Real-Time Prediction of Line-Shaped Rainband Considering 'Growing Forecast Uncertainty' Estimated from Update History of Ensemble Forecast

Autor: YAMAGUCHI, Kosei, KURODA, Nana, NAKAKITA, Eiichi
Jazyk: japonština
Rok vydání: 2021
Předmět:
Zdroj: 京都大学防災研究所年報. B. 64:237-276
ISSN: 0386-412X
Popis: 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.
Databáze: OpenAIRE