Recorded presentation5.3
Local ensemble transform Kalman filtering with JMA global model
Takemasa Miyoshi, Japan Meteorological Agency, Tokyo, Japan; and Y. Sato, T. Kadowaki, and M. Kazumori
A local ensemble transform Kalman filter (LETKF) has been applied to Japan Meteorological Agency (JMA)'s global forecasting system and compared with the operational four-dimensional variational (4D-Var) data assimilation system. LETKF indicates smaller forecast errors in wind fields in the Tropics and NH. Partly due to the better wind forecast, LETKF is superior to 4D-Var in typhoon track forecasts. A typhoon case in August 2004 indicates advantages of LETKF as an ensemble prediction system (EPS). Recently, a novel method of adaptive bias correction for satellite radiances has been developed, indicating significant positive impact. By virtue of the adaptive bias correction, LETKF indicates forecast performance generally superior to 4D-Var in the NH and Tropics, but still inferior in the SH. This presentation overviews recent developments of LETKF at JMA, including the description of the adaptive bias correction method as well as the latest progress up to the time of conference. Recorded presentation
Session 5, Advanced Methods for Data Assimilation-I
Tuesday, 22 January 2008, 8:30 AM-9:45 AM, 204
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