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Origins of the Excessive Westward Extension of ENSO SST Simulated in CMIP5 and CMIP6 Models

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  • 1 Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources/College of Oceanography, Hohai University, Nanjing, China
  • | 2 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • | 3 Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • | 4 University of Chinese Academy of Sciences, Beijing, China
  • | 5 State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China
  • | 6 Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
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Abstract

An excessive westward extension of the simulated ENSO-related sea surface temperature (ENSO SST) variability in the CMIP5 and CMIP6 models is the most apparent ENSO SST pattern bias and dominates the intermodel spread in ENSO SST variability among the models. The ENSO SST bias lowers the models’ skill in ENSO-related simulations and induces large intermodel uncertainty in ENSO-related projections. The present study investigates the origins of the excessive westward extension of ENSO SST in 25 CMIP5 and 25 CMIP6 models. Based on the intermodel spread of ENSO SST variability simulated in the 50 models, we reveal that this ENSO SST bias among the models largely depends on the simulated cold tongue strength in the equatorial western Pacific (EWP). Models simulating a stronger cold tongue tend to simulate a larger mean zonal SST gradient in the EWP and then a larger zonal advection feedback in the EWP, favoring a more westward extension of the ENSO SST pattern. In addition, with the overall improvement in the EWP cold tongue from CMIP5 to CMIP6, the excessive westward extension bias of ENSO SST in CMIP6 models is also reduced relative to those in CMIP5 models. The results suggest that the bias and intermodel disagreement in the mean-state SST have been improved, which improves ENSO simulation.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-20-0551.s1.

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

Corresponding authors: Dr. Ping Huang, huangping@mail.iap.ac.cn; Dr. Wenping Jiang, jiangwenping@hhu.edu.cn

Abstract

An excessive westward extension of the simulated ENSO-related sea surface temperature (ENSO SST) variability in the CMIP5 and CMIP6 models is the most apparent ENSO SST pattern bias and dominates the intermodel spread in ENSO SST variability among the models. The ENSO SST bias lowers the models’ skill in ENSO-related simulations and induces large intermodel uncertainty in ENSO-related projections. The present study investigates the origins of the excessive westward extension of ENSO SST in 25 CMIP5 and 25 CMIP6 models. Based on the intermodel spread of ENSO SST variability simulated in the 50 models, we reveal that this ENSO SST bias among the models largely depends on the simulated cold tongue strength in the equatorial western Pacific (EWP). Models simulating a stronger cold tongue tend to simulate a larger mean zonal SST gradient in the EWP and then a larger zonal advection feedback in the EWP, favoring a more westward extension of the ENSO SST pattern. In addition, with the overall improvement in the EWP cold tongue from CMIP5 to CMIP6, the excessive westward extension bias of ENSO SST in CMIP6 models is also reduced relative to those in CMIP5 models. The results suggest that the bias and intermodel disagreement in the mean-state SST have been improved, which improves ENSO simulation.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-20-0551.s1.

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

Corresponding authors: Dr. Ping Huang, huangping@mail.iap.ac.cn; Dr. Wenping Jiang, jiangwenping@hhu.edu.cn

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