Wednesday, 25 January 2017: 10:45 AM
620 (Washington State Convention Center )
Information of moisture distribution and transportation in pre-convection environment and during storm development is very important for forecast decisions. NOAA’s next generation of Geostationary Operational Environmental Satellite (GOES-R) series provides high temporal (every 5 minutes) and spatial (2 km) resolution moisture information useful for weather monitoring and forecasting. Since there will be no sounder onboard the GOES-R series, the GOES-R Advanced Baseline Imager (ABI) will be used to continue the current GOES Sounder legacy atmospheric profile (LAP) products. However, the current GOES Sounder and the GOES-R operational LAP products are only available in clear skies. Extending the use of infrared (IR) measurements into cloudy regions will increase the completeness of moisture information. Algorithms have been developed for all-weather total precipitable water (TPW) and three layered precipitable water (LPW: surface - 0.9, 0.9 – 0.7, and 0.7 – 0.3 in sigma coordinate) retrievals by fusing the ABI IR band radiances, numerical weather prediction (NWP) model moisture forecasts, and surface temperature and moisture observations. The methodologies have been validated and applied to process the current GOES Sounder and the Advanced Himawari Imager (AHI) radiance measurements. The TPW and LPW products from GOES Sounder and AHI have been generated at University of Wisconsin-Madison, and put into the Advanced Weather Interactive Processing System (AWIPS II) in near real time (NRT) to allow forecasters to monitor a critical ingredient in the initiation, development, and decay of convective cells and systems. These unique TPW/LPW products have the advantages of availability in all sky weather conditions, depicting high temporal and spatial features such as dryline. Examples from GOES-R Proving Ground (PG) at the Hazardous Weather Testbed (HWT) taken place 04 May - 12 June 2015 and 18 April – 13 May 2016 are presented to demonstrate the forecast applications of these very useful products. Another important application is to improve the storm forecasts through assimilating the high temporal and spatial resolution moisture information into regional and storm scale NWP models. Techniques have been developed and results will be presented for effectively assimilating high temporal and spatial resolution moisture information from a geostationary satellite for local storm forecast over CONUS.
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