Seasonal and Interannual Behaviour of Wave Characteristics and Its Long‐Term Evolution Over the Bay of Bengal

ABSTRACT

This study investigates the influence of large‐scale climatic modes like El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on the seasonal and annual wave characteristics over the Bay of Bengal (BoB). It is based on 44 years (June 1980–May 2024) of ERA5 reanalysis data, validated against in situ observations. The climatology results reveal a distinct seasonally reversing wind regime that governs the corresponding wave height and period variations. The windspeed reaches its maximum during the monsoon (June–September) and minimum during the pre‐monsoon (March–May), while wave activity peaks in the monsoon and weakens during winter (December–February). Statistically significant negative decadal trends in annual mean windspeed and sea height () are observed over the northern BoB, whereas swell height (), significant wave height (), and maximum wave height () exhibit increasing trends across the southern BoB. The mean wave period () shows an overall increasing trend throughout the basin. On an annual scale, and contribute 15.44% and 84.56%, respectively, to , with enhanced influence near coastal zones. Over the recent decades, statistically significant decreases in the contribution of in the northwestern and southeastern BoB indicate a transition towards a swell‐dominated condition associated with weakening of local winds. Composite analysis relative to climatology, cumulative anomaly and Gaussian kernel density analysis reveal that ENSO and IOD phases strongly modulate wind and wave anomalies, with the post‐monsoon (October–November) season emerging as the most sensitive period. Co‐occurring phases of ENSO and IOD events (El Niño+pIOD, La Niña+nIOD) further amplify the anomalies, indicating non‐linear interactions between the two modes. Overall, the findings highlight an ongoing shift towards swell dominance in the BoB and emphasise the importance of incorporating ENSO–IOD coupling in regional wave climate prediction and storm surge assessments.