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.
Data description paper
| 
21 Dec 2022
Data description paper |
| 21 Dec 2022
| 21 Dec 2022
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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Total article views: 5,420 (including HTML, PDF, and XML)
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- Assessment of daytime and nighttime surface urban heat islands across local climate zones – A case study in Florianópolis, Brazil B. Rech et al. 10.1016/j.uclim.2024.101954
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- Ground-air temperature tracking from a geothermal climate-change observatory in South India V. Akkiraju et al. 10.1016/j.tecto.2023.230154
- Residential segregation and outdoor urban moist heat stress disparities in the United States T. Chakraborty et al. 10.1016/j.oneear.2023.05.016
- More extremely hot days, more heat exposure and fewer cooling options for people of color in Connecticut, U.S. S. Chen et al. 10.1038/s42949-024-00186-5
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Latest update: 13 Dec 2024
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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