How extreme heat is impacting India

This study maps heat risk across 734 districts of India using 35 indicators spanning hazard, exposure, and vulnerability. Going beyond just daytime temperatures, it includes night-time heat and relative humidity, offering a clearer picture of how climate change has altered the frequency, intensity, and duration of heat hazard from 1982 to 2022. Using high-resolution IMDAA climate data (12 km), satellite imagery, and the latest socio-economic and health datasets (NFHS 2019-21, Census 2011), the study identifies areas most at risk from this growing 'invisible disaster'.

Key recommendations from the study:

• Go beyond just daytime temperatures when planning for heat risk reduction: Most HAPs still focus mainly on daytime temperatures. But extreme heat risks are also driven by warm nights, high humidity, and local vulnerabilities. To fill this gap, this study provides created ready-to-use heat risk handbooks for every state and UT (Annexure 1), with district-level maps and risk scores. Further, the India Meteorological Department (IMD) now provides advanced forecasts that include percentile-based heat thresholds, night-time warnings, and hot-humid alerts that should be integrated into local early warning systems and HAPs, to anticipate heat-related illnesses, energy demand spikes, and service disruptions, and to reach vulnerable communities more effectively.
• Tap into State Disaster Mitigation Fund (SDMF): In 2024, heatwaves were officially added as eligible for project-based funding under the SDMF. States can use this for cooling shelters, early warning systems, green infrastructure, and more. As per guidelines, detailed risk assessments are crucial for planning-our district-level analysis (Annexure 1) can support these proposals.
• States where more than half of districts face high heat risk should notify heatwaves as a state-specific disaster. This unlocks an extra 10 per cent of SDRF funds, which can support relief for heat-related deaths, farm losses, and emergency worker training. States like Maharashtra, Tamil Nadu, and Andhra Pradesh have already done this-others should follow.
• Promote heat insurance to protect livelihoods. We need to shift from post-disaster relief to pre-arranged financial protection. Parametric insurance-based on temperature thresholds-can enable quick payouts after extreme heat events. Successful pilots already exist in Nagaland and among SEWA workers in Ahmedabad. These models should be scaled to protect outdoor workers and vulnerable communities.
• Create a national repository of HAPs. Lack of open access HAPs makes it hard to track what exists and what's missing for institutional adaptive capacity. We recommend setting up an open-access national HAP repository, managed by NDMA and updated by states, to support transparency, learning, and accountability.