The use of climate reanalysis data to understand historical storm impacts recorded in coastal environments with geomorphological methods

Abstract

International audienceIn the current context of climate change, extreme coastal events are becoming a major environmental challenge. According to the latest findings from the Intergovernmental Panel on Climate Change (IPCC), rising sea levels could ultimately displace 280 million people worldwide (Pörtner et al., 2019). With nearly 60% of the global population living within 150 km of the coast, as reported by the International Union for Conservation of Nature (IUCN), coastal flooding poses a significant and ongoing threat to nearshore societies. While the influence of climate change on tropical cyclones is well-documented, its impact on extratropical storms remains uncertain (Masson-Delmotte et al., 2021). The IPCC has observed a poleward drift in extratropical storm trajectories over recent decades in both hemispheres but highlights the difficulty of assessing the future effects of rising greenhouse gas emissions on these storms (Wang et al., 2006). Currently, only the increase in associated precipitation is widely accepted by the scientific community (Semmler et al., 2004). Although European coastal extreme events are becoming more frequent due to global mean sea-level rise, the long-term climatological dynamics of storms affecting Europe remain poorly understood. To address this gap, historical storm records are essential. For instance, new digital approaches based on a 1996–2015 dataset have been applied to predict storm characteristics and occurrences in Western France (Frifra et al., 2024).To support these new digital methods, this study aims to improve the precision of historical storm archives using reanalysis data. Geomorphological methods, such as sedimentology and dendrochronology (Pouzet et al., 2018), have been used to understand short- and long-term storm variability in western France, supplemented by detailed written archives. These environmental methods extend storm chronologies back several decades or even centuries, providing greater temporal depth for predictive models. However, the accuracy of dating decreases with the age of the archives, increasing uncertainty for older records. To address this limitation, climate reanalysis data are used to improve dating precision and identify specific weather and/or marine parameters that played key roles in generating the environmental impacts recorded in geomorphological archives (Pouzet and Idier, 2024).This study explores the potential of reanalysis data to understand how historical storms have impacted coastal physical and societal environments. Using ERA5 ocean-atmosphere data (Hersback et al., 2020) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), we present new methodologies to apprehend the evolution of historical storm activity in western Europe. These approaches are tested on major storms that impacted coastal environments during the XIXth and the XXth centuries, within the temporal scope of the ERA5 reanalysis data. The storm tracks of historical events that caused geomorphological marks detected in the environment are estimated based on their wind gust records. A spatial analysis model, utilizing GIS techniques, is employed to understand the overall extent of the most intense winds per storm. This model helps identify potential physical and societal impacts of historical storms and refines historical spatial storm parameters, including their precise “impact trajectories”. Additionally, we present new methods to detect the specific ocean-atmospheric parameters that induced geomorphological imprints on coastal environments and impacted nearshore societies. Our findings indicate that wave height is one of the main oceanographic parameters explaining marine impacts along the coastline, while maximum wind gusts play a key role in storm impacts inland.This study demonstrates that climatic reanalysis data are essential for understanding historical storm dynamics recorded during the reanalysis timespan, reducing dating uncertainties, and confirming the hazardousness of these storms in relation to current coastal issues. Combining reanalysis data with geomorphological archives is crucial, as environmental dating remains subject to significant error margins. In future research, extending climatic reanalysis datasets to earlier periods could provide critical insights for interpreting geomorphological data, as sedimentological and dendrochronological archives now offer storm records spanning millennia. By obtaining more accurate and ancient historical data through these methods, future models will be able to make precise predictions in the context of ongoing climate change. Given the high uncertainty surrounding extratropical storm dynamics, this research addresses a major contemporary issue