Evaluating Added Benefits of Assimilating GOES Imager Radiance Data in GSI for Coastal QPFs

Zhengkun Qin Center of Data Assimilation for Research and Application, Nanjing University of Information and Science and Technology, Nanjing, China, and Department of Earth, Ocean and Atmospheric Sciences, The Florida State University, Tallahassee, Florida

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Xiaolei Zou Department of Earth, Ocean and Atmospheric Sciences, The Florida State University, Tallahassee, Florida

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Fuzhong Weng NOAA/National Environmental Satellite, Data, and Information Service, Washington, D.C.

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Abstract

The Geostationary Operational Environmental Satellites (GOES) provide high-resolution, temporally continuous imager radiance data over the West Coast (GOES-West currently known as GOES-11) and East Coast (GOES-East currently GOES-12) of the United States. Through a real case study, benefits of adding GOES-11/12 imager radiances to the satellite data streams in NWP systems for improved coastal precipitation forecasts are examined. The Community Radiative Transfer Model (CRTM) is employed for GOES imager radiance simulations in the National Centers for Environmental Prediction (NCEP) gridpoint statistical interpolation (GSI) analysis system. The GOES imager radiances are added to conventional data for coastal quantitative precipitation forecast (QPF) experiments near the northern Gulf of Mexico and the derived precipitation threat score was compared with those from six other satellite instruments. It is found that the GOES imager radiance produced better precipitation forecasts than those from any other satellite instrument. However, when GOES imager radiance and six different types of satellite instruments are all assimilated, the score becomes much lower than the individual combination of GOES and any other instrument. Our analysis shows that an elimination of Advance Microwave Sounding Unit-B (AMSU-B)/Microwave Humidity Sounder (MHS) data over areas where GOES detects clouds significantly improved the forecast scores from AMSU-B/MHS data assimilation.

Corresponding author address: Xiaolei Zou, Department of Earth, Ocean and Atmospheric Sciences, The Florida State University, 404 Love Building, Tallahassee, FL 32306-4520. E-mail: xzou@fsu.edu

Abstract

The Geostationary Operational Environmental Satellites (GOES) provide high-resolution, temporally continuous imager radiance data over the West Coast (GOES-West currently known as GOES-11) and East Coast (GOES-East currently GOES-12) of the United States. Through a real case study, benefits of adding GOES-11/12 imager radiances to the satellite data streams in NWP systems for improved coastal precipitation forecasts are examined. The Community Radiative Transfer Model (CRTM) is employed for GOES imager radiance simulations in the National Centers for Environmental Prediction (NCEP) gridpoint statistical interpolation (GSI) analysis system. The GOES imager radiances are added to conventional data for coastal quantitative precipitation forecast (QPF) experiments near the northern Gulf of Mexico and the derived precipitation threat score was compared with those from six other satellite instruments. It is found that the GOES imager radiance produced better precipitation forecasts than those from any other satellite instrument. However, when GOES imager radiance and six different types of satellite instruments are all assimilated, the score becomes much lower than the individual combination of GOES and any other instrument. Our analysis shows that an elimination of Advance Microwave Sounding Unit-B (AMSU-B)/Microwave Humidity Sounder (MHS) data over areas where GOES detects clouds significantly improved the forecast scores from AMSU-B/MHS data assimilation.

Corresponding author address: Xiaolei Zou, Department of Earth, Ocean and Atmospheric Sciences, The Florida State University, 404 Love Building, Tallahassee, FL 32306-4520. E-mail: xzou@fsu.edu
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