@article{KaiserGrosseBoikeetal.2021, author = {Kaiser, Soraya and Grosse, Guido and Boike, Julia and Langer, Moritz}, title = {Monitoring the transformation of Arctic landscapes}, series = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, volume = {13}, journal = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, number = {14}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs13142802}, pages = {19}, year = {2021}, abstract = {Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their movement rate and direction on the basis of ortho-ready very high resolution satellite imagery from Arctic permafrost lowlands. We applied this workflow to typical Arctic lake areas on the Alaska North Slope and achieved a successful and fast detection of water bodies. We derived representative values for shoreline movement rates ranging from 0.40-0.56 m yr(-1) for lake sizes of 0.10 ha-23.04 ha. The approach also gives an insight into seasonal water level changes. Based on an extensive quantification of error sources, we discuss how the results of the automated workflow can be further enhanced by incorporating additional information on weather conditions and image metadata and by improving the input database. The workflow is suitable for the seasonal to annual monitoring of lake changes on a sub-meter scale in the study areas in northern Alaska and can readily be scaled for application across larger regions within certain accuracy limitations.}, language = {en} } @article{RolphOverduinRavensetal.2022, author = {Rolph, Rebecca and Overduin, Pier Paul and Ravens, Thomas and Lantuit, Hugues and Langer, Moritz}, title = {ArcticBeach v1.0}, series = {Frontiers in Earth Science}, volume = {10}, journal = {Frontiers in Earth Science}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-6463}, doi = {10.3389/feart.2022.962208}, pages = {19}, year = {2022}, abstract = {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.}, language = {en} } @article{StuenziKruseBoikeetal.2022, author = {Stuenzi, Simone Maria and Kruse, Stefan and Boike, Julia and Herzschuh, Ulrike and Oehme, Alexander and Pestryakova, Luidmila A. and Westermann, Sebastian and Langer, Moritz}, title = {Thermohydrological impact of forest disturbances on ecosystem-protected permafrost}, series = {Journal of geophysical research : Biogeosciences}, volume = {127}, journal = {Journal of geophysical research : Biogeosciences}, number = {5}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-8953}, doi = {10.1029/2021JG006630}, pages = {24}, year = {2022}, abstract = {Boreal forests cover over half of the global permafrost area and protect underlying permafrost. Boreal forest development, therefore, has an impact on permafrost evolution, especially under a warming climate. Forest disturbances and changing climate conditions cause vegetation shifts and potentially destabilize the carbon stored within the vegetation and permafrost. Disturbed permafrost-forest ecosystems can develop into a dry or swampy bush- or grasslands, shift toward broadleaf- or evergreen needleleaf-dominated forests, or recover to the pre-disturbance state. An increase in the number and intensity of fires, as well as intensified logging activities, could lead to a partial or complete ecosystem and permafrost degradation. We study the impact of forest disturbances (logging, surface, and canopy fires) on the thermal and hydrological permafrost conditions and ecosystem resilience. We use a dynamic multilayer canopy-permafrost model to simulate different scenarios at a study site in eastern Siberia. We implement expected mortality, defoliation, and ground surface changes and analyze the interplay between forest recovery and permafrost. We find that forest loss induces soil drying of up to 44\%, leading to lower active layer thicknesses and abrupt or steady decline of a larch forest, depending on disturbance intensity. Only after surface fires, the most common disturbances, inducing low mortality rates, forests can recover and overpass pre-disturbance leaf area index values. We find that the trajectory of larch forests after surface fires is dependent on the precipitation conditions in the years after the disturbance. Dryer years can drastically change the direction of the larch forest development within the studied period.}, language = {en} }