ArcticBeach v1.0: A physics-based parameterization of pan-Arctic coastline erosion

Abstract

Abstract. In the Arctic, air temperatures are warming and sea ice is declining, resulting in larger waves and a longer open water season, all of which intensify the thaw and erosion of ice-rich coasts. This change in climate has been shown to increase the rate of Arctic coastal erosion, causing problems for industrial, military, and civil infrastructure as well as changes in nearshore biogeochemistry. Numerical models that reproduce historical and project future Arctic erosion rates are necessary to understand how further climate change will affect these problems, and no such model yet exists to simulate the physics of erosion on a pan-Arctic scale. We have coupled a bathystrophic storm surge model to a simplified physical erosion model of a partially frozen cliff and beach. This Arctic erosion model, called ArcticBeach v1.0, is a first step toward a parameterization of Arctic shoreline erosion for larger-scale models, which are not able to resolve the fine spatial scale (up to about 40 m) needed to capture shoreline erosion rates from years to decades. It is forced by wind speeds and directions, wave period and height, sea surface temperature, all of which are masked during times of sea ice cover near the coastline. Model tuning requires observed historical retreat rates (at least one value), as well as rough nearshore bathymetry. These parameters are already available on a pan-Arctic scale. The model is validated at two study sites at Drew Point (DP), Alaska, and Mamontovy Khayata (MK), Siberia, which are respectively located in the Beaufort and Laptev Seas, on different sides of the Arctic Ocean. Simulated cumulative retreat rates for DP and MK respectively (169 and 170 m) over the time periods studied at each site (2007–2016, and 1995–2018) are found to be within the same order of magnitude as observed cumulative retreat rates (172 and 120 m). Given the large differences in geomorphology and weather systems between the two study sites, this study provides a proof-of-concept that ArcticBeach v1.0 can be applied on very different partially frozen coastlines. ArcticBeach v1.0 provides a promising starting point to project the retreat of Arctic shorelines, or to evaluate historical retreat in places that have had few observations. Further, this model can provide estimates of the flux of sediment from land to sea for Arctic nearshore biogeochemical studies, while leaving an opportunity for further development of modelling the physics of a partially frozen shoreline.

Degrading permafrost river catchments and their impact on Arctic Ocean nearshore processes

“…Coastal erosion also delivers large amounts of OC into the nearshore, for example from the Mamontovy Khayata coastal cliff on the Bykovsky Peninsula (Fig. 2 ) (Lantuit et al 2011 ; Rolph et al 2021 ) or other Yedoma coastal segments along the Laptev Sea coast (Günther et al 2013 ; Strauss et al 2021b ).…”

High-resolution bathymetry models for the Lena Delta and Kolyma Gulf coastal zones

“…For example, local bathymetry can be used for validating the mapping of landfast sea ice stability with inter-ferometric synthetic aperture radar (Dammann et al, 2019). Further, coastal bathymetry and water level are important parameters for determining rates of coastal erosion (e.g., Barnhart et al, 2014;Pearson et al, 2016), and an improvement of local bathymetry will therefore help to improve model forecasts of coastal erosion in the Laptev Sea region (e.g., Rolph et al, 2021). In addition, for determining the extent of subsea permafrost, knowledge of water depth and sea surface morphology is essential.…”

Geotechnical Measurements for the Investigation and Assessment of Arctic Coastal Erosion—A Review and Outlook

“…This also applies to models specific to Arctic environments. For example, Arctic Beach 1.0 requires historic coastal retreat values (or at least one starting value) and a nearshore bathymetry [56]. Shoreline retreat rates can be determined from historic or current aerial imagery, aerial light distance and ranging (lidar), satellite imagery, historic maps, and local knowledge and environmental observations [2,[57][58][59].…”