide researchers a valuable tool for developing cost and impact models of forest operations under a wide range of conditions, making the development of true planning tools for tailoring logging systems to a particular site a reality. An automated time study system for skidders was developed, and in this study application of...

  2. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; hide

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

  3. Satellite Radiation Products for Ocean Biology and Biogeochemistry: Needs, State-of-the-Art, Gaps, Development Priorities, and Opportunities

    Directory of Open Access Journals (Sweden)

    Robert Frouin

    2018-02-01

    Full Text Available Knowing the spatial and temporal distribution of the underwater light field, i.e., the spectral and angular structure of the radiant intensity at any point in the water column, is essential to understanding the biogeochemical processes that control the composition and evolution of aquatic ecosystems and their impact on climate and reaction to climate change. At present, only a few properties are reliably retrieved from space, either directly or via water-leaving radiance. Existing satellite products are limited to planar photosynthetically available radiation (PAR and ultraviolet (UV irradiance above the surface and diffuse attenuation coefficient. Examples of operational products are provided, and their advantages and drawbacks are examined. The usefulness and convenience of these products notwithstanding, there is a need, as expressed by the user community, for other products, i.e., sub-surface planar and scalar fluxes, average cosine, spectral fluxes (UV to visible, diurnal fluxes, absorbed fraction of PAR by live algae (APAR, surface albedo, vertical attenuation, and heating rate, and for associating uncertainties to any product on a pixel-by-pixel basis. Methodologies to obtain the new products are qualitatively discussed in view of most recent scientific knowledge and current and future satellite missions, and specific algorithms are presented for some new products, namely sub-surface fluxes and average cosine. A strategy and roadmap (short, medium, and long term for usage and development priorities is provided, taking into account needs and readiness level. Combining observations from satellites overpassing at different times and geostationary satellites should be pursued to improve the quality of daily-integrated radiation fields, and products should be generated without gaps to provide boundary conditions for general circulation and biogeochemical models. Examples of new products, i.e., daily scalar PAR below the surface, daily average

  4. SPATIOTEMPORAL VISUALIZATION OF TIME-SERIES SATELLITE-DERIVED CO2 FLUX DATA USING VOLUME RENDERING AND GPU-BASED INTERPOLATION ON A CLOUD-DRIVEN DIGITAL EARTH

    Directory of Open Access Journals (Sweden)

    S. Wu

    2017-10-01

    Full Text Available The ocean carbon cycle has a significant influence on global climate, and is commonly evaluated using time-series satellite-derived CO2 flux data. Location-aware and globe-based visualization is an important technique for analyzing and presenting the evolution of climate change. To achieve realistic simulation of the spatiotemporal dynamics of ocean carbon, a cloud-driven digital earth platform is developed to support the interactive analysis and display of multi-geospatial data, and an original visualization method based on our digital earth is proposed to demonstrate the spatiotemporal variations of carbon sinks and sources using time-series satellite data. Specifically, a volume rendering technique using half-angle slicing and particle system is implemented to dynamically display the released or absorbed CO2 gas. To enable location-aware visualization within the virtual globe, we present a 3D particlemapping algorithm to render particle-slicing textures onto geospace. In addition, a GPU-based interpolation framework using CUDA during real-time rendering is designed to obtain smooth effects in both spatial and temporal dimensions. To demonstrate the capabilities of the proposed method, a series of satellite data is applied to simulate the air-sea carbon cycle in the China Sea. The results show that the suggested strategies provide realistic simulation effects and acceptable interactive performance on the digital earth.

  5. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    Science.gov (United States)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  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. 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

  8. Recent Advances in Microbial Production of Aromatic Chemicals and Derivatives.

    Science.gov (United States)

    Noda, Shuhei; Kondo, Akihiko

    2017-08-01

    Along with the development of metabolic engineering and synthetic biology tools, various microbes are being used to produce aromatic chemicals. In microbes, aromatics are mainly produced via a common important precursor, chorismate, in the shikimate pathway. Natural or non-natural aromatics have been produced by engineering metabolic pathways involving chorismate. In the past decade, novel approaches have appeared to produce various aromatics or to increase their productivity, whereas previously, the targets were mainly aromatic amino acids and the strategy was deregulating feedback inhibition. In this review, we summarize recent studies of microbial production of aromatics based on metabolic engineering approaches. In addition, future perspectives and challenges in this research area are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Production of irradiated bone derivatives for odontology and traumatology

    International Nuclear Information System (INIS)

    Martin, Hugo R.; Murature, D.A.

    2004-01-01

    In 2003, the National Atomic Energy Commission (CNEA), the Industrial Human Tissue Processing Plant of the Cordoba University and the Cordoba Science Agency analyzed the joint installation and operation of a Gamma Radiosterilization Module for the production of sterile human bone tissues as allografts for odontology and traumatology. The irradiation procedures were developed at the CNEA's Ezeiza Atomic Center. The irradiated bone tissues are being used in odontology with an excellent clinical behaviour. (author)

  10. An analysis of FDA-approved drugs: natural products and their derivatives.

    Science.gov (United States)

    Patridge, Eric; Gareiss, Peter; Kinch, Michael S; Hoyer, Denton

    2016-02-01

    Natural products contribute greatly to the history and landscape of new molecular entities (NMEs). An assessment of all FDA-approved NMEs reveals that natural products and their derivatives represent over one-third of all NMEs. Nearly one-half of these are derived from mammals, one-quarter from microbes and one-quarter from plants. Since the 1930s, the total fraction of natural products has diminished, whereas semisynthetic and synthetic natural product derivatives have increased. Over time, this fraction has also become enriched with microbial natural products, which represent a significant portion of approved antibiotics, including more than two-thirds of all antibacterial NMEs. In recent years, the declining focus on natural products has impacted the pipeline of NMEs from specific classes, and this trend is likely to continue without specific investment in the pursuit of natural products. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Near Real Time Operational Satellite Ocean Color Products From NOAA OSPO CoastWatch Okeanos System:: Status and Challenges

    Science.gov (United States)

    Banghua Yan, B.

    2016-02-01

    Near real-time (NRT) ocean color (OC) satellite operation products are generated and distributed in NOAA Okeanos Operational Product System, by using the CWAPS including the Multi-Sensor Level (MSL) 12 and the chlorophyll-a frontal algorithms. Current OC operational products include daily chlorophyll concentration (anomaly), water turbidity, remote sensing reflectance and chlorophyll frontal products from Moderate-resolution Imaging Spectroradiometer (MODIS)/Aqua. The products have been widely applied to USA local and state ecosystem research, ecosystem observations, and fisheries managements for coastal and regional forecasting of ocean water quality, phytoplankton concentrations, and primary production. Users of the products have the National Ocean Service, National Marine Fisheries Service, National Weather Service, and Oceanic and Atmospheric Research. Recently, the OC products are being extended to S-NPP VIIRS to provide global NRT ocean color products to user community suh as National Weatrher Service for application for Global Data Assimilation System and Real-Time Ocean Forecast System. However, there remain some challenges in application of the products due to certain product quality and coverage issues. Recent efforts were made to provide a comprehensive web-based Quality Assurance (QA) tool for monitoring OC products quality in near real time mode, referring to http://www.ospo.noaa.gov/Products/ocean/color_new/color.htm. The new QA monitoring tool includes but not limited to the following advanced features applicable for MODIS/Aqua and NPP/VIIRS OC products: 1) Monitoring product quality in NRT mode; 2) Monitoring the availability and quality of OC products with time; 3) Detecting anomalous OC products due to low valid pixels and other quality issues. As an example, potential application and challenges of the ocean color products to oceanic oil spill detection are investigated. It is thus expected that the Okeanos ocean color operational system in

  12. Methods for conversion of lignocellulosic-derived products to transportation fuel precursors

    Science.gov (United States)

    Lilga, Michael A.; Padmaperuma, Asanga B.

    2017-10-03

    Methods are disclosed for converting a biomass-derived product containing levulinic acid and/or gamma-valerolactone to a transportation fuel precursor product containing diesel like hydrocarbons. These methods are expected to produce fuel products at a reduced cost relative to conventional approaches.

  13. Effects of titanium dioxide nanoparticles derived from consumer products on the marine diatom Thalassiosira pseudonana

    Science.gov (United States)

    Increased manufacture of TiO2 nano-products has caused concern about the potential toxicity of these products to the environment and in public health. Identification and confirmation of the presence of TiO2 nanoparticles derived from consumer products as opposed to industrial TiO...

  14. Preparing for Operational Use of High Priority Products from the Joint Polar Satellite System (JPSS) in Numerical Weather Prediction

    Science.gov (United States)

    Nandi, S.; Layns, A. L.; Goldberg, M.; Gambacorta, A.; Ling, Y.; Collard, A.; Grumbine, R. W.; Sapper, J.; Ignatov, A.; Yoe, J. G.

    2017-12-01

    This work describes end to end operational implementation of high priority products from National Oceanic and Atmospheric Administration's (NOAA) operational polar-orbiting satellite constellation, to include Suomi National Polar-orbiting Partnership (S-NPP) and the Joint Polar Satellite System series initial satellite (JPSS-1), into numerical weather prediction and earth systems models. Development and evaluation needed for the initial implementations of VIIRS Environmental Data Records (EDR) for Sea Surface Temperature ingestion in the Real-Time Global Sea Surface Temperature Analysis (RTG) and Polar Winds assimilated in the National Weather Service (NWS) Global Forecast System (GFS) is presented. These implementations ensure continuity of data in these models in the event of loss of legacy sensor data. Also discussed is accelerated operational implementation of Advanced Technology Microwave Sounder (ATMS) Temperature Data Records (TDR) and Cross-track Infrared Sounder (CrIS) Sensor Data Records, identified as Key Performance Parameters by the National Weather Service. Operational use of SNPP after 28 October, 2011 launch took more than one year due to the learning curve and development needed for full exploitation of new remote sensing capabilities. Today, ATMS and CrIS data positively impact weather forecast accuracy. For NOAA's JPSS initial satellite (JPSS-1), scheduled for launch in late 2017, we identify scope and timelines for pre-launch and post-launch activities needed to efficiently transition these capabilities into operations. As part of these alignment efforts, operational readiness for KPPs will be possible as soon as 90 days after launch. The schedule acceleration is possible because of the experience with S-NPP. NOAA operational polar-orbiting satellite constellation provides continuity and enhancement of earth systems observations out to 2036. Program best practices and lessons learned will inform future implementation for follow-on JPSS-3 and -4

  15. Comparison of the peak resolution and the stationary phase retention between the satellite and the planetary motions using the coil satellite centrifuge with counter-current chromatographic separation of 4-methylumbelliferyl sugar derivatives.

    Science.gov (United States)

    Shinomiya, Kazufusa; Zaima, Kazumasa; Harada, Yukina; Yasue, Miho; Harikai, Naoki; Tokura, Koji; Ito, Yoichiro

    2017-01-20

    Coil satellite centrifuge (CSC) produces the complex satellite motion consisting of the triplicate rotation of the coiled column around three axes including the sun axis (the angular velocity, ω 1 ), the planet axis (ω 2 ) and the satellite axis (the central axis of the column) (ω 3 ) according to the following formula: ω 1 =ω 2 +ω 3 . Improved peak resolution in the separation of 4-methylumbelliferyl sugar derivatives was achieved using the conventional multilayer coiled columns with ethyl acetate/1-butanol/water (3: 2: 5, v/v) for the lower mobile phase at the combination of the rotation speeds (ω 1 , ω 2 , ω 3 )=(300, 150, 150rpm), and (1:4:5, v/v) for the upper mobile phase at (300:100:200rpm). The effect of the satellite motion on the peak resolution and the stationary phase retention was evaluated by each CSC separation with the different rotation speeds of ω 2 and ω 3 under the constant revolution speed at ω 1 =300rpm. With the lower mobile phase, almost constant peak resolution and stationary phase retention were yielded regardless of the change of ω 2 and ω 3 , while with the upper mobile phase these two values were sensitively varied according to the different combination of ω 2 and ω 3 . For example, when ω 2 =147 or 200rpm is used, no stationary phase was retained in the coiled column while ω 2 =150rpm could retain enough volume of stationary phase for separation. On the other hand, the combined rotation speeds at (ω 1 , ω 2 , ω 3 )=(300, 300, 0rpm) or (300, 0, 300rpm) produced insufficient peak resolution regardless of the choice of the mobile phase apparently due to the lack of rotation speed except at (300, 0, 300rpm) with the upper mobile phase. At lower rotation speed of ω 1 =300rpm, better peak resolution and stationary phase retention were obtained by the satellite motion (ω 3 ) than by the planetary motion (ω 2 ), or ω 3 >ω 2 . The effect of the hydrophobicity of the two-phase solvent systems on the stationary phase

  16. Example of industrial valorisation of derivative products of Castor oil

    Directory of Open Access Journals (Sweden)

    Borg Patrick

    2009-07-01

    Full Text Available Known since antiquity, Castor Oil has been first used in medicine. Now, even if it remains present in small quantities as an excipient in many pharmaceutical specialties, it finds a lot of applicationsin cosmetics, industrial applications and chemical industry. Castor Oil specificity comes from its high content of ricinoleic acid (up to 85% that combines a double bond and an hydroxyl function in the heart of a 18 carbons linear chain. This particular structure is the key of an unique chemistry developed by ARKEMA that gives by thermal cracking a wide range of compounds with either 7 or 11 carbon atoms. A whole range of innovative chemistries and end use products are generated from these base reaction products. They are used in every-day life, to improve our comfort and safety but also in very specific applications with very high technical requirements. Synthesized from undecylenic acid, 11-amino-undecanoic acid, 100% based on renewable resources, is the precursor to biobased polymers combining high performance and sustainability: Rilsan®, Rilsan Fine Powder®, Pebax Rnew®.

  17. Comparison between satellite precipitation product and observation rain gauges in the Red-Thai Binh River Basin

    Science.gov (United States)

    Lakshmi, V.; Le, M. H.; Sutton, J. R. P.; Bui, D. D.; Bolten, J. D.

    2017-12-01

    The Red-ThaiBinh River is the second largest river in Vietnam in terms of economic impact and is home to around 29 million people. The river has been facing challenges for water resources allocation, which require reliable and routine hydrological assessments. However, hydrological analysis is difficult due to insufficient spatial coverage by rain gauges. Satellite-based precipitation estimates are a promising alternative with high-resolution in both time and space. This study aims at investigating the uncertainties in satellite-based precipitation product TRMM 3B42 v7.0 by comparing them against in-situ measurements over the Red-ThaiBinh River basin. The TRMM 3B42 v7.0 are assessed in terms of seasonal, monthly and daily variations over a 17-year period (1998 - 2014). Preliminary results indicate that at a daily scale, except for low Mean Bias Error (MBE), satellite based rainfall product has weak relationship with ground observation data, indicating by average performance of 0.326 and -0.485 for correlation coefficient and Nash Sutcliffe Efficiency (NSE), respectively. At monthly scale, we observe that the TRMM 3B42 v7.0 has higher correlation with the correlation increased significantly to 0.863 and NSE of 0.522. By analyzing wet season (May - October) and dry season (November - April) separately we find that the correlation between the TRMM 3B42 v7.0 with ground observations were higher for wet season than the dry season.

  18. Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

    Science.gov (United States)

    Sure, A.; Dikshit, O.

    2017-12-01

    Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

  19. Assessing the landscape context and conversion risk of protected areas using satellite data products

    Science.gov (United States)

    Svancara, Leona K.; Scott, J.M.; Loveland, Thomas R.; Pidgorna, Anna

    2009-01-01

    Since the establishment of the first national park (Yellowstone National Park in 1872) and the first wildlife refuge (Pelican Island in 1903), dramatic changes have occurred in both ecological and cultural landscapes across the U.S. The ability of these protected areas to maintain current levels of biodiversity depend, at least in part, on the integrity of the surrounding landscape. Our objective was to quantify and compare the extent and pattern of natural land cover, risk of conversion, and relationships with demographic and economic variables in counties near National Park Service units and U.S. Fish and Wildlife Service refuges with those counties distant from either type of protected area in the coterminous United States. Our results indicate that landscapes in counties within 10 km of both parks and refuges and those within 10 km of just parks were more natural, more intact, and more protected than those in counties within 10 km of just refuges and counties greater than 10 km from either protected area system. However, they also had greater human population density and change in population, indicating potential conversion risk since the percent of landscape protected averaged  2) in 76% of counties near both parks and refuges, 81% of counties near just parks, 91% of counties near just refuges, and 93% of distant counties. Thirteen percent of counties in the coterminous U.S. had moderate to high amounts of natural land cover (> 60%), low protection ( 20%). Although these areas are not the most critically endangered, they represent the greatest conservation opportunity, need, and urgency. Our approach is based on national level metrics that are simple, general, informative, and can be understood by broad audiences and by policy makers and managers to assess the health of lands surrounding parks and refuges. Regular monitoring of these metrics with satellite data products in counties surrounding protected areas provides a consistent, national level

  20. Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing.

    Science.gov (United States)

    Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve

    2018-04-09

    Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

  1. Risk communication related to animal products derived from biotechnology.

    Science.gov (United States)

    McCrea, D

    2005-04-01

    Previous chapters of this review have dealt with the key considerations related to the application of biotechnology in veterinary science and animal production. This article explores the theory and practice of risk communication and sets out the basic principles for good risk communication when dealing with new technologies, uncertainty, and cautious and sceptical consumers. After failure to communicate with consumers and stakeholders about the risk to human health from bovine spongiform encephalopathy (BSE) in the 1990s, Government Agencies in the United Kingdom have made significant improvements in risk communication. The official inquiry that followed the BSE crisis concluded that a policy of openness was the correct approach, and this article emphasises the importance of consultation, consistency and transparency. There are, however, many different factors that affect public perception of risk (religious, political, social, cultural, etc.) and developing effective risk communication strategies must take all of these complex issues into consideration.

  2. Comment on 'The remote sensing of ocean primary productivity - Use of a new data compilation to test satellite algorithms' by William Balch et al

    Science.gov (United States)

    Platt, Trevor; Sathyendranath, Shubha

    1993-01-01

    Various conclusions by Balch et al. (1992) about the current state of modeling primary production in the sea (lack of improvement in primary production models, since 1957, utility of analytical models, and merits or weaknesses of complex models) are commented on. It is argued that since they are based on a false premise, these conclusions are not robust, and that the approach used by Balch et al. (the model of Platt and Sathyendranath, 1988) was inadequate for the question they set out to address. The present criticism is based mainly on the issue of whether implementation was correct with respect to parameter selection. It is concluded that the findings of Balch et al. with respect to the model of Platt and Sathyendranath is unreliable. Balch replies that satellite-derived estimates of primary production should be compared directly to that measured in situ in as many regions as possible. This will provide a first-order estimate of the magnitude of the error involved in estimating primary production from space.

  3. The Swarm Satellite Constellation Application and Research Facility (SCARF) and Swarm data products

    DEFF Research Database (Denmark)

    Olsen, Nils; Friis-Christensen, Eigil; Floberghagen, R.

    2013-01-01

    Swarm, a three-satellite constellation to study the dynamics of the Earth's magnetic field and its interactions with the Earth system, is expected to be launched in late 2013. The objective of the Swarm mission is to provide the best ever survey of the geomagnetic field and its temporal evolution...

  4. Monitoring Multidecadal satellite earth observation of soil moisture products through land surface reanalysis

    NARCIS (Netherlands)

    Albergel, C.; Dorigo, W.; Balsamo, G.; Sabatar, J; de Rosnay, P.; Isaksen, I; Brocca, L; de Jeu, R.A.M.; Wagner, W.

    2013-01-01

    Soil moisture from ERA-Land, a revised version of the land surface components of the European Centre for Medium-Range Weather Forecasts Interim reanalysis (ERA-Interim), is used to monitor at a global scale the consistency of a new microwave based multi-satellite surface soil moisture date set

  5. An Historical Overview of the Production Requirement for the Satellite Technology Demonstration. Technical Report No. 0504.

    Science.gov (United States)

    Smith, Myron P.; Sosey, Phillip

    The Satellite Technology Demonstration employs the latest telecommunications technology to deliver community oriented programing to rural areas. To meet the demand for contemporary broadcasts responsive to community needs, a studio was constructed in the Denver area to produce and coordinate future programs for the Rocky Mountains area. Problems…

  6. Evaluation of the MiKlip decadal prediction system using satellite based cloud products

    Directory of Open Access Journals (Sweden)

    Thomas Spangehl

    2016-12-01

    Full Text Available The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1 provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF and from the International Satellite Cloud Climatology Project (ISCCP. The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA, analysis rank histograms (ARH and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0 emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP. By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only

  7. 17 CFR 39.4 - Procedures for implementing derivatives clearing organization rules and clearing new products.

    Science.gov (United States)

    2010-04-01

    ... 17 Commodity and Securities Exchanges 1 2010-04-01 2010-04-01 false Procedures for implementing derivatives clearing organization rules and clearing new products. 39.4 Section 39.4 Commodity and Securities Exchanges COMMODITY FUTURES TRADING COMMISSION DERIVATIVES CLEARING ORGANIZATIONS § 39.4 Procedures for...

  8. Cost function approach for estimating derived demand for composite wood products

    Science.gov (United States)

    T. C. Marcin

    1991-01-01

    A cost function approach was examined for using the concept of duality between production and input factor demands. A translog cost function was used to represent residential construction costs and derived conditional factor demand equations. Alternative models were derived from the translog cost function by imposing parameter restrictions.

  9. Kojyl cinnamate ester derivatives promote adiponectin production during adipogenesis in human adipose tissue-derived mesenchymal stem cells.

    Science.gov (United States)

    Rho, Ho Sik; Hong, Soo Hyun; Park, Jongho; Jung, Hyo-Il; Park, Young-Ho; Lee, John Hwan; Shin, Song Seok; Noh, Minsoo

    2014-05-01

    The subcutaneous fat tissue mass gradually decreases with age, and its regulation is a strategy to develop anti-aging compounds to ameliorate the photo-aging of human skin. The adipogenesis of human adipose tissue-mesenchymal stem cells (hAT-MSCs) can be used as a model to discover novel anti-aging compounds. Cinnamomum cassia methanol extracts were identified as adipogenesis-promoting agents by natural product library screening. Cinnamates, the major chemical components of Cinnamomum cassia extracts, promoted adipogenesis in hAT-MSCs. We synthesized kojyl cinnamate ester derivatives to improve the pharmacological activity of cinnamates. Structure-activity studies of kojyl cinnamate derivatives showed that both the α,β-unsaturated carbonyl ester group and the kojic acid moiety play core roles in promoting adiponectin production during adipogenesis in hAT-MSCs. We conclude that kojyl cinnamate ester derivatives provide novel pharmacophores that can regulate adipogenesis in hAT-MSCs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Validation of ozone profile retrievals derived from the OMPS LP version 2.5 algorithm against correlative satellite measurements

    Science.gov (United States)

    Kramarova, Natalya A.; Bhartia, Pawan K.; Jaross, Glen; Moy, Leslie; Xu, Philippe; Chen, Zhong; DeLand, Matthew; Froidevaux, Lucien; Livesey, Nathaniel; Degenstein, Douglas; Bourassa, Adam; Walker, Kaley A.; Sheese, Patrick

    2018-05-01

    The Limb Profiler (LP) is a part of the Ozone Mapping and Profiler Suite launched on board of the Suomi NPP satellite in October 2011. The LP measures solar radiation scattered from the atmospheric limb in ultraviolet and visible spectral ranges between the surface and 80 km. These measurements of scattered solar radiances allow for the retrieval of ozone profiles from cloud tops up to 55 km. The LP started operational observations in April 2012. In this study we evaluate more than 5.5 years of ozone profile measurements from the OMPS LP processed with the new NASA GSFC version 2.5 retrieval algorithm. We provide a brief description of the key changes that had been implemented in this new algorithm, including a pointing correction, new cloud height detection, explicit aerosol correction and a reduction of the number of wavelengths used in the retrievals. The OMPS LP ozone retrievals have been compared with independent satellite profile measurements obtained from the Aura Microwave Limb Sounder (MLS), Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Odin Optical Spectrograph and InfraRed Imaging System (OSIRIS). We document observed biases and seasonal differences and evaluate the stability of the version 2.5 ozone record over 5.5 years. Our analysis indicates that the mean differences between LP and correlative measurements are well within required ±10 % between 18 and 42 km. In the upper stratosphere and lower mesosphere (> 43 km) LP tends to have a negative bias. We find larger biases in the lower stratosphere and upper troposphere, but LP ozone retrievals have significantly improved in version 2.5 compared to version 2 due to the implemented aerosol correction. In the northern high latitudes we observe larger biases between 20 and 32 km due to the remaining thermal sensitivity issue. Our analysis shows that LP ozone retrievals agree well with the correlative satellite observations in characterizing vertical, spatial and temporal

  11. Implementation of the DINEOF ArcGIS Toolbox: Case study of reconstruction of Chlorophyll-a missing data over the Mediterranean using MyOcean satellite data products.

    Science.gov (United States)

    Nikolaidis, Andreas; Stylianou, Stavros; Georgiou, Georgios; Hadjimitsis, Diofantos; Akylas, Evangelos

    2014-05-01

    ArcGIS® is a well known standard on Geographical Information Systems, used over the years for various remote sensing procedures. During the last decade, Rixen (2003) and Azcarate (2011) presented the DINEOF (Data Interpolating Empirical Orthogonal Functions) method, a EOF-based technique to reconstruct missing data in satellite images. The recent results of the DINEOF method in various experimental trials (Wang and Liu, 2013; Nikolaidis et al., 2013;2014) showed that this computationally affordable method leads to effective reconstruction of missing data from geophysical fields, such as chlorophyll-a, sea surface temperatures or salinities and geophysical fields derived from satellite data. Implementing the method in a GIS system will lead to a complete and integrated approach, enhancing its applicability. The inclusion of statistical tools within the GIS, will multiply the effectiveness, providing interoperability with other sources in the same application environment. This may be especially useful in studies where various different kinds of data are of interest. For this purpose, in this study we have implemented a new GIS toolbox that aims at automating the usage of the algorithm, incorporating the DINEOF codes provided by GHER (GeoHydrodynamics and Environment Research Group of University of Liege) into the ArcGIS®. A case-study of filling the chlorophyll-a missing data in the Mediterranean Sea area, for a 18-day period is analyzed, as an example for the effectiveness and simplicity of the toolbox. More specifically, we focus on chlorophyll-a MODIS satellite data collected by CNR-ISAC (Italian National Research Council, Institute of Atmospheric Sciences and Climate), from the respective products of MyOcean2® organization, that provides free online access to Level 3, with 1 km resolution. All the daily products with an initial level of only 27% data coverage were successfully reconstructed over the Mediterranean Sea. [1] Alvera-Azcárate A., Barth A

  12. Local time dependences of electron flux changes during substorms derived from mulit-satellite observation at synchronous orbit

    International Nuclear Information System (INIS)

    Nagai, T.

    1982-01-01

    Energetic electron (energy higher than 2 MeV) observation by a synchronous satellite chain (which consists of GOES 2, GOES 3, and GMS covering the local time extent of approximately 10 hr) have been used to study the large-scale characteristics of the dynamic behavior in the near-earth magnetosphere for substorms, in which low-latitude positive bay aspects are clearly seen in the ground magnetic data. Simultaneous multi-satellite observations have clearly demonstrated the local time dependence of electron flux changes during substorms and the longitudinal extent of electron flux variations. Before a ground substorm onset the energetic electron flux decreases in a wide longitudinal region of the nighttime and the flux decrease is seen even on the afternoonside. For the flux behavior associated with the onset of the substorm expansion phase, there exists a demarcation line, the LT position of which can be represented as LT = 24.3-1.5 K/sub p/. The flux shows a recovery to a normal level east of the demarcation line, and it shows a decrease west of the demarcation line. The region of the flux decrease during the expansion phase is restricted, and it is observed mainly on the afternoonside. The afternoonside flux decrease has a different characteristic from the nightside flux decrease preceding the expansion phase. The nighside flux decrease-recovery sequence is observed in a wide region of more than 6 hr in the nighttime and the center of this variation exists in the premidnight region. It should be noted that the afternoonside flux decrease is not observed for every substorm and the nightside signature noted that the afternoonside flux sometimes becomes a dominent feature even on the afternoonside

  13. Towards a merged satellite and in situ fluorescence ocean chlorophyll product

    OpenAIRE

    Lavigne, H.; D'Ortenzio, F.; Claustre, H.; Poteau, A.

    2012-01-01

    Understanding the ocean carbon cycle requires a precise assessment of phytoplankton biomass in the oceans. In terms of numbers of observations, satellite data represents the largest available data set. However, as they are limited to surface waters, they have to be merged with in situ observations. Amongst the in situ data, fluorescence profiles constitute the greatest data set available, because fluorometers operate routinely on oceanographic cruise since the seventies. Nevertheless,...

  14. The application of transcriptomics in the comparative safety assessment of (GMO-derived) plant products

    NARCIS (Netherlands)

    Kok, E.J.

    2008-01-01

    National and international organizations have discussed current approaches to the safety assessment of complex (plant) food products in general and the safety assessment of GMO-derived food products in particular. One of the recommendations of different expert meetings was that the new analytical

  15. Nuclear-derived techniques improve cattle productivity and milk quality in Cameroon

    International Nuclear Information System (INIS)

    Dixit, Aabha

    2016-01-01

    Increasing agricultural production and improving the quality of milk and meat are key to combating poverty and increasing food security in Africa. Countries such as Cameroon are increasingly turning to innovative, nuclear and nuclear-derived techniques to control and prevent diseases among livestock, and boost cattle and milk production.

  16. Biorefineries for the production of top building block chemicals and their derivatives

    DEFF Research Database (Denmark)

    Choi, Sol; Song, Chan Woo; Shin, Jae Ho

    2015-01-01

    commercialized or are close to commercialization. In this paper, we review the current status of biorefinery development for the production of these platform chemicals and their derivatives. In addition, current technological advances on industrial strain development for the production of platform chemicals...... years after its announcement, many studies have been performed for the development of efficient technologies for the bio-based production of these chemicals and derivatives. Now, ten chemicals among these top 12 chemicals, excluding the l-aspartic acid and 3-hydroxybutyrolactone, have already been...

  17. Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.

    Directory of Open Access Journals (Sweden)

    Wenquan Zhu

    Full Text Available Carbon Flux Phenology (CFP can affect the interannual variation in Net Ecosystem Exchange (NEE of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands, using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU by more than 70% and End of Carbon Uptake (ECU by more than 60%. The Root Mean Square Error (RMSE of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.

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

    Science.gov (United States)

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

    2017-12-01

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

  19. 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.

  20. Hurricane Satellite (HURSAT) Microwave (MW)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Hurricane Satellite (HURSAT) from Microwave (MW) observations of tropical cyclones worldwide data consist of raw satellite observations. The data derive from the...

  1. Monitoring Cyanobacteria with Satellites Webinar

    Science.gov (United States)

    real-world satellite applications can quantify cyanobacterial harmful algal blooms and related water quality parameters. Provisional satellite derived cyanobacteria data and different software tools are available to state environmental and health agencies.

  2. Intraseasonal patterns in coastal plankton biomass off central Chile derived from satellite observations and a biochemical model

    Science.gov (United States)

    Gomez, Fabian A.; Spitz, Yvette H.; Batchelder, Harold P.; Correa-Ramirez, Marco A.

    2017-10-01

    Subseasonal (5-130 days) environmental variability can strongly affect plankton dynamics, but is often overlooked in marine ecology studies. We documented the main subseasonal patterns of plankton biomass in the coastal upwelling system off central Chile, the southern part of the Humboldt System. Subseasonal variability was extracted from temporal patterns in satellite data of wind stress, sea surface temperature, and chlorophyll from the period 2003-2011, and from a realistically forced eddy-resolving physical-biochemical model from 2003 to 2008. Although most of the wind variability occurs at submonthly frequencies (< 30 days), we found that the dominant subseasonal pattern of phytoplankton biomass is within the intraseasonal band (30-90 days). The strongest intraseasonal coupling between wind and plankton is in spring-summer, when increased solar radiation enhances the phytoplankton response to upwelling. Biochemical model outputs show intraseasonal shifts in plankton community structure, mainly associated with the large fluctuations in diatom biomass. Diatom biomass peaks near surface during strong upwelling, whereas small phytoplankton biomass peaks at subsurface depths during relaxation or downwelling periods. Strong intraseasonally forced changes in biomass and species composition could strongly impact trophodynamics connections in the ecosystem, including the recruitment of commercially important fish species such as common sardine and anchovy. The wind-driven variability of chlorophyll concentration was connected to mid- and high-latitude atmospheric anomalies, which resemble disturbances with frequencies similar to the tropical Madden-Julian Oscillation.

  3. Estimation of biogenic emissions with satellite-derived land use and land cover data for air quality modeling of Houston-Galveston ozone nonattainment area.

    Science.gov (United States)

    Byun, Daewon W; Kim, Soontae; Czader, Beata; Nowak, David; Stetson, Stephen; Estes, Mark

    2005-06-01

    The Houston-Galveston Area (HGA) is one of the most severe ozone non-attainment regions in the US. To study the effectiveness of controlling anthropogenic emissions to mitigate regional ozone nonattainment problems, it is necessary to utilize adequate datasets describing the environmental conditions that influence the photochemical reactivity of the ambient atmosphere. Compared to the anthropogenic emissions from point and mobile sources, there are large uncertainties in the locations and amounts of biogenic emissions. For regional air quality modeling applications, biogenic emissions are not directly measured but are usually estimated with meteorological data such as photo-synthetically active solar radiation, surface temperature, land type, and vegetation database. In this paper, we characterize these meteorological input parameters and two different land use land cover datasets available for HGA: the conventional biogenic vegetation/land use data and satellite-derived high-resolution land cover data. We describe the procedures used for the estimation of biogenic emissions with the satellite derived land cover data and leaf mass density information. Air quality model simulations were performed using both the original and the new biogenic emissions estimates. The results showed that there were considerable uncertainties in biogenic emissions inputs. Subsequently, ozone predictions were affected up to 10 ppb, but the magnitudes and locations of peak ozone varied each day depending on the upwind or downwind positions of the biogenic emission sources relative to the anthropogenic NOx and VOC sources. Although the assessment had limitations such as heterogeneity in the spatial resolutions, the study highlighted the significance of biogenic emissions uncertainty on air quality predictions. However, the study did not allow extrapolation of the directional changes in air quality corresponding to the changes in LULC because the two datasets were based on vastly different

  4. Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

    Science.gov (United States)

    Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

    2011-11-01

    In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

  5. Evaluation of altimetry-derived surface current products using Lagrangian drifter trajectories in the eastern Gulf of Mexico

    Science.gov (United States)

    Liu, Yonggang; Weisberg, Robert H.; Vignudelli, Stefano; Mitchum, Gary T.

    2014-05-01

    Lagrangian particle trajectory models based on several altimetry-derived surface current products are used to hindcast the drifter trajectories observed in the eastern Gulf of Mexico during May to August 2010 (the Deepwater Horizon oil spill incident). The performances of the trajectory models are gauged in terms of Lagrangian separation distances (d) and a nondimensional skill score (s), respectively. A series of numerical experiments show that these altimetry-based trajectory models have about the same performance, with a certain improvement by adding surface wind Ekman components, especially over the shelf region. However, their hindcast skills are slightly better than those of the data assimilative numerical model output. After 3 days' simulation the altimetry-based trajectory models have mean d values of 75-83 and 34-42 km (s values of 0.49-0.51 and 0.35-0.43) in the Gulf of Mexico deep water area and on the West Florida Continental Shelf, respectively. These satellite altimetry data products are useful for providing essential information on ocean surface currents of use in water property transports, offshore oil and gas operations, hazardous spill mitigation, search and rescue, etc.

  6. Satellite-derived surface and sub-surface water storage in the Ganges–Brahmaputra River Basin

    Directory of Open Access Journals (Sweden)

    Fabrice Papa

    2015-09-01

    New hydrological insights: Basin-scale monthly SWS variations for the period 2003–2007 show a mean annual amplitude of ∼410 km3, contributing to about 45% of the Gravity Recovery And Climate Experiment (GRACE-derived total water storage variations (TWS. During the drought-like conditions in 2006, we estimate that the SWS deficit over the entire GB basin in July–August–September was about 30% as compared to other years. The SWS variations are then used to decompose the GB GRACE-derived TWS and isolate the variations of SSWS whose mean annual amplitude is estimated to be ∼550 km3. This new dataset of water storage variations represent an unprecedented source of information for hydrological and climate modeling studies of the ISC.

  7. Production of solar radiation bankable datasets from high-resolution solar irradiance derived with dynamical downscaling Numerical Weather prediction model

    Directory of Open Access Journals (Sweden)

    Yassine Charabi

    2016-11-01

    Full Text Available A bankable solar radiation database is required for the financial viability of solar energy project. Accurate estimation of solar energy resources in a country is very important for proper siting, sizing and life cycle cost analysis of solar energy systems. During the last decade an important progress has been made to develop multiple solar irradiance database (Global Horizontal Irradiance (GHI and Direct Normal Irradiance (DNI, using satellite of different resolution and sophisticated models. This paper assesses the performance of High-resolution solar irradiance derived with dynamical downscaling Numerical Weather Prediction model with, GIS topographical solar radiation model, satellite data and ground measurements, for the production of bankable solar radiation datasets. For this investigation, NWP model namely Consortium for Small-scale Modeling (COSMO is used for the dynamical downscaling of solar radiation. The obtained results increase confidence in solar radiation data base obtained from dynamical downscaled NWP model. The mean bias of dynamical downscaled NWP model is small, on the order of a few percents for GHI, and it could be ranked as a bankable datasets. Fortunately, these data are usually archived in the meteorological department and gives a good idea of the hourly, monthly, and annual incident energy. Such short time-interval data are valuable in designing and operating the solar energy facility. The advantage of the NWP model is that it can be used for solar radiation forecast since it can estimate the weather condition within the next 72–120 hours. This gives a reasonable estimation of the solar radiation that in turns can be used to forecast the electric power generation by the solar power plant.

  8. Peak Satellite-to-Earth Data Rates Derived From Measurements of a 20 Gbps Bread-Board Modem

    Science.gov (United States)

    Landon, David G.; Simons, Rainee N.; Wintucky, Edwin G.; Sun, Jun Y.; Winn, James S.; Laraway, Stephen A.; McIntire, William K.; Metz, John L.; Smith, Francis J.

    2011-01-01

    A prototype data link using a Ka-band space qualified, high efficiency 200 W TWT amplifier and a bread-board modem emulator were created to explore the feasibility of very high speed communications in satellite-to-earth applications. Experiments were conducted using a DVB-S2-like waveform with modifications to support up to 20 Gbps through the addition of 128-Quadrature Amplitude Modulation (QAM). Limited by the bandwidth of the amplifier, a constant peak symbol rate of 3.2 Giga-symbols/sec was selected and the modulation order was varied to explore what peak data rate might be supported by an RF link through this amplifier. Using 128-QAM, an implementation loss of 3 dB was observed at 20 Gbps, and the loss decreased as data rate or bandwidth were reduced. Building on this measured data, realistic link budget calculations were completed. Low-Earth orbit (LEO) missions based on this TWTA with reasonable hardware assumptions and antenna sizing are found to be bandwidth-limited, rather than power-limited, making the spectral efficiency of 9/10-rate encoded 128-QAM very attractive. Assuming a bandwidth allocation of 1 GHz, these computations indicate that low-Earth orbit vehicles could achieve data rates up to 5 Gbps-an order of magnitude beyond the current state-of-practice, yet still within the processing power of a current FPGA-based software-defined modem. The measured performance results and a description of the experimental setup are presented to support these conclusions.

  9. Satellite-derived submarine melt rates and mass balance (2011-2015) for Greenland's largest remaining ice tongues

    Science.gov (United States)

    Wilson, Nat; Straneo, Fiammetta; Heimbach, Patrick

    2017-12-01

    Ice-shelf-like floating extensions at the termini of Greenland glaciers are undergoing rapid changes with potential implications for the stability of upstream glaciers and the ice sheet as a whole. While submarine melting is recognized as a major contributor to mass loss, the spatial distribution of submarine melting and its contribution to the total mass balance of these floating extensions is incompletely known and understood. Here, we use high-resolution WorldView satellite imagery collected between 2011 and 2015 to infer the magnitude and spatial variability of melt rates under Greenland's largest remaining ice tongues - Nioghalvfjerdsbræ (79 North Glacier, 79N), Ryder Glacier (RG), and Petermann Glacier (PG). Submarine melt rates under the ice tongues vary considerably, exceeding 50 m a-1 near the grounding zone and decaying rapidly downstream. Channels, likely originating from upstream subglacial channels, give rise to large melt variations across the ice tongues. We compare the total melt rates to the influx of ice to the ice tongue to assess their contribution to the current mass balance. At Petermann Glacier and Ryder Glacier, we find that the combined submarine and aerial melt approximately balances the ice flux from the grounded ice sheet. At Nioghalvfjerdsbræ the total melt flux (14.2 ± 0.96 km3 a-1 w.e., water equivalent) exceeds the inflow of ice (10.2 ± 0.59 km3 a-1 w.e.), indicating present thinning of the ice tongue.

  10. Comparison of surface energy fluxes with satellite-derived surface energy flux estimates from a shrub-steppe

    International Nuclear Information System (INIS)

    Kirkham, R.R.

    1993-12-01

    This thesis relates the components of the surface energy balance (i.e., net radiation, sensible and latent heat flux densities, soil heat flow) to remotely sensed data for native vegetation in a semi-arid environment. Thematic mapper data from Landsat 4 and 5 were used to estimate net radiation, sensible heat flux (H), and vegetation amount. Several sources of ground truth were employed. They included soil water balance using the neutron thermalization method and weighing lysimeters, and the measurement of energy fluxes with the Bowen ratio energy balance (BREB) technique. Sensible and latent heat flux were measured at four sites on the U.S. Department of Energy's Hanford Site using a weighing lysimeter and/or BREB stations. The objective was to calibrate an aerodynamic transport equation that related H to radiant surface temperature. The transport equation was then used with Landsat thermal data to generate estimates of H and compare these estimates against H values obtained with BREB/lysimeters at the time of overflight. Landsat and surface meteorologic data were used to estimate the radiation budget terms at the surface. Landsat estimates of short-wave radiation reflected from the surface correlate well with reflected radiation measured using inverted Eppley pyranometers. Correlation of net radiation estimates determined from satellite data, pyranometer, air temperature, and vapor pressure compared to net radiometer values obtained at time of overflight were excellent for a single image, but decrease for multiple images. Soil heat flux, G T , is a major component of the energy balance in arid systems and G T generally decreases as vegetation cover increases. Normalized difference vegetation index (NDVI) values generated from Landsat thermatic mapper data were representative of field observations of the presence of green vegetation, but it was not possible to determine a single relationship between NDVI and G T for all sites

  11. Multiscale assessment of progress of electrification in Indonesia based on brightness level derived from nighttime satellite imagery.

    Science.gov (United States)

    Ramdani, Fatwa; Setiani, Putri

    2017-06-01

    Availability of electricity can be used as an indicator to proximate parameters related to human well-being. Overall, the electrification process in Indonesia has been accelerating in the past two decades. Unfortunately, monitoring the country's progress on its effort to provide wider access to electricity poses challenges due to inconsistency of data provided by each national bureau, and limited availability of information. This study attempts to provide a reliable measure by employing nighttime satellite imagery to observe and to map the progress of electrification within a duration of 20 years, from 1993 to 2013. Brightness of 67,021 settlement-size points in 1993, 2003, and 2013 was assessed using data from DMSP/OLS instruments to study the electrification progress in the three service regions (Sumatera, Java-Bali, and East Indonesia) of the country's public electricity company, PLN. Observation of all service areas shows that the increase in brightness, which correspond with higher electricity development and consumption, has positive correlation with both population density (R 2  = 0.70) and urban change (R 2  = 0.79). Moreover, urban change has a stronger correlation with brightness, which is probably due to the high energy consumption in urban area per capita. This study also found that the brightness in Java-Bali region is very dominant, while the brightness in other areas has been lagging during the period of analysis. The slow development of electricity infrastructure, particularly in major parts of East Indonesia region, affects the low economic growth in some areas and formed vicious cycle.

  12. Impact of highway construction on land surface energy balance and local climate derived from LANDSAT satellite data.

    Science.gov (United States)

    Nedbal, Václav; Brom, Jakub

    2018-08-15

    Extensive construction of highways has a major impact on the landscape and its structure. They can also influence local climate and heat fluxes in the surrounding area. After the removal of vegetation due to highway construction, the amount of solar radiation energy used for plant evapotranspiration (latent heat flux) decreases, bringing about an increase in landscape surface temperature, changing the local climate and increasing surface run-off. In this study, we evaluated the impact of the D8 highway construction (Central Bohemia, Czech Republic) on the distribution of solar radiation energy into the various heat fluxes (latent, sensible and ground heat flux) and related surface functional parameters (surface temperature and surface wetness). The aim was to describe the severity of the impact and the distance from the actual highway in which it can be observed. LANDSAT multispectral satellite images and field meteorological measurements were used to calculate surface functional parameters and heat balance before and during the highway construction. Construction of a four-lane highway can influence the heat balance of the landscape surface as far as 90m in the perpendicular direction from the highway axis, i.e. up to 75m perpendicular from its edge. During a summer day, the decrease in evapotranspired water can reach up to 43.7m 3 per highway kilometre. This means a reduced cooling effect, expressed as the decrease in latent heat flux, by an average of 29.7MWh per day per highway kilometre and its surroundings. The loss of the cooling ability of the land surface by evaporation can lead to a rise in surface temperature by as much as 7°C. Thus, the results indicate the impact of extensive line constructions on the local climate. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. The Precipitation Products Generation Chain for the EUMETSAT Hydrological Satellite Application Facility at C.N.M.C.A.

    Science.gov (United States)

    Zauli, Francesco; Biron, Daniele; Melfi, Davide

    2009-11-01

    The EUMETSA T Satellite Application Facility in support to Hydrology (H-SAF) focuses on the development of new geophysical products on precipitation, soil moisture and snow parameters and the utilisation of these parameters in hydrological models, NWP models and water management. The development phase of the H-SAF started in September 2005 under the leadership of Italian Meteorological Service.The Centro Nazionale di Meteorologia e Climatologia Aeronautica (C.N.M.C.A.), the Italian National Weather Centre, that physically hosts the generation chain of precipitation products, developed activities to reach the final target: development of algorithms, validation of results, implementation of operative procedure to supply the service and to monitor the service performances.The paper shows the recent architectural review of H- SAF precipitation group, stressing components of operation for high sustainability, full redundancy, absolute continuity of service.

  14. Trustworthy Variant Derivation with Translation Validation for Safety Critical Product Lines

    DEFF Research Database (Denmark)

    Iosif-Lazăr, Alexandru Florin; Wasowski, Andrzej

    2016-01-01

    Software product line (SPL) engineering facilitates development of entire families of software products with systematic reuse. Model driven SPLs use models in the design and development process. In the safety critical domain, validation of models and testing of code increases the quality...... of the products altogether. However, to maintain this trustworthiness it is necessary to know that the SPL tools, which manipulate models and code to derive concrete product variants, do not introduce errors in the process. We propose a general technique of checking correctness of product derivation tools through...... translation validation. We demonstrate it using Featherweight VML—a core language for separate variability modeling relying on a single kind of variation point to define transformations of artifacts seen as object models. We use Featherweight VML with its semantics as a correctness specification...

  15. Accuracy Investigation of PPP Method Versus Relative Positioning Using Different Satellite Ephemerides Products Near/Under Forest Environment

    Directory of Open Access Journals (Sweden)

    Taylan Ocalan

    2016-10-01

    Full Text Available In recent years, due to the increase in providers of orbit and clock corrections of satellites for data evaluation in real-time and post-processing the method of Precise Point Positioning (PPP using measurements of Global Navigation Satellite System (GNSS and Web-based online positioning services have become widespread. Owing to some advantages, such as work-duration and cost-effectiveness, many of users have implemented PPP method instead of the traditional relative positioning method for several applications. On GNSS applications the quality of satellite ephemerides products used for data evaluation is a significant factor that affects the results in post-processing solutions either applying relative or PPP methods on analyses. These products, classified as ultra-rapid, rapid and final orbits, are regularly provided by several national and international organizations to the users. In this paper, the accuracy of PPP method has been studied comparing the outcomes from various online Web services using different software and satellite ephemerides products. For this purpose, three test points were established in a place with completely free satellite visibility (AC01 and on the other two places with partially (YC01 and vastly (KC01 prevention of satellite signals near and within a forest area at Campus of Davutpaşa of the Yildiz Technical University in Istanbul. At these stations, static observations have been conducted with a time span of 6 hours on 4th May 2015. The dataset collected using Topcon HiperPro receiver, a receiver for GPS and GLONASS data, was evaluated manually by means of the Bernese v5.2 (BSW and GIPSY-OASIS v6.3 (Gipsy scientific software. Moreover, the GNSS data were also proceeded using six different Web-based online services (AUSPOS, OPUS, CSRS-PPP, APPS, GAPS, Trimble-RTX with ultra-rapid, rapid and final satellite ephemerides products. For the station with free satellite visibility (AC01, the analyses of outcomes indicate a

  16. Particle production after inflation with non-minimal derivative coupling to gravity

    International Nuclear Information System (INIS)

    Ema, Yohei; Jinno, Ryusuke; Nakayama, Kazunori; Mukaida, Kyohei

    2015-01-01

    We study cosmological evolution after inflation in models with non-minimal derivative coupling to gravity. The background dynamics is solved and particle production associated with rapidly oscillating Hubble parameter is studied in detail. In addition, production of gravitons through the non-minimal derivative coupling with the inflaton is studied. We also find that the sound speed squared of the scalar perturbation oscillates between positive and negative values when the non-minimal derivative coupling dominates over the minimal kinetic term. This may lead to an instability of this model. We point out that the particle production rates are the same as those in the Einstein gravity with the minimal kinetic term, if we require the sound speed squared is positive definite

  17. Reusing Joint Polar Satellite System (jpss) Ground System Components to Process AURA Ozone Monitoring Instrument (omi) Science Products

    Science.gov (United States)

    Moses, J. F.; Jain, P.; Johnson, J.; Doiron, J. A.

    2017-12-01

    New Earth observation instruments are planned to enable advancements in Earth science research over the next decade. Diversity of Earth observing instruments and their observing platforms will continue to increase as new instrument technologies emerge and are deployed as part of National programs such as Joint Polar Satellite System (JPSS), Geostationary Operational Environmental Satellite system (GOES), Landsat as well as the potential for many CubeSat and aircraft missions. The practical use and value of these observational data often extends well beyond their original purpose. The practicing community needs intuitive and standardized tools to enable quick unfettered development of tailored products for specific applications and decision support systems. However, the associated data processing system can take years to develop and requires inherent knowledge and the ability to integrate increasingly diverse data types from multiple sources. This paper describes the adaptation of a large-scale data processing system built for supporting JPSS algorithm calibration and validation (Cal/Val) node to a simplified science data system for rapid application. The new configurable data system reuses scalable JAVA technologies built for the JPSS Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) system to run within a laptop environment and support product generation and data processing of AURA Ozone Monitoring Instrument (OMI) science products. Of particular interest are the root requirements necessary for integrating experimental algorithms and Hierarchical Data Format (HDF) data access libraries into a science data production system. This study demonstrates the ability to reuse existing Ground System technologies to support future missions with minimal changes.

  18. Exploring Global Patterns in Human Appropriation of Net Primary Production Using Earth Observation Satellites and Statistical Data

    Science.gov (United States)

    Imhoff, M.; Bounoua, L.

    2004-12-01

    A unique combination of satellite and socio-economic data were used to explore the relationship between human consumption and the carbon cycle. Biophysical models were applied to consumption data to estimate the annual amount of Earth's terrestrial net primary production humans require for food, fiber and fuel using the same modeling architecture as satellite-supported NPP measurements. The amount of Earth's NPP required to support human activities is a powerful measure of the aggregate human impacts on the biosphere and indicator of societal vulnerability to climate change. Equations were developed estimating the amount of landscape-level NPP required to generate all the products consumed by 230 countries including; vegetal foods, meat, milk, eggs, wood, fuel-wood, paper and fiber. The amount of NPP required was calculated on a per capita basis and projected onto a global map of population to create a spatially explicit map of NPP-carbon demand in units of elemental carbon. NPP demand was compared to a map of Earth's average annual net primary production or supply created using 17 years (1982-1998) of AVHRR vegetation index to produce a geographically accurate balance sheet of terrestrial NPP-carbon supply and demand. Globally, humans consume 20 percent of Earth's total net primary production on land. Regionally the NPP-carbon balance percentage varies from 6 to over 70 percent and locally from near 0 to over 30,000 percent in major urban areas. The uneven distribution of NPP-carbon supply and demand, indicate the degree to which various human populations rely on NPP imports, are vulnerable to climate change and suggest policy options for slowing future growth in NPP demand.

  19. New Generation of Satellite-Derived Ocean Thermal Structure for the Western North Pacific Typhoon Intensity Forecasting

    Science.gov (United States)

    2013-10-26

    took 35% of error as a threshold to deter- mine whether the parameters derived by the REGWNP are of acceptable accuracy. Fig. 13 shows the applicable...2000. The interaction between Hurricane Opal (1995) and a warm core ring in the Gulf of Mexico. Monthly Weather Review 128, 1347–1365. Jacob, S.D...Hurricane Opal . Monthly Weather Review 128, 1366–1383. Stephens, C., Antonov, J.I., Boyer, T.P., Conkright, M.E., Locarnini, R.A., O’Brien, T.D., Carcia

  20. Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing in the Wind River Range, Wyoming

    Science.gov (United States)

    Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

    2010-01-01

    MODIS-derived snow cover measured on 30 April in any given year explains approximately 89 % of the variance in stream discharge for maximum monthly streamflow in that year. Observed changes in streamflow appear to be related to increasing maximum air temperatures over the last four decades causing lower spring snow-cover extent. The majority (>70%) of the water supply in the western United States comes from snowmelt, thus analysis of the declining spring snowpack (and resulting declining stream discharge) has important implications for streamflow management in the drought-prone western U.S.

  1. A model of regional primary production for use with coarse resolution satellite data

    Science.gov (United States)

    Prince, S. D.

    1991-01-01

    A model of crop primary production, which was originally developed to relate the amount of absorbed photosynthetically active radiation (APAR) to net production in field studies, is discussed in the context of coarse resolution regional remote sensing of primary production. The model depends on an approximately linear relationship between APAR and the normalized difference vegetation index. A more comprehensive form of the conventional model is shown to be necessary when different physiological types of plants or heterogeneous vegetation types occur within the study area. The predicted variable in the new model is total assimilation (net production plus respiration) rather than net production alone or harvest yield.

  2. Developing the science product algorithm testbed for Chinese next-generation geostationary meteorological satellites: Fengyun-4 series

    Science.gov (United States)

    Min, Min; Wu, Chunqiang; Li, Chuan; Liu, Hui; Xu, Na; Wu, Xiao; Chen, Lin; Wang, Fu; Sun, Fenglin; Qin, Danyu; Wang, Xi; Li, Bo; Zheng, Zhaojun; Cao, Guangzhen; Dong, Lixin

    2017-08-01

    Fengyun-4A (FY-4A), the first of the Chinese next-generation geostationary meteorological satellites, launched in 2016, offers several advances over the FY-2: more spectral bands, faster imaging, and infrared hyperspectral measurements. To support the major objective of developing the prototypes of FY-4 science algorithms, two science product algorithm testbeds for imagers and sounders have been developed by the scientists in the FY-4 Algorithm Working Group (AWG). Both testbeds, written in FORTRAN and C programming languages for Linux or UNIX systems, have been tested successfully by using Intel/g compilers. Some important FY-4 science products, including cloud mask, cloud properties, and temperature profiles, have been retrieved successfully through using a proxy imager, Himawari-8/Advanced Himawari Imager (AHI), and sounder data, obtained from the Atmospheric InfraRed Sounder, thus demonstrating their robustness. In addition, in early 2016, the FY-4 AWG was developed based on the imager testbed—a near real-time processing system for Himawari-8/AHI data for use by Chinese weather forecasters. Consequently, robust and flexible science product algorithm testbeds have provided essential and productive tools for popularizing FY-4 data and developing substantial improvements in FY-4 products.

  3. A new 1 km digital elevation model of the Antarctic derived from combined satellite radar and laser data – Part 1: Data and methods

    Directory of Open Access Journals (Sweden)

    J. L. Bamber

    2009-05-01

    Full Text Available Digital elevation models (DEMs of the whole of Antarctica have been derived, previously, from satellite radar altimetry (SRA and limited terrestrial data. Near the ice sheet margins and in other areas of steep relief the SRA data tend to have relatively poor coverage and accuracy. To remedy this and to extend the coverage beyond the latitudinal limit of the SRA missions (81.5° S we have combined laser altimeter measurements from the Geosciences Laser Altimeter System onboard ICESat with SRA data from the geodetic phase of the ERS-1 satellite mission. The former provide decimetre vertical accuracy but with poor spatial coverage. The latter have excellent spatial coverage but a poorer vertical accuracy. By combining the radar and laser data using an optimal approach we have maximised the vertical accuracy and spatial resolution of the DEM and minimised the number of grid cells with an interpolated elevation estimate. We assessed the optimum resolution for producing a DEM based on a trade-off between resolution and interpolated cells, which was found to be 1 km. This resulted in just under 32% of grid cells having an interpolated value. The accuracy of the final DEM was assessed using a suite of independent airborne altimeter data and used to produce an error map. The RMS error in the new DEM was found to be roughly half that of the best previous 5 km resolution, SRA-derived DEM, with marked improvements in the steeper marginal and mountainous areas and between 81.5 and 86° S. The DEM contains a wealth of information related to ice flow. This is particularly apparent for the two largest ice shelves – the Filchner-Ronne and Ross – where the surface expression of flow of ice streams and outlet glaciers can be traced from the grounding line to the calving front. The surface expression of subglacial lakes and other basal features are also illustrated. We also use the DEM to derive new estimates of balance velocities and ice divide locations.

  4. Energy and materials flows in the production of olefins and their derivatives

    Energy Technology Data Exchange (ETDEWEB)

    Gaines, L.L.; Shen, S.Y.

    1980-08-01

    Production of olefins and their derivatives uses almost 3.5% of the oil and gas consumed annually in the United States. It is estimated that their production requires an input energy of 2 Q, which is 50% of the energy used in the production of all petrochemicals. Substantial amounts of this energy could be recovered through recycling. For example, recycling of a single plastic product, polyester soft drink bottles, could have recovered about 0.014 Q in 1979. (About 1.4 Q is used to produce plastic derivatives of olefins). Petrochemical processes use fuels as feedstocks, as well as for process energy, and a portion of this energy is not foregone and can be recovered through combustion of the products. The energy foregone in the production of ethylene is estimated to be 7800 Btu/lb. The energy foregone in plastics production ranges from 12,100 Btu/lb for the new linear low-density polyethylene to 77,200 Btu/lb for nylon 66, which is about 60% of the total energy input for that product. Further investigation of the following areas could yield both material and energy savings in the olefins industry: (1) recycling of petrochemical products to recover energy in addition to that recoverable through combustion, (2) impact of feedstock substitution on utilization of available national resources, and (3) effective use of the heat embodied in process steam. This steam accounts for a major fraction of the industry's energy input.

  5. Simulation of olive grove gross primary production by the combination of ground and multi-sensor satellite data

    Science.gov (United States)

    Brilli, L.; Chiesi, M.; Maselli, F.; Moriondo, M.; Gioli, B.; Toscano, P.; Zaldei, A.; Bindi, M.

    2013-08-01

    We developed and tested a methodology to estimate olive (Olea europaea L.) gross primary production (GPP) combining ground and multi-sensor satellite data. An eddy-covariance station placed in an olive grove in central Italy provided carbon and water fluxes over two years (2010-2011), which were used as reference to evaluate the performance of a GPP estimation methodology based on a Monteith type model (modified C-Fix) and driven by meteorological and satellite (NDVI) data. A major issue was related to the consideration of the two main olive grove components, i.e. olive trees and inter-tree ground vegetation: this issue was addressed by the separate simulation of carbon fluxes within the two ecosystem layers, followed by their recombination. In this way the eddy covariance GPP measurements were successfully reproduced, with the exception of two periods that followed tillage operations. For these periods measured GPP could be approximated by considering synthetic NDVI values which simulated the expected response of inter-tree ground vegetation to tillages.

  6. Characterizing Global Flood Wave Travel Times to Optimize the Utility of Near Real-Time Satellite Remote Sensing Products

    Science.gov (United States)

    Allen, G. H.; David, C. H.; Andreadis, K. M.; Emery, C. M.; Famiglietti, J. S.

    2017-12-01

    Earth observing satellites provide valuable near real-time (NRT) information about flood occurrence and magnitude worldwide. This NRT information can be used in early flood warning systems and other flood management applications to save lives and mitigate flood damage. However, these NRT products are only useful to early flood warning systems if they are quickly made available, with sufficient time for flood mitigation actions to be implemented. More specifically, NRT data latency, or the time period between the satellite observation and when the user has access to the information, must be less than the time it takes a flood to travel from the flood observation location to a given downstream point of interest. Yet the paradigm that "lower latency is always better" may not necessarily hold true in river systems due to tradeoffs between data latency and data quality. Further, the existence of statistical breaks in the global distribution of flood wave travel time (i.e. a jagged statistical distribution) would represent preferable latencies for river-observation NRT remote sensing products. Here we present a global analysis of flood wave velocity (i.e. flow celerity) and travel time. We apply a simple kinematic wave model to a global hydrography dataset and calculate flow wave celerity and travel time during bankfull flow conditions. Bankfull flow corresponds to the condition of maximum celerity and thus we present the "worst-case scenario" minimum flow wave travel time. We conduct a similar analysis with respect to the time it takes flood waves to reach the next downstream city, as well as the next downstream reservoir. Finally, we conduct these same analyses, but with regards to the technical capabilities of the planned Surface Water and Ocean Topography (SWOT) satellite mission, which is anticipated to provide waterbody elevation and extent measurements at an unprecedented spatial and temporal resolution. We validate these results with discharge records from paired

  7. Forty years of the Weglopochodne Enterprise for Sale of Coal-Derived Products

    Energy Technology Data Exchange (ETDEWEB)

    Pinkowski, Z.

    1986-02-01

    Organizational structure of trade in coal-derived products in Poland from 1945 to 1985 is discussed. Fluctuations of organizational structures reflecting phases of centralization and decentralization of the national economy are analyzed. Coordinating role of the Weglopochodne Enterprise in the coking and chemical industries is stressed. Types of products produced by coking plants in Poland, trade and exports are discussed. Effects of organizational structures on development of coking plants are also discussed (increasing wear of coking plants, insufficient investment etc.). 3 references.

  8. Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

    Science.gov (United States)

    Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

    2018-04-01

    Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0

  9. National Satellite Land Remote Sensing Data Archive

    Science.gov (United States)

    Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

    2013-01-01

    The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

  10. Atmospheric CH4 and CO2 enhancements and biomass burning emission ratios derived from satellite observations of the 2015 Indonesian fire plumes

    Directory of Open Access Journals (Sweden)

    R. J. Parker

    2016-08-01

    subsequent large increases in regional greenhouse gas concentrations. CH4 is particularly enhanced, due to the dominance of smouldering combustion in peatland fires, with CH4 total column values typically exceeding 35 ppb above those of background “clean air” soundings. By examining the CH4 and CO2 excess concentrations in the fire-affected GOSAT observations, we determine the CH4 to CO2 (CH4 ∕ CO2 fire emission ratio for the entire 2-month period of the most extreme burning (September–October 2015, and also for individual shorter periods where the fire activity temporarily peaks. We demonstrate that the overall CH4 to CO2 emission ratio (ER for fires occurring in Indonesia over this time is 6.2 ppb ppm−1. This is higher than that found over both the Amazon (5.1 ppb ppm−1 and southern Africa (4.4 ppb ppm−1, consistent with the Indonesian fires being characterised by an increased amount of smouldering combustion due to the large amount of organic soil (peat burning involved. We find the range of our satellite-derived Indonesian ERs (6.18–13.6 ppb ppm−1 to be relatively closely matched to that of a series of close-to-source, ground-based sampling measurements made on Kalimantan at the height of the fire event (7.53–19.67 ppb ppm−1, although typically the satellite-derived quantities are slightly lower on average. This seems likely because our field sampling mostly intersected smaller-scale peat-burning plumes, whereas the large-scale plumes intersected by the GOSAT Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS footprints would very likely come from burning that was occurring in a mixture of fuels that included peat, tropical forest and already-cleared areas of forest characterised by more fire-prone vegetation types than the natural rainforest biome (e.g. post-fire areas of ferns and scrubland, along with agricultural vegetation.The ability to determine large-scale ERs from

  11. ASSESSMENT OF SEA ICE FREEBOARD AND THICKNESS IN MCMURDO SOUND, ANTARCTICA, DERIVED BY GROUND VALIDATED SATELLITE ALTIMETER DATA

    Directory of Open Access Journals (Sweden)

    D. Price

    2012-07-01

    Full Text Available This investigation employs the use of ICESat to derive freeboard measurements in McMurdo Sound in the western Ross Sea, Antarctica, for the time period 2003-2009. Methods closely follow those previously presented in the literature but are complemented by a good understanding of general sea ice characteristics in the study region from extensive temporal ground investigations but with limited spatial coverage. The aim of remote sensing applications in this area is to expand the good knowledge of sea ice characteristics within these limited areas to the wider McMurdo Sound and western Ross Sea region. The seven year Austral Spring (September, October, and November investigation is presented for sea ice freeboard alone. An interannual comparison of mean freeboard indicates an increase in multiyear sea ice freeboard from 1.08 m in 2003 to 1.15 m in 2009 with positive and negative variation in between. No significant trend was detected for first year sea ice freeboard. Further, an Envisat imagery investigation complements the freeboard assessment. The multiyear sea ice was observed to increase by 254 % of its original 2003 area, as firstyear sea ice persisted through the 2004 melt season into 2005. This maximum coverage then gradually diminished by 2009 to 20 % above the original 2003 value. The mid study period increase is likely attributed to the passage of iceberg B-15A minimising oceanic pressures and preventing sea ice breakout in the region.

  12. 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, an