A Global High-Resolution Comprehensive Heat Indices Dataset from 1950 to 2024

Heatwaves are becoming more intense and frequent as global temperatures rise, affecting vulnerable populations, particularly in low-income communities. Addressing the impacts of heatwaves requires high-resolution data to assess their influence on labour productivity, public health, and climate risk. We introduce the Comprehensive Heat Indices (CHI) dataset, a high-resolution (0.1° × 0.1°) hourly dataset from 1950 to 2024, derived from the ERA5 and ERA5-Land reanalyses. The CHI dataset encompasses thirteen heat stress indices, including wet-bulb temperature, universal thermal climate index, mean radiant temperature, wind chill, and lethal heat stress index (Ls). Thresholds for Ls are empirically linked to mortality, enabling the identification of life-threatening heat events. Ls is sensitive to soil moisture variability, improving assessments in agricultural regions. The CHI dataset supports indoor and outdoor applications and is sensitive to humidity, radiation, and wind. Covering the global land area from 60°S to 75°N and 180°W to 180°E, it provides a unique, long-term perspective on spatial and temporal trends in heat stress, which are critical for climate impact research and adaptation planning.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2026-01-16
DOI
https://doi.org/10.1038/s41597-025-06519-y
Primary Topic
Climate Change and Health Impacts
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Global High-Resolution Comprehensive Heat Indices Dataset from 1950 to 2024

Abdul Malik, Sateesh Masabathini, Dasari Hari Prasad, Mohsin Ahmed Shaikh et al.
Scientific Data
Climate Change and Health Impacts
article

A Global High-Resolution Comprehensive Heat Indices Dataset from 1950 to 2024

Abdul Malik, Sateesh Masabathini, Dasari Hari Prasad, Mohsin Ahmed Shaikh, Ibrahim Hoteit, Muhammad Usman, Qinqin Kong
article en

Abstract

Heatwaves are becoming more intense and frequent as global temperatures rise, affecting vulnerable populations, particularly in low-income communities. Addressing the impacts of heatwaves requires high-resolution data to assess their influence on labour productivity, public health, and climate risk. We introduce the Comprehensive Heat Indices (CHI) dataset, a high-resolution (0.1° × 0.1°) hourly dataset from 1950 to 2024, derived from the ERA5 and ERA5-Land reanalyses. The CHI dataset encompasses thirteen heat stress indices, including wet-bulb temperature, universal thermal climate index, mean radiant temperature, wind chill, and lethal heat stress index (Ls). Thresholds for Ls are empirically linked to mortality, enabling the identification of life-threatening heat events. Ls is sensitive to soil moisture variability, improving assessments in agricultural regions. The CHI dataset supports indoor and outdoor applications and is sensitive to humidity, radiation, and wind. Covering the global land area from 60°S to 75°N and 180°W to 180°E, it provides a unique, long-term perspective on spatial and temporal trends in heat stress, which are critical for climate impact research and adaptation planning.

Scientific DataVol. 13(1)
King Abdulaziz University (SA), King Abdullah University of Science and Technology (SA), Zayed University (AE), Stanford University (US)
European Commission, King Abdullah University of Science and Technology, Zayed University
Openalex Percentile: Top 88%
Climate Change and Health Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Global High-Resolution Comprehensive Heat Indices Dataset from 1950 to 2024 — Abdul Malik, Sateesh Masabathini, et al. · Scientific Data (2026) | TGRS Research Map | TGRS