Abstract Windstorms are the principal cause of disturbance to European forests, and their frequency and magnitude are expected to increase by the end of the century due to climate change. Several studies have assessed the risk of forest damage from wind disturbances, but most were limited by the accuracy of forest vulnerability or by climate data, especially in complex terrain such as the Alps. In this study, we assessed and mapped forest wind risk at high resolution (20 × 20 m) under historical (1996–2005) and future (2090–2099, Representative Concentration Pathway 8.5) reference periods. The study takes advantage of high-resolution remotely sensed data to derive individual tree and stand characteristics for calculating forest vulnerability with ForestGALES, a hybrid mechanistic-empirical forest wind risk model. The investigation focuses on the impact of changes in wind intensities between the historical and the future scenarios on forest risk by fixing the same forest vulnerability map derived from a LiDAR survey acquired in 2019. Wind intensities were derived from an ensemble of high temporal and spatial resolution convection-permitting models. Combining these two datasets, we produced high resolution mapping of forest wind risk for an area in the Dolomites in North-east Italy. This study classifies the forest area into three levels of risk, and it quantitatively assesses the relative amount of growing stock at risk. Results for a case study forest area of 268 km 2 show that the growing stock at risk is equal to 8.5% and increasing to 10.0% under the historical and future reference periods, respectively. The risk maps clearly identified the areas at higher risk, mainly those composed of pure Norway spruce stands, providing fundamental insights for improving forest resistance to wind at the regional scale.
Baggio et al. (2026) studied this question.