アンサンブル予測の更新に伴う不確実性の増幅を考慮したリアルタイム線状降水帯予測

Abstract

For disaster prevention, it is important to predict the duration and the amount of rainfall brought by line-shaped rainbands. We examined a prediction method of ensemble forecast under a hypothesis that ensemble forecasts for difficult-to-predict events show the characteristic that the ensemble spread does not decrease. We call “𝐺𝐹𝑈” (Growing Forecast Uncertainty) as how became large the spread of updated forecast compare with the past ones. We analyzed ensemble forecast data of the recent line-shaped rainbands events and we found when the precipitation forecast was underpredicted, the 𝐺𝐹𝑈 becomes larger. From these analysis, we think that 𝐺𝐹𝑈 can be used to predict the occurrence and duration of line-shaped rainbands heavy rainfall and how forecast will go wrong.