日本地球惑星科学連合2022年大会
セッション概要| 大気水圏科学 (A) | ||||
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| セッション小記号 | 大気海洋・環境科学複合領域・一般 (CG) |  |
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| セッション ID | A-CG34 | |||
| タイトル | Climate Variability and Predictability on Subseasonal to Multidecadal Timescales | |||
| タイトル短縮名 | Climate Variability and Predictability | |||
| 開催日時 | 口頭セッション | 5/25(水) AM1 |
現地会場 | |
| 現地ポスターコアタイム | 5/25(水) PM3 | |||
| 代表コンビーナ | 氏名 | 森岡 優志 | ||
| 所属 | 海洋研究開発機構 | |||
| 共同コンビーナ 1 | 氏名 | Hiroyuki Murakami | ||
| 所属 | Geophysical Fluid Dynamics Laboratory/University Corporation for Atmospheric Research | |||
| 共同コンビーナ 2 | 氏名 | 那須野 智江 | ||
| 所属 | 国立研究開発法人 海洋研究開発機構 | |||
| 共同コンビーナ 3 | 氏名 | Liping Zhang | ||
| 所属 | NOAA GFDL Princeton | |||
| セッション言語 | E | |||
| 』スコープ |
Climate variability on subseasonal to multidecadal timescales (e.g., Madden-Julian Oscillation, El Nino/Southern Oscillation (ENSO), Indian Ocean Dipole, Pacific Decadal Variability, Atlantic Multidecadal Variability, Southern Ocean Centennial Variability) exerts great influences on global socioeconomic activities by modulating physical characteristics of extreme weather events (e.g., heatwaves/coldwaves, tropical cyclones, and floods/droughts). Many efforts have been made to accurately understand and skillfully predict subseasonal to multidecadal climate variability. However, models have shown systematic biases in amplitude, spatial pattern, and frequency of these climate variabilities. These model biases often stem from multiple factors such as poor understanding of weather and climate interactions across different spatiotemporal scales (e.g., tropical cyclones-ENSO) and insufficient representation of the complex and non-linear climate system (e.g., troposphere-stratosphere coupling, atmosphere-ocean-sea ice interactions) so that seamless studies on climate variability are required. This session invites all research activities related to the subseasonal to multidecadal climate variability using observational data (e.g., satellite, ship, buoy/float, proxy data), theoretical/modeling approaches, and artificial intelligence/machine learning frameworks. The research topics through analyzing Coupled Model Intercomparison Project Phase 6 (CMIP6) are also welcomed. |
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| 発表方法 | 口頭およびポスターセッション | |||
| 共催情報 | 学協会 | 日本海洋学会, 日本気象学会 | ||
| ジョイント | AGU, EGU, AOGS | |||