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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TL;DR: In this paper, an algorithm for automatic atmospheric correction of satellite imagery of the earth's surface is proposed which is applicable to low-resolution and high-resolution imagery of land areas.
Abstract: An algorithm for automatic atmospheric correction of satellite imagery of the earth's surface is proposed which is applicable to low-resolution and high-resolution imagery of land areas. The algorithm is based on the satellite image being corrected and on the climatology of the area, and it requires that some pixels in the image correspond to dense dark vegetation as the surface cover. The algorithm is sensitive to the assumed reflectance of the dense dark vegetation, and the accuracy of the corrected surface reflectance is expected to be + or - 0.01. Using the method, aerosol optical thicknesses were derived from clear and hazy Landsat MSS images in the Washington, D.C. and Chesapeake Bay region, and the results are found to agree well with simultaneous sunphotometer ground measurements.
543 citations
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TL;DR: In this article, a quasi-stationary co-rotating structure in interplanetary field observed with IMP-I SATELLITE during three solar rotations was observed with the ImP-I satellite.
Abstract: Quasi-stationary co-rotating structure in interplanetary field observed with IMP-I SATELLITE during three solar rotations
543 citations
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TL;DR: In this article, the results of applying MODIS-derived aerosol optical depths (T a ) to regional and local air pollution in terms of accuracy (ΔT a = ±0.05 ± 0.2τ a ) and spatial sensitivity of the retrievals.
Abstract: [1] Moderate Resolution Imaging Spectroradiometer (MODIS) measurements (7 channels: 0.47-2.1 μm, 250-500 m resolutions) provide us with new insights into the characteristics of global aerosols. MODIS retrieves not only aerosol loading but also the fraction of fine mode particle. In this paper we demonstrate MODIS capability for use in monitoring global, regional, and local air pollution. Three case studies in northern Italy, Los Angeles, and Beijing showed the conclusive results of applying MODIS-derived aerosol optical depths (T a ) to regional and local air pollution in terms of accuracy (ΔT a = ±0.05 ± 0.2τ a ) and spatial sensitivity of the retrievals. Under stagnant condition, accumulated aerosol abundance can reach T a > 1 (at 0.55 μm) before being removed by wind or precipitation. The correlation found between Aerosol Robotic Network (AERONET) daily averaged T a and 24-hour PM 10 (particulate matter with diameter <10 μm) concentration (μg/m 3 ) in northern Italy is encouraging with correlation coefficient ∼0.82. The derivation of PM concentration from satellite measurements may be possible once we know the detailed aerosol vertical distribution. To compare aerosol loading in different regions of the globe, we choose the two most populated regions (eastern China and India) and the two most industrialized regions (the eastern United States/Canada and western Europe). The time series of MODIS monthly mean T a from July 2000 to May 2001 depicts a strong seasonal variation with maxima in the spring/ summer and minima in the winter. The clear separation between (1) the eastern United States/Canada and western Europe and (2) eastern China and India shows that the T a values in (2) are 50% to 2-3 times higher compared to those in (1). The enhancements of aerosol loading were due to smoke as originated from Montana/Idaho forest fires transported to the eastern United States in late August 2000 and dust outbreaks from Taklimakan and Gobi Deserts to eastern China as well as smoke from Southeast Asia to southern China in February-April 2001.
542 citations
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06 Aug 2013
TL;DR: In this paper, the authors used the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model to simulate the atmospheric sulfur cycle.
Abstract: The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model is used to simulate the atmospheric sulfur cycle. The model uses the assimilated meteorological data from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). Global sulfur budgets from a 6-year simulation for SO2, sulfate, dimethylsulfide (DMS), and methanesulfonic acid (MSA) are presented in this paper. In a normal year without major volcanic perturbations, about 20% of the sulfate precursor emission is from natural sources (biogenic and volcanic), and 80% is anthropogenic; the same sources contribute 33% and 67%, respectively, to the total sulfate burden. A sulfate production efficiency of 0.41–0.42 is estimated in the model, an efficiency which is defined as a ratio of the amount of sulfate produced to the total amount of SO2 emitted and produced in the atmosphere. This value indicates that less than half of the SO2 entering the atmosphere contributes to the sulfate production, the rest being removed by dry and wet depositions. In a simulation for 1990 we estimate a total sulfate production of 39 Tg S yr−1, with 36% and 64% from in-air and in-cloud oxidation, respectively, of SO2. We also demonstrate that major volcanic eruptions, such as the Mount Pinatubo eruption in 1991, can significantly change the sulfate formation pathways, distributions, abundance, and lifetime. Comparison with other models shows that the parameterizations for wet removal or wet production of sulfate are the most critical factors in determining the burdens of SO2 and sulfate. Therefore a priority for future research should be to reduce the large uncertainties associated with the wet physical and chemical processes.
542 citations
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Princeton University1, Carnegie Learning2, University of Leicester3, University College London4, Dartmouth College5, University of Wisconsin-Madison6, Nanjing University7, California Institute of Technology8, Pennsylvania State University9, Weizmann Institute of Science10, University of California, Berkeley11, University of Arizona12, University of Texas at Austin13, Goddard Space Flight Center14, York University15, Clemson University16, University of Virginia17, National Tsing Hua University18, Universities Space Research Association19, University of Southampton20, Max Planck Society21, University of Amsterdam22, University of Chicago23
TL;DR: This work reports the serendipitous discovery of a supernova at the time of the explosion, marked by an extremely luminous X-ray outburst, and attributes the outburst to the ‘break-out’ of the supernova shock wave from the progenitor star, and shows that the inferred rate of such events agrees with that of all core-collapse supernovae.
Abstract: Massive stars end their short lives in spectacular explosions—supernovae—that synthesize new elements and drive galaxy evolution. Historically, supernovae were discovered mainly through their 'delayed' optical light (some days after the burst of neutrinos that marks the actual event), preventing observations in the first moments following the explosion. As a result, the progenitors of some supernovae and the events leading up to their violent demise remain intensely debated. Here we report the serendipitous discovery of a supernova at the time of the explosion, marked by an extremely luminous X-ray outburst. We attribute the outburst to the 'break-out' of the supernova shock wave from the progenitor star, and show that the inferred rate of such events agrees with that of all core-collapse supernovae. We predict that future wide-field X-ray surveys will catch each year hundreds of supernovae in the act of exploding.
542 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 |