Journal Article

A spatially explicit database of wind disturbances in European forests over the period 2000–2018

Rüetschi, Marius, Forzieri, Giovanni, Wurpillot-Lucas, Stéphanie, Cescatti, Alessandro, Catani, Filippo, Wolynski, Alessandro, Maistrelli, Fabio, Chen, Yi-Ying, Nikolov, Christo, Gardiner, Barry, Krejci, Lukas, Beck, Pieter S. A., Spinoni, Jonathan, Savulescu, Ionut, Giannetti, Francesca, Karlsson, Stefan, Chirici, Gherardo, Jonikavicius, Donatas, Small, David, Comino, Rinaldo, Nilsson, Mats, Zieba-Kulawik, Karolina, Klaus, Marcus, Luyssaert, Sebastiaan, Feyen, Luc, Strejczek-Jazwinska, Paulina, Mauri, Achille, Tomaštík, Julián, Pecchi, Matteo, Haidu, Ionel, Girardello, Marco, Mokroš, Martin, Franz, Stefan, Wezyk, Piotr, Pirotti, Francesco, Nistor, Constantin

2020

Overview

Strong winds may uproot and break trees and represent a major natural disturbance for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the effects of climate change. Despite the importance of such natural disturbances, there are currently no spatially explicit databases of wind-related impact at a pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND is comprised of more than 80 000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018 and describes them in a harmonized and consistent geographical vector format. The database includes all major windstorms that occurred over the observational period (e.g. Gudrun, Kyrill, Klaus, Xynthia and Vaia) and represents approximately 30 % of the reported damaging wind events in Europe. Correlation analyses between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p value < 0.05). When recorded forest areas are rescaled based on their damage degree, correlation increases to 0.54. Wind-damaged growing stock volumes reported in national inventories (FORESTORM dataset) are generally higher than analogous metrics provided by FORWIND in combination with satellite-based biomass and country-scale statistics of growing stock volume. The potential of FORWIND is explored for a range of challenging topics and scientific fields, including scaling relations of wind damage, forest vulnerability modelling, remote sensing monitoring of forest disturbance, representation of uprooting and breakage of trees in large-scale land surface models, and hydrogeological risks following wind damage. Overall, FORWIND represents an essential and open-access spatial source that can be used to improve the understanding, detection and prediction of wind disturbances and the consequent impacts on forest ecosystems and the land–atmosphere system. Data sharing is encouraged in order to continuously update and improve FORWIND. The dataset is available at https://doi.org/10.6084/m9.figshare.9555008 (Forzieri et al., 2019).

• Publisher: Copernicus GmbH,Copernicus Publications
• Subject: Analysis / Atmospheric models / Climate change / Climate effects / Climatic changes / Coefficients / Correlation / Correlation analysis / Data retrieval / Datasets / Disturbances / Ecosystem disturbance / Ecosystems / Forest damage / Forest ecosystems / Forest management / Forest Science / Forests / Forests and forestry / Geography / Geology / Global temperature changes / Humanities and Social Sciences / Hydrogeology / Land cover / Land surface models / Landsat / Landsat satellites / Meteorologi och atmosfärforskning / Meteorology and Atmospheric Sciences / Natural disturbance / Online databases / Rankings / Remote monitoring / Remote sensing / Scaling / Skogsvetenskap / Statistical methods / Strong winds / Terrestrial ecosystems / Trees / Uprooting / Vulnerability / Wind / Wind damage / Winds