The Impact of Vegetation Dynamics on Atmospheric Teleconnections and Predictability.

Vegetation is a key component of the Earth system, regulating surface energy and water fluxes through its influence on surface roughness, albedo, and evapotranspiration. Its high spatial and temporal variability—ranging from seasonal to decadal timescales—plays a fundamental role in shaping both local climate and large-scale atmospheric circulation. Despite its importance, vegetation dynamics remain a challenging component to represent realistically in many Earth system models.
In this study, we assess the impact of improved vegetation representation on the simulated climate system by introducing a new parameterization of effective vegetation cover. This parameterization is derived from the latest satellite-based vegetation datasets, offering a more physically consistent and temporally responsive characterization of vegetation states.
The new parameterization is implemented in the land surface scheme HTESSEL, used within the IFS/OpenIFS modeling framework. A set of sensitivity experiments is carried out to evaluate the role of vegetation in modulating surface climate and atmospheric circulation patterns. Results show that the enhanced vegetation representation leads to a substantial reduction in surface climate biases, with notable improvements in near-surface temperature (T2M), mean sea level pressure, and zonal wind across mid-to-high latitudes.
Beyond local improvements, the new vegetation dynamics induce changes in large-scale atmospheric teleconnections. In particular, over Siberia—where vegetation changes exert the most pronounced influence on surface temperature—a circulation response is initiated, extending across the Northern Hemisphere. This includes a marked enhancement in the simulation of the North Atlantic Oscillation (NAO), with significantly stronger correlations between the modeled NAO index and its observational counterpart from ERA5.
These findings highlight the central role of vegetation–atmosphere interactions in controlling not only local energy balance but also hemispheric-scale circulation and predictability. The results underscore the importance of accurately representing land surface processes in Earth system models to enhance both seasonal forecasting skills and long-term climate projections. This study supports continued efforts in land surface model development and provides a clear pathway toward more realistic and skillful climate simulations.