Contributions of upper layer processes on the mixed layer temperature in the Bay of Bengal using relative importance methods

The Mixed Layer Heat Budget (MLHB) is based on energy conservation wherein Mixed Layer Temperature (MLT) tendency equals the sum of Net Surface Heat Flux (NSHF), Horizontal Advection (HA), Vertical Entrainment (VE), Vertical Diffusion (VD), and residual. This study utilizes 25 years (1991–2015) of data from a Regional Ocean Modeling System (ROMS) simulation for quantifying the Relative Importance (RI) of MLHB terms, using Johnson’s Relative Weight Analysis (RWA) approach, in the Bay of Bengal (BoB). The RIs obtained from the RWA approach fall within their respective 95% confidence intervals obtained through bootstrapping. The analysis showed that the NSHF, dependent on spatio-temporally varying Mixed Layer Depth (MLD), plays a greater role in modulating the MLT tendency ( \(\approx \) $\approx$ 50%) over the whole BoB during different seasons. Moreover, HA ( \(\approx \) $\approx$ 20%) prominently impacts the southern and western BoB, which is related to the boundary current system and the associated thermal gradients. During monsoon, it was found that HA warms the Sri Lanka dome region due to meridional heat transport from around the east coast of India while cooling the southern BoB through cooler south-west monsoon currents. Finally, VE ( \(\approx \) $\approx$ 20%) and VD ( \(\approx \) $\approx$ 10%) contribute higher around the Sri Lanka dome due to the presence of a cyclonic eddy during pre-monsoon and monsoon. Also, VE and VD have a higher role during post-monsoon and winter due to the presence of thermal inversion in the northern BoB. Lastly, the residual showed an average RI of about 15%, which is of the same order as HA, VE, and VD. This suggests that the residual is not only composed of errors associated with the MLHB terms but there might also be some unknown physical processes at play that significantly impact MLT. This points toward the need for improvement in the MLHB, which holds a key for a better assessment of the ocean state.