Predictability of record-breaking rainfall in Japan in july 2018: Ensemble forecast experiments with the near-real-time global atmospheric data assimilation system NEXRA

Abstract

This paper is the first publication presenting the predictability of the record-breaking rainfall in Japan in July 2018 (RJJ18), the severest flood-related disaster since 1982. Of the three successive precipitation stages in RJJ18, this study investigates synoptic-scale predictability of the third-stage precipitation using the near-realtime global atmospheric data assimilation system named NEXRA. With NEXRA, intense precipitation in western Japan on July 6 was well predicted 3 days in advance. Comparing forecasts at different initial times revealed that the predictability of the intense rains was tied to the generation of a low-pressure system in the middle of the frontal system over the Sea of Japan. Observation impact estimates showed that radiosondes in Kyusyu and off the east coast of China significantly reduced the forecast errors. Since the forecast errors grew more rapidly during RJJ18, data assimilation played a crucial role in improving the predictability.