Improving the spin-up of the regional EnKF for typhoon assimilation and forecast with the 2008 Typhoon Sinlaku

The Running-In-Place method (RIP, Kalnay and Yang, 2010) is implemented in the framework of the Local Ensemble Transform Kalman Filter (LETKF) coupled with the Weather Research and Forecasting (WRF) model. The RIP method aims at improving the ensemble-based background error covariance and the accuracy of the ensemble mean state when the ensemble is initialized from a global analysis obtained at coarser resolution, lacking features related to the underlying mesoscale evolution. The RIP method is further proposed to serve as an outer-loop scheme to improve the nonlinear evolution of the ensemble when the error statics rapidly change due to the strong nonlinear dynamics. The impact of using the RIP as an outer-loop for the WRF-LETKF system is tested for typhoon assimilation and prediction with the case of 2008 Typhoon Sinlaku.

Compared to the results from the standard WRF-LETKF system without RIP, the typhoon track prediction is significantly improved with the RIP scheme, especially during the spin-up period of the LETKF assimilation when Sinlaku is at its rapid developing stage from a severe tropical storm. Also, the impact of the dropsonde of the flight data is significantly increased at early assimilation cycles. Results suggest that these improvements are due to the positive impact on the nonlinear evolution of the ensemble so that the environmental condition for the typhoon movement is better represented. Results also suggest that adaptively using the RIP scheme can provide further impact.