日本地球惑星科学連合2022年大会

講演情報

[E] ポスター発表

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-AS03] 大規模な水蒸気場と組織化した雲システム

2022年6月2日(木) 11:00 〜 13:00 オンラインポスターZoom会場 (6) (Ch.06)

コンビーナ:横井 覚(海洋研究開発機構)、コンビーナ:三浦 裕亮(国立大学法人 東京大学大学院 理学系研究科 地球惑星科学専攻)、濱田 篤(富山大学)、コンビーナ:高須賀 大輔(海洋研究開発機構)、座長:横井 覚(海洋研究開発機構)、三浦 裕亮(国立大学法人 東京大学大学院 理学系研究科 地球惑星科学専攻)

11:00 〜 13:00

[AAS03-P03] Classification of Quasi-Seasonal Synoptic Fields Using Self-Organizing Map and Occurrence Trend of Line-shaped Rainbands

*大屋 祐太1山田 朋人2 (1.北海道大学大学院工学院、2.北海道大学)


キーワード:線状降水帯、準季節気象場

In recent years, Line-shaped rainbands (hereinafter referred to as LRB) have occurred frequently in Japan. LRB is precipitation systems with meso-scale convective systems in which cumulus clouds are continuously distributed in a linear pattern. In Japan, Hokkaido is considered the region where annual rainfall is relatively low compared to that in Kyushu, and other western regions. Extreme rainfall events such as LRB tend to increase in this island, such as the extreme rainfall event in 2010, the frequency of LRB is extremely high in this island. In such years, the sea surface temperature around Hokkaido is higher than climatology, and the positive anomaly associated with the active Pacific high pressure system, brings a huge water vapor supply to the region in sub-seasonally.
Considering the aforementioned information, sub-seasonal meteorological fields were classified by applying machine learning to reanalysis data and large ensemble data in this study. The method is Self-Organizing Map, which has an advantage in mapping multidimensional vectors to two-dimensional vectors.
Meteorological fields similar to those in multiple LRB years would be identified from these classifications. The results indicated that in those clusters, the number of LRB occurrences in the same area was relatively high. In order to take advantage of the application to large ensemble data, the statistical advantages of the classification will be explained in the further study.