The Impact of the High Temporal Resolution GOES/GOES-R Moisture Information on Severe Weather Systems in a Regional NWP Model

The quality of a humidity analysis directly impacts severe storm analysis and forecasts. With high temporal and spatial resolution, GOES-R's humidity information can improve regional/storm scale initialization through data assimilation. The Advanced Baseline Imager (ABI) (Schmit et al. 2005) from GOES-R will provide atmospheric water vapor with three water vapor absorption spectral bands during both day and night, which is very important for improving the initialization of regional/storm scale numerical weather prediction (NWP) models. However, utilization of high temporal resolution moisture information in NWP remains challenge. In order to enhance the use of GOES-R water vapor regional and storm scale NWP, the current GOES Sounder data are used as proxy for investigating the assimilation of high temporal resolution moisture information in a regional NWP model. Both radiances and layer precipitable water (LPW) products at three sigma level values (0.3-0.7, 0.7-0.9, and 0.9-1) are assimilated and compared. The Weather Research and Forecasting (WRF) with 4 km resolution is used in the forecast experiments while the DTC-GSI 3D-var is used as assimilation system, the LPW products from GOES-13/-15 Sounder are retrieved using the GOES-R legacy atmospheric profile (LAP) algorithm (Lee et al. 2014) and a forward operator is developed and integrated into GSI for assimilating LPW. Focuses are on how to better assimilate the high temporal moisture information, including cycling assimilation scheme, bias adjustment, observation error setting, use of information in cloudy region, radiance assimilation versus retrieval assimilation, etc. To verify the impacts of assimilating GOES Sounder radiances and LPW, the forecasted accumulated precipitation, radar reflectivity, and temperature and moisture profiles are compared with the in-situ measurements. The 24 hour, 6 hour and 1 hour accumulated precipitation from forecasts are verified against the NCEP Stage IV analysis precipitation. The temperature and moisture profiles are verified with the radiosondes profiles. Both the frequency bias and the equitable threat score (ETS) are calculated to show the impacts of LPW and radiances on storm precipitation forecasts over CONUS.