1:45 PM - 2:00 PM
*Jacob Gunnarson1, Malte F Stuecker1, Zhao Sen1 (1. University of Hawaii at Manoa)
[E] Oral
A (Atmospheric and Hydrospheric Sciences ) » A-CG Complex & General
Sun. May 24, 2026 1:45 PM - 3:15 PM 104 (International Conference Hall, Makuhari Messe)
Chairperson:Yamagami Yoko(Japan Agency for Marine-Earth Science and Technology), Morioka Yushi(Japan Agency for Marine-Earth Science and Technology), Miyamoto Ayumu(Scripps Institution of Oceanography, University of California San Diego), Kim Soong-Ki(Yale University)
Climate variability on subseasonal to centennial timescales (e.g., Madden-Julian Oscillation, El Nino/Southern Oscillation (ENSO), Indian Ocean Dipole, Pacific Decadal Variability, Atlantic Multidecadal Variability, Southern Ocean Centennial Variability) has significant impacts on global socioeconomic activities by inducing extreme climate events (e.g., atmospheric and marine heatwaves/coldwaves, hurricanes/typhoons/cyclones, and floods/droughts) and influencing their physical characteristics. Numerous efforts have been made to comprehensively understand and skillfully predict subseasonal to centennial climate variabilities using observation data and dynamical/statistical models. However, most models still undergo systematic biases in the amplitude, spatial patterns, and frequency of these climate variabilities. These model biases often stem from an inadequate grasp of weather and climate interactions across different spatiotemporal scales (e.g., tropical cyclones-ENSO) and incomplete representation of the complex and nonlinear processes within the climate system (e.g., troposphere-stratosphere coupling, atmosphere-ocean-sea ice interactions). Therefore, a seamless approach to climate modeling and observational studies across different spatiotemporal scales is essential. This session welcomes all research activities related to subseasonal to centennial climate variabilities utilizing observational data (e.g., satellite, ship, buoy/float, proxy data), theoretical/modeling approaches, and artificial intelligence/machine learning frameworks. Research topics involving the analysis of the Coupled Model Intercomparison Project Phase (CMIP) are also welcome.
1:45 PM - 2:00 PM
*Jacob Gunnarson1, Malte F Stuecker1, Zhao Sen1 (1. University of Hawaii at Manoa)
2:00 PM - 2:15 PM
*KENTA OBARA1, Yukiko Imada1 (1. Atmosphere and Ocean Research Institute, the University of Tokyo)
2:15 PM - 2:30 PM
*Ryo Satoh1, Yu Kosaka1 (1. Research Center for Advanced Science and Technology, the University of Tokyo)
2:30 PM - 2:45 PM
*Ko Tsuchida1, Yu Kosaka1, Takahito Kataoka2, Ayumu Miyamoto3, Masahiro Watanabe4, Hideo Shiogama5 (1. Research Center for Advanced Science and Technology, the University of Tokyo, Japan, 2. Japan Agency for Marine-Earth Science and Technology, Japan, 3. Scripps Institution of Oceanography, University of California San Diego, US, 4. Atmosphere and Ocean Research Institute, The University of Tokyo, Japan, 5. National Institute for Environmental Studies, Japan)
2:45 PM - 3:00 PM
*Kazuki Igari1, Saori Sakai1, Yu Kosaka1 (1. Research Center for Advanced Science and Technology, the University of Tokyo)
3:00 PM - 3:15 PM
*Yuki Maeda1, Masaki Satoh1 (1. Atmosphere and Ocean Research Institute, The University of Tokyo)
Please log in with your participant account.
» Participant Log In