165 Assimilation of Polar Winds Data in HRRR-Alaska

Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Jiang Zhu, Univ. of Alaska Fairbanks, Fairbanks, AK; and D. Morton, E. Stevens, T. Heinrichs, M. Hu, and T. Alcott

GINA is conducting cooperative research with NOAA GSD on improving a high-resolution rapid-refresh WRF model for Alaska (HRRR-Alaska). GINA focuses on HRRR-Alaska model validation, parameter optimization, and data assimilation to improve the quality of the model short-term forecast. The HRRR-Alaska is running experimentally on a NOAA research and development supercomputer, and will be operational by early 2018. The effort to assimilate satellite Polar Winds into the HRRR-Alaska model will be introduced. The Polar Winds product is derived from the AVHRR, MODIS, and VIIRS instruments. There are two ways to include satellite wind data in the GSI data assimilation scheme. Satellite wind data can either be treated as upper level observation data and appended to conventional observation data (RAP PREPBUFR files); or they can be integrated into global satellite wind data (gdas1.satwnd files). A case study will be presented to show the impact of satellite wind data assimilation on the HRRR-Alaska short-term forecast. MET tools are used to pair the upper atmospheric data from RAOB and HRRR-Alaska outputs. Values of root-mean-square error (RMSE) between forecast output and observation are calculated to quantitatively evaluate the improvement of performance.
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