Origins of Underestimated Indian Ocean Dipole Skewness in CMIP5/6 Models

Yiling Zheng aEarth System Science Programme, The Chinese University of Hong Kong, Hong Kong, China
bShenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China

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Chi-Yung Tam aEarth System Science Programme, The Chinese University of Hong Kong, Hong Kong, China
bShenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China

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Kang Xu cState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

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Matthew Collins dDepartment of Mathematics and Statistics, University of Exeter, Exeter, United Kingdom

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Abstract

The Indian Ocean dipole (IOD) is the dominant mode of interannual variability in the tropical Indian Ocean (TIO), characterized by warming (cooling) in western TIO and cooling (warming) in eastern TIO during its positive (negative) phase. Observed IOD events exhibit distinct amplitude asymmetry in relation to negative nonlinear dynamic heating. Nearly all models in phase 5 of the Coupled Model Intercomparison Project (CMIP) simulate a less-skewed IOD than observed, but 6 out of 20 CMIP6 models can reproduce realistic high skewness. Analysis of less-skewed models indicates that the positive IOD-like biases in the mean state, which can be traced back to their weaker simulations of the preceding Indian summer monsoon, reduce the convective response to positive sea surface temperature anomalies in the western TIO, resulting in a weaker zonal wind response and weaker nonlinear zonal advection during positive IOD events. Besides, ocean stratification in the eastern TIO influences the IOD skewness: stronger stratification leads to larger mixed-layer temperature response to thermocline changes, contributing to larger anomalous vertical temperature gradient, larger nonlinear vertical advection, and thus stronger positive IOD skewness. Our findings underscore the importance of reducing Indian summer monsoon biases and eastern TIO stratification biases, for properly representing the IOD in Earth system models.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is included in the Process diagnostics in CMIP6 Special Collection.

Corresponding author: Chi-Yung Tam, francis.tam@cuhk.edu.hk

Abstract

The Indian Ocean dipole (IOD) is the dominant mode of interannual variability in the tropical Indian Ocean (TIO), characterized by warming (cooling) in western TIO and cooling (warming) in eastern TIO during its positive (negative) phase. Observed IOD events exhibit distinct amplitude asymmetry in relation to negative nonlinear dynamic heating. Nearly all models in phase 5 of the Coupled Model Intercomparison Project (CMIP) simulate a less-skewed IOD than observed, but 6 out of 20 CMIP6 models can reproduce realistic high skewness. Analysis of less-skewed models indicates that the positive IOD-like biases in the mean state, which can be traced back to their weaker simulations of the preceding Indian summer monsoon, reduce the convective response to positive sea surface temperature anomalies in the western TIO, resulting in a weaker zonal wind response and weaker nonlinear zonal advection during positive IOD events. Besides, ocean stratification in the eastern TIO influences the IOD skewness: stronger stratification leads to larger mixed-layer temperature response to thermocline changes, contributing to larger anomalous vertical temperature gradient, larger nonlinear vertical advection, and thus stronger positive IOD skewness. Our findings underscore the importance of reducing Indian summer monsoon biases and eastern TIO stratification biases, for properly representing the IOD in Earth system models.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

This article is included in the Process diagnostics in CMIP6 Special Collection.

Corresponding author: Chi-Yung Tam, francis.tam@cuhk.edu.hk

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