[A-CG61] Carbon Cycle Observation and Analysis

[ACG61-P20] Deciphering Spatiotemporal Heterogeneity of Carbon Fluxes on the Tibetan Plateau: A Daily, 500m NEE Dataset (2000–2024) via Mechanism-Constrained Machine Learning

*WEIMO LI^1,2,3, Binbin Wang^2,5,6, Kazuhito Ichii³, Yaoming Ma^1,2,4,5,6,7, Zhengling Cai^1,2, Beichen Zhang³, Changrong Tan^1,2, Hongchao Zuo¹, Zhipeng Xie², Xingdong Shi^1,2, Wei Li³ (1. College of Atmospheric Science, Lanzhou University, Lanzhou 730000, China , 2. Land-Atmosphere Interaction and its Climatic Effects Group, TPESER, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, 3. Center for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi-cho, Inage-ku,Chiba 263-8522, Japan, 4. College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China , 5. National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes, Dingri 858200, China , 6. Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China , 7. China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, Islamabad 45320, Pakistan )

Keywords:Net Ecosystem Exchange (NEE), Tibetan Plateau, Mechanism-Constrained ML, High-spatial Resolution