A 1024-Member NICAM-LETKF Experiment for the July 2020 Heavy Rainfall Event

Abstract

This study investigated the predictability and causes of the heavy rainfall event that brought severe disasters in Kyushu in July 2020 with a global numerical weather prediction system composed of the NICAM (non-hydrostatic icosahedral atmospheric model) and the LETKF (local ensemble transform Kalman filter). We performed ensemble data assimilation and forecast experiments using the NICAM-LETKF system with 1,024 members and 56-km horizontal resolution on the supercomputer Fugaku. The results showed that 1,024-member ensemble forecasts captured the probability of heavy rainfall in Kyushu about five days before it happens, although a 10-day-lead forecast is difficult. Ensemble-based lag-correlation analyses with the 1024-member ensemble showed very small sampling errors in the correlation patterns and showed that the moist air inflow in the lower troposphere associated with a low-pressure anomaly over the Baiu front was related to this heavy rainfall in Kyushu.