Observed declining strength of vegetation-atmosphere coupling
文献类型：期刊论文
| 作者 | Li, Shijie1,2,3,4; Wang, Guojie1,9; Sun, Shanlei1; Chen, Zefeng4; Mura, Matteo4; Lu, Jiao8; Liu, Qi7; Li, Ji6; Hagan, Daniel Fiifi Tawia5; Garcia-Garcia, Almudena2,3 |
| 刊名 | AGRICULTURAL AND FOREST METEOROLOGY
 |
| 出版日期 | 2026-03-15 |
| 卷号 | 379页码:111051 |
| 关键词 | Vegetation-atmosphere coupling Canopy conductance LAI Wind speed |
| ISSN号 | 0168-1923 |
| DOI | 10.1016/j.agrformet.2026.111051 |
| 产权排序 | 8 |
| 文献子类 | Article |
| 英文摘要 | Land-atmosphere coupling (LAC) directly influences the occurrence of extreme climate events. Traditionally, the studies of LAC strength have primarily used soil moisture as a proxy for land conditions. However, recent research has highlighted the significant role of vegetation-atmosphere coupling (VC) in the evolution of extreme climate events through its regulation of the water and energy cycles. Despite this progress, the global patterns and driving mechanisms of VC remain unclear. In this study, the index with a clear physical meaning, omega, defined as the relationship between the canopy conductance (gc) and aerodynamic conductance (ga), was introduced to represent VC values. Long-term (1981-2018) global annual VC values were derived using two high-quality reanalysis datasets (ERA5 and MERRA2) based on two different gc models. Both gc models exhibited similar spatial distributions that the highest VC values in Arid regions, the lowest in Humid regions, and intermediate values in Transition zones. Results showed 38.84-61.98 % of global land with decreasing VC trend. An attribution analysis using a nonlinear machine learning approach revealed that leaf area index (LAI) and wind speed dominated the VC changes across different climate zones. An increase in LAI reduced VC strength, whereas enhanced wind speed increased VC values. LAI was the dominant factor influencing VC through transpiration regulation (i.e., gc) over Transition and Arid regions, while wind speed controlled VC variations via ga over Humid regions. Our study analyzed the spatiotemporal changes in VC values and their driving mechanisms across global land areas. These findings contribute to a deeper understanding of vegetation-climate feedback and its role in amplifying extreme climate events. |
| URL标识 | 查看原文 |
| WOS关键词 | LAND ; MODEL ; EVAPOTRANSPIRATION ; PHOTOSYNTHESIS ; TRANSPIRATION |
| WOS研究方向 | Agriculture ; Forestry ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001683715400001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/220911]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Wang, Guojie |
| 作者单位 | 1.Nanjing Univ Informat Sci & Technol, Minist Educ, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Key Lab Meteorol Disaster,State Key Lab Climate Sy, Nanjing, Peoples R China; 2.Univ Leipzig, Inst Earth Syst Sci & Remote Sensing, Talstr 35, D-04103 Leipzig, Germany; 3.UFZ Helmholtz Ctr Environm Res, Dept Remote Sensing, Permoserstr 15, D-04318 Leipzig, Germany; 4.Univ Florence, Dept Civil & Environm Engn, I-50139 Florence, Italy; 5.Univ Ghent, Hydroclimate Extremes Lab, B-9000 Ghent, Belgium 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China; 7.Jiangsu Univ Technol, Sch Comp Engn, Zhongwu Rd 1801, Changzhou 213001, Peoples R China; 8.Wuxi Univ, Sch Atmospher Sci & Remote Sensing, Wuxi 214105, Peoples R China; 9.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Li, Shijie,Wang, Guojie,Sun, Shanlei,et al. Observed declining strength of vegetation-atmosphere coupling[J]. AGRICULTURAL AND FOREST METEOROLOGY,2026,379:111051. |
| APA | Li, Shijie.,Wang, Guojie.,Sun, Shanlei.,Chen, Zefeng.,Mura, Matteo.,...&Peng, Jian.(2026).Observed declining strength of vegetation-atmosphere coupling.AGRICULTURAL AND FOREST METEOROLOGY,379,111051. |
| MLA | Li, Shijie,et al."Observed declining strength of vegetation-atmosphere coupling".AGRICULTURAL AND FOREST METEOROLOGY 379(2026):111051. |
入库方式： OAI收割
来源：地理科学与资源研究所
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