定性積雲モデルを用いた短時間降雨予測手法の開発に関する研究

Abstract

本論文では, 貯水池を用いた洪水制御支援のための短時間降雨予測システムとして, 積雲中の降水物理過程をルールベースで表現し, 定性推論・モデルベース推論を用いて積雲の発達を推論することによって降雨予測を行う。定性積雲モデルを用いた短時間降雨予測システムを提案する。さらに, 本手法を実際に生起した梅雨前線帯降雨の予測に適用し, 本手法の有効性を確認した上で, 従来の数値計算による降雨予測と本手法との違いを論じている。

Generally, it is dificult to forecast the weather of meso‐β to γscales numerically because of limited computational resources, stability of calculation, time and cost for computer and exactness of calculation.On the other hand, six hour ahead runoff forecasting is necessary for the real‐time flood control. Therefore, it is indispensable to get the information of the forecasted rainfall which is the input of the runoff. In this paper, based on these background, we develop the Severe Rainfall prediction method using Artificial Intelligence, SRAI, which can forecast the time series variation of distribution of severe rainfall.This is the unprecedented method in the sence that severe rainfall is predicted mainly based on Qualitative Reasoning, QR, and Model Based Reasoning, MBR, without calculating numerically.