Articles | Volume 14, issue 11
https://doi.org/10.5194/essd-14-4793-2022
© 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-14-4793-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China
Rongzhu Qin
State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China
Zeyu Zhao
State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China
Jia Xu
State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China
Jian-Sheng Ye
State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China
Feng-Min Li
State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China
Feng Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, 730000, China
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Latest update: 26 Dec 2024
Short summary
This work presents a new high-resolution daily gridded maximum temperature, minimum temperature, and precipitation dataset for China (HRLT) with a spatial resolution of 1 × 1 km for the period 1961 to 2019. This dataset is valuable for crop modelers and climate change studies. We created the HRLT dataset using comprehensive statistical analyses, which included machine learning, the generalized additive model, and thin-plate splines.
This work presents a new high-resolution daily gridded maximum temperature, minimum temperature,...
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