Ocean heat content variability in the Bay of Bengal: a CMIP6 model analysis with implications on the Indian Ocean Dipole

The present study evaluates the performance of CMIP6 models in capturing ocean heat content (OHC) variations in the Bay of Bengal. The seawater potential temperature of the six best-performing models up to a depth of 500 m from the sea surface was chosen for the study on a 1° ´ 1° horizontal resolution and monthly temporal scale, compared with RAMA buoy and North Indian Ocean Atlas data. Performance indices such as root mean square error (RMSE), average error, absolute average error (AAE) and Willmott score were used. The GISS-E2-1-G model performed better with lower RMSE and AAE values, while the IPSL-CM6A-LR model performed poorly. Monthly climatology variations showed increased temperature and OHC during the summer. Annual trends in OHC revealed negative trends for some models, indicating a net loss of heat, while others showed positive trends, indicating heat accumulation. Comparison with RAMA buoy data consistently showed lower heat content than the models, indicating overestimation. The study emphasizes the importance of incorporating observational data to improve accuracy. The findings highlight variations in model performance, and the need for understanding uncertainties and biases in climate models for reliable projections. Additionally, the study suggests that the interaction between the North and South Bay of Bengal can affect the Indian Ocean Dipole phenomenon, influencing temperature gradients and hence OHC