Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-3273-2022
© 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-14-3273-2022
© 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
| 
15 Jul 2022
Data description paper |
| 15 Jul 2022
| 15 Jul 2022
GPRChinaTemp1km: a high-resolution monthly air temperature data set for China (1951–2020) based on machine learning
Qian He
Academy of Disaster Reduction and Emergency Management, Beijing
Normal University, 100875 Beijing, China
Faculty of Geographical Science, Beijing Normal University, 100875
Beijing, China
Ming Wang
CORRESPONDING AUTHOR
Academy of Disaster Reduction and Emergency Management, Beijing
Normal University, 100875 Beijing, China
School of National Safety and Emergency Management, Beijing Normal
University, 100875 Beijing, China
Kai Liu
Academy of Disaster Reduction and Emergency Management, Beijing
Normal University, 100875 Beijing, China
School of National Safety and Emergency Management, Beijing Normal
University, 100875 Beijing, China
Kaiwen Li
Academy of Disaster Reduction and Emergency Management, Beijing
Normal University, 100875 Beijing, China
Faculty of Geographical Science, Beijing Normal University, 100875
Beijing, China
Ziyu Jiang
Academy of Disaster Reduction and Emergency Management, Beijing
Normal University, 100875 Beijing, China
Faculty of Geographical Science, Beijing Normal University, 100875
Beijing, China
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16 citations as recorded by crossref.
- Evaluation of TerraClimate gridded data in investigating the changes of reference evapotranspiration in different climates of Iran K. Solaimani & S. Bararkhanpour Ahmadi 10.1016/j.ejrh.2024.101678
- Analyzing the environmental evolution of the Tibetan Plateau based on open-source data K. Zou et al. 10.1051/e3sconf/202336901002
- Dynamic Vegetation Responses to Climate and Land Use Changes over the Inner Mongolia Reach of the Yellow River Basin, China T. Liu et al. 10.3390/rs15143531
- Analysis of Spatial and Temporal Changes in Vegetation Cover and Driving Forces in the Wuding River Basin, Loess Plateau H. Zhang et al. 10.3390/f15010082
- Increased background precipitation masks the moisture deficit caused by crop greening in Northeast China L. Yu et al. 10.1016/j.jhydrol.2023.129857
- HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China R. Qin et al. 10.5194/essd-14-4793-2022
- 1 km monthly precipitation and temperatures dataset for China from 1952 to 2019 based on new baseline climatology surfaces H. Gong et al. 10.1016/j.scitotenv.2023.167613
- Optimizing geothermal reservoir modeling: A unified bayesian PSO and BiGRU approach for precise history matching under uncertainty J. Ullah et al. 10.1016/j.geothermics.2024.102958
- Integrated assessment of potentially toxic elements in soil of the Kangdian metallogenic province: A two-point machine learning approach W. Yang et al. 10.1016/j.ecoenv.2024.116248
- High-resolution grids of daily air temperature for Peru - the new PISCOt v1.2 dataset A. Huerta et al. 10.1038/s41597-023-02777-w
- Prediction of forest fire occurrence in China under climate change scenarios Y. Shao et al. 10.1007/s11676-023-01605-6
- The impact of long-term PM1 exposure on all-cause mortality and its interaction with BMI: A nationwide prospective cohort study in China J. Jiang et al. 10.1016/j.scitotenv.2023.168997
- HiTIC-Monthly: a monthly high spatial resolution (1 km) human thermal index collection over China during 2003–2020 H. Zhang et al. 10.5194/essd-15-359-2023
- Distinguishing natural and anthropogenic contributions to biological soil crust distribution in China's drylands Z. Wang et al. 10.1016/j.scitotenv.2023.168009
- Earlier Precipitation Enhances Dryland Annual Primary Production H. Zhao et al. 10.1029/2022JG007127
- Spatial and temporal analysis of drought resistance of different vegetation in the Ta-pieh Mountains based on multi-source data H. Li et al. 10.2166/wcc.2023.584
2 citations as recorded by crossref.
- Analysis of Spatial and Temporal Changes in Vegetation Cover and Driving Forces in the Yan River Basin, Loess Plateau Z. He et al. 10.3390/rs15174240
- Temporal and Spatial Assessment of Carbon Flux Dynamics: Evaluating Emissions and Sequestration in the Three Northern Protection Forest Project Areas Supported by Google Earth Engine Y. Shao et al. 10.3390/rs16050777
Latest update: 24 Apr 2024
Short summary
We used three machine learning models and determined that Gaussian process regression (GPR) is best suited to the interpolation of air temperature data for China. The GPR-derived results were compared with that of traditional interpolation techniques and existing data sets and it was found that the accuracy of the GPR-derived data was better. Finally, we generated a gridded monthly air temperature data set with 1 km resolution and high accuracy for China (1951–2020) using the GPR model.
We used three machine learning models and determined that Gaussian process regression (GPR) is...
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