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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9,005
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Total article views: 8,051 (including HTML, PDF, and XML)
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6,452
1,474
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8,051
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PDF: 1,474
XML: 125
Total: 8,051
Supplement: 402
BibTeX: 109
EndNote: 169
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Total article views: 3,256 (including HTML, PDF, and XML)
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2,553
669
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3,256
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15
15
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Total article views: 11,307 (including HTML, PDF, and XML)
Thereof 10,855 with geography defined
and 452 with unknown origin.
Total article views: 8,051 (including HTML, PDF, and XML)
Thereof 7,757 with geography defined
and 294 with unknown origin.
Total article views: 3,256 (including HTML, PDF, and XML)
Thereof 3,098 with geography defined
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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...
