Japan Geoscience Union Meeting 2022

Session information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-CG Complex & General

[A-CG34] Climate Variability and Predictability on Subseasonal to Multidecadal Timescales

Wed. May 25, 2022 10:45 AM - 12:15 PM 201A (International Conference Hall, Makuhari Messe)

convener:Yushi Morioka(Japan Agency for Marine-Earth Science and Technology), convener:Hiroyuki Murakami(Geophysical Fluid Dynamics Laboratory/University Corporation for Atmospheric Research), Tomoe Nasuno(Japan Agency for Marine-Earth Science and Technology), convener:Liping Zhang(NOAA GFDL Princeton), Chairperson:Liping Zhang(NOAA GFDL Princeton), Yushi Morioka(Japan Agency for Marine-Earth Science and Technology)


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.

10:45 AM - 11:00 AM

*Nathaniel C Johnson1, Kai-Chih Tseng1,3, Thomas L Delworth1, Liwei Jia1,2, Feiyu Lu1,3, William Cooke1, Colleen McHugh1,4, Andrew T Wittenberg1 (1.NOAA Geophysical Fluid Dynamics Laboratory, 2.University Corporation for Atmospheric Research, 3.Department of Geosciences, Program in Atmospheric and Oceanic Science, Princeton University, 4.SAIC, Science Applications International Corporation)

11:30 AM - 11:45 AM

*Patrick Martineau1, Swadhin Behera1, Masami Nonaka1, Venkata Ratnam Jayanthi1, Takayoshi Ikeda2, Noboru Minakawa3, Philip Kruger4, Qavanisi Mabunda4 (1.Japan Agency for Marine-Earth Science and Technology, 2.Blue Earth Security Co., Ltd., Tokyo, Japan, 3.Nagasaki University, Institute of Tropical Medicine, Nagasaki, Japan, 4.Malaria Control Programme, Limpopo Department of Health, Tzaneen, South Africa)

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