Impacts of The STMAS Cycling Data Assimilation System On Improving Severe Weather Forecasting

Abstract

his project will study the impacts on analysis and forecast by cycling model forecasts as analysis background fields for the severe weather cases, including hurricane Katrina and Windsor tornado. The impacts of the cycling technique (using high-resolution model as the background information) will be investigated in a data assimilation system - the Space and Time Multiscale Analysis System (STMAS, Xie et al. 2005, 2010). The objectives are to assess the capability of STMAS data assimilation technique in forecasting extreme weather events at very high resolution, and to examine the cycling method (i.e., with updated background information at fine resolution) on improving model initialization and short-term weather forecast, and to understand the formation, structure, and development of a vortex (hurricane or tornado). The ultimate goal is to establish an operational framework using the STMAS cycling data assimilation in the future forecasts.