Articles | Volume 14, issue 12
https://doi.org/10.5194/essd-14-5651-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-5651-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
GSDM-WBT: global station-based daily maximum wet-bulb temperature data for 1981–2020
Jianquan Dong
Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
Institute of Geography and Oeschger Centre for Climate Change
Research, University of Bern, Bern, 3012, Switzerland
Stefan Brönnimann
Institute of Geography and Oeschger Centre for Climate Change
Research, University of Bern, Bern, 3012, Switzerland
Tao Hu
Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
Yanxu Liu
State Key Laboratory of Earth Surface Processes and Resource Ecology,
Faculty of Geographical Science, Beijing Normal University, Beijing 100875,
China
Jian Peng
CORRESPONDING AUTHOR
Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
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Cited
14 citations as recorded by crossref.
- GloUTCI-M: a global monthly 1 km Universal Thermal Climate Index dataset from 2000 to 2022 Z. Yang et al. https://doi.org/10.5194/essd-16-2407-2024
- Exacerbated heat stress induced by urban browning in the Global South H. Du et al. https://doi.org/10.1038/s44284-024-00184-9
- Increasing probability of extreme rainfall preconditioned by humid heatwaves in global coastal megacities P. Ganguli & B. Merz https://doi.org/10.1038/s41612-025-01023-x
- Stronger rise in humid heatwaves over China shown by homogenized data from 1961 to 2022 L. Chen et al. https://doi.org/10.1016/j.atmosres.2025.108620
- Uniformly elevated future heat stress in China driven by spatially heterogeneous water vapor changes F. Wang et al. https://doi.org/10.1038/s41467-024-48895-w
- Anthropogenic climate change drives rising global heat stress and its spatial inequality J. Peng et al. https://doi.org/10.1038/s41467-026-69164-y
- A supply-demand model of vegetation cooling for urban heatwave mitigation W. Li & R. Sun https://doi.org/10.1016/j.uclim.2023.101699
- Divergent latitude-specific urban humid heat risks are regulated by local climate types L. Xu et al. https://doi.org/10.1038/s43247-026-03437-8
- Urban-rural differences in the local human exposure to humid heatwaves in the Northern Hemisphere J. Dong et al. https://doi.org/10.1016/j.scs.2024.105415
- Intense humid heat ─ tropical cyclone compound hazards in eastern coastal India P. Ganguli & N. Lin https://doi.org/10.1038/s44304-025-00103-5
- Synergistic effects of compound temperature-humidity extremes and urban heat-moisture islands: An observational study in high-density humid subtropical twin cities Y. He et al. https://doi.org/10.1016/j.uclim.2025.102455
- Non-Optimal Wet-Bulb Temperature and Short-Term Black Carbon Exposure Largely Impact Emergency Department Visits for Cause-Stable Ischemic Heart Disease Q. Chen et al. https://doi.org/10.3390/atmos16050542
- A review on extreme heat risk assessment: Indicators-integrating versus exposure-response approaches J. Dong & J. Peng https://doi.org/10.1177/2754124X251343605
- Heat disproportionately kills young people: Evidence from wet-bulb temperature in Mexico A. Wilson et al. https://doi.org/10.1126/sciadv.adq3367
14 citations as recorded by crossref.
- GloUTCI-M: a global monthly 1 km Universal Thermal Climate Index dataset from 2000 to 2022 Z. Yang et al. https://doi.org/10.5194/essd-16-2407-2024
- Exacerbated heat stress induced by urban browning in the Global South H. Du et al. https://doi.org/10.1038/s44284-024-00184-9
- Increasing probability of extreme rainfall preconditioned by humid heatwaves in global coastal megacities P. Ganguli & B. Merz https://doi.org/10.1038/s41612-025-01023-x
- Stronger rise in humid heatwaves over China shown by homogenized data from 1961 to 2022 L. Chen et al. https://doi.org/10.1016/j.atmosres.2025.108620
- Uniformly elevated future heat stress in China driven by spatially heterogeneous water vapor changes F. Wang et al. https://doi.org/10.1038/s41467-024-48895-w
- Anthropogenic climate change drives rising global heat stress and its spatial inequality J. Peng et al. https://doi.org/10.1038/s41467-026-69164-y
- A supply-demand model of vegetation cooling for urban heatwave mitigation W. Li & R. Sun https://doi.org/10.1016/j.uclim.2023.101699
- Divergent latitude-specific urban humid heat risks are regulated by local climate types L. Xu et al. https://doi.org/10.1038/s43247-026-03437-8
- Urban-rural differences in the local human exposure to humid heatwaves in the Northern Hemisphere J. Dong et al. https://doi.org/10.1016/j.scs.2024.105415
- Intense humid heat ─ tropical cyclone compound hazards in eastern coastal India P. Ganguli & N. Lin https://doi.org/10.1038/s44304-025-00103-5
- Synergistic effects of compound temperature-humidity extremes and urban heat-moisture islands: An observational study in high-density humid subtropical twin cities Y. He et al. https://doi.org/10.1016/j.uclim.2025.102455
- Non-Optimal Wet-Bulb Temperature and Short-Term Black Carbon Exposure Largely Impact Emergency Department Visits for Cause-Stable Ischemic Heart Disease Q. Chen et al. https://doi.org/10.3390/atmos16050542
- A review on extreme heat risk assessment: Indicators-integrating versus exposure-response approaches J. Dong & J. Peng https://doi.org/10.1177/2754124X251343605
- Heat disproportionately kills young people: Evidence from wet-bulb temperature in Mexico A. Wilson et al. https://doi.org/10.1126/sciadv.adq3367
Saved (final revised paper)
Latest update: 07 Jun 2026
Short summary
We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT)...
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