• Energy Research
• 2016-2025close

Climate change is having a profound effect on every part of the globe but perhaps nowhere more so than on the Earth’s cryosphere. The Arctic Permafrost Atlas is a consolidation of the available knowledge on permafrost, offering insights into the diverse aspects of permafrost and the impacts of climate change on permafrost. It gathers the knowledge from the voices of scientists, Indigenous Peoples, northern residents, and local practitioners to provide a holistic and inclusive view of today’s challenges in the “country of permafrost”. The atlas is divided into seven chapters: introduction to permafrost; permafrost and climate change; permafrost change in terrestrial, coastal, and subsea permafrost; impacts of permafrost thaw on infrastructure, health, and economies; adaptation to permafrost thaw; permafrost outside the Arctic; and concludes by showing the links between the physical processes, key hazards, and consequences and the actions needed to address them.

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.