Editorial Type:
Article
Article Type:
Research Article

Real-Time Simulation of the GOES-R ABI for User Readiness and Product Evaluation

Thomas J. Greenwald Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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R. Bradley Pierce NOAA/National Environmental Satellite, Data, and Information Service, Madison, Wisconsin

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Todd Schaack Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Jason Otkin Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Marek Rogal Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Kaba Bah Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Allen Lenzen Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Jim Nelson Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Jun Li Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Hung-Lung Huang Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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Print Publication:
01 Feb 2016
DOI:
https://doi.org/10.1175/BAMS-D-14-00007.1
Page(s):
245–261
Restricted access

Abstract

In support of the Geostationary Operational Environmental Satellite R series (GOES-R) program, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin–Madison is generating high quality simulated Advanced Baseline Imager (ABI) radiances and derived products in real time over the continental United States. These data are mainly used for testing data-handling systems, evaluating ABI-derived products, and providing training material for forecasters participating in GOES-R Proving Ground test bed activities. The modeling system used to generate these datasets consists of advanced regional and global numerical weather prediction models in addition to state-of-the-art radiative transfer models, retrieval algorithms, and land surface datasets. The system and its generated products are evaluated for the 2014 Pacific Northwest wildfires; the 2013 Moore, Oklahoma, tornado; and Hurricane Sandy. Simulated aerosol optical depth over the Front Range of Colorado during the Pacific Northwest wildfires was validated using high-density Aerosol Robotic Network (AERONET) measurements. The aerosol, cloud, and meteorological modeling system used to generate ABI radiances was found to capture the transport of smoke from the Pacific wildfires into the Front Range of Colorado and true-color imagery created from these simulated radiances provided visualization of the smoke plumes. Evaluation of selected simulated ABI-derived products for the Moore tornado and Hurricane Sandy cases was done using real-time GOES sounder/imager products produced at CIMSS. Results show that simulated ABI moisture and atmospheric stability products, cloud products, and red–green–blue (RGB) airmass composite imagery are well suited as proxy ABI data for user preparedness.

CORRESPONDING AUTHOR: Thomas J. Greenwald, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, 1225 West Dayton St., Madison, WI 53706, E-mail: tomg@ssec.wisc.edu

A supplement to this article is available online (10.1175/BAMS-D-14-00007.2)

Abstract

In support of the Geostationary Operational Environmental Satellite R series (GOES-R) program, the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the University of Wisconsin–Madison is generating high quality simulated Advanced Baseline Imager (ABI) radiances and derived products in real time over the continental United States. These data are mainly used for testing data-handling systems, evaluating ABI-derived products, and providing training material for forecasters participating in GOES-R Proving Ground test bed activities. The modeling system used to generate these datasets consists of advanced regional and global numerical weather prediction models in addition to state-of-the-art radiative transfer models, retrieval algorithms, and land surface datasets. The system and its generated products are evaluated for the 2014 Pacific Northwest wildfires; the 2013 Moore, Oklahoma, tornado; and Hurricane Sandy. Simulated aerosol optical depth over the Front Range of Colorado during the Pacific Northwest wildfires was validated using high-density Aerosol Robotic Network (AERONET) measurements. The aerosol, cloud, and meteorological modeling system used to generate ABI radiances was found to capture the transport of smoke from the Pacific wildfires into the Front Range of Colorado and true-color imagery created from these simulated radiances provided visualization of the smoke plumes. Evaluation of selected simulated ABI-derived products for the Moore tornado and Hurricane Sandy cases was done using real-time GOES sounder/imager products produced at CIMSS. Results show that simulated ABI moisture and atmospheric stability products, cloud products, and red–green–blue (RGB) airmass composite imagery are well suited as proxy ABI data for user preparedness.

CORRESPONDING AUTHOR: Thomas J. Greenwald, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, 1225 West Dayton St., Madison, WI 53706, E-mail: tomg@ssec.wisc.edu

A supplement to this article is available online (10.1175/BAMS-D-14-00007.2)

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