Articles | Volume 19, issue 12
https://doi.org/10.5194/gmd-19-5743-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-5743-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
01 Jul 2026
Model evaluation paper |
| 01 Jul 2026
| 01 Jul 2026
Optimization of snow cover fraction parameterization in the Community Land Model: implementation and preliminary validation over the Tibetan Plateau
Kai Yang
CORRESPONDING AUTHOR
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China
Chenghai Wang
Key Laboratory of Climate Resource Development and Disaster Prevention of Gansu Province, Research and Development Center of Earth System Model, College of Atmospheric Sciences, Lanzhou University, Lanzhou, China
Ningxia Meteorological Bureau, Yinchuan, China
Lingyun Ai
Key Laboratory of Climate Resource Development and Disaster Prevention of Gansu Province, Research and Development Center of Earth System Model, College of Atmospheric Sciences, Lanzhou University, Lanzhou, China
Feimin Zhang
Key Laboratory of Climate Resource Development and Disaster Prevention of Gansu Province, Research and Development Center of Earth System Model, College of Atmospheric Sciences, Lanzhou University, Lanzhou, China
Pinghan Zhaoye
Key Laboratory of Climate Resource Development and Disaster Prevention of Gansu Province, Research and Development Center of Earth System Model, College of Atmospheric Sciences, Lanzhou University, Lanzhou, China
Changzhou Environmental Monitoring Center of Jiangsu Province, Changzhou, China
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Short summary
Climate models still exhibit substantial cold biases over the Tibetan Plateau, with snow cover biases recognized as one of the major contributing factors. By incorporating the effects of standing dead grass stems and topographic relief on snow distribution and snow depletion processes, the snow cover fraction (SCF) parameterization was optimized, reducing positive SCF biases by 63 % and alleviating surface cold biases by approximately 1–2 °C in snow-affected regions.
Climate models still exhibit substantial cold biases over the Tibetan Plateau, with snow cover...
