Editorial Type:
Article
Article Type:
Research Article

Assimilation of Synthetic GOES-R ABI Infrared Brightness Temperatures and WSR-88D Radar Observations in a High-Resolution OSSE

Rebecca M. Cintineo Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin

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

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Thomas A. Jones Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

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Steven Koch NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma

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David J. Stensrud Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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Print Publication:
01 Sep 2016
DOI:
https://doi.org/10.1175/MWR-D-15-0366.1
Page(s):
3159–3180
Restricted access

Abstract

This study uses an observing system simulation experiment to explore the impact of assimilating GOES-R Advanced Baseline Imager (ABI) 6.95-μm brightness temperatures and Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity observations in an ensemble data assimilation system. A high-resolution truth simulation was used to create synthetic radar and satellite observations of a severe weather event that occurred across the U.S. central plains on 4–5 June 2005. The experiment employs the Weather Research and Forecasting Model at 4-km horizontal grid spacing and the ensemble adjustment Kalman filter algorithm in the Data Assimilation Research Testbed system. The ability of GOES-R ABI brightness temperatures to improve the analysis and forecast accuracy when assimilated separately or simultaneously with Doppler radar reflectivity and radial velocity observations was assessed, along with the use of bias correction and different covariance localization radii for the brightness temperatures. Results show that the radar observations accurately capture the structure of a portion of the storm complex by the end of the assimilation period, but that more of the storms and atmospheric features are reproduced and the accuracy of the ensuing forecast improved when the brightness temperatures are also assimilated.

Corresponding author address: Jason Otkin, CIMSS, University of Wisconsin–Madison, 1225 West Dayton St., Madison, WI 53706. E-mail: jasono@ssec.wisc.edu

Abstract

This study uses an observing system simulation experiment to explore the impact of assimilating GOES-R Advanced Baseline Imager (ABI) 6.95-μm brightness temperatures and Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity observations in an ensemble data assimilation system. A high-resolution truth simulation was used to create synthetic radar and satellite observations of a severe weather event that occurred across the U.S. central plains on 4–5 June 2005. The experiment employs the Weather Research and Forecasting Model at 4-km horizontal grid spacing and the ensemble adjustment Kalman filter algorithm in the Data Assimilation Research Testbed system. The ability of GOES-R ABI brightness temperatures to improve the analysis and forecast accuracy when assimilated separately or simultaneously with Doppler radar reflectivity and radial velocity observations was assessed, along with the use of bias correction and different covariance localization radii for the brightness temperatures. Results show that the radar observations accurately capture the structure of a portion of the storm complex by the end of the assimilation period, but that more of the storms and atmospheric features are reproduced and the accuracy of the ensuing forecast improved when the brightness temperatures are also assimilated.

Corresponding author address: Jason Otkin, CIMSS, University of Wisconsin–Madison, 1225 West Dayton St., Madison, WI 53706. E-mail: jasono@ssec.wisc.edu
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