Greenbelt, MD, United States
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Percivall G.S.,Open Geospatial Consortium | Alameh N.S.,Open Geospatial Consortium | Caumont H.,Terradue | Moe K.L.,NASA | Evans J.D.,Global Science and Technology Inc.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2013

This paper describes how the Group on Earth Observations (GEO) and the Committee on Earth Observation Satellites (CEOS) are individually and collaboratively strengthening worldwide ability for agencies to manage the disasters lifecycle. The Architecture Implementation Pilot (AIP) of GEO has, through an agile development process, deployed and tested advanced information systems for Earth Observations based on interoperability arrangements. In particular, AIP has focused on several disaster management scenarios resulting in an architecture that has improved the ready viability and usability of data for disasters. CEOS is constructing a reference architecture, intended to streamline access to satellite data and services for disaster management and risk assessment. The CEOS approach aims to support disaster management activities with satellite information in a holistic fashion, taking account of their overlaps and interdependencies. Jointly GEO and CEOS are now working to align the approaches for disaster management to describe enterprise components and improve understanding of contributed systems and their roles. The coordination has lead to refinements of the Disaster Management Scenario via further implementation in AIP-5. By collaborating via the CEOS working groups and the Global Earth Observing System of Systems (GEOSS) communities of practice, these efforts are intended to engage the international community focused on disaster management and risk assessment to fully utilize remote sensing resources for societal benefit. © 2013 IEEE.


Mikelsons K.,The Center for Satellite Applications and Research | Mikelsons K.,Global Science and Technology Inc. | Wang M.,The Center for Satellite Applications and Research | Jiang L.,The Center for Satellite Applications and Research | And 2 more authors.
Optics Express | Year: 2014

While modern multi-detector sensors offer a much improved image resolution and signal-to-noise ratio among other performance benefits, the multi-detector arrangement gives rise to striping in satellite imagery due to various sources, which cannot be perfectly corrected by sensor calibration. Recently, Bouali and Ignatov (2014) [J. Atmos. Oceanic Technol., 31 , 150-163 (2014)] introduced a new approach to remove relatively small detector performance-related striping from thermal infrared bands for improved sea surface temperature data. We show that this methodology, with appropriately chosen parameters and adjustments, can also be applied to remove striping of a much larger variance from the solar reflective band data. Specifically, we modify and apply this new approach to remove striping from satellite-derived normalized water-leaving radiance spectra nLw(λ) obtained from solar reflective bands. It is important that the destriping approach not be applied to the top-of-atmosphere radiances. The results show a significant improvement in image quality for both nLw(λ) spectra and nLw(λ)-derived ocean biological and biogeochemical products such as chlorophyll-a concentration, and the water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490). ©2014 Optical Society of America


Sun J.,The Center for Satellite Applications and Research | Sun J.,Global Science and Technology Inc. | Wang M.,The Center for Satellite Applications and Research
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

The on-orbit calibration of the reflective solar bands (RSBs) of VIIRS and the result from the analysis of the up-to-date 3 years of mission data are presented. The VIIRS solar diffuser (SD) and lunar calibration methodology are discussed, and the calibration coefficients, called F-factors, for the RSBs are given for the latest reincarnation. The coefficients derived from the two calibrations are compared and the uncertainties of the calibrations are discussed. Numerous improvements are made, with the major improvement to the calibration result come mainly from the improved bidirectional reflectance factor (BRF) of the SD and the vignetting functions of both the SD screen and the sun-view screen. The very clean results, devoid of many previously known noises and artifacts, assures that VIIRS has performed well for the three years on orbit since launch, and in particular that the solar diffuser stability monitor (SDSM) is functioning essentially without flaws. The SD degradation, or H-factors, for most part shows the expected decline except for the surprising rise on day 830 lasting for 75 days signaling a new degradation phenomenon. Nevertheless the SDSM and the calibration methodology have successfully captured the SD degradation for RSB calibration. The overall improvement has the most significant and direct impact on the ocean color products which demands high accuracy from RSB observations. © 2014 SPIE.


Ruane A.C.,NASA | Mcdermid S.,NASA | Mcdermid S.,Oak Ridge Associated Universities | Rosenzweig C.,NASA | And 4 more authors.
Global Change Biology | Year: 2014

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach. © 2013 John Wiley & Sons Ltd.


Zheng G.,Global Science and Technology Inc. | Stramski D.,University of California San DiegoLa Jolla | Digiacomo P.M.,Center for Satellite Application and ResearchCollege Park
Journal of Geophysical Research C: Oceans | Year: 2015

We present a model, referred to as Generalized Stacked-Constraints Model (GSCM), for partitioning the total light absorption coefficient of natural water (with pure-water contribution subtracted), anw(λ), into phytoplankton, aph(λ), nonalgal particulate, ad(λ), and CDOM, ag(λ), components. The formulation of the model is based on the so-called stacked-constraints approach, which utilizes a number of inequality constraints that must be satisfied simultaneously by the model outputs of component absorption coefficients. A major advancement is that GSCM provides a capability to separate the ad(λ) and ag(λ) coefficients from each other using only weakly restrictive assumptions about the component absorption coefficients. In contrast to the common assumption of exponential spectral shape of ad(λ) and ag(λ) in previous models, in our model these two coefficients are parameterized in terms of several distinct spectral shapes. These shapes are determined from field data collected in the Chesapeake Bay with an ultimate goal to adequately account for the actual variability in spectral shapes of ad(λ) and ag(λ) in the study area. Another advancement of this model lies in its capability to account for potentially nonnegligible magnitude of ad(λ) in the near-infrared spectral region. Evaluation of model performance demonstrates good agreement with measurements in the Chesapeake Bay. For example, the median ratio of the model-derived to measured ad(λ), ag(λ), and aph(λ) at 443 nm is 0.913, 1.064, and 1.056, respectively. Whereas our model in its present form can be a powerful tool for regional studies in the Chesapeake Bay, the overall approach is readily adaptable to other regions or bio-optical water types. © 2015. American Geophysical Union. All Rights Reserved.


Hoy E.E.,Global Science and Technology Inc. | Turetsky M.R.,University of Guelph | Kasischke E.S.,University of Maryland University College
Environmental Research Letters | Year: 2016

Much recent research has investigated the effects of burning on mature black spruce (Picea mariana) forests in interior Alaska, however little research has focused on how frequent reburning affects soil organic layer (SOL) vulnerability in these ecosystems. We compared organic soil layer characteristics in black spruce stands that burned after two fire-free intervals (FFI), including an intermediate-interval (37-52 years) and a more typical long-interval (70-120 years). We found that depth of burn varied significantly between intermediate-interval and long-interval sites, and as there was less material available to burn in intermediate-interval stands, percent depth reduction was greater in these stands (78.9% ±2.6%) than in long-interval stands (62.9% ±1.5%). As a result, less residual organic soil carbon remained post-fire in intermediate-interval than long-interval stands. Post-fire organic soil carbon stocks averaged 0.51 ±0.08 kg C m-2 in the intermediate-interval sites, which is less than estimates of soil carbon stock for long-interval fire events (ranging from 2.07 to 5.74 kg C m-2). In addition to altering soil carbon storage, a depletion of the SOL during more frequent fire events will likely delay the recovery of permafrost and could trigger a change in the possible successional trajectory of a site, from black spruce dominated to deciduous or even shrub dominated ecosystems in the future. © 2016 IOP Publishing Ltd.


Zheng G.,National Oceanic and Atmospheric Administration | Zheng G.,The Interdisciplinary Center | Zheng G.,Global Science and Technology Inc. | Stramski D.,University of California at San Diego | Digiacomo P.M.,National Oceanic and Atmospheric Administration
Journal of Geophysical Research C: Oceans | Year: 2015

We present a model, referred to as Generalized Stacked-Constraints Model (GSCM), for partitioning the total light absorption coefficient of natural water (with pure-water contribution subtracted), anw(λ), into phytoplankton, aph(λ), nonalgal particulate, ad(λ), and CDOM, ag(λ), components. The formulation of the model is based on the so-called stacked-constraints approach, which utilizes a number of inequality constraints that must be satisfied simultaneously by the model outputs of component absorption coefficients. A major advancement is that GSCM provides a capability to separate the ad(λ) and ag(λ) coefficients from each other using only weakly restrictive assumptions about the component absorption coefficients. In contrast to the common assumption of exponential spectral shape of ad(λ) and ag(λ) in previous models, in our model these two coefficients are parameterized in terms of several distinct spectral shapes. These shapes are determined from field data collected in the Chesapeake Bay with an ultimate goal to adequately account for the actual variability in spectral shapes of ad(λ) and ag(λ) in the study area. Another advancement of this model lies in its capability to account for potentially nonnegligible magnitude of ad(λ) in the near-infrared spectral region. Evaluation of model performance demonstrates good agreement with measurements in the Chesapeake Bay. For example, the median ratio of the model-derived to measured ad(λ), ag(λ), and aph(λ) at 443 nm is 0.913, 1.064, and 1.056, respectively. Whereas our model in its present form can be a powerful tool for regional studies in the Chesapeake Bay, the overall approach is readily adaptable to other regions or bio-optical water types. © 2015. American Geophysical Union. All Rights Reserved.


Xu F.,National Oceanic and Atmospheric Administration | Ignatov A.,Global Science and Technology Inc.
Journal of Atmospheric and Oceanic Technology | Year: 2014

The quality of in situ sea surface temperatures (SSTs) is critical for calibration and validation of satellite SSTs. In situ SSTs come fromdifferent countries, agencies, and platforms.As a result, their quality is often suboptimal,nonuniform, and measurement-type specific. This paper describes a system developed at the National Oceanic and Atmospheric Administration (NOAA), the in situ SST Quality Monitor (iQuam; www.star.nesdis.noaa. gov/sod/sst/iquam/). It performs threemajor functions with the Global Telecommunication System(GTS) data: 1) quality controls (QC) in situ SSTs, using Bayesian reference and buddy checks similar to those adopted in the MetOffice, in addition to providing basic screenings, such as duplicate removal, plausibility, platformtrack, and SST spike checks; 2)monitors quality-controlled SSTs online, in near-real time; and 3) serves reformatted GTS SST data to NOAA and external userswith quality flags appended.Currently, iQuam'sweb page displays global monthlymaps ofmeasurement locations stratified by four in situ platformtypes (drifters, ships, and tropical and coastal moorings) as well as their corresponding ''in situ minus reference'' SST statistics. Time series of all corresponding SST and QC statistics are also trended. The web page user can also monitor individual in situ platforms. The current status of iQuam and ongoing improvements are discussed. © 2014 American Meteorological Society.


Ashouri H.,University of California at Irvine | Hsu K.-L.,University of California at Irvine | Sorooshian S.,University of California at Irvine | Braithwaite D.K.,University of California at Irvine | And 4 more authors.
Bulletin of the American Meteorological Society | Year: 2015

A new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band 60°S-60°N for the period of 1 January 1983 to 31 December 2012 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution, and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data. It is adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5° monthly scale throughout the entire record. Three case studies for testing the efficacy of the dataset against available observations and satellite products are reported. The verification study over Hurricane Katrina (2005) shows that PERSIANN-CDR has good agreement with the stage IV radar data, noting that PERSIANN-CDR has more complete spatial coverage than the radar data. In addition, the comparison of PERSIANN-CDR against gauge observations during the 1986 Sydney flood in Australia reaffirms the capability of PERSIANN-CDR to provide reasonably accurate rainfall estimates. Moreover, the probability density function (PDF) of PERSIANN-CDR over the contiguous United States exhibits good agreement with the PDFs of the Climate Prediction Center (CPC) gridded gauge data and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product. The results indicate high potential for using PERSIANN-CDR for long-term hydroclimate studies in regional and global scales. © 2015 American Meteorological Society.


Pietras J.V.,Global Science and Technology Inc.
13th International Conference on Space Operations, SpaceOps 2014 | Year: 2014

The Consultative Committee for Space Data Systems (CCSDS) is developing the Monitored Data Cross Support Transfer Service (MD-CSTS), a standard service by which a spaceflight mission can obtain real-time status of the space communication and tracking services being provided by a Tracking, Telemetry and Command network. The MD-CSTS provides cyclic reports and event notifications that are associated with the status and performance of space link services provided by ground stations and relay satellites during a space link contact. The MD-CSTS also allows the spaceflight mission to query the current values of monitored status and performance parameters. These parameters and events will be registered with the Space Assigned Numbers Authority. This paper presents an overview of the capabilities of the MD-CSTS and presents an operational scenario that exercises those capabilities.

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