J7.6
Local ensemble transform Kalman filter experiments with the WRF model

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Monday, 24 January 2011: 5:15 PM
Local ensemble transform Kalman filter experiments with the WRF model
2B (Washington State Convention Center)
Masaru Kunii, University of Maryland, College Park, MD, College Park, MD; and T. Miyoshi

The local ensemble transform Kalman filter (LETKF, Hunt et al. 2007) is a realistic implementation of ensemble Kalman square root filters for advanced data assimilation and ensemble prediction. The LETKF has been successfully applied to various numerical models including global and regional numerical weather prediction (NWP) models, global and regional ocean models, and even a Martian atmospheric model. Recently the LETKF has been applied to the Weather Research and Forecasting (WRF) model, a widely used nonhydrostatic regional NWP model. The LETKF system includes the recently developed adaptive inflation method. The WRF-LETKF system performed properly with real observations, so that a 9-day assimilation cycle experiment reproduced Typhoon Sinlaku (2008) very well although the typhoon was not generated at all without assimilation. . Experiments are performed for the typhoon case with T-PARC (THORPEX Pacific Asian Regional Campaign) observations to investigate their impact.