Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-4849-2023
© Author(s) 2023. 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-15-4849-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
31 Oct 2023
Data description paper |
| 31 Oct 2023
| 31 Oct 2023
A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model
Shanlei Sun
CORRESPONDING AUTHOR
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Zaoying Bi
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Jingfeng Xiao
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, USA
Yi Liu
School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia
Ge Sun
Eastern Forest Environmental Threat Assessment Center, Southern Research Station, USDA Forest Service, Raleigh, USA
Weimin Ju
International Institute for Earth System Science, Nanjing University, Nanjing, China
Chunwei Liu
Jiangsu Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
Mengyuan Mu
ARC Centre of Excellence for Climate Extremes and Climate Change Research Centre, University of New South Wales, Sydney, Australia
Jinjian Li
School of Atmospheric Sciences/Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu University of Information Technology, Chengdu, China
Yang Zhou
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Xiaoyuan Li
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
Jiangsu Key Laboratory of Agricultural Meteorology, School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
Haishan Chen
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education/International Joint Research Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing, China
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Cited
7 citations as recorded by crossref.
- An enhanced Standardized Precipitation–Evapotranspiration Index (SPEI) drought-monitoring method integrating land surface characteristics L. Peng et al. 10.5194/esd-15-1277-2024
- A three-layer evapotranspiration model considering the vertical structure of urban green spaces Q. Li et al. 10.1016/j.ufug.2024.128389
- Ecohydrological processes can predict biocrust cover at regional scale but not global scale N. Chen et al. 10.1007/s11104-024-07079-7
- A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model S. Sun et al. 10.5194/essd-15-4849-2023
- Satellite-based near-real-time global daily terrestrial evapotranspiration estimates L. Huang et al. 10.5194/essd-16-3993-2024
- Global estimation of terrestrial evapotranspiration based on the atmospheric water balance approach S. Shang et al. 10.1007/s00382-024-07536-0
- A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model S. Sun et al. 10.5194/essd-15-4849-2023
6 citations as recorded by crossref.
- An enhanced Standardized Precipitation–Evapotranspiration Index (SPEI) drought-monitoring method integrating land surface characteristics L. Peng et al. 10.5194/esd-15-1277-2024
- A three-layer evapotranspiration model considering the vertical structure of urban green spaces Q. Li et al. 10.1016/j.ufug.2024.128389
- Ecohydrological processes can predict biocrust cover at regional scale but not global scale N. Chen et al. 10.1007/s11104-024-07079-7
- A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model S. Sun et al. 10.5194/essd-15-4849-2023
- Satellite-based near-real-time global daily terrestrial evapotranspiration estimates L. Huang et al. 10.5194/essd-16-3993-2024
- Global estimation of terrestrial evapotranspiration based on the atmospheric water balance approach S. Shang et al. 10.1007/s00382-024-07536-0
Latest update: 04 Feb 2025
Short summary
Based on various existing datasets, we comprehensively considered spatiotemporal differences in land surfaces and CO2 effects on plant stomatal resistance to parameterize the Shuttleworth–Wallace model, and we generated a global 5 km ensemble mean monthly potential evapotranspiration (PET) dataset (including potential transpiration PT and soil evaporation PE) during 1982–2015. The new dataset may be used by academic communities and various agencies to conduct various studies.
Based on various existing datasets, we comprehensively considered spatiotemporal differences in...
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