Asymmetric response of Atlantic Nino on heatwaves over Northern India

Due to global warming, climate extremes like heatwave events will rise further in the 21^st century. Earlier, heatwave characteristics like duration, intensity, and frequency have been studied independently, ignoring interdependence among them, leading to biases in the heatwave impact assessment. The heatwave intensity duration frequency(HIDF) model provides a feasible framework incorporating interdependencies among heatwave characteristics, helping quantify heatwave hazards more accurately. HIDF curves are produced for six metropolitan cities, namely, Ahmedabad, Bhopal, and Gwalior over the western part and Patna, Varanasi, and Deoghar over the eastern part of northern India using the Indian Meteorological Department daily maximum temperature from 1961-2023 for March-June months. Heatwave events of durations ranging from one to ten and their respective intensities are modeled using the nonparametric kernel distribution method. HIDF curves reveal that the intensity and frequency of heatwave events for each duration increased(decreased) in the western(eastern) cities. In Ahmedabad city, the likelihood of a six-day heatwave event increased by 59 %, whereas it decreased by 66 % over Patna, reflecting east-west asymmetry. We found that a positive anomaly pattern over the southern Atlantic Ocean, i.e., Atlantic Nino, influences heatwaves occurring over northern India, causing east-west asymmetry. Due to the Atlantic Nino, the cross-equatorial flow reversed its direction as the moisture from the northern Indian Ocean, instead of traveling towards north China, entered the eastern part of India. This resulted in entry of moisture laden winds from the Bay of Bengal and it contributed to more convection activity in northeast India causing temperature drop in the region. The strength of moisture-laden winds is reduced when they reach the western part; the chance of convection decreases, contributing to a rise in temperature. Our results provide significant inputs in understanding heatwave dynamics over northern India, which will be helpful in predicting the heatwaves more accurately in the future.