Zhao, Q. et al. Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study. The Lancet Planetary Health 5, e415–e425 (2021).
Lüthi, S. et al. Rapid increase in the risk of heat-related mortality. Nat Commun 14, 4894 (2023).
Voogt, J. A. & Oke, T. R. Thermal remote sensing of urban climates. Remote Sensing of Environment 86, 370–384 (2003).
Khanh, D. N., Varquez, A. C. G. & Kanda, M. Impact of urbanization on exposure to extreme warming in megacities. Heliyon 9, e15511 (2023).
IPCC WGII (Intergovernmental Panel on Climate Change, Working Group II). AR6 Climate Change 2022: Impacts, Adaptation and Vulnerability | Climate Change 2022: Impacts, Adaptation and Vulnerability. https://www.ipcc.ch/report/ar6/wg2/ (2022).
Ebi, K. L. et al. Hot weather and heat extremes: health risks. The Lancet 398, 698–708 (2021).
Gasparrini, A. et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study. The Lancet 386, 369–375 (2015).
Tuholske, C. et al. Global urban population exposure to extreme heat. Proceedings of the National Academy of Sciences 118, e2024792118 (2021).
Liu, Y., Song, C., Ye, S., Lv, J. & Gao, P. Daily Max Simplified Wet-Bulb Globe Temperature and its Climate Networks for Teleconnection Study, 1940–2022. Sci Data 12, 584 (2025).
Spangler, K. R., Liang, S. & Wellenius, G. A. Wet-Bulb Globe Temperature, Universal Thermal Climate Index, and Other Heat Metrics for US Counties, 2000–2020. Sci Data 9, 326 (2022).
Ronnkvist, S. R. et al. What’s the TEE: Metrics of Temperature Extremes in Europe NUTS Regions (1980-2024). Sci Data 12, 1114 (2025).
Wang, Y. et al. Global future population exposure to heat-waves. Environment International 178, 108049 (2023).
Kong, Q. & Huber, M. A global high-resolution and bias-corrected dataset of CMIP6 projected heat stress metrics. Sci Data 12, 1–13 (2025).
Yin, C. et al. Changes in global heat waves and its socioeconomic exposure in a warmer future. Climate Risk Management 38, 100459 (2022).
Lowry, W. P. Empirical estimation of urban effects on climate: a problem analysis. Journal of Applied Meteorology and Climatology 16, 129–135 (1977).
Yu, W. et al. Attribution of Urban Diurnal Thermal Environmental Change: Importance of Global–Local Effects. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 16, 8087–8101 (2023).
Du, H. et al. Contrasting Trends and Drivers of Global Surface and Canopy Urban Heat Islands. Geophysical Research Letters 50, e2023GL104661 (2023).
Li, K. & Chen, Y. Characterizing the indicator-based, day-and-night, and climate-based variations in response of surface urban heat island during heat wave across global 561 cities. Sustainable Cities and Society 99, 104877 (2023).
Guo, A. et al. Divergent impact of urban 2D/3D morphology on thermal environment along urban gradients. Urban Climate 45, 101278 (2022).
Ren, J. et al. Spatiotemporal evolution of surface urban heat islands: Concerns regarding summer heat wave periods. J. Geogr. Sci. 34, 1065–1082 (2024).
Zhang, T., Zhou, Y., Zhu, Z., Li, X. & Asrar, G. R. A global seamless 1 km resolution daily land surface temperature dataset (2003–2020). Earth System Science Data 14, 651–664 (2022).
Dugord, P.-A., Lauf, S., Schuster, C. & Kleinschmit, B. Land use patterns, temperature distribution, and potential heat stress risk – The case study Berlin, Germany. Comput. Environ. Urban Syst. 48, 86–98 (2014).
Li, L. & Zha, Y. Population exposure to extreme heat in China: Frequency, intensity, duration and temporal trends. Sustainable Cities and Society 60, 102282 (2020).
Yuan, B., Zhou, L., Hu, F. & Zhang, Q. Diurnal dynamics of heat exposure in Xi’an: A perspective from local climate zone. Building and Environment 222, 109400 (2022).
Zhang, T., Zhou, Y., Zhu, Z., Li, X. & Asrar, G. A global seamless 1 km resolution daily land surface temperature dataset (2003–2020), https://doi.org/10.25380/iastate.c.5078492.v3 (2022)
Lebakula, V. et al. LandScan Global 30 Arcsecond Annual Global Gridded Population Datasets from 2000 to 2022. Sci Data 12, 495 (2025).
Li, X. et al. Mapping global urban boundaries from the global artificial impervious area (GAIA) data. Environ. Res. Lett. 15, 094044 (2020).
World Bank Group. Global Subnational Atlas of Poverty (version October 2025). https://datacatalog.worldbank.org/search/dataset/0042041/global_subnational_poverty_atlas_gsap (2025).
Chen, B., Xie, M., Feng, Q., Wu, R. & Jiang, L. Diurnal heat exposure risk mapping and related governance zoning: A case study of Beijing, China. Sustainable Cities and Society 81, 103831 (2022).
Meque, A., Pinto, I., Maúre, G. & Beleza, A. Understanding the variability of heat-wave characteristics in southern Africa. Weather and Climate Extremes 38, 100498 (2022).
Yu, Z., Yao, Y., Yang, G., Wang, X. & Vejre, H. Spatiotemporal patterns and characteristics of remotely sensed region heat islands during the rapid urbanization (1995–2015) of Southern China. Science of The Total Environment 674, 242–254 (2019).
Yu, W., Yang, J., Zhou, Y. & Xiao, X. Global UHE dataset. figshare https://doi.org/10.6084/m9.figshare.c.8208956 (2025).
