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ArcticBeach v1.0
(2022)
In the Arctic, air temperatures are increasing 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. Climate change has been shown to increase the rate of Arctic coastal erosion, causing problems for Arctic cultural heritage, existing 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 permafrost coastline. This Arctic erosion model, called ArcticBeach v1.0, is a first step toward a physical parameterization of Arctic shoreline erosion for larger-scale models. It is forced by wind speed and direction, 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 three study sites at 1) Drew Point (DP), Alaska, 2) Mamontovy Khayata (MK), Siberia, and 3) Veslebogen Cliffs, Svalbard. 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 the same order of magnitude as observed cumulative retreat (172 and 120 m). The rocky Veslebogen cliffs have small observed cumulative retreat rates (0.05 m over 2014-2016), and our model was also able to reproduce this same order of magnitude of retreat (0.08 m). Given the large differences in geomorphology between the study sites, this study provides a proof-of-concept that ArcticBeach v1.0 can be applied on very different permafrost coastlines. ArcticBeach v1.0 provides a promising starting point to project retreat of Arctic shorelines, or to evaluate historical retreat in places that have had few observations.
Thermokarst lakes are prevalent in Arctic coastal lowland regions and sublake permafrost degradation and talik development contributes to greenhouse gas emissions by tapping the large permafrost carbon pool. Whereas lateral thermokarst lake expansion is readily apparent through remote sensing and shoreline measurements, sublake thawed sediment conditions and talik growth are difficult to measure. Here we combine transient electromagnetic surveys with thermal modeling, backed up by measured permafrost properties and radiocarbon ages, to reveal closed-talik geometry associated with a thermokarst lake in continuous permafrost. To improve access to talik geometry data, we conducted surveys along three transient electromagnetic transects perpendicular to lakeshores with different decadal-scale expansion rates of 0.16, 0.38, and 0.58m/year. We modeled thermal development of the talik using boundary conditions based on field data from the lake, surrounding permafrost and a borehole, independent of the transient electromagnetics. A talik depth of 91m was determined from analysis of the transient electromagnetic surveys. Using a lake initiation age of 1400years before present and available subsurface properties the results from thermal modeling of the lake center arrived at a best estimate talk depth of 80m, which is on the same order of magnitude as the results from the transient electromagnetic survey. Our approach has provided a noninvasive estimate of talik geometry suitable for comparable settings throughout circum-Arctic coastal lowland regions.