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<p>In recent years, anthropogenic factors have continuously warmed the ocean’s top layers, increasing heat accumulation and key ocean parameters, including ocean surface temperature and ocean heat potential in the Bay of Bengal. Previous research indicates that the depth of the ocean’s mixed layer significantly influences air-sea interactions, warming trends and regional climate changes. The current study analyzes the effectiveness of the 30 CMIP6 global circulation model in predicting the regional Mixed Layer Depth (MLD) accuracy in the Bay of Bengal. For deriving the Mixed Layer Depth of each subdomain, the Seawater Potential Temperature (Thetao) and salinity (so) from 30 models were taken, each with a spatial resolution of 100&#xa0;km on a monthly scale. To check the reliability of the CMIP6 model-simulated Mixed-layer depth (MLD) data, MLD data from the Estimating the Circulation and Climate of the Ocean (ECCO) project and Rama Buoy data for the location 15<sup>0</sup> N 90<sup>0</sup> E are chosen for validation. The CAMS-CSM1-0 model demonstrates superior performance with higher skill scores and lower performance indices matrix in all subdomains. ACCESS-CM2 and MCM-UA-1-0 models exhibit poor performance in general. The seasonal pattern of Mixed Layer Depth has been analyzed, employing Empirical Orthogonal Functions to examine the underlying climate phenomena. The result shows that the CAMS-CSM1-0 model can capture Indian Ocean Dipole events and Kelvin wave propagation in the Bay of Bengal region, implying the accuracy of the global circulation model in regional oceans.</p>

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Precision of CMIP6 models in acquiring mixed layer depth and climate events in the Bay of Bengal

  • 期刊论文

  • 发表日期：

    2025年10月13日

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  • A. B. Asok,
  • H. V. Warrior

摘要

In recent years, anthropogenic factors have continuously warmed the ocean’s top layers, increasing heat accumulation and key ocean parameters, including ocean surface temperature and ocean heat potential in the Bay of Bengal. Previous research indicates that the depth of the ocean’s mixed layer significantly influences air-sea interactions, warming trends and regional climate changes. The current study analyzes the effectiveness of the 30 CMIP6 global circulation model in predicting the regional Mixed Layer Depth (MLD) accuracy in the Bay of Bengal. For deriving the Mixed Layer Depth of each subdomain, the Seawater Potential Temperature (Thetao) and salinity (so) from 30 models were taken, each with a spatial resolution of 100 km on a monthly scale. To check the reliability of the CMIP6 model-simulated Mixed-layer depth (MLD) data, MLD data from the Estimating the Circulation and Climate of the Ocean (ECCO) project and Rama Buoy data for the location 150 N 900 E are chosen for validation. The CAMS-CSM1-0 model demonstrates superior performance with higher skill scores and lower performance indices matrix in all subdomains. ACCESS-CM2 and MCM-UA-1-0 models exhibit poor performance in general. The seasonal pattern of Mixed Layer Depth has been analyzed, employing Empirical Orthogonal Functions to examine the underlying climate phenomena. The result shows that the CAMS-CSM1-0 model can capture Indian Ocean Dipole events and Kelvin wave propagation in the Bay of Bengal region, implying the accuracy of the global circulation model in regional oceans.