Event Description

A sequence of heatwave spells impacted large areas of central, northern and western India since late March 2026. This culminated in late April 2026, with a severe heatwave affecting an extensive region of India, pushing temperatures to dangerous levels and increasing heat stress on millions of people before the arrival of the summer monsoon. Between April 24 and 28, several regions of northern, central, and western India recorded extreme heat, with temperatures widely exceeding 40°C. In Ahmedabad, temperatures reached 44.8°C, among the hottest April days observed there in recent years, while Delhi climbed to around 44–45°C during the peak of the event. Lucknow and other cities across the Indo-Gangetic Plain also experienced intense heat, prompting official alerts and emergency measures. Additionally, several cities, including Chandrapur and Yavatmal, recorded daily minimum air temperatures around 30 °C, so without the cooling effect of nighttime conditions, populations experienced greater discomfort and an increased risk of heat exhaustion and heatstroke. 

The intensity of the event was also reflected in strong temperature anomalies relative to seasonal conditions. During the peak phase, maximum temperatures were generally around 3 to 6°C above normal across several major cities, with locally higher departures in northern India. In Delhi, official reports indicated many areas were markedly above normal by more than 5°C. Ahmedabad showed lower anomalies, around 3°C, despite higher absolute temperatures, because late April is climatologically hotter there. Lucknow likely experienced anomalies comparable to northern India, near 4 to 6°C.  

Overall, this pronounced heatwave increased risks of heat-related illness, reduced labour capacity for outdoor workers, and strained electricity systems through surging cooling demand. It also raised concerns for water resources and agriculture in already stressed regions, where pre-monsoon heat can damage crops and intensify irrigation needs. In densely populated urban areas, prolonged exposure combined with warm nights can further increase health risks, especially for vulnerable populations.

The first four plots describe the meteorological conditions observed during the India early heatwave of 24 to 28 April 2026.

The surface pressure anomalies show broadly negative values over northern India, the Himalayan region, and parts of Pakistan, with departures locally below −5 hPa. This indicates lower than average surface pressure across the northern sector of the domain, while much of peninsular India remained closer to normal. Such a pressure configuration is consistent with strong continental heating and a deepened thermal low over the Indo-Gangetic region. The temperature anomalies plot shows widespread positive anomalies across nearly all of India. The strongest warm departures are concentrated over northern India, Nepal, Pakistan, and the Himalayan foothills, where anomalies exceed +5°C and locally approach +7 to +8°C. Central and western India, including the Ahmedabad region, also display clear positive anomalies, generally around +2 to +4°C. This confirms that the event was not only hot in absolute terms, but exceptionally warm relative to climatology. The precipitation pattern during the event indicates that most of western and central India remained very dry, with little or no rainfall during the analysed period. Higher precipitation totals are confined to northeastern India, Bangladesh, and areas along the eastern Himalayan foothills, where daily accumulations locally exceed 10 to 20 mm/day. This contrast suggests that the core heatwave region coincided with dry skies, strong solar influence,  and limited evaporative cooling, favouring stronger daytime heating. The wind speed during the event plot shows moderate winds over much of India, generally around 10 to 20 km/h, but with stronger winds over eastern and southeastern India and nearby coastal areas, where values locally exceed 30 to 40 km/h. Over the main heatwave zone in northwestern and central India, winds appear weaker to moderate, implying that ventilation was limited in several inland regions, which can aggravate thermal stress,  while La Niña is decaying and ENSO is entering neutral phase (with expected further evolution towards El Niño later this year).

Climate and Data Background for the Analysis

The occurrence of large positive anomalies of air temperature and extremely dry conditions in the pre-monsoonal season is becoming commonplace in South Asia, as shown by the persistent and spatially extended events in 2015, 2019, 2022 and 2024, which have led to thousands of deaths and disruption to ecosystems and society, with temperature records repeatedly exceeded every few years. The IPCC AR6 report provides a clear relationship between heatwaves and climate change in South Asia. Climate change is significantly contributing to the increase in heatwaves over India through various mechanisms: warming resulting from climate change has led to an increased frequency, intensity, and duration of heat-related events, including heatwaves, in most land regions, with high confidence (IPCC Special Report on the Ocean and Cryosphere in a Changing Climate  Chapter 6 - Page 27). Climate change is projected to alter land conditions, affecting temperature and rainfall in regions, which can enhance winter warming due to decreased snow cover and albedo in boreal regions, while reducing warming during the growing season in tropical areas with increased rainfall. Global warming and urbanization can enhance warming in cities and their surroundings, especially during heatwaves, with a higher impact on night-time temperatures than daytime temperatures (IPCC AR6 WGII Full Report - Page 1058). Observed near-surface air temperature has been increasing since the 20th century in Asia, intensifying the threat of heatwaves across the region. In South Asia specifically, the frequency and duration of heatwaves have increased, associated with Indian Ocean basin-wide warming and, in some years, El Niños, leading to severe impacts on agriculture and human discomfort. However, several recent extreme pre-monsoonal heat events unfolded before El Niño fully developed, indicating that these events cannot be explained by ENSO alone and instead reflect the growing influence of anthropogenic warming superimposed on regional climate variability. The combination of global warming and population growth in already-warm cities in regions like India is a major driver for increased heat exposure, with urban heat islands elevating temperatures within cities relative to their surroundings. Indeed, South Asia is considered to be one of the regions most impacted in the future by the climate crisis.

Our analysis approach rests on looking for weather conditions similar to those of the event of interest having been observed in the past. For this event we have low confidence in the robustness of the attribution estimates given the available climate data, as the event is very exceptional in the database.

ClimaMeter Analysis 

We analyze here (see Methodology for more details)  how events similar to the meteorological conditions leading to the late April 2026 India heat wave have changed in the present (1988–2025) compared to what they would have looked like if they had occurred in the past (1950–1987) in the region [68°E 98°E 8°N 38°N]. Surface pressure changes over India are limited, generally within about ±1 hPa and only locally larger, indicating little change in the large-scale circulation compared with similar past events. Temperature changes show that present-day events occur in a warmer climate, with most regions around +0.5 to +1.5°C warmer than comparable past events, and stronger warming of about +1.5 to +2°C over northern India and near the Himalayan region. Precipitation changes are weak and spatially mixed, with no robust regional signal. Wind speed changes are also modest, with localized increases and decreases of only a few km/h.

Similar past events suggest that the atmospheric patterns linked to this heatwave occur with comparable frequency in past and present periods. This implies that the circulation pattern itself is not the main driver of change. Instead, when these patterns occur today, they produce higher temperatures because they develop in a warmer background climate. Changes in urban areas show positive temperature signals in Ahmedabad, Delhi, and Lucknow, strongest in Ahmedabad, while precipitation changes remain small and wind changes are negative in all three cities, especially Ahmedabad. 

Finally, we find that sources of natural climate variability, notably the Pacific Decadal Oscillation and El Niño-Southern Oscillation, may have only partly influenced the event. This means that the changes we see in the event compared to the past may be mostly due to human-driven climate change.

Exposure 

We quantify socioeconomic exposure to heat conditions enhanced by climate change by combining event day hazard masks with spatially gridded population and economic data over the study domain used in the meteorological analysis. Population is taken from the Global Human Settlement Layer (GHSL, 2025) and regridded to 0.5° spatial resolution (Schiavina et al., 2022). Economic exposure is estimated using gridded gross domestic product (GDP) per capita data at the same resolution (Kummu et al., 2018). This framework is intended to quantify the spatial coincidence between extreme heat events and socioeconomic assets, rather than to provide an assessment of vulnerability, adaptive capacity, or realized impacts.

The heat hazard is defined from detrended and deseasonalized temperature anomalies during the event and restricted to areas where the ClimaMeter analysis detects a statistically significant positive warming signal in present-day conditions relative to the past. In this way, the exposure estimate focuses on zones where climate change has increased the intensity of the event, albeit with low confidence.

Three nested hazard levels are then defined from the upper tail of the anomaly distribution using the 0.98, 0.99, and 0.995 quantiles, corresponding respectively to moderate, severe, and extreme heat conditions. Socioeconomic exposure is calculated by summing the population and economic activity located within each hazard class under present-day conditions.

For the April 2026 India heatwave, the analysis (see Figure) indicates that about 146.53 million people were exposed to heat conditions intensified by climate change, across areas representing approximately 1,343.60 billion USD of economic activity. Of these totals, 47.31 million people and 388.98 billion USD were in the moderate hazard class, 55.27 million people and 613.48 billion USD in the severe class, and 43.94 million people and 341.13 billion USD in the extreme class. These values highlight that a substantial share of the exposed population and economic assets were located in the highest intensity categories. We remark that these values represent the population and economic activity exposed to the heatwave. They do not represent impacts. For details and limitations about the exposure analysis, the interested reader may consult Faranda et al. (2026).

Conclusion

Based on the above, we conclude that meteorological conditions similar to the April 2026 India heatwave have become up to 2°C warmer in the present than in the past. The exposure analysis shows that about 43.94 million people and 341.13 billion USD of economic activity were in the regions that experienced the most extreme heat conditions intensified by climate change. We interpret the April 2026 India heatwave  as an event driven by very exceptional meteorological conditions whose characteristics can mostly be ascribed to human-driven climate change, albeit with low confidence.