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Evaluation of the Performance of CMIP5 and CMIP6 Models in Simulating the Victoria Mode–El Niño Relationship

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  • 1 a School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
  • | 2 b State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
  • | 3 c State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
  • | 4 d Frontiers Science Center for Deep Ocean Multispheres and Earth System (FDOMES), Key Laboratory of Physical Oceanography, Institute for Advanced Ocean Studies, Ocean University of China, Qingdao, China
  • | 5 e Laboratory for Ocean Dynamics and Climate, Pilot Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
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Abstract

The Victoria mode (VM) is the second dominant sea surface temperature mode in the North Pacific, forced by North Pacific Oscillation–like extratropical atmospheric variability. Observational studies have shown that the boreal spring VM is closely connected to the following winter El Niño, with the VM efficiently acting as a precursor signal to El Niño events. This study evaluates the relationship of the spring VM with subsequent winter El Niño in the preindustrial simulations of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). We found that most CMIP5 and CMIP6 models can simulate the basic characteristics of the VM reasonably well. The current CMIP6 models simulate the VM–El Niño connections more realistically as compared to the earlier CMIP5 models. The analysis further suggests that the improved capability of the CMIP6 models to simulate the VM–El Niño relationship is because the CMIP6 models are better able to capture the VM-related surface air–sea thermodynamic coupling process over the subtropical/tropical Pacific and the seasonal evolution of VM-related anomalous subsurface ocean temperature in the equatorial Pacific.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Wang’s current affiliation: Hebei Xiongan New Area Meteorological Service, Xiongan New Area 071700, China.

Publisher’s Note: This article was revised on 27 August 2021 to include the current affiliation of author Wang.

Corresponding author: Ruiqiang Ding, drq@bnu.edu.cn

Abstract

The Victoria mode (VM) is the second dominant sea surface temperature mode in the North Pacific, forced by North Pacific Oscillation–like extratropical atmospheric variability. Observational studies have shown that the boreal spring VM is closely connected to the following winter El Niño, with the VM efficiently acting as a precursor signal to El Niño events. This study evaluates the relationship of the spring VM with subsequent winter El Niño in the preindustrial simulations of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). We found that most CMIP5 and CMIP6 models can simulate the basic characteristics of the VM reasonably well. The current CMIP6 models simulate the VM–El Niño connections more realistically as compared to the earlier CMIP5 models. The analysis further suggests that the improved capability of the CMIP6 models to simulate the VM–El Niño relationship is because the CMIP6 models are better able to capture the VM-related surface air–sea thermodynamic coupling process over the subtropical/tropical Pacific and the seasonal evolution of VM-related anomalous subsurface ocean temperature in the equatorial Pacific.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Wang’s current affiliation: Hebei Xiongan New Area Meteorological Service, Xiongan New Area 071700, China.

Publisher’s Note: This article was revised on 27 August 2021 to include the current affiliation of author Wang.

Corresponding author: Ruiqiang Ding, drq@bnu.edu.cn
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