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The relatively weak sea surface temperature bias in the tropical Indian Ocean (TIO) simulated in the coupledgeneral circulation model (CGCM) from the recently released CMIP6 has been found to be important in model simulationsof regional and global climate. However, the cause of the bias is debated because the bias is strongly modeldependent and shows marked seasonality. In this study, we separate the bias in CGCMs into bias arising from oceanicGCMs (OGCMs) and bias that is independent of OGCMs using a set of CMIP6 and OMIP6 models. We found thatOGCMs contribute little to mixed layer bias in the CGCMs. The OGCM-independent bias exhibits a large-scale coldmixed layer bias in the TIO throughout the year, with an unexpectedly high degree of model consistency. By conducting aset of OGCM experiments, we show that the OGCM-independent mixed layer bias is caused mainly by surface wind biasin the utilized CGCMs. About 89% of surface wind bias in the CGCMs is due to the inability of atmospheric GCMs(AGCMs), whereas atmosphere–ocean coupling in the CGCMs has only a minor influence on surface wind bias. The biasin surface wind is also found to be the cause of subsurface temperature bias besides the ocean dynamics such as verticalmixing and vertical shear in currents. Our results indicate that correcting TIO mixed layer bias in CGCMs requires improvementin the capability of AGCM in simulating the climatological surface winds. The results improve our understanding of the cause of the bias in the IndianOcean and show that our method of bias separation is effective for attributing the source of bias to different proposedmechanisms.
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Jie Feng (2024) studied this question.
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