A41E-0111
Improving US Winter Storm Forecasts using Simulated Dropsondes in the GFS Model
Thursday, 17 December 2015
Poster Hall (Moscone South)
Jason M English1,2, Tanya Rae Peevey1,2, Hongli Wang3 and Lidia Cucurull2, (1)University of Colorado at Boulder, Cooperative Institute for Research in Environmental Sciences, Boulder, CO, United States, (2)NOAA Boulder, ESRL Global Systems Division, Boulder, CO, United States, (3)Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
Abstract:
Observing System Simulation Experiments (OSSEs) can be a cost-effective approach to evaluate the potential impact of new observing systems. In this study, the NCEP Global Forecast System (GFS) is initialized with simulated dropsonde data of temperature, wind, and humidity fields over the Pacific Ocean, and the accuracy of predicting winter storms over the continental United States is compared with the T511 ECMWF Joint OSSE Nature Run. Interestingly, the addition of perfect simulated dropsonde data improves GFS forecasts for one winter storm but not the other. Details of the two winter storms are compared to better understand under which circumstances the addition of dropsonde data may improve forecasts for winter storms in the United States.
