Typhoon Track Forecast with a Hybrid GSI-ETKF Data Assimilation System
LUO Jing-Yao1,2, CHEN Bao-De2, LI Hong2, FAN Guang-Zhou1, WANG Xiao-Feng2
1College of Atmospheric Sciences, Chengdu University of Informational Technology, Chengdu 610225, China 2Shanghai Typhoon Institute, China Meteorological Administration (CMA), Shanghai 200030, China
A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track forecast with simulated dropsonde observations. This hybrid system showed significantly improved results with respect to tropical cyclone track forecast compared to the standard GSI system in the case of Muifa in 2011. Further analyses revealed that the flow-depen-dent ensemble covariance was the major contributor to the better performance of the GSI-ETKF system than the standard GSI system; the GSI-ETKF system was found to be potentially able to adjust the position of the typhoon vortex systematically and better update the environmental field.
LUO Jing-Yao, CHEN Bao-De, LI Hong, FAN Guang-Zhou, WANG Xiao-Feng, 2013: Typhoon Track Forecast with a Hybrid GSI-ETKF Data Assimilation System . Atmos. Oceanic Sci. Lett., 6(3), 161-166, doi: 10.3878/j.issn.1674-2834.12.0102.
