A near real time regional satellite data assimilation system for high impact weather research and application

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Thursday, 8 January 2015: 3:30 PM
131AB (Phoenix Convention Center - West and North Buildings)
Jinlong Li, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Li, P. Wang, H. Han, T. J. Schmit, M. Goldberg, and S. J. Goodman

Under the NOAA JPSS and GOES-R program support, scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have recently developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT). With its core system built with GSI/WRF, SDAT can assimilate GOES, AMSUA/AMSUB, HIRS, MHS, ATMS, AIRS and IASI radiances. In addition, the system is able to assimilate satellite-derived products such as hyperspectral IR retrieved temperature and moisture profiles and total precipitable water (TPW). We are currently working on adding GOES sounder layer precipitable water (LPW) and GOES imager atmospheric motion vector (AMV) products into the system. Using SDAT as a research testbed, studies have been conducted on improving the use of satellite data in NWP models, for example, how to better perform cloud detection for hyperspectral IR sounder radiance assimilation. A new GOES imager simulation from the NWP model output has also been added into SDAT system. Since the fall of 2013, the SDAT system has been running in near real time. The 2014 hurricane forecasts in the Northern Atlantic Ocean will be analyzed for the whole season and compared with other operational models. The results along with recent progress from SDAT will be presented in the meeting.