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Rockville, MD, United States

Kogan F.,National Oceanic and Atmospheric Administration | Guo W.,IM Systems Group Inc.
Geomatics, Natural Hazards and Risk | Year: 2014

The first 13 years of the twenty-first century have begun with a series of widespread, long and intensive droughts around the world. Extreme and severe-to-extreme intensity droughts covered 2%-6% and 7%-16% of the world land, respectively, affecting environment, economies and humans. These droughts reduced agricultural production, leading to food shortages, human health deterioration, poverty, regional disturbances, population migration and death. This feature article is a travelogue of the twenty-first-century global and regional droughts during the warmest years of the past 100 years. These droughts were identified and monitored with the National Oceanic and Atmospheric Administration operational space technology, called vegetation health (VH), which has the longest period of observation and provides good data quality. The VH method was used for assessment of vegetation condition or health, including drought early detection and monitoring. The VH method is based on operational satellites data estimating both land surface greenness (NDVI) and thermal conditions. The twenty-first-century droughts in the USA, Russia, Australia and Horn of Africa were intensive, long, covered large areas and caused huge losses in agricultural production, which affected food security and led to food riots in some countries. This research also investigates drought dynamics presenting no definite conclusion about drought intensification or/and expansion during the time of the warmest globe. © 2014 © 2014 Taylor & Francis. Source


Edwards P.E.T.,National Oceanic and Atmospheric Administration | Edwards P.E.T.,IM Systems Group Inc. | Sutton-Grier A.E.,National Oceanic and Atmospheric Administration | Sutton-Grier A.E.,Earth Resources Technology Inc. | Coyle G.E.,Wesleyan University
Marine Policy | Year: 2013

This study examines the economic impact of the expenditures from the American Recovery and Reinvestment Act (ARRA) of 2009 that the National Oceanic and Atmospheric Administration (NOAA) administered for coastal habitat restoration projects around the United States. Estimates of the total jobs created as well as the average number of jobs created per million dollars spent are provided. The study shows that the 50 ARRA projects administered by NOAA in the first year and half generated a total of 1409 jobs. These habitat restoration projects created, on average, 17 jobs per million dollars spent which is similar to other conservation industries such as parks and land conservation, and much higher than other traditional industries including coal, gas, and nuclear energy generation. This suggests that habitat restoration is indeed an effective way to stimulate job creation. In addition, habitat restoration has longer-term economic benefits, including future job creation in rebuilt fisheries and coastal tourism, and benefits to coastal economies including higher property values and better water quality. Therefore, investing in blue infrastructure habitat restoration is a green opportunity benefiting coastal economies and societies in both the short and the long term. © 2012 Elsevier Ltd. Source


Liu X.,NASA | Kizer S.,Science Systems And Applications Inc. | Larar A.,NASA | Zhou D.,Science Systems And Applications Inc. | And 9 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010

As a part of the Joint Polar Satellite System (JPSS, formerly the NPOESS afternoon orbit), the instruments Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) make up the Cross-track Infrared and Microwave Sounder Suite (CrIMSS). CrIMSS will primarily provide global temperature, moisture, and pressure profiles and calibrated radiances [1]. In preparation for the NPP launch in 2011, we have ported and tested the operational CrIMSS Environmental Data Record (EDR) algorithms using both synthetic and proxy data generated from the IASI, AMSU, MHS data from Metop-A satellite. © 2010 Copyright SPIE - The International Society for Optical Engineering. Source


Errico R.M.,Morgan State University | Errico R.M.,NASA | Yang R.,IM Systems Group Inc. | Prive N.C.,Morgan State University | And 5 more authors.
Quarterly Journal of the Royal Meteorological Society | Year: 2013

Initial design and validation of baseline Observing System Simulation Experiments (OSSEs) at NASA's Global Modeling and Assimilation Office (GMAO) are described. The OSSEs mimic the procedures used to analyze global observations for specifying states of the atmosphere. As simulations, however, OSSEs are not only confined to already existing observations and they provide a perfect description of the true state being analyzed. These two properties of the simulations can be exploited to improve both existing and envisioned observing systems and the algorithms to analyze them. Preliminary to any applications, however, the OSSE framework must be adequately validated. This first version of the simulated observations is drawn from a 13 month simulation of nature produced by the European Center for Medium-Range Weather Forecasts. These observations include simulated errors of both instruments and representativeness. Since the statistics of analysis and forecast errors are partially determined by these observational errors, their appropriate modelling can be crucial for validating the realism of the OSSE. That validation is performed by comparing the statistics of the results of assimilating these simulated observations for one summer month compared with the corresponding statistics obtained from assimilating real observations during the same time of year. The assimilation system is the three-dimensional variational analysis (GSI) scheme used at both the National Centers for Environmental Prediction and GMAO. Here, only statistics concerning observation innovations or analysis increments within the troposphere are considered for the validation. In terms of the examined statistics, the OSSE is validated remarkably well, even with some simplifications currently employed. In order to obtain this degree of success, it was necessary to employ horizontally correlated observation errors for both atmospheric motion vectors and some satellite observed radiances. The simulated observations with added observation errors appear suitable for some initial OSSE applications. © 2012 Royal Meteorological Society. Source


Shao M.,Nanjing University | Shao M.,George Mason University | Xu J.,George Mason University | Powell A.M.,The Center for Satellite Applications and Research | And 2 more authors.
International Journal of Remote Sensing | Year: 2015

The decadal variability of sea surface temperature (SST) and sea level pressure (SLP) anomalies, as well as the response of global land vegetation and marine fisheries, are investigated for three periods: 1982–1988, 1989–1998, and 1999–2008, separated by the 1988–89 and 1998–99 regime shifts. The goal is to develop a global-scale ecosystem concept to support an improved understanding of the corresponding changes in atmospheric, oceanic, and biological responses. The analysis is based on global SST, SLP, precipitable water content (PWC), land vegetation condition index (VCI), and the United Nations Food and Agriculture Organization’s (FAO) fish capture data. The results show that SST and SLP displayed significant decadal variability. The decadal variability of sea surface temperature anomalies (SSTA) associated with sea level pressure anomalies (SLPA) has an influence on the land vegetation moisture condition (VCI). Positive SSTA tends to be associated with negative SLPA, and vice versa, in the corresponding ocean areas and most land areas. Consequently, clearly opposing distributions of SSTA and SLPA are observed in the periods 1982–1988 and 1999–2008. With positive SSTA and negative SLPA, VCI tends to increase in value representing more favourable vegetation conditions. Negative SSTA and positive SLPA is generally unfavourable for global vegetation development. The decadal variability of SSTA is closely related to the number of fish species (NFS) doing better or worse based on normalized fish landing data. However, the fishery responses show different yet consistent trends in the three ocean basins. When SSTA is negative, it appears more beneficial for the number of fish species with improved landings in the Atlantic Ocean. However, positive SSTA leads to more fish species with improved landings in the Indian and Pacific Oceans. © 2015 Taylor & Francis. Source

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