Malik et al. (2026) A Global High-Resolution Comprehensive Heat Indices Dataset from 1950 to 2024

Identification

• Journal: Scientific Data
• Year: 2026
• Date: 2026-01-16
• Authors: Abdul Malik, Sateesh Masabathini, Mohsin Ahmed Shaikh, Qinqin Kong, Muhammad Usman, Dasari Hari Prasad, Ibrahim Hoteit
• DOI: 10.1038/s41597-025-06519-y

Research Groups

• Climate Change Center, King Abdullah University of Science and Technology, Jeddah, Saudi Arabia
• Supercomputing Lab, King Abdullah University of Science and Technology, Jeddah, Saudi Arabia
• School of Medicine, Stanford University, Stanford, CA, US
• College of Natural and Health Sciences, Zayed University, Abu Dhabi, United Arab Emirates

Short Summary

This paper introduces the Comprehensive Heat Indices (CHI) dataset, a global, high-resolution (0.1° × 0.1°) hourly dataset of thirteen heat stress indices from 1950 to 2024, derived from ERA5 and ERA5-Land reanalyses, to support climate impact research and adaptation planning.

Objective

• To develop and provide a global, high-resolution (0.1° × 0.1°) hourly comprehensive dataset of thirteen diverse heat stress indices (CHI) from 1950 to 2024, derived from ERA5 and ERA5-Land reanalyses, to overcome limitations of existing datasets and support climate impact research and adaptation planning.

Study Configuration

• Spatial Scale: Global land area from 60°S to 75°N and 180°W to 180°E, with a spatial resolution of 0.1° × 0.1° (approximately 9 km).
• Temporal Scale: Hourly data from January 1, 1950, to December 31, 2024.

Methodology and Data

• Models used:
  • Thermofeel (Python library from ECMWF) for calculating most heat stress indices (Mean Radiant Temperature (Tmrt), Globe Temperature (Tg), Universal Thermal Climate Index (UTCI), Indoor Wet-bulb Temperature (Twb), Indoor Lethal Heat Stress Index (Lsi), Natural Lethal Heat Stress Index (Lsin), Wet-Bulb Globe Temperature (Twbg), Humidex (Hu), Normal Effective Temperature (NET), Apparent Temperature (AT), Wind Chill (WC), Heat Index Adjusted (HI)) and relative humidity.
  • Python code by Kong et al. for calculating Natural Wet-bulb Temperature (Tnwb) and intermediate variables (cosine of the solar zenith angle (cosθ), wind speed at 10 m (ws10), wind speed at 2 m (ws2), direct radiation from the sun (dsrp), and ratio of direct solar radiation (fdir)).
• Data sources:
  • ERA5 reanalysis (Copernicus Climate Change Service, C3S) for total sky direct solar radiation at the surface (tsdsrs).
  • ERA5-Land reanalysis (Copernicus Climate Change Service, C3S) for all other atmospheric variables (e.g., eastward and northward components of 10 m wind, 2 m temperature, 2 m dewpoint temperature, surface pressure, surface net solar radiation, surface net thermal radiation, surface solar radiation downwards, surface thermal radiation downwards).

Main Results

• The Comprehensive Heat Indices (CHI) dataset provides 13 heat stress indices (Tmrt, Tg, Twbg, UTCI, Twb, Tnwb, indoor and outdoor Lsi, Hu, NET, AT, WC, HI) at a high resolution (0.1° × 0.1°) and hourly temporal resolution, covering the global land area from 1950 to 2024.
• The dataset is derived from ERA5 and ERA5-Land reanalyses, utilizing 2-meter wind speed and averaging the cosine of the solar zenith angle only over sunlit periods, which enhances accuracy compared to previous datasets.
• The Lethal Heat Stress Index (Lsi) and Natural Lethal Heat Stress Index (Lsin) are included, with Lsin being sensitive to soil moisture variability, improving assessments in agricultural regions and accounting for radiative effects.
• Technical validation against ERA5-HEAT, HiTiSEA, and HiGTS datasets demonstrates that CHI successfully captures spatial patterns of heatwaves and generally aligns well, with observed differences in colder regions attributed to resolution and methodological variations.
• The CHI dataset is provided in NetCDF format, totaling approximately 73 terabytes (TB) and 11,700 files, accessible via Globus.

Contributions

• Presents the first long-term (1950-2024) comprehensive and diverse dataset of 13 high-resolution (0.1° × 0.1°) hourly heat stress indices derived from ERA5 and ERA5-Land reanalyses, offering global coverage.
• Includes the first dataset on the Lethal Heat Stress Index (Lsi and Lsin), addressing critical gaps in regional heat stress research, particularly its sensitivity to soil moisture.
• Enhances accuracy by using 2-meter wind speed (instead of 10-meter) and calculating the average cosine of the solar zenith angle only over the sunlit part of each model interval, preventing overestimation of solar radiation.
• Provides outdoor Wet-Bulb Globe Temperature (Twbg) with full radiation inputs, unlike previous indoor-focused approximations.
• Offers both indoor (Twb) and natural (Tnwb) wet-bulb temperatures using a physically-based model.
• Supports multidisciplinary applications in climate science, public health, labor productivity, climate risk assessment, and adaptation planning for both indoor and outdoor environments.

Funding

• Climate Change Center, King Abdullah University of Science and Technology (KAUST)
• Zayed University (Research Incentive Fund: RIF 23021), Abu Dhabi, UAE (for Muhammad Usman)
• KAUST Supercomputing Laboratory (computing resources, Shaheen III Supercomputer)
• Copernicus Climate Change Service (C3S) for reanalysis products

Citation

@article{Malik2026Global,
  author = {Malik, Abdul and Masabathini, Sateesh and Shaikh, Mohsin Ahmed and Kong, Qinqin and Usman, Muhammad and Prasad, Dasari Hari and Hoteit, Ibrahim},
  title = {A Global High-Resolution Comprehensive Heat Indices Dataset from 1950 to 2024},
  journal = {Scientific Data},
  year = {2026},
  doi = {10.1038/s41597-025-06519-y},
  url = {https://doi.org/10.1038/s41597-025-06519-y}
}