Japan Geoscience Union Meeting 2021

Session information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-OS Ocean Sciences & Ocean Environment

[A-OS09] Climate variability and predictability on subseasonal to multidecadal timescales

Thu. Jun 3, 2021 1:45 PM - 3:15 PM Ch.09 (Zoom Room 09)

convener:Yushi Morioka(Japan Agency for Marine-Earth Science and Technology), Hiroyuki Murakami(Geophysical Fluid Dynamics Laboratory/University Corporation for Atmospheric Research), Masuo Nakano(JAMSTEC Japan Agency for Marine-Earth Science and Technology), V Ramaswamy(NOAA GFDL), Chairperson:Hiroyuki Murakami(Geophysical Fluid Dynamics Laboratory/University Corporation for Atmospheric Research), Masuo Nakano(JAMSTEC Japan Agency for Marine-Earth Science and Technology)

Climate variability on subseasonal-multidecadal timescales (e.g. Madden-Julian Oscillation, ENSO, Indian Ocean Dipole, Pacific Decadal Variability, Atlantic Multidecadal Variability) has serious impacts on global and regional socioeconomic activities through changes in intensity and frequency of extreme weather events (e.g. cold/heat waves, tropical storms, and floods/droughts). Efforts have been made to understand and predict subseasonal-multidecadal climate variability, but climate simulations and predictions using state-of-the-art coupled general circulation models have biases that represent large uncertainties in amplitude and spatial patterns of the climate variability. The model uncertainties arise from multiple factors such as inadequate 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-land interactions). Recently, Coupled Model Intercomparison Project Phase 6 (CMIP6) has opened up new model simulation datasets to the public, which can be expected to further advance our understanding and prediction of subseasonal-multidecadal climate variability under the changing climate. This session invites all research related to the subseasonal-multidecadal climate variability using observational, theoretical, modelling and AI/ML frameworks and especially novel approaches.

2:15 PM - 2:30 PM

*Shreya Dhame1, Andrea Taschetto1, Agus Santoso1,2, Giovanni Liguori3, Katrin Meissner1 (1.ARC Centre of Excellence for Climate Extremes, Climate Change Research Centre, University of New South Wales, Sydney, Australia, 2.Centre for Southern Hemisphere Oceans Research (CSHOR), CSIRO Oceans and Atmosphere, Hobart, Australia, 3.ARC Centre of Excellence for Climate Extremes, School of Earth, Atmosphere and Environment, Monash University, Melbourne, Australia)


2:30 PM - 2:45 PM

*Yu Zhang1,2, Shiyun Yu1,2, Dillon J. Amaya3, Yu Kosaka4, Sarah M. Larson5, Xudong Wang6, Jun-Chao Yang1,2, Malte F. Stuecker7, Shang-Ping Xie8, Arthur J. Miller8, Xiaopei Lin1,2 (1.Ocean University of China, 2.Qingdao National Laboratory for Marine Science and Technology, 3.University of Colorado Boulder, 4.The University of Tokyo, 5.North Carolina State University, 6.Nanjing University of Information Science and Technology, 7.University of Hawai'i at Mānoa, 8.University of California San Diego)

2:45 PM - 3:00 PM

*Jun-Chao Yang1,2, Xiaopei Lin1,2, Shang-Ping Xie3, Yu Zhang1,2, Yu Kosaka4, Ziguang Li1,2 (1.Frontiers Science Center for Deep Ocean Multispheres and Earth System and Physical Oceanography Laboratory, Ocean University of China, 2.Qingdao National Laboratory for Marine Science and Technology, 3.Scripps Institution of Oceanography, University of California, 4.Research Center for Advanced Science and Technology, University of Tokyo)

3:00 PM - 3:15 PM

*Tamaki Suematsu1, Tomoro Yanase4,2, Hiroaki Miura3, Chihiro Kodama5, Masaki Satoh1 (1.Atmosphere and Ocean Research Institute, The University of Tokyo, 2.RIKEN Center for Computational Science, 3.Graduate School of Science, The University of Tokyo , 4.Graduate School of Science, Kyoto University , 5.Japan Agency for Marine-Earth Science and Technology )

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