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

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 com-posed of the NICAM (non-hydrostatic icosahedral atmospheric model) and the LETKF (local ensemble transform Kalman filter). We performed ensemble data assimilation and forecast experi-ments 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 associat-ed with a low-pressure anomaly over the Baiu front was related to this heavy rainfall in Kyushu.

Automated summary

This study investigated the predictability and causes of a heavy rainfall event in Kyushu in July 2020. The results showed that ensemble forecasts with 1024 members were able to predict the probability of heavy rainfall in Kyushu about five days in advance, and identified the moist air inflow associated with a low-pressure anomaly as a cause of this heavy rainfall.