Improving a precipitation forecast by assimilating all-sky himawari-8 satellite radiances: A case of Typhoon Malakas (2016)

Abstract

Tropical cyclones (TCs) and associated heavy precipitation have large impacts in Japan. This study aims to find how data assimilation (DA) of every-10-minute all-sky Himawari-8 radiances could improve the quantitative precipitation forecast (QPF) for TC cases. As the first step, this study performs a single case study of Typhoon Malakas (2016) using a regional atmospheric model from the Scalable Computing for Advanced Library and Environment (SCALE) coupled with the local ensemble Kalman filter (LETKF). The results show that the all-sky Himawari-8 radiance DA at 6-km resolution improves the representation of Malakas and may provide more accurate deterministic and probabilistic precipitation forecasts if the horizontal localization scale is chosen appropriately.