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


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.

Article / Publication Data
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Fiscal Year
Published On
January 01, 2011
Submitted On
March 15, 2021

This publication was presented at the following:

15th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans and Land
American Meteorological Society


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