Mechanism of pre-monsoon heat waves over southeast and central northeast regions of India

Pre-monsoon heatwaves are among the most critical weather phenomena in India, exerting serious impacts on human health and livelihoods. In this study, we examine the driving mechanisms of heatwaves over two contrasting regions: Southeast (SE, comprising Tamil Nadu, Andhra Pradesh, and Karnataka) and Central Northeast (CNE, parts of Bihar, Jharkhand, and West Bengal). These regions display markedly different trends during the 1951–2024 periods with increasing (decreasing) trend over SE(NE) regions. During heatwave episodes, sharp reductions are observed in soil moisture, sensible heat flux, cloud cover, and vertical motion, all of which act together to intensify surface warming in both the regions. In SE, soil moisture and sensible heat flux begin to decline nearly 5–6 days before the onset of a heatwave, highlighting the strong role of local land–atmosphere processes. In addition, sea surface temperatures (SST) over the northern Indian Ocean show positive anomalies that further enhance warming in this region. The drier phase of the Madden–Julian Oscillation (MJO) also favours heatwave development in this region. Heatwaves in CNE are primarily driven by upper-level mid-latitude waves, which induce subsidence and reduce cloud cover that precedes the heatwave events by about a week. The MJO dry phase has no significant association with CNE heatwaves. The decreasing trend over CNE heatwaves is associated with reduced anticyclonic vorticity and increased rainfall. Intensified Indian Ocean Dipole (IOD) conditions during the recent warming period also appear unfavorable for CNE heatwave formation. Large-scale climate drivers such as the El Niño–Southern Oscillation (ENSO) and IOD positively influence SE India heatwaves, while IOD and the Atlantic Meridional Oscillation (AMO) exhibit inverse relationships with CNE India heatwaves. This understanding of the lead–lag relationships between local variables and large-scale climate patterns is crucial for the regional heatwave prediction across multiple timescales.