Li et al. (2026) Observed declining strength of vegetation-atmosphere coupling

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2026
• Date: 2026-02-02
• Authors: Shijie Li, Guojie Wang, Shanlei Sun, Zefeng Chen, Matteo Mura, Jiao Lu, Qi Liu, Ji Li, Daniel Fiifi Tawia Hagan, Almudena García-García, Jian Peng
• DOI: 10.1016/j.agrformet.2026.111051

Research Groups

• State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster, Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China
• Department of Civil and Environmental Engineering, University of Florence, Firenze, Italy
• Department of Remote Sensing, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
• Institute for Earth System Science and Remote Sensing, Leipzig University, Leipzig, Germany
• School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, China
• School of Atmospheric Science and Remote Sensing, Wuxi University, Wuxi, China
• School of Computer Engineering, Jiangsu University of Technology, Changzhou, China
• Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
• Hydro-Climate Extremes Lab, Ghent University, Ghent, Belgium

Short Summary

This study investigates the global patterns and driving mechanisms of vegetation-atmosphere coupling (VC) strength using a novel physically-based index, revealing a widespread declining trend in VC across 38.84–61.98 % of global land, primarily driven by changes in leaf area index and wind speed.

Objective

• To analyze the global spatiotemporal changes in vegetation-atmosphere coupling (VC) values and their underlying driving mechanisms.

Study Configuration

• Spatial Scale: Global land areas
• Temporal Scale: Long-term annual values from 1981 to 2018

Methodology and Data

• Models used: Two different canopy conductance (gc) models were employed to derive the vegetation-atmosphere coupling index (ω), defined as the relationship between canopy conductance (gc) and aerodynamic conductance (ga). A nonlinear machine learning approach was used for attribution analysis.
• Data sources: Two high-quality reanalysis datasets (ERA5 and MERRA2).

Main Results

• The vegetation-atmosphere coupling index (ω) exhibited highest values in Arid regions, lowest in Humid regions, and intermediate values in Transition zones.
• A decreasing trend in VC strength was observed across 38.84–61.98 % of global land over the period 1981–2018.
• Leaf area index (LAI) and wind speed were identified as the dominant factors influencing VC changes across different climate zones.
• An increase in LAI was found to reduce VC strength, while enhanced wind speed increased VC values.
• LAI primarily influenced VC through transpiration regulation (via gc) in Transition and Arid regions, whereas wind speed controlled VC variations via aerodynamic conductance (ga) in Humid regions.

Contributions

• Introduced a physically meaningful index (ω) to quantify vegetation-atmosphere coupling, moving beyond traditional soil moisture-based land-atmosphere coupling studies.
• Provided a comprehensive global analysis of the spatiotemporal changes and driving mechanisms of vegetation-atmosphere coupling.
• Enhanced understanding of vegetation-climate feedback and its implications for the amplification of extreme climate events.

Funding

• Not specified in the provided text.

Citation

@article{Li2026Observed,
  author = {Li, Shijie and Wang, Guojie and Sun, Shanlei and Chen, Zefeng and Mura, Matteo and Lu, Jiao and Liu, Qi and Li, Ji and Hagan, Daniel Fiifi Tawia and García-García, Almudena and Peng, Jian},
  title = {Observed declining strength of vegetation-atmosphere coupling},
  journal = {Agricultural and Forest Meteorology},
  year = {2026},
  doi = {10.1016/j.agrformet.2026.111051},
  url = {https://doi.org/10.1016/j.agrformet.2026.111051}
}