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Global Scale
Data Details

Dataset of Population Exposure to Extreme Heatwaves in China (2000, 2010, 2020)


NONG Kaisen1,2WANG Minghao1,2HUANG Yaobang1,2SUN Wenhao3CHU Mingruo*3
1 College of Urban and Environmental Sciences，Peking University，Beijing 100871，China2 Center for Urban Future Research，Peking University，Beijing 100871，China3 Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences，Beijing 100101，China

DOI:10.3974/geodb.2025.12.08.V1

Published:Dec. 2025

Visitors：28       Data Files Downloaded：0      
Data Downloaded： 无      Citations：

Key Words：

extreme heatwave,population exposure,MERRA-2,climate risk,dissertation

Abstract：

To address the scale mismatch between gridded meteorological data and socioeconomic administrative units, the authors integrated MERRA-2 reanalysis data with multisource census data to develop the dataset of population exposure to extreme heatwaves in China (2000, 2010, 2020). A 5-year moving average window was utilized to eliminate interannual climate noise, and the heatwave events were identified based on a combined relative and absolute threshold method, and maps continuous meteorological grid points to 367 administrative units in China through population weighting and zonal statistics. The dataset covers multidimensional indicators, including population exposure to heatwave frequency, exposure duration, and cumulative heat load at three key time points: 2000, 2010, and 2020. Accuracy validation shows that the source MERRA-2 data exhibits extremely high consistency with ground-observed temperatures (R² > 0.97). Compared with insitu measurements from 35 key cities, the Root Mean Square Error (RMSE) of the heatwave frequency extracted from the dataset is only 0.89 events, indicating reliable data quality. The dataset is archived in .xlsx and .shp formats, and consists of 9 data files with data size of 27.1 MB. The dataset supports scientific findings for dissertation.

Foundation Item：

Data Citation：

NONG Kaisen, WANG Minghao, HUANG Yaobang, SUN Wenhao, CHU Mingruo*. Dataset of Population Exposure to Extreme Heatwaves in China (2000, 2010, 2020)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2025. https://doi.org/10.3974/geodb.2025.12.08.V1.

References：


     [1] Jay, O., Capon, A., Berry, P., et al. Reducing the health effects of hot weather and heat extremes: from personal cooling strategies to green cities [J]. The Lancet, 2021, 398(10301): 709-724.
     [2] Gao, S. J., Chen, Y. H., Chen, D. L., et al. Urbanization-induced warming amplifies population exposure to compound heatwaves but narrows exposure inequality between global North and South cities [J]. npj Climate and Atmospheric Science, 2024, 7(1): 154.
     [3] Stalhandske, Z., Ruiter, M. C. D., Chambers, J., et al. Global assessment of population exposure to multiple climate-related hazards from 2003 to 2021: a retrospective analysis [J]. The Lancet Planetary Health, 2025, 9(8).
     [4] Yin, J. B., Gentine, P., Slater, L., et al. Future socio-ecosystem productivity threatened by compound drought-heatwave events [J]. Nature Sustainability, 2023, 6(3): 259-272.
     [5] Wang, J., Li, M. C., Liu, Y. J., et al. Large-scale climatic drivers for warm-season compound drought and heatwave frequency over North China [J]. Atmospheric Research, 2023, 288: 106727.
     [6] Liu, J. H., Chen, J., Yin, J. B., et al. Time of emergence of record‐shattering compound heatwave‐extreme precipitation events and their socio‐economic exposures [J]. Geophysical Research Letters, 2025, 52(16): e2025GL116884.
     [7] Urraca, R., Cappucci, F., Lanconelli, C., et al. Assessing discrepancies in global aerosol trends from satellites, models and reanalyses [J]. Remote Sensing of Environment, 2025, 328: 114827.
     [8] Martin, G. K., Rojas-Rueda, D., Fong, K. C., et al. A health impact assessment of progress towards urban nature targets in the 96 C40 cities [J]. The Lancet Planetary Health, 2025, 9(4): e284-e293.
     [9] Xie, W. X., Zhou, B. T., You, Q. L., et al. Observed changes in heat waves with different severities in China during 1961-2015 [J]. Theoretical and Applied Climatology, 2020, 141(3): 1529-1540.
     [10] Yin, C., Yang, Y. P., Chen, X. N., et al. Changes in global heat waves and its socioeconomic exposure in a warmer future [J]. Climate Risk Management, 2022, 38: 100459.
     [11] Cai, F. Y., Liu, C. H., Gerten, D., et al. Sketching the spatial disparities in heatwave trends by changing atmospheric teleconnections in the Northern Hemisphere [J]. Nature Communications, 2024, 15(1): 8012.
     [12] Li, X. F., Zhao, L., Wang, S., et al. Unstable permafrost regions experience more severe heatwaves in a warming climate [J]. npj Climate and Atmospheric Science, 2025, 8(1): 147.
     [13] Tian, P., Zhang, F. Q., Yan, Y. Y., et al. Spatial inequalities in global population exposure to extreme heats and heatwaves [J]. Applied Geography, 2025, 174: 103474.
     [14] Wang, C. C., Ren, Z. B., Guo, Y. J., et al. Assessing urban population exposure risk to extreme heat: Patterns, trends, and implications for climate resilience in China (2000-2020) [J]. Sustainable Cities and Society, 2024, 103: 105260.
     [15] Shen, H. J., You, Q. L., Wang, P. L., et al. Analysis on heat waves variation features in China during 1961-2014 [J]. Journal of the Meteorological Sciences, 2018, 38(1): 28-36.

Data Product:

ID Data Name Data Size Operation
1 EHW_PE_China_2000-2020.rar 18300.05KB
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