Articles | Volume 14, issue 12
https://doi.org/10.5194/essd-14-5637-2022
© 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-14-5637-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A global dataset of daily maximum and minimum near-surface air temperature at 1 km resolution over land (2003–2020)
Tao Zhang
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA
Kaiguang Zhao
School of Environment and Natural Resources, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691, USA
Zhengyuan Zhu
Department of Statistics, Iowa State University, Ames, IA 50011, USA
Gang Chen
Laboratory for Remote Sensing and Environmental Change (LRSEC), Department of Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
Jia Hu
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA
Li Wang
Department of Statistics, George Mason University, Fairfax, VA 22030, USA
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71 citations as recorded by crossref.
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- Influence of urban ecotypes and built-up morphology on extreme heat events R. Qiao et al.
- Urbanization brings earlier onset of summertime compound heatwaves P. Ji et al.
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- Intensified exposure to compound extreme heat and ozone pollution in summer across Chinese cities J. Su et al.
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- Local temperature impact of urban heat mitigation strategy based on WRF integrating urban canopy parameters and local climate zones J. Chen et al.
- Strategic renewable energy forecasting and monthly disaggregation in data-scarce regions: a cross-continental SARIMA-based framework for policy planning W. Mbasso et al.
- Global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset (1950–2100) X. Lei et al.
- Space-time deep hybrid boosting learning for investigating day-night hourly seamless air temperature distribution from FY-4A over China Q. Su et al.
- Urban compound heatwaves substantially offset by cooling from urbanization–promoted vegetation growth S. Gao et al.
- Geospatial and Temporal Analysis of Temperature-Humidity Index (THI) as Climate Mitigation Tool in Glamping Site in Cimahi North, West Java, Indonesia M. Prihandrijanti & V. Azzizi
- Daytime urban heat stress in North America reduced by irrigation T. Chakraborty et al.
- Stepwise Downscaling of ERA5-Land Reanalysis Air Temperature: A Case Study in Nanjing, China X. Li et al.
- SOC content of global Mollisols at a 30 m spatial resolution from 1984 to 2021 generated by the novel ML-CNN prediction model X. Meng et al.
- Urbanization-induced warming amplifies population exposure to compound heatwaves but narrows exposure inequality between global North and South cities S. Gao et al.
- Tree species composition governs urban phenological responses to warming Z. Wu et al.
- Exacerbated heat stress induced by urban browning in the Global South H. Du et al.
- A novel scheme for seamless global mapping of daily mean air temperature (SGM_DMAT) at 1-km spatial resolution using satellite and auxiliary data R. Huang et al.
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- Multi-city assessments of human exposure to extreme heat during heat waves in the United States J. Hu et al.
- Heatwaves and its impact on the depressive symptoms among Chinese community-dwelling older adults: Examining the role of social participation B. Fang & Q. Zhang
- Rising heat, rising sirens: Spatiotemporal disparities and socio-spatial drivers of heat-related illness exposure risk in Japan J. Chen et al.
- An improved fusion of Landsat-7/8, Sentinel-2, and Sentinel-1 data for monitoring alfalfa: Implications for crop remote sensing J. Chen & Z. Zhang
- Global hotspots of compound extreme heat-pollution linked to local surface and atmospheric conditions Z. Huang et al.
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- Extreme heat events increase stroke risk among India’s older adults: evidence from longitudinal ageing study in India A. Khanduri et al.
- The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States A. Newman et al.
- Compound heat and ozone pollution in the urban environment C. Wang et al.
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- Comparison of Temperature–Mortality Associations across the Middle East Using Different Exposure Estimation Approaches Y. Alwadi et al.
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- Modelling Europe-wide fine resolution daily ambient temperature for 2003–2020 using machine learning A. Bussalleu et al.
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Saved (final revised paper)
Latest update: 28 Apr 2026
Short summary
We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and Tmin) dataset (2003–2020) using a novel statistical model. The average root mean square errors ranged from 1.20 to 2.44 °C for Tmax and 1.69 to 2.39 °C for Tmin. The gridded global air temperature dataset is of great use in a variety of studies such as the urban heat island phenomenon, hydrological modeling, and epidemic forecasting.
We generated a global 1 km daily maximum and minimum near-surface air temperature (Tmax and...
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