日本地球惑星科学連合2023年大会

講演情報

[E] 口頭発表

セッション記号 A (大気水圏科学) » A-AS 大気科学・気象学・大気環境

[A-AS02] 気象の予測可能性から制御可能性へ

2023年5月22日(月) 13:45 〜 15:00 104 (幕張メッセ国際会議場)

コンビーナ:三好 建正(理化学研究所)、中澤 哲夫(東京大学大気海洋研究所)、Shu-Chih Yang(National Central University)、高玉 孝平(科学技術振興機構)、座長:三好 建正(理化学研究所)、Tetsuo Nakazawa(Meteorological Research Institute, Japan Meteorological Agency)

14:30 〜 14:45

[AAS02-04] Quantifying Weather Controllability and Mitigatable Flood Damage Based on Ensemble Weather Forecast

*小槻 峻司1 (1.千葉大学 国際高等研究基幹)

キーワード:気象制御、アンサンブル予測、情報圧縮、有向グラフ

For realizing a weather-controlled society, we need to discuss the way to maximize the effect of manipulations to the atmosphere. For that purpose, this project aims at developing methods that quantify weather controllability and mitigatable flood damage based on ensemble weather forecasts. To quantify weather controllability, this project investigates meteorological landscapes that separate disaster and non-disaster regimes which may be controllable with small manipulations. We also estimate economic damages under non-controlled/controlled scenarios, in order to quantify avoidable damage by weather control.
We have started illustrating directed graphs as the first step in understanding the meteorological landscape. Typhoon Prapiroon in 2018 was used for the case study. Singular value decomposition (SVD) is employed for Japan Meteorological Agency’s operational meso-scale ensemble prediction data to extract principle components of atmospheric states, followed by a clustering using density-based spatial clustering of applications with noise known as DBSCAN. The illustrated graph succeeded in detecting separated two clusters that correspond to faster and slower movements of predicted Parapiroon. The developed algorithm is currently applied to other disastrous events as well as further investigations on non-linear data compression methods beyond SVD. This presentation includes the most recent achievements up to the time of the conference.