Institution
Goddard Space Flight Center
Facility•Greenbelt, Maryland, United States•
About: Goddard Space Flight Center is a facility organization based out in Greenbelt, Maryland, United States. It is known for research contribution in the topics: Galaxy & Solar wind. The organization has 19058 authors who have published 63344 publications receiving 2786037 citations. The organization is also known as: GSFC & Space Flight Center.
Topics: Galaxy, Solar wind, Magnetosphere, Stars, Population
Papers published on a yearly basis
Papers
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Max Planck Society1, Woods Hole Research Center2, University of Exeter3, Stanford University4, Karlsruhe Institute of Technology5, University of Valencia6, Centre national de la recherche scientifique7, Japan Agency for Marine-Earth Science and Technology8, National Institute for Environmental Studies9, University of Illinois at Urbana–Champaign10, Tuscia University11, Goddard Space Flight Center12, Université Paris-Saclay13, Commonwealth Scientific and Industrial Research Organisation14, Chinese Academy of Sciences15
TL;DR: The study indicates that spatial climate covariation drives the global carbon cycle response and helps to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance.
Abstract: Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.
467 citations
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TL;DR: In this paper, the authors describe the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from MODIS Aqua against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties.
Abstract: The "Deep Blue" aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (MODIS) product suite, and complemented the existing "Dark Target" land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of MODIS products will include a "second generation" Deep Blue algorithm, expanding coverage to all cloud-free and snow-free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm (Tau(sub M)) from MODIS Aqua against Aerosol Robotic Network (AERONET) data from 60 sites to quantify these uncertainties. The highest quality (denoted quality assurance flag value 3) data are shown to have an absolute uncertainty of approximately (0.086+0.56Tau(sub M))/AMF, where AMF is the geometric air mass factor. For a typical AMF of 2.8, this is approximately 0.03+0.20Tau(sub M), comparable in quality to other satellite AOD datasets. Regional variability of retrieval performance and comparisons against Collection 5 results are also discussed.
467 citations
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466 citations
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TL;DR: In this paper, an aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented, which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing.
Abstract: [1] An aerosol component of a new multiangle implementation of atmospheric correction (MAIAC) algorithm is presented. MAIAC is a generic algorithm developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs aerosol retrievals and atmospheric correction over both dark vegetated surfaces and bright deserts based on a time series analysis and image-based processing. The MAIAC look-up tables explicitly include surface bidirectional reflectance. The aerosol algorithm derives the spectral regression coefficient (SRC) relating surface bidirectional reflectance in the blue (0.47 μm) and shortwave infrared (2.1 μm) bands; this quantity is prescribed in the MODIS operational Dark Target algorithm based on a parameterized formula. The MAIAC aerosol products include aerosol optical thickness and a fine-mode fraction at resolution of 1 km. This high resolution, required in many applications such as air quality, brings new information about aerosol sources and, potentially, their strength. AERONET validation shows that the MAIAC and MOD04 algorithms have similar accuracy over dark and vegetated surfaces and that MAIAC generally improves accuracy over brighter surfaces due to the SRC retrieval and explicit bidirectional reflectance factor characterization, as demonstrated for several U.S. West Coast AERONET sites. Due to its generic nature and developed angular correction, MAIAC performs aerosol retrievals over bright deserts, as demonstrated for the Solar Village Aerosol Robotic Network (AERONET) site in Saudi Arabia.
466 citations
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TL;DR: In this article, data from the Tropical Rainfall Measuring Mission (TRMM) satellite's precipitation radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Georgia; Montgomery, Alabama; Nashville, Tennessee; and San Antonio, Waco, and Dallas, Texas.
Abstract: Data from the Tropical Rainfall Measuring Mission (TRMM) satellite's precipitation radar (PR) were employed to identify warm-season rainfall (1998–2000) patterns around Atlanta, Georgia; Montgomery, Alabama; Nashville, Tennessee; and San Antonio, Waco, and Dallas, Texas. Results reveal an average increase of about 28% in monthly rainfall rates within 30–60 km downwind of the metropolis, with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%–116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with the Metropolitan Meteorological Experiment (METROMEX) studies of St. Louis, Missouri, almost two decades ago and with more recent stud...
466 citations
Authors
Showing all 19247 results
Name | H-index | Papers | Citations |
---|---|---|---|
Anton M. Koekemoer | 168 | 1127 | 106796 |
Alexander S. Szalay | 166 | 936 | 145745 |
David W. Johnson | 160 | 2714 | 140778 |
Donald G. York | 160 | 681 | 156579 |
Takeo Kanade | 147 | 799 | 103237 |
Gillian R. Knapp | 145 | 460 | 121477 |
Olaf Reimer | 144 | 716 | 74359 |
R. A. Sunyaev | 141 | 848 | 107966 |
Christopher T. Russell | 137 | 2378 | 97268 |
Hui Li | 135 | 2982 | 105903 |
Neil Gehrels | 134 | 727 | 80804 |
Christopher B. Field | 133 | 408 | 88930 |
Igor V. Moskalenko | 132 | 542 | 58182 |
William T. Reach | 131 | 535 | 90496 |
Adam Burrows | 130 | 623 | 55483 |