Articles | Volume 19, issue 7
https://doi.org/10.5194/tc-19-2733-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-19-2733-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dynamic identification of snow phenology in the Northern Hemisphere
Le Wang
School of Atmospheric Sciences, Nanjing University, Nanjing, China
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Xinyun Hu
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Yizhuo Li
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Bo Qiu
School of Atmospheric Sciences, Nanjing University, Nanjing, China
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Weidong Guo
School of Atmospheric Sciences, Nanjing University, Nanjing, China
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A process-based plant Carbon (C)-Nitrogen (N) interface coupling framework has been developed, which mainly focuses on the plant resistance and N limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem-biogeochemical model and testing results show a general improvement in simulating plant properties with this framework.
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Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
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Short summary
Snow phenology is a crucial indicator for assessing seasonal changes in snow. In this work, we find that snow phenology is significantly impacted by the datasets and methods used, and current methods often overlook the spatial and temporal variability in snow across the Northern Hemisphere. To address this, we develop a dynamic-threshold method, which contributes to better representing the seasonal changes in snow cover across the Northern Hemisphere, especially on the Tibetan Plateau.
Snow phenology is a crucial indicator for assessing seasonal changes in snow. In this work, we...