Japan Geoscience Union Meeting 2023

Presentation information

[E] Oral

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

[A-CG32] Climate Variability and Predictability on Subseasonal to Centennial Timescales

Mon. May 22, 2023 10:45 AM - 12:00 PM 104 (International Conference Hall, Makuhari Messe)

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

11:15 AM - 11:30 AM

[ACG32-08] ENSO feedback biases common to the uncoupled and coupled climate model simulations of CMIP6

*Michiya Hayashi1 (1.National Institute for Environmental Studies)

Keywords:El Niño/Southern Oscillation, Climate models, model bias

Systematic errors in the dynamic and thermodynamic feedback processes of El Niño/Southern Oscillation (ENSO) tend to be compensated for each other in atmosphere-ocean coupled climate models, which reasonably reproduce ENSO’s sea surface temperature (SST) variability. Surface zonal wind response to SST anomalies over the equatorial Pacific is key positive dynamic feedback to developing ENSO but underestimated in the majority of coupled climate models. This wind feedback bias tends to be reduced substantially in atmosphere-only (AMIP) simulations where the SST is prescribed by observations, but it still remains in most models. In this study, the wind feedback bias is revisited by focusing on two physical relationships: the equatorial Pacific precipitation response to the Niño-3.4 SST anomalies (P-SST relation) and the central Pacific zonal wind response to the equatorial Pacific precipitation anomalies (U-P relation). The coupled historical and AMIP simulations of CMIP6 climate models are compared with multiple observational datasets. The wind feedback is too weak on average in the coupled historical simulations but it is much improved in the AMIP simulations as the observed P-SST relation is reasonably reproduced. In contrast, the U-P relation is underestimated similarly in both the historical and AMIP simulations despite that the mean states in the historical simulations are largely biased. The underestimation of the U-P relation is seasonally robust in boreal winter to early spring in both simulations, characterized by too weak southern off-equatorial wind and precipitation anomalies relative to the equatorial Pacific precipitation anomalies. This systematic error due to atmospheric processes should be improved to make future projections of ENSO more reliable.