Articles | Volume 27, issue 15
https://doi.org/10.5194/hess-27-2919-2023
© Author(s) 2023. This work is distributed under
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the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-27-2919-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Aug 2023
Research article |
| 09 Aug 2023
| 09 Aug 2023
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
Yuanhong You
Key
Laboratory of Earth Surface Processes and Regional Response in the
Yangtze-Huaihe River Basin of Anhui Province, Anhui Normal University, School of Geography and Tourism, Wuhu, 241002, China
Engineering Technology Research Center of Resource Environment and
GIS, Wuhu, 241002, China
Key Laboratory of Remote Sensing of
Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou, 730000, China
Zuo Wang
Key
Laboratory of Earth Surface Processes and Regional Response in the
Yangtze-Huaihe River Basin of Anhui Province, Anhui Normal University, School of Geography and Tourism, Wuhu, 241002, China
Jinliang Hou
Key Laboratory of Remote Sensing of
Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou, 730000, China
Ying Zhang
Key Laboratory of Remote Sensing of
Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou, 730000, China
Peipei Xu
Key
Laboratory of Earth Surface Processes and Regional Response in the
Yangtze-Huaihe River Basin of Anhui Province, Anhui Normal University, School of Geography and Tourism, Wuhu, 241002, China
Related authors
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Jinliang Hou, Mingkai Zhang, Xiaohua Hao, Jifu Guo, Peng Dou, Ying Zhang, and Chunlin Huang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-662, https://doi.org/10.5194/essd-2025-662, 2025
Preprint under review for ESSD
Short summary
Short summary
ChinaAI-FSC provides the first large-scale, AI-ready snow dataset for mainland China, spanning 2000–2022. By integrating MODIS, Landsat, and Sentinel-2 observations with advanced quality control, it supports AI model training, benchmarking, and large-scale snow mapping. The dataset enhances snow monitoring accuracy and fosters reproducible research on climate and hydrological processes.
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Short summary
This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
This study aims to investigate the performance of a genetic particle filter which was used as a...
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