ArticleScientific reports2026
A framework for impact based heat stress warning system for a coastal city in India.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
Urban Heat Islands (UHIs) pose a significant challenge to densely populated cities of India, intensifying heat stress and impacting public health, energy consumption, and urban sustainability. This study aims to identify Urban Heat Stress Risk in Mumbai (India) through the heat stress event of April-May 2024 using satellite data and by assessing thermal stress risk through a systematic approach combining urban weather modelling and in-situ observations along with vulnerability and exposure of the residents. Satellite-derived surface temperature data is analyzed to detect spatial patterns of UHI hotspots across the region. To deepen the understanding of thermal dynamics, the Weather Research and Forecasting Model with Urban Canopy Model (WRF-UCM) is employed, utilizing Local Climate Zone (LCZ) global data to simulate the Universal Thermal Climate Index (UTCI). A nested domain structure with spatial resolutions of 3*3 km, 1*1 km and 333*333 m are used to capture regional and localized variations of urban weather parameters. Validation of the WRF-UCM simulated meteorological variables is carried out using data from 36 Automatic Weather Stations across Mumbai (India). A correlation analysis between satellite-derived UHI hotspots and validated model results provides comprehensive insights into heat stress distribution. The findings highlight critical zones experiencing increased heat stress. The vulnerability and exposure index formulated through the Principal Component Analysis tool helped as additional overlaid layers to assess the risk over the study area, serving as an additional tool for urban planning interventions and policy recommendations related to heat stress risk.
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