Year: 2025
Type: article
Abstract: Monitoring sandy shoreline evolution from years to decades the closest coast. Because spatial averaging can help to is critical to understand the past and predict the future of our smooth out uncertain and noisy SDS, we also defined a coasts. Interannual shoreline variability is often primarily moving average distance L. enforced by large-scale climate patterns of atmospheric or coupled ocean-atmospheric variability (e.g. El Niño– Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO)). The seasonal to decadal predictability of these climate patterns recently showed increasing skill (Athanasiadis et al., 2020), which may allow a reduction in shoreline evolution uncertainties in the next decades. Understanding shoreline evolution on interannual to decadal timescales is therefore critical, particularly along the Atlantic coast of Europe, where previous work on a limited number of intensively monitored sites showed a strong control of large-scale climate modes of atmospheric variability on shoreline change (e.g., Dodet et al., 2019, Masselink et al., 2023). In this contribution, we consult an improved state-of-the-art global SDS dataset (Luijendijk et al., 2018) to address the spatial distribution of interannual variability of sandy shores along the Atlantic coast of Europe, and to further identify the primary drivers and coastal settings affecting this spatial variability.
Source: Coastal Engineering Proceedings
Authors: Bruno Castelle, Etiënne Kras, Gerd Masselink, Tim Scott, Aikaterini Konstantinou, Arjan Luijendijk
Language: English
Topic: Coastal and Marine Dynamics
Subfield: Earth-Surface Processes
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410872086