Impact of Geostationary Satellite Data on Superstorm Sandy Forecast

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Wednesday, 5 February 2014
Hall C3 (The Georgia World Congress Center )
Tong Zhu, NOAA/NESDIS, College Park, MD; and S. A. Boukabara

To optimize the usage of geostationary satellite data in numerical weather prediction and study the potential impact of the Joint Polar Satellite System (JPSS) data coverage gap, an impact study is performed for the simulation of Superstorm Sandy with the Weather Research and Forecasting Nonhydrostatic Multiscale Model (WRF-NMM). The geostationary satellite sensors can provide high spatial and temporal resolution observations, which are great benefit in monitoring and forecasting severe weather events. In this study, The Geostationary Operational Environmental Satellite (GOES) 13 and 15 Sounder and Imager and the Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI) radiances under clear sky condition are assimilated into the model with the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) analysis system. In Sandy case study, most of geostationary sounder and imager data can be assimilated because the size of Sandy is very large and there is a lot of clear sky area in the environment and southeast quadrant. In sensitive experiments, the Advanced Microwave Sounding Unit-A (AMSU-A) / Microwave Humidity Sounder (MHS) data on afternoon orbit is removed in one experiment, and the GOES Sounder and Imager data is assimilated in another experiment. The detailed diagnostic result of the experiments will be given at the conference.