2022年5月25日(水) 10:45 〜 12:15 201A (幕張メッセ国際会議場)

コンビーナ:森岡 優志(海洋研究開発機構)、コンビーナ:Murakami Hiroyuki(Geophysical Fluid Dynamics Laboratory/University Corporation for Atmospheric Research)、那須野 智江(国立研究開発法人　海洋研究開発機構)、コンビーナ:Zhang Liping(NOAA GFDL Princeton)、Chairperson:Liping Zhang(NOAA GFDL Princeton)、森岡 優志(海洋研究開発機構)

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.