Analysis of vegetation-atmosphere transfers simulated by the Interaction Soil-Biosphere-Atmosphere (ISBA) model for a beech forest in Lorraine, France

Abstract

Climate change is anticipated to increase the frequency of drought events, posing a significant threat to the European Beech, Fagus Sylvatica L., known for its high sensitivity to such conditions. This heightened vulnerability may lead to a northward migration of its distribution, impacting carbon sequestration. In light of these concerns, developing land surface models tailored to forest ecosystems becomes crucial for predicting their fate under changing climate conditions. To address this, the Interaction Soil-Biosphere-Atmosphere (ISBA) component of the SURFEX model underwent adjustments to refine predictions under drought events, specifically considering the unique phenology of the Beech. The study focuses on the ICOS network station located in the Beech forest of Hesse, France, providing standardized, high-precision, high-frequency, and long-term observations. Initially, a simulation was conducted, keeping the ISBA model intact to evaluate its baseline performance. Subsequently, two simulations were implemented to impose phenological adjustments, enhancing the representation of carbon transfers between the soil-plant system and the atmosphere. The first simulation incorporated the observed Leaf Area Index (LAI) into the photosynthesis subroutine, while the second, more performant, additionally implemented observed LAI in the carbon allocation scheme. Despite these advancements, the drought-induced reduction in latent heat flux and gross primary production were poorly represented. Further adjustments, such as implementing hydraulic architecture, are necessary to refine the drought response regarding the water vapour fluxes. The promising results of imposing phenology hold the potential to yield an enhanced representation of soil-plant system exchanges with the atmosphere. This improvement, once achieved, would enable more accurate forecasting of forest responses under climate change conditions.