Sebastian Westermann

• Czekirda, Justyna; Rempel, Alan W.; Etzelmüller, Bernd & Westermann, Sebastian (2024). Spatiotemporal variations in frost cracking measures in two dimensions: A case study for rock walls in Jotunheimen, southern Norway. Geomorphology. ISSN 0169-555X. 453. doi: 10.1016/j.geomorph.2024.109112.
• Treat, Claire C.; Virkkala, Anna-Maria; Burke, Eleanor; Bruhwiler, Lori; Chatterjee, Abhishek & Fisher, Joshua B. [Vis alle 32 forfattere av denne artikkelen] (2024). Permafrost Carbon: Progress on Understanding Stocks and Fluxes Across Northern Terrestrial Ecosystems. Journal of Geophysical Research (JGR): Biogeosciences. ISSN 2169-8953. 129(3). doi: 10.1029/2023JG007638.
• Langer, Moritz; Nitzbon, Jan; Groenke, Brian; Assmann, Lisa-Marie; Schneider Von Deimling, Thomas & Stuenzi, Simone Maria [Vis alle 7 forfattere av denne artikkelen] (2024). The evolution of Arctic permafrost over the last 3 centuries from ensemble simulations with the CryoGridLite permafrost model. The Cryosphere. ISSN 1994-0416. 18(1), s. 363–385. doi: 10.5194/tc-18-363-2024.
• Hellevang, Helge; Ippach, Mats Rouven; Westermann, Sebastian & Nooraiepour, Mohammad (2023). Formation of giant Siberian gas emission craters (GECs). EarthArXiv preprint platform. doi: 10.31223/X59Q3K. Vis sammendrag

  The recent discovery of eight giant gas escape craters (GECs) in the Russian Yamal and Gydan peninsulas has challenged researchers for the past decade. Despite numerous proposed models, ranging from meteor impacts to gas explosions, none provide a comprehensive explanation for why the GECs are found only in this specific region. This study proposes a new general model for the formation of GECs in which local permafrost thinning is linked to the local geology, i.e., discrete conductive faults bring natural gas and heat to the base permafrost, deforming and melting the base leading to the development of domal gas and heat traps. Atmospheric warming results in further local thinning and eventually mechanical collapse. The morphology of the GECs initially reflects the concentric deformation above domal base-permafrost structures but are after a short time disguised by water and sediment infill, and over time peatification, and cannot be distinguished from e.g., thermokarst lakes. Thus, the true number of GECs may largely exceed those already discovered.

• Etzelmüller, Bernd; Isaksen, Ketil; Czekirda, Justyna; Westermann, Sebastian; Hilbich, Christin & Hauck, Christian (2023). Rapid warming and degradation of mountain permafrost in Norway and Iceland. The Cryosphere. ISSN 1994-0416. 17(12), s. 5477–5497. doi: 10.5194/tc-17-5477-2023. Fulltekst i vitenarkiv
• Martin, Leo Celestin Paul; Westermann, Sebastian; Magni, Michele; Brun, Fanny; Fiddes, Joel & Lei, Yanbin [Vis alle 11 forfattere av denne artikkelen] (2023). Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 27(24), s. 4409–4436. doi: 10.5194/hess-27-4409-2023. Fulltekst i vitenarkiv
• Alonso-Gonzalez, Esteban; Aalstad, Kristoffer; Pirk, Norbert; Mazzolini, Marco; Treichler, Désirée & Leclercq, Paul [Vis alle 9 forfattere av denne artikkelen] (2023). Spatio-temporal information propagation using sparse observations in hyper-resolution ensemble-based snow data assimilation. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 27(24), s. 4637–4659. doi: 10.5194/hess-27-4637-2023. Fulltekst i vitenarkiv Vis sammendrag

  Data assimilation techniques that integrate available observations with snow models have been proposed as a viable option to simultaneously help constrain model uncertainty and add value to observations by improving estimates of the snowpack state. However, the propagation of information from spatially sparse observations in high-resolution simulations remains an under-explored topic. To remedy this, the development of data assimilation techniques that can spread information in space is a crucial step. Herein, we examine the potential of spatio-temporal data assimilation for integrating sparse snow depth observations with hyper-resolution (5 m) snow simulations in the Izas central Pyrenean experimental catchment (Spain). Our experiments were developed using the Multiple Snow Data Assimilation System (MuSA) with new improvements to tackle the spatio-temporal data assimilation. Therein, we used a deterministic ensemble smoother with multiple data assimilation (DES-MDA) with domain localization. Three different experiments were performed to showcase the capabilities of spatio-temporal information transfer in hyper-resolution snow simulations. Experiment I employed the conventional geographical Euclidean distance to map the similarity between cells. Experiment II utilized the Mahalanobis distance in a multi-dimensional topographic space using terrain parameters extracted from a digital elevation model. Experiment III utilized a more direct mapping of snowpack similarity from a single complete snow depth map together with the easting and northing coordinates. Although all experiments showed a noticeable improvement in the snow patterns in the catchment compared with the deterministic open loop in terms of correlation (r=0.13) and root mean square error (RMSE = 1.11 m), the use of topographical dimensions (Experiment II, r=0.63 and RMSE =  0.89 m) and observations (Experiments III, r=0.92 and RMSE =  0.44 m) largely outperform the simulated patterns in Experiment I (r=0.38 and RMSE = 1.16 m). At the same time, Experiments II and III are considerably more challenging to set up. The results of these experiments can help pave the way for the creation of snow reanalysis and forecasting tools that can seamlessly integrate sparse information from national monitoring networks and high-resolution satellite information.

• Aga, Juditha; Boike, Julia; Langer, Moritz; Ingeman-Nielsen, Thomas & Westermann, Sebastian (2023). Simulating ice segregation and thaw consolidation in permafrost environments with the CryoGrid community model. The Cryosphere. ISSN 1994-0416. 17(10), s. 4179–4206. doi: 10.5194/tc-17-4179-2023. Fulltekst i vitenarkiv
• Ben-Asher, Matan; Magnin, Florence; Westermann, Sebastian; Bock, Josué; Malet, Emmanuel & Berthet, Johan [Vis alle 8 forfattere av denne artikkelen] (2023). Estimating surface water availability in high mountain rock slopes using a numerical energy balance model. Earth Surface Dynamics. ISSN 2196-6311. 11(5), s. 899–915. doi: 10.5194/esurf-11-899-2023. Fulltekst i vitenarkiv
• Groenke, Brian; Langer, Moritz; Nitzbon, Jan; Westermann, Sebastian; Gallego, Guillermo & Boike, Julia (2023). Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer. The Cryosphere. ISSN 1994-0416. 17(8), s. 3505–3533. doi: 10.5194/tc-17-3505-2023. Fulltekst i vitenarkiv
• Czekirda, Justyna; Etzelmüller, Bernd; Westermann, Sebastian; Isaksen, Ketil & Magnin, Florence (2023). Post-Little Ice Age rock wall permafrost evolution in Norway. The Cryosphere. ISSN 1994-0416. 17(7), s. 2725–2754. doi: 10.5194/tc-17-2725-2023. Fulltekst i vitenarkiv
• Schmidt, Louise Steffensen; Schuler, Thomas; Thomas, Erin E. & Westermann, Sebastian (2023). Meltwater runoff and glacier mass balance in the high Arctic: 1991-2022 simulations for Svalbard. The Cryosphere. ISSN 1994-0416. 17(7), s. 2941–2963. doi: 10.5194/tc-17-2941-2023. Fulltekst i vitenarkiv
• Pirk, Norbert; Aalstad, Kristoffer; Yilmaz, Yeliz A.; Vatne, Astrid; Popp, Andrea & Horvath, Peter [Vis alle 12 forfattere av denne artikkelen] (2023). Snow-vegetation-atmosphere interactions in alpine tundra. Biogeosciences. ISSN 1726-4170. 20(11), s. 2031–2047. doi: 10.5194/bg-20-2031-2023. Fulltekst i vitenarkiv Vis sammendrag

  The interannual variability of snow cover in alpine areas is increasing, which may affect the tightly coupled cycles of carbon and water through snow–vegetation–atmosphere interactions across a range of spatio-temporal scales. To explore the role of snow cover for the land–atmosphere exchange of CO2 and water vapor in alpine tundra ecosystems, we combined 3 years (2019–2021) of continuous eddy covariance flux measurements of the net ecosystem exchange of CO2 (NEE) and evapotranspiration (ET) from the Finse site in alpine Norway (1210 m a.s.l.) with a ground-based ecosystem-type classification and satellite imagery from Sentinel-2, Landsat 8, and MODIS. While the snow conditions in 2019 and 2021 can be described as site typical, 2020 features an extreme snow accumulation associated with a strong negative phase of the Scandinavian pattern of the synoptic atmospheric circulation during spring. This extreme snow accumulation caused a 1-month delay in melt-out date, which falls in the 92nd percentile in the distribution of yearly melt-out dates in the period 2001–2021. The melt-out dates follow a consistent fine-scale spatial relationship with ecosystem types across years. Mountain and lichen heathlands melt out more heterogeneously than fens and flood plains, while late snowbeds melt out up to 1 month later than the other ecosystem types. While the summertime average normalized difference vegetation index (NDVI) was reduced considerably during the extreme-snow year 2020, it reached the same maximum as in the other years for all but one of the ecosystem types (late snowbeds), indicating that the delayed onset of vegetation growth is compensated to the same maximum productivity. Eddy covariance estimates of NEE and ET are gap-filled separately for two wind sectors using a random forest regression model to account for complex and nonlinear ecohydrological interactions. While the two wind sectors differ markedly in vegetation composition and flux magnitudes, their flux response is controlled by the same drivers as estimated by the predictor importance of the random forest model, as well as by the high correlation of flux magnitudes (correlation coefficient r=0.92 for NEE and r=0.89 for ET) between both areas. The 1-month delay of the start of the snow-free season in 2020 reduced the total annual ET by 50 % compared to 2019 and 2021 and reduced the growing-season carbon assimilation to turn the ecosystem from a moderate annual carbon sink (−31 to −6 gC m−2 yr−1) to a source (34 to 20 gC m−2 yr−1). These results underpin the strong dependence of ecosystem structure and functioning on snow dynamics, whose anomalies can result in important ecological extreme events for alpine ecosystems.

• Langer, Moritz; von Deimling, Thomas Schneider; Westermann, Sebastian; Rolph, Rebecca; Rutte, Ralph & Antonova, Sofia [Vis alle 10 forfattere av denne artikkelen] (2023). Thawing permafrost poses environmental threat to thousands of sites with legacy industrial contamination. Nature Communications. ISSN 2041-1723. 14. doi: 10.1038/s41467-023-37276-4. Fulltekst i vitenarkiv
• Miesner, F.; Overduin, P.P.; Grosse, G.; Strauss, J.; Langer, M. & Westermann, Sebastian [Vis alle 9 forfattere av denne artikkelen] (2023). Subsea permafrost organic carbon stocks are large and of dominantly low reactivity. Scientific Reports. ISSN 2045-2322. 13. doi: 10.1038/s41598-023-36471-z. Fulltekst i vitenarkiv
• Westermann, Sebastian; Ingeman-Nielsen, Thomas; Scheer, Johanna; Aalstad, Kristoffer; Aga, Juditha & Chaudhary, Nitin [Vis alle 24 forfattere av denne artikkelen] (2023). The CryoGrid community model (version 1.0) - a multi-physics toolbox for climate-driven simulations in the terrestrial cryosphere. Geoscientific Model Development. ISSN 1991-959X. 16(9), s. 2607–2647. doi: 10.5194/gmd-16-2607-2023. Fulltekst i vitenarkiv Vis sammendrag

  The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice–water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2, and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Different model components, characterized by their process representations and parameterizations, are realized as classes (i.e., objects) in CryoGrid. Standardized communication protocols between these classes ensure that they can be stacked vertically. For example, the CryoGrid community model features several classes with different complexity for the seasonal snow cover, which can be flexibly combined with a range of classes representing subsurface materials, each with their own set of process representations (e.g., soil with and without water balance, glacier ice). We present the CryoGrid architecture as well as the model physics and defining equations for the different model classes, focusing on one-dimensional model configurations which can also interact with external heat and water reservoirs. We illustrate the wide variety of simulation capabilities for a site on Svalbard, with point-scale permafrost simulations using, e.g., different soil freezing characteristics, drainage regimes, and snow representations, as well as simulations for glacier mass balance and a shallow water body. The CryoGrid community model is not intended as a static model framework but aims to provide developers with a flexible platform for efficient model development. In this study, we document both basic and advanced model functionalities to provide a baseline for the future development of novel cryosphere models.

• Peter, Maria; Andersen, Jane Lund; Nixon, Francis Chantel; Etzelmüller, Bernd; Westermann, Sebastian & Fredin, Ola (2023). Near-surface temperatures and potential for frost weathering in blockfields in Norway and Svalbard. Earth Surface Processes and Landforms. ISSN 0197-9337. 48(5), s. 940–955. doi: 10.1002/esp.5528. Fulltekst i vitenarkiv Vis sammendrag

  Blockfields remain enigmatic regarding their origin, internal structure, surface processes, and glaciological implications. In Scandinavia, blockfields are found on high-elevation, low-relief mountains (plateaus) across the Arctic and Subarctic. In this study, we present a 1D numerical model that uses near-surface temperatures measured between summer 2018 and summer 2020 to calculate frost-cracking intensities (FCI) within the ground column in three different blockfields in Norway and Svalbard. Eighty-nine miniature temperature loggers were distributed on Tron Mountain (1650 m a.s.l.) in Alvdal, Gamlemsveten (780 m a.s.l.) near Ålesund in southwestern Norway and on Platåberget (460 m a.s.l.) near Longyearbyen, Svalbard. We modelled FCI by scaling the time spent in the frost cracking window (between −3 and −8°C) with the temperature gradient and a penalty function for distance to available water. At Tron and Gamlemsveten, ground temperatures never reached the frost cracking window at one third of our sites due to insulation by a thick snow cover in depressions and on the lee sides of summits. The highest FCI (0.05–0.4 K m) are obtained where the subsurface consists of boulders and stones in a matrix of relatively fine sediment (sand, silt, gravel). In contrast, very low FCI (0.003–0.02 K m) were modelled for blocky layers with large air-filled pores because of the low water availability. On Platåberget, all sensors reached the frost-cracking window during the annual temperature cycle, but FCI are extremely low (0.0004–0.15 K m) as water availability is limited due to (i) permafrost and (ii) near-surface temperatures remaining below the frost-cracking window for 3/4 of the year. This indicates that boulder-rich blockfields with air-filled hollows are preserved in very cold climates, whereas warmer, maritime settings with higher availability of fine interstitial material place blockfields in the fast lane for frost weathering.

• Renette, Cas; Aalstad, Kristoffer; Aga, Juditha; Zweigel, Robin Benjamin; Etzelmüller, Bernd & Lilleøren, Karianne Staalesen [Vis alle 8 forfattere av denne artikkelen] (2023). Simulating the effect of subsurface drainage on the thermal regime and ground ice in blocky terrain in Norway. Earth Surface Dynamics. ISSN 2196-6311. 11(1), s. 33–50. doi: 10.5194/esurf-11-33-2023. Fulltekst i vitenarkiv Vis sammendrag

  Ground temperatures in coarse, blocky deposits such as mountain blockfields and rock glaciers have long been observed to be lower in comparison with other (sub)surface material. One of the reasons for this negative temperature anomaly is the lower soil moisture content in blocky terrain, which decreases the duration of the zero curtain in autumn. Here we used the CryoGrid community model to simulate the effect of drainage on the ground thermal regime and ground ice in blocky terrain permafrost at two sites in Norway. The model set-up is based on a one-dimensional model domain and features a surface energy balance, heat conduction and advection, as well as a bucket water scheme with adjustable lateral drainage. We used three idealized subsurface stratigraphies, blocks only, blocks with sediment and sediment only, which can be either drained (i.e. with strong lateral subsurface drainage) or undrained (i.e. without drainage), resulting in six scenarios. The main difference between the three stratigraphies is their ability to retain water against drainage: while the blocks only stratigraphy can only hold small amounts of water, much more water is retained within the sediment phase of the two other stratigraphies, which critically modifies the freeze–thaw behaviour. The simulation results show markedly lower ground temperatures in the blocks only, drained scenario compared to other scenarios, with a negative thermal anomaly of up to 2.2 ∘C. For this scenario, the model can in particular simulate the time evolution of ground ice, with build-up during and after snowmelt and spring and gradual lowering of the ice table in the course of the summer season. The thermal anomaly increases with larger amounts of snowfall, showing that well-drained blocky deposits are less sensitive to insulation by snow than other soils. We simulate stable permafrost conditions at the location of a rock glacier in northern Norway with a mean annual ground surface temperature of 2.0–2.5 ∘C in the blocks only, drained simulations. Finally, transient simulations since 1951 at the rock glacier site (starting with permafrost conditions for all stratigraphies) showed a complete loss of perennial ground ice in the upper 5 m of the ground in the blocks with sediment, drained run; a 1.6 m lowering of the ground ice table in the sediment only, drained run; and only 0.1 m lowering in the blocks only, drained run. The interplay between the subsurface water–ice balance and ground freezing/thawing driven by heat conduction can at least partly explain the occurrence of permafrost in coarse blocky terrain below the elevational limit of permafrost in non-blocky sediments. It is thus important to consider the subsurface water–ice balance in blocky terrain in future efforts in permafrost distribution mapping in mountainous areas. Furthermore, an accurate prediction of the evolution of the ground ice table in a future climate can have implications for slope stability, as well as water resources in arid environments.

• Pirk, Norbert; Aalstad, Kristoffer; Westermann, Sebastian; Vatne, Astrid; van Hove, Alouette & Tallaksen, Lena Merete [Vis alle 8 forfattere av denne artikkelen] (2022). Inferring surface energy fluxes using drone data assimilation in large eddy simulations. Atmospheric Measurement Techniques. ISSN 1867-1381. 15(24), s. 7293–7314. doi: 10.5194/amt-15-7293-2022. Fulltekst i vitenarkiv Vis sammendrag

  Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.

• Chaudhary, Nitin; Zhang, Wenxin; Lamba, Shubhangi & Westermann, Sebastian (2022). Modeling Pan-Arctic Peatland Carbon Dynamics Under Alternative Warming Scenarios. Geophysical Research Letters. ISSN 0094-8276. 49(10). doi: 10.1029/2021GL095276. Fulltekst i vitenarkiv
• Stuenzi, Simone Maria; Kruse, Stefan; Boike, Julia; Herzschuh, Ulrike; Oehme, Alexander & Pestryakova, Luidmila A. [Vis alle 8 forfattere av denne artikkelen] (2022). Thermohydrological Impact of Forest Disturbances on Ecosystem-Protected Permafrost. Journal of Geophysical Research (JGR): Biogeosciences. ISSN 2169-8953. 127(5). doi: 10.1029/2021JG006630. Fulltekst i vitenarkiv
• Smith, Noah D.; Burke, Eleanor J.; Aas, Kjetil Schanke; Althuizen, Inge; Boike, Julia & Christiansen, Casper Tai [Vis alle 13 forfattere av denne artikkelen] (2022). Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography). Geoscientific Model Development. ISSN 1991-959X. 15(9), s. 3603–3639. doi: 10.5194/gmd-15-3603-2022. Fulltekst i vitenarkiv Vis sammendrag

  Microtopography can be a key driver of heterogeneity in the ground thermal and hydrological regime of permafrost landscapes. In turn, this heterogeneity can influence plant communities, methane fluxes, and the initiation of abrupt thaw processes. Here we have implemented a two-tile representation of microtopography in JULES (the Joint UK Land Environment Simulator), where tiles are representative of repeating patterns of elevation difference. Tiles are coupled by lateral flows of water, heat, and redistribution of snow, and a surface water store is added to represent ponding. Simulations are performed of two Siberian polygon sites, (Samoylov and Kytalyk) and two Scandinavian palsa sites (Stordalen and Iškoras). The model represents the observed differences between greater snow depth in hollows vs. raised areas well. The model also improves soil moisture for hollows vs. the non-tiled configuration (“standard JULES”) though the raised tile remains drier than observed. The modelled differences in snow depths and soil moisture between tiles result in the lower tile soil temperatures being warmer for palsa sites, as in reality. However, when comparing the soil temperatures for July at 20 cm depth, the difference in temperature between tiles, or “temperature splitting”, is smaller than observed (3.2 vs. 5.5 ∘C). Polygons display small (0.2 ∘C) to zero temperature splitting, in agreement with observations. Consequently, methane fluxes are near identical (+0 % to 9 %) to those for standard JULES for polygons, although they can be greater than standard JULES for palsa sites (+10 % to 49 %). Through a sensitivity analysis we quantify the relative importance of model processes with respect to soil moisture and temperatures, identifying which parameters result in the greatest uncertainty in modelled temperature. Varying the palsa elevation between 0.5 and 3 m has little effect on modelled soil temperatures, showing that using only two tiles can still be a valid representation of sites with a range of palsa elevations. Mire saturation is heavily dependent on landscape-scale drainage. Lateral conductive fluxes, while small, reduce the temperature splitting by ∼ 1 ∘C and correspond to the order of observed lateral degradation rates in peat plateau regions, indicating possible application in an area-based thaw model.

• Chadburn, Sarah E.; Burke, Eleanor J.; Gallego-Sala, Angela V.; Smith, Noah D.; Bret-Harte, M. Syndonia & Charman, Dan J. [Vis alle 15 forfattere av denne artikkelen] (2022). A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8 accumulate soil) for northern and temperate peatlands. Geoscientific Model Development. ISSN 1991-959X. 15(4), s. 1633–1657. doi: 10.5194/gmd-15-1633-2022. Fulltekst i vitenarkiv
• Etzelmüller, Bernd; Czekirda, Justyna; Magnin, Florence; Duvillard, Pierre-Allain; Ravanel, Ludovic & Malet, Emanuelle [Vis alle 20 forfattere av denne artikkelen] (2022). Permafrost in monitored unstable rock slopes in Norway-New insights from temperature and surface velocity measurements, geophysical surveying, and ground temperature modelling. Earth Surface Dynamics. ISSN 2196-6311. 10(1), s. 97–129. doi: 10.5194/esurf-10-97-2022. Fulltekst i vitenarkiv Vis sammendrag

  The warming and subsequent degradation of mountain permafrost within alpine areas represent an important process influencing the stability of steep slopes and rock faces. The unstable and monitored slopes of Mannen (Møre and Romsdal county, southern Norway) and Gámanjunni-3 (Troms and Finnmark county, northern Norway) were classified as high-risk sites by the Norwegian Geological Survey (NGU). Failure initiation has been suggested to be linked to permafrost degradation, but the detailed permafrost distribution at the sites is unknown. Rock wall (RW) temperature loggers at both sites have measured the thermal regime since 2015, showing mean rock surface temperatures between 2.5 and −1.6 ∘C depending on site and topographic aspect. Between 2016 and 2019 we conducted 2D and 3D electrical resistivity tomography (ERT) surveys on the plateau and directly within the rock wall back scarp of the unstable slopes at both sites. In combination with geophysical laboratory analysis of rock wall samples from both sites, the ERT soundings indicate widespread permafrost areas, especially at Gámanjunni-3. Finally, we conducted 2D thermal modelling to evaluate the potential thermal regime, along with an analysis of available displacement rate measurements based on Global Navigation Satellite System (GNSS) and ground- and satellite-based interferometric synthetic aperture radar (InSAR) methods. Surface air and ground temperatures have increased significantly since ca. 1900 by 1 and 1.5 ∘C, and the highest temperatures have been measured and modelled since 2000 at both study sites. We observed a seasonality of displacement, with increasing velocities during late winter and early spring and the highest velocities in June, probably related to water pressure variations during snowmelt. The displacement rates of Gámanjunni-3 rockslide co-vary with subsurface resistivity and modelled ground temperature. Increased displacement rates seem to be associated with sub-zero ground temperatures and higher ground resistivity. This might be related to the presence of ground ice in fractures and pores close to the melting point, facilitating increased deformation. The study demonstrates and discusses the possible influence of permafrost, at least locally, on the dynamics of large rock slope instabilities

• Qiu, Chunjing; Ciais, Philippe; Zhu, Dan; Guenet, Bertrand; Chang, Jinfeng & Chaudhary, Nitin [Vis alle 33 forfattere av denne artikkelen] (2022). A strong mitigation scenario maintains climate neutrality of northern peatlands. One Earth. ISSN 2590-3330. 5(1), s. 86–97. doi: 10.1016/j.oneear.2021.12.008. Fulltekst i vitenarkiv
• Martin, Leo Celestin Paul; Nitzbon, Jan; Scheer, Johanna; Aas, Kjetil Schanke; Eiken, Trond & Langer, Moritz [Vis alle 9 forfattere av denne artikkelen] (2021). Lateral thermokarst patterns in permafrost peat plateaus in northern Norway. The Cryosphere. ISSN 1994-0416. 15(7), s. 3423–3442. doi: 10.5194/tc-15-3423-2021. Fulltekst i vitenarkiv
• Stuenzi, Simone M.; Boike, Julia; Gadeke, Anne; Herzschuh, Ulrike; Kruse, Stefan & Pestryakova, Luidmila A. [Vis alle 8 forfattere av denne artikkelen] (2021). Sensitivity of ecosystem-protected permafrost under changing boreal forest structures. Environmental Research Letters. ISSN 1748-9326. 16(8). doi: 10.1088/1748-9326/ac153d. Fulltekst i vitenarkiv
• Schneider Von Deimling, Thomas; Lee, Hanna; Ingeman-Nielsen, Thomas; Westermann, Sebastian; Romanovsky, Vladimir & Lamoureux, Scott [Vis alle 13 forfattere av denne artikkelen] (2021). Consequences of permafrost degradation for Arctic infrastructure - Bridging the model gap between regional and engineering scales. The Cryosphere. ISSN 1994-0416. 15(5), s. 2451–2471. doi: 10.5194/tc-15-2451-2021. Fulltekst i vitenarkiv
• Ramage, Justine; Jungsberg, Leneisja; Wang, Shinan; Westermann, Sebastian; Lantuit, Hugues & Heleniak, Timothy (2021). Population living on permafrost in the Arctic. Population and environment. ISSN 0199-0039. 43, s. 22–38. doi: 10.1007/s11111-020-00370-6. Fulltekst i vitenarkiv
• Angelopoulos, Michael; Overduin, Pier Paul; Jenrich, Maren; Nitze, Ingmar; Günther, Frank & Strauss, Jens [Vis alle 12 forfattere av denne artikkelen] (2021). Onshore Thermokarst Primes Subsea Permafrost Degradation. Geophysical Research Letters. ISSN 0094-8276. 48(20). doi: 10.1029/2021GL093881. Fulltekst i vitenarkiv
• Dashtseren, Avirmed; Temuujin, Khurelbaatar; Westermann, Sebastian; Batbold, Altangerel; Amarbayasgalan, Yondon & Battogtokh, Dorjgotov (2021). Spatial and Temporal Variations of Freezing and Thawing Indices From 1960 to 2020 in Mongolia. Frontiers in Earth Science. ISSN 2296-6463. 9. doi: 10.3389/feart.2021.713498. Fulltekst i vitenarkiv
• Schmidt, Juditha; Etzelmüller, Bernd; Schuler, Thomas; Magnin, Florence; Boike, Julia & Langer, Moritz [Vis alle 7 forfattere av denne artikkelen] (2021). Surface temperatures and their influence on the permafrost thermal regime in high-Arctic rock walls on Svalbard. The Cryosphere. ISSN 1994-0416. 15(5), s. 2491–2509. doi: 10.5194/tc-15-2491-2021. Fulltekst i vitenarkiv
• Zweigel, Robin Benjamin; Westermann, Sebastian; Nitzbon, Jan; Langer, M; Boike, Julia & Etzelmüller, Bernd [Vis alle 7 forfattere av denne artikkelen] (2021). Simulating Snow Redistribution and its Effect on Ground Surface Temperature at a High‐Arctic Site on Svalbard. Journal of Geophysical Research (JGR): Earth Surface. ISSN 2169-9003. 126(3). doi: 10.1029/2020JF005673. Fulltekst i vitenarkiv
• Stuenzi, Simone Maria; Boike, Julia; Cable, William; Herzschuh, Ulrike; Kruse, Stefan & Pestryakova, Luidmila A. [Vis alle 10 forfattere av denne artikkelen] (2021). Variability of the surface energy balance in permafrost-underlain boreal forest. Biogeosciences. ISSN 1726-4170. 18(2), s. 343–365. doi: 10.5194/bg-18-343-2021. Fulltekst i vitenarkiv
• Nitzbon, Jan; Langer, Moritz; Martin, Leo; Westermann, Sebastian; Schneider von Deimling, T & Boike, Julia (2021). Effects of multi-scale heterogeneity on the simulated evolution of ice-rich permafrost lowlands under a warming climate. The Cryosphere. ISSN 1994-0416. 15(3), s. 1399–1422. doi: 10.5194/tc-15-1399-2021. Fulltekst i vitenarkiv
• Chaudhary, Nitin; Westermann, Sebastian; Lamba, Shubhangi; Shurpali, Narasinha J.; Sannel, A. Britta K. & Schurgers, Guy [Vis alle 8 forfattere av denne artikkelen] (2020). Modelling past and future peatland carbon dynamics across the pan‐Arctic. Global Change Biology. ISSN 1354-1013. 26(7), s. 4119–4133. doi: 10.1111/gcb.15099. Fulltekst i vitenarkiv
• Angelopoulos, Michael; Overduin, Pier Paul; Westermann, Sebastian; Tronicke, Jens; Strauss, Jens & Schirrmeister, Lutz [Vis alle 11 forfattere av denne artikkelen] (2020). Thermokarst Lake to Lagoon Transitions in Eastern Siberia: Do Submerged Taliks Refreeze? Journal of Geophysical Research (JGR): Earth Surface. ISSN 2169-9003. 125(10). doi: 10.1029/2019JF005424. Fulltekst i vitenarkiv
• Nitzbon, Jan; Westermann, Sebastian; Langer, Moritz; Martin, Leo Celestin Paul; Strauss, Jens & Laboor, Sebastian [Vis alle 7 forfattere av denne artikkelen] (2020). Fast response of cold ice-rich permafrost in northeast Siberia to a warming climate. Nature Communications. ISSN 2041-1723. 11. doi: 10.1038/s41467-020-15725-8. Fulltekst i vitenarkiv
• Sayedi, Sayedeh Sara; Abbott, Benjamin W.; Thornton, Brett F.; Frederick, Jennifer M.; Vonk, Jorien E. & Overduin, Paul [Vis alle 32 forfattere av denne artikkelen] (2020). Subsea permafrost carbon stocks and climate change sensitivity estimated by expert assessment. Environmental Research Letters. ISSN 1748-9326. 15(12). doi: 10.1088/1748-9326/abcc29. Fulltekst i vitenarkiv
• Cai, Lei; Lee, Hanna; Aas, Kjetil Schanke & Westermann, Sebastian (2020). Projecting circum-Arctic excess-ground-ice melt with a sub-grid representation in the Community Land Model. The Cryosphere. ISSN 1994-0416. 14( 12), s. 4611–4626. doi: 10.5194/tc-14-4611-2020. Fulltekst i vitenarkiv Vis sammendrag

  To address the long-standing underrepresentation of the influences of highly variable ground ice content on the trajectory of permafrost conditions simulated in Earth system models under a warming climate, we implement a sub-grid representation of excess ground ice within permafrost soils using the latest version of the Community Land Model (CLM5). Based on the original CLM5 tiling hierarchy, we duplicate the natural vegetated land unit by building extra tiles for up to three cryostratigraphies with different amounts of excess ice for each grid cell. For the same total amount of excess ice, introducing sub-grid variability in excess-ice contents leads to different excess-ice melting rates at the grid level. In addition, there are impacts on permafrost thermal properties and local hydrology with sub-grid representation. We evaluate this new development with single-point simulations at the Lena River delta, Siberia, where three sub-regions with distinctively different excess-ice conditions are observed. A triple-land-unit case accounting for this spatial variability conforms well to previous model studies for the Lena River delta and displays markedly different dynamics of future excess-ice thaw compared to a single-land-unit case initialized with average excess-ice contents. For global simulations, we prescribed a tiling scheme combined with our sub-grid representation to the global permafrost region using presently available circum-Arctic ground ice data. The sub-grid-scale excess ice produces significant melting of excess ice under a warming climate and enhances the representation of sub-grid variability of surface subsidence on a global scale. Our model development makes it possible to portray more details on the permafrost degradation trajectory depending on the sub-grid soil thermal regime and excess-ice melting, which also shows a strong indication that accounting for excess ice is a prerequisite of a reasonable projection of permafrost thaw. The modeled permafrost degradation with sub-grid excess ice follows the pathway that continuous permafrost transforms into discontinuous permafrost before it disappears, including surface subsidence and talik formation, which are highly permafrost-relevant landscape changes excluded from most land models. Our development of sub-grid representation of excess ice demonstrates a way forward to improve the realism of excess-ice melt in global land models, but further developments require substantially improved global observational datasets on both the horizontal and vertical distributions of excess ground ice.

• Chadburn, Sarah E.; Aalto, Tuula; Aurela, Mika; Baldocchi, Dennis; Biasi, Christina & Boike, Julia [Vis alle 25 forfattere av denne artikkelen] (2020). Modeled Microbial Dynamics Explain the Apparent Temperature Sensitivity of Wetland Methane Emissions. Global Biogeochemical Cycles. ISSN 0886-6236. 34( 11). doi: 10.1029/2020GB006678. Fulltekst i vitenarkiv Vis sammendrag

  Methane emissions from natural wetlands tend to increase with temperature and therefore may lead to a positive feedback under future climate change. However, their temperature response includes confounding factors and appears to differ on different time scales. Observed methane emissions depend strongly on temperature on a seasonal basis, but if the annual mean emissions are compared between sites, there is only a small temperature effect. We hypothesize that microbial dynamics are a major driver of the seasonal cycle and that they can explain this apparent discrepancy. We introduce a relatively simple model of methanogenic growth and dormancy into a wetland methane scheme that is used in an Earth system model. We show that this addition is sufficient to reproduce the observed seasonal dynamics of methane emissions in fully saturated wetland sites, at the same time as reproducing the annual mean emissions. We find that a more complex scheme used in recent Earth system models does not add predictive power. The sites used span a range of climatic conditions, with the majority in high latitudes. The difference in apparent temperature sensitivity seasonally versus spatially cannot be recreated by the non-microbial schemes tested. We therefore conclude that microbial dynamics are a strong candidate to be driving the seasonal cycle of wetland methane emissions. We quantify longer-term temperature sensitivity using this scheme and show that it gives approximately a 12% increase in emissions per degree of warming globally. This is in addition to any hydrological changes, which could also impact future methane emissions.

• Pastorello, Gilberto; Trotta, Carlo; Canfora, Eleonora; Chu, Housen; Christianson, Danielle & Cheah, You-Wei [Vis alle 287 forfattere av denne artikkelen] (2020). The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Scientific Data. ISSN 2052-4463. 7. doi: 10.1038/s41597-020-0534-3. Fulltekst i vitenarkiv Vis sammendrag

  The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

• Etzelmüller, Bernd; Patton, Henry; Schomacker, Anders; Czekirda, Justyna; Girod, Luc Maurice Ramuntcho & Hubbard, Alun Lloyd [Vis alle 8 forfattere av denne artikkelen] (2020). Icelandic permafrost dynamics since the Last Glacial Maximum – model results and geomorphological implications. Quaternary Science Reviews. ISSN 0277-3791. 233:106236. doi: 10.1016/j.quascirev.2020.106236. Fulltekst i vitenarkiv Vis sammendrag

  Iceland’s periglacial realm is one of the most dynamic on the planet, with active geomorphologicalprocesses and high weathering rates of young bedrock resulting in high sediment yields and ongoingmass movement. Permafrost is discontinuous in Iceland’s highlands and mountains over c. 800 m a.s.l,and sporadic in palsa mires in the central highlands. During the late Pleistocene and Holocene, Iceland’speriglacial environment varied considerably in time and space, dominated by glacialfluctuations andperiglacial processes. To evaluate the dynamics of permafrost in Iceland since the last deglaciation, weuse the output of a coupled climate/ice sheet model to force a transient permafrost model (CryoGRID 2)from the Last Glacial Maximum (LGM) through to the present. Wefind that permafrost was widespreadacross the deglaciated areas of western, northern and eastern Iceland after the LGM, and that up to 20% ofIceland’s terrestrial area was underlain by permafrost throughout the late Pleistocene. This influencedgeomorphological processes and landform generation: the early collapse of the marine-based ice sheettogether with the aggradation of permafrost in these zones initiated the formation of abundant and nowrelict rock glaciers across coastal margins. Permafrost degraded rapidly after the Younger Dryas, with amarked impact on slope stability. Permafrost that formed during the Little Ice Age is again thawingrapidly, and an escalation in slope failure and mass-movement might be currently underway. Our studydemonstrates that large regions of Iceland have been underlain by permafrost for millennia, facilitatinglandform development and influencing the stability of steep slopes

• Obu, Jaroslav; Westermann, Sebastian; Vieira, Gonçalo; Abramov, Andrey; Balks, Megan Ruby & Bartsch, Annett [Vis alle 9 forfattere av denne artikkelen] (2020). Pan-Antarctic map of near-surface permafrost temperatures at 1 km2 scale. The Cryosphere. ISSN 1994-0416. 14(2), s. 497–519. doi: 10.5194/tc-14-497-2020. Fulltekst i vitenarkiv Vis sammendrag

  Permafrost is present within almost all of the Antarctic's ice-free areas, but little is known about spatial variations in permafrost temperatures except for a few areas with established ground temperature measurements. We modelled a temperature at the top of the permafrost (TTOP) for all the ice-free areas of the Antarctic mainland and Antarctic islands at 1 km2 resolution during 2000–2017. The model was driven by remotely sensed land surface temperatures and downscaled ERA-Interim climate reanalysis data, and subgrid permafrost variability was simulated by variable snow cover. The results were validated against in situ-measured ground temperatures from 40 permafrost boreholes, and the resulting root-mean-square error was 1.9 ∘C. The lowest near-surface permafrost temperature of −36 ∘C was modelled at Mount Markham in the Queen Elizabeth Range in the Transantarctic Mountains. This is the lowest permafrost temperature on Earth, according to global-scale modelling results. The temperatures were most commonly modelled between −23 and −18 ∘C for mountainous areas rising above the Antarctic Ice Sheet and between −14 and −8 ∘C for coastal areas. The model performance was good where snow conditions were modelled realistically, but errors of up to 4 ∘C occurred at sites with strong wind-driven redistribution of snow.

• Aalstad, Kristoffer; Westermann, Sebastian & Bertino, Laurent (2020). Evaluating satellite retrieved fractional snow-covered area at a high-Arctic site using terrestrial photography. Remote Sensing of Environment. ISSN 0034-4257. 239. doi: 10.1016/j.rse.2019.111618. Fulltekst i vitenarkiv Vis sammendrag

  The seasonal snow-cover is one of the most rapidly varying natural surface features on Earth. It strongly modulates the terrestrial water, energy, and carbon balance. Fractional snow-covered area (fSCA) is an essential snow variable that can be retrieved from multispectral satellite imagery. In this study, we evaluate fSCA retrievals from multiple sensors that are currently in polar orbit: the operational land imager (OLI) on-board Landsat 8, the multispectral instrument (MSI) on-board the Sentinel-2 satellites, and the moderate resolution imaging spectroradiometer (MODIS) on-board Terra and Aqua. We consider several retrieval algorithms that fall into three classes: thresholding of the normalized difference snow index (NDSI), regression on the NDSI, and spectral unmixing. We conduct the evaluation at a high-Arctic site in Svalbard, Norway, by comparing satellite retrieved fSCA to coincident high-resolution snow-cover maps obtained from a terrestrial automatic camera system. For the lower resolution MODIS retrievals, the regression-based retrievals outperformed the unmixing-based retrievals for all metrics but the bias. For the higher resolution sensors (OLI and MSI), retrievals based on NDSI thresholding overestimated the fSCA due to the mixed pixel problem whereas spectral unmixing retrievals provided the most reliable estimates across the board. We therefore encourage the operationalization of spectral unmixing retrievals of fSCA from both OLI and MSI.

• Myhra, Kristin Sæterdal; Westermann, Sebastian & Etzelmüller, Bernd (2019). Modelling conductive heat flow between steep rock walls and talus slopes–thermal processes and geomorphological implications. Frontiers in Earth Science. ISSN 2296-6463. 7, s. 1–14. doi: 10.3389/feart.2019.00192. Fulltekst i vitenarkiv
• Magnin, Florence; Etzelmüller, Bernd; Westermann, Sebastian; Isaksen, Ketil; Hilger, Paula & Hermanns, Reginald (2019). Permafrost distribution in steep rock slopes in Norway: measurements, statistical modelling and implications for geomorphological processes . Earth Surface Dynamics. ISSN 2196-6311. 7(4), s. 1019–1040. doi: 10.5194/esurf-7-1019-2019. Fulltekst i vitenarkiv
• Fiddes, Joel; Aalstad, Kristoffer & Westermann, Sebastian (2019). Hyper-resolution ensemble-based snow reanalysis in mountain regions using clustering. Hydrology and Earth System Sciences (HESS). ISSN 1027-5606. 23(11), s. 4717–4736. doi: 10.5194/hess-23-4717-2019. Fulltekst i vitenarkiv Vis sammendrag

  Spatial variability in high-relief landscapes is immense, and grid-based models cannot be run at spatial resolutions to explicitly represent important physical processes. This hampers the assessment of the current and future evolution of important issues such as water availability or mass movement hazards. Here, we present a new processing chain that couples an efficient sub-grid method with a downscaling tool and a data assimilation method with the purpose of improving numerical simulation of surface processes at multiple spatial and temporal scales in ungauged basins. The novelty of the approach is that while we add 1–2 orders of magnitude of computational cost due to ensemble simulations, we save 4–5 orders of magnitude over explicitly simulating a high-resolution grid. This approach makes data assimilation at large spatio-temporal scales feasible. In addition, this approach utilizes only freely available global datasets and is therefore able to run globally. We demonstrate marked improvements in estimating snow height and snow water equivalent at various scales using this approach that assimilates retrievals from a MODIS snow cover product. We propose that this as a suitable method for a wide variety of operational and research applications where surface models need to be run at large scales with sparse to non-existent ground observations and with the flexibility to assimilate diverse variables retrieved by Earth observation missions.

• Martin, Leo Celestin Paul; Nitzbon, Jan; Aas, Kjetil Schanke; Etzelmüller, Bernd; Kristiansen, Håvard & Westermann, Sebastian (2019). Stability Conditions of Peat Plateaus and Palsas in Northern Norway. Journal of Geophysical Research (JGR): Earth Surface. ISSN 2169-9003. 124(3), s. 705–719. doi: 10.1029/2018JF004945. Fulltekst i vitenarkiv
• Overduin, PP; Schneider von Deimling, T; Miesner, F; Grigoriev, Mikhail N; Ruppel, Carolyn & Vasiliev, Alexander [Vis alle 9 forfattere av denne artikkelen] (2019). Submarine Permafrost Map in the Arctic Modeled Using 1-D Transient Heat Flux (SuPerMAP). Journal of Geophysical Research (JGR): Oceans. ISSN 2169-9275. 124(6), s. 3490–3507. doi: 10.1029/2018JC014675.
• Nitzbon, Jan; Langer, Moritz; Westermann, Sebastian; Martin, Leo Celestin Paul; Aas, Kjetil Schanke & Boike, Julia (2019). Pathways of ice-wedge degradation in polygonal tundra under different hydrological conditions. The Cryosphere. ISSN 1994-0416. 13(4), s. 1089–1123. doi: 10.5194/tc-13-1089-2019. Fulltekst i vitenarkiv
• Angelopoulos, Michael; Westermann, Sebastian; Overduin, Paul; Faguet, Alexey; Olenchenko, Vladimir & Grosse, Guido [Vis alle 7 forfattere av denne artikkelen] (2019). Heat and Salt Flow in Subsea Permafrost Modeled with CryoGRID2. Journal of Geophysical Research (JGR): Earth Surface. ISSN 2169-9003. 124, s. 920–937. doi: 10.1029/2018JF004823. Fulltekst i vitenarkiv
• Zwieback, Simon; Westermann, Sebastian; Langer, Moritz; Boike, Julia; Marsh, Philip & Berg, Aaron (2019). Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture. Water Resources Research. ISSN 0043-1397. 55(3), s. 1814–1832. doi: 10.1029/2018WR023247.
• Karjalainen, Olli; Aalto, Juha; Luoto, Miska; Westermann, Sebastian; Romanovsky, Vladimir E & Nelson, Frederick E. [Vis alle 8 forfattere av denne artikkelen] (2019). Data Descriptor: Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments. Scientific Data. ISSN 2052-4463. 6. doi: 10.1038/sdata.2019.37. Fulltekst i vitenarkiv
• Czekirda, Justyna; Westermann, Sebastian; Etzelmüller, Bernd & Jóhannesson, Tómas (2019). Transient Modelling of Permafrost Distribution in Iceland. Frontiers in Earth Science. ISSN 2296-6463. 7(130). doi: 10.3389/feart.2019.00130. Fulltekst i vitenarkiv
• Obu, Jaroslav; Westermann, Sebastian; Bartsch, Annett; Berdnikov, Nikolai M.; Christiansen, Hanne H & Dashtseren, Avirmed [Vis alle 21 forfattere av denne artikkelen] (2019). Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale. Earth-Science Reviews. ISSN 0012-8252. 193, s. 299–316. doi: 10.1016/j.earscirev.2019.04.023. Fulltekst i vitenarkiv

Se alle arbeider i Cristin

• Filhol, Simon; Vasile, Mirela; Sîrbu, Flavius; Onaca, Alexandru; Etzelmüller, Bernd & Westermann, Sebastian (2023). Climate Downscaling in the Southern Carpathians for Climate Analysis and Permafrost Conditions Change (1950-2020).
• Marthinsen, Erik; Thompson, Rona Louise; Pisso, Ignacio; Westermann, Sebastian; Müller, Jurek & Sasakawa, Motoki [Vis alle 7 forfattere av denne artikkelen] (2023). Top-down estimate of methane fluxes in Siberia in 2020.
• Schmidt, Louise Steffensen; Schuler, Thomas Vikhamar & Westermann, Sebastian (2023). Towards an interdisciplinary information platform displaying the state of the cryosphere on Svalbard.
• Bender, Esther Karin; Debolskiy, Matvey V.; Steinert, Norman; Lambert, M; Aas, Kjetil Schanke & Westermann, Sebastian [Vis alle 7 forfattere av denne artikkelen] (2023). Modeling permafrost landscape evolution and greenhouse gas emissions from rapid thawing of ground ice with a new subgrid permafrost representation in CLM5.
• Steinert, Norman; Burke, Eleanor J.; Debolskiy, Matvey V.; Lee, Hanna & Westermann, Sebastian (2023). Impact of different permafrost definitions on the interpretation of modeling results on different scales.
• Nitzbon, Jan; von Deimling, Thomas Schneider; Chadburn, Sarah E.; Grosse, Guido; Laboor, Sebastian & Lee, Hanna [Vis alle 10 forfattere av denne artikkelen] (2023). Is Arctic Permafrost a Climate Tipping Element? – Potentials for Rapid Permafrost Loss Across Spatial Scales.
• Aga, Juditha; Westermann, Sebastian; Landgren, Oskar Andreas; Willmes, Clarissa & Sinitsyn, Anatoly (2023). Cultural heritage in a changing climate: The crucial role of snow management and the influence of warming permafrost on historical buildings in Ny-Ålesund. I et al., - (Red.), Svalbard Science Conference 2023. Book of Abstracts . SSC . ISSN 0-000-00001-9.
• Aga, Juditha; Westermann, Sebastian; Landgren, Oskar Andreas; Willmes, Clarissa & Sinitsyn, Anatoly (2023). Cultural heritage in a changing climate. I et al., - (Red.), Svalbard Science Conference 2023. Book of Abstracts . SSC . ISSN 0-000-00001-9.
• Sinitsyn, Anatoly; Aga, Juditha; Arlov, Thor Bjørn; Bekele, Yared Worku; Seljelv, Ingalill Johansen & Landgren, Oskar Andreas [Vis alle 13 forfattere av denne artikkelen] (2023). Polar Climate and Cultural Heritage: outline of the PCCH-Arctic project and first results. I et al., - (Red.), Svalbard Science Conference 2023. Book of Abstracts . SSC . ISSN 0-000-00001-9.
• Schmidt, Louise Steffensen; Schuler, Thomas; Westermann, Sebastian & Thomas, Erin E. (2022). Climatic mass balance simulations of glaciers in the Russian Arctic (Novaya Zemlya and Franz Josef Land), 1991-2021.
• Schmidt, Louise Steffensen; Thomas, Erin E.; Westermann, Sebastian & Schuler, Thomas (2022). Climatic mass balance simulations of glaciers in the Russian Arctic (Novaya Zemlya and Franz Josef Land), 1991-2021.
• Knutson, Jacqueline; Clayer, Francois; Dörsch, Peter; Westermann, Sebastian & de Wit, Heleen (2022). Investigating hydrology and carbon cycling connections in peatland permafrost, northern Norway.
• Sinitsyn, Anatoly; Westermann, Sebastian; Arlov, Thor Bjørn; Landgren, Oskar Andreas; Meyer, A. & Lutz, J. [Vis alle 8 forfattere av denne artikkelen] (2022). PCCH-Arctic – Polar Climate and Cultural Heritage – Preservation and Restoration Management.
• Sinitsyn, Anatoly; Flyen, Anne Cathrine; Mattsson, Johan & Westermann, Sebastian (2022). Taubanebukkene – de vaklende kjempene . www.sintef.no.
• Sinitsyn, Anatoly; Flyen, Anne Cathrine; Mattsson, Johan & Westermann, Sebastian (2022). Gruvehistorien i Longyearbyen sliter med klimaendringene. blogg.forskning.no.
• Sinitsyn, Anatoly; Sand, Gunnar; Arlov, Thor Bjørn; Landgren, Oskar Andreas & Westermann, Sebastian (2022). Kan vi redde Taubanestasjonen i Hiorthhamn? Svalbardposten.
• Pastorello, Gilberto; Trotta, Carlo; Canfora, Eleonora; Chu, Housen; Christianson, Danielle & Cheah, You-Wei [Vis alle 288 forfattere av denne artikkelen] (2021). Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data (Scientific Data, (2020), 7, 1, (225), 10.1038/s41597-020-0534-3). Scientific Data. ISSN 2052-4463. 8(1). doi: 10.1038/s41597-021-00851-9.
• Salzano, Roberto; Aalstad, Kristoffer; Boldrini, Enrico; Gallet, Jean-Charles; Kepski, Daniel & Luks, Bartlomiej [Vis alle 9 forfattere av denne artikkelen] (2021). Terrestrial photography applications on snow cover in Svalbard (PASSES), The State of Environmental Science in Svalbard. Svalbard Integrated Arctic Earth Observing System. ISSN 978-82-93871-00-2. s. 236–251. doi: 10.5281/zenodo.4294084.
• Salzano, Roberto; Aalstad, Kristoffer; Boldrini, Enrico; Gallet, Jean-Charles; Kȩpski, Daniel & Luks, Bartlomiej [Vis alle 9 forfattere av denne artikkelen] (2021). Terrestrial photography applications on snow cover in Svalbard (PASSES), The State of Environmental Science in Svalbard. Svalbard Integrated Arctic Earth Observing System. ISSN 978-82-93871-00-2. s. 236–251. doi: 10.5281/zenodo.4294084. Vis sammendrag

  Ground-based observations are critical requirements for many disciplines that are trying to monitor climate change in a remote environment such as the Svalbard archipelago. This overview of cameras operating in Svalbard has been compiled by searching for specific applications that monitor the snow cover and by collecting information about images that can be accessed on the internet, including those not solely dedicated to cryospheric research. The survey identified 43 cameras operating in the region that are managed by research institutions and private companies. These cameras include facilities operated by different nationalities. The datasets vary, but the feasibility of using them to determine fractional snow cover is generally limited. Identifying the key metadata necessary to survey the available devices revealed problems and knowledge gaps that prevent using the full potential of terrestrial photography networks in Svalbard.

• Aalstad, Kristoffer; Alonso-Gonzalez, Esteban; Bazilova, Varvara; Bertino, Laurent; Fiddes, Joel & Filhol, Simon [Vis alle 9 forfattere av denne artikkelen] (2021). Unmixing satellite imagery using data assimilation to map snow and albedo.
• Aalstad, Kristoffer; Alonso-Gonzalez, Esteban; Bertino, Laurent; Fiddes, Joel; van Hove, Alouette & Pirk, Norbert [Vis alle 8 forfattere av denne artikkelen] (2021). Learning from Earth observations using data assimilation.
• Aalstad, Kristoffer; Westermann, Sebastian; Pirk, Norbert; Fiddes, Joel & Bertino, Laurent (2021). Retrieving fractional snow-covered area from optical satellites using data assimilation. Vis sammendrag

  Mapping from noisy observations to the latent states that may have generated them falls under the umbrella of inverse problems. These problems are abundant in Earth system science since our uncertain mechanistic models need to be fully specified while the system is only partially and imperfectly observed. Combined with a steadily growing observing system, this abundance has fueled the development of probabilistic Data Assimilation (DA) schemes that use Bayesian inference to fuse uncertain information from models and observations. Widely used applications of DA include the production of global atmospheric reanalyses and initializing numerical weather predictions. At the same time, the added value that DA can bring to remote sensing as a generalized framework for building retrieval algorithms remains largely untapped. In our contribution, we demonstrate the potential of data assimilation in the task of retrieving fractional snow-covered area (fSCA) from multispectral satellite imagery from moderate (MODIS) and higher (Sentinel-2 MSI, Landsat 8 OLI) optical sensors. In this analysis, we build on our previous work by focusing on the Bayelva catchment near Ny-Ålesund we have access to independent high-quality validation data obtained from terrestrial photography. We show how the general problem of linear spectral unmixing that is widely used for land cover classification can be recast as a Bayesian inverse problem. This can then be readily solved using ensemble-based data assimilation schemes, where we test both vanilla and sophisticated flavors of the particle filter and the ensemble Kalman filter, as well as Markov chain Monte Carlo benchmarks. By solving the problem in a transformed parameter space, the physical constraints of spectral unmixing are satisfied while reducing the need for ad hocery. The Bayesian data assimilation fSCA retrieval approach lets us deal with ill-posedness, incorporate physical knowledge, and account for uncertainty in the observed reflectances. It performs favorably compared to widely used techniques for fSCA retrieval such as thresholding of the NDSI, regression on the NDSI, and classical (non-negative least squares) spectral unmixing. This method is also much more scalable than classical unmixing since iterations are pre-determined and can fully exploit vectorization. Furthermore, it does not require any tuning on in-situ observations and it can also be used to solve the endmember selection problem using the concept of model evidence. Crucially, the retrieved fSCA includes dynamic uncertainty estimates that are required for satellite retrievals to be of any use in dynamic data assimilation frameworks. We envisage further validation by leveraging the network of terrestrial cameras operated by our partners in the PASSES consortium (Salzano et al., 2021; SESS Report 2021, Ch. 10). Our aim is to exploit these satellite retrievals in our ongoing efforts to produce tailored high resolution permafrost and snow reanalyses in cold regions, including Svalbard. At the same time, the approach outlined here could also be modified to retrieve surface albedo and (sub-pixel) land cover globally with even broader implications to Earth system science.

• Aalstad, Kristoffer; Alonso-Gonzalez, Esteban; Bazilova, Varvara; Bertino, Laurent; Fiddes, Joel & Pirk, Norbert [Vis alle 7 forfattere av denne artikkelen] (2021). Leveraging emerging Earth observations using data assimilation. Vis sammendrag

  The task of mapping from noisy observations to the states that (given a forward model) may have generated them falls under the umbrella of inverse problems. These problems are abundant in Earth system science since our uncertain mechanistic models need to be fully specified while the system is only partially and imperfectly observed. This abundance has, combined with a steadily growing observing system, fueled the development of probabilistic Data Assimilation (DA) schemes that use Bayesian inference to fuse uncertain information from models and observations. Notable operational applications of DA include the production of global atmospheric reanalyses and initializing numerical weather predictions. Perhaps less appreciated is the added value that DA can bring to Earth Observations (EO) as a generalized framework for building retrieval algorithms. In our work we present two completely different inverse problems that show how DA can help us to make the most out of emerging EO. The first problem is snowpack reconstruction where we constrain snow models using highly informative observations of the dynamics of snow cover depletion retrieved using satellite remote sensing. We provide examples assimilating retrievals from moderate (MODIS) and higher resolution (Landsat, Sentinel-2, PlanetScope cubesats) optical sensors as well as from all-weather radar data (Sentinel-1) in the Californian Sierra Nevada, Svalbard, Finse, the Pyrenees, the Swiss Alps, and Lebanon. This method is being developed to build tailored snow and permafrost reanalysis frameworks that lead to improved global cryospheric mapping capabilities and provide new benchmarks for Earth system models. The second problem is flux inversion where we seek to infer surface fluxes of carbon, water, and heat using a drone swarm that provides distributed measurements of temperature, gas concentrations, and wind in the atmospheric boundary layer. To achieve this, we assimilate drone data into various boundary layer models, building up complexity from analytical flux-profile relationships based on the widely used Monin-Obukhov Similarity Theory to turbulence resolving large eddy simulations. Through flux inversion with the latter the hope is that we will be able to map fluxes in highly heterogeneous landscapes at the scale of Earth system models (10 km). This is not possible with existing methods like eddy covariance and can thereby shed new light on the role of flux heterogeneities in land-atmosphere coupling. When solving these problems we test various probabilistic DA schemes including variants of the ensemble Kalman filter, the particle filter, and Markov chain Monte Carlo. These schemes have been adapted to our problems by casting them as smoothers that condition the model on future observations, rather than as sequential filters, which crucially allows information to propagate backwards in time. We also emphasize how we can use DA to move beyond the usual first level of inference where we “fit” our model to data, up to the second level of inference where we can compare different competing model structures and parametrizations using the model evidence framework.

• Aalstad, Kristoffer; Fiddes, Joel; Martin, Leo Celestin Paul; Alonso-Gonzalez, Esteban; Yilmaz, Yeliz A. & Pirk, Norbert [Vis alle 7 forfattere av denne artikkelen] (2021). Workshop on downscaling with TopoSCALE for cryospheric applications. Vis sammendrag

  Meteorological forcing data is a crucial ingredient when modeling the past, present, and future state of the cryosphere. At the same time, cold regions (i.e. the high elevations and/or latitudes of our planet) where most of the cryosphere is found are typically remote with a very low density of in-situ observations. The few meteorological stations that do exist are typically quite unrepresentative due to the often extreme surface heterogeneity and complex terrain in these regions. This makes empirical-statistical and geostatistical downscaling techniques that rely heavily on station data somewhat impractical for cryospheric applications. On the other side of the scale, we have dynamical downscaling techniques that rely on using sophisticated regional climate models to downscale historical global reanalysis data or projections from global climate models. Although these are not as dependent on local observations in that they are able to mechanistically model the state of the atmosphere, they are prohibitively expensive to run at the decadal timescales and hillslope (1 km - 100 m) spatial scale that is often sought in cryospheric applications. In this workshop, we will provide an overview of various downscaling techniques and introduce the topography-based downscaling routine TopoSCALE as well as its many applications and downstream methods listed below. TopoSCALE was developed to provide a computationally feasible technique for generating hourly hillslope scale atmospheric forcing for cryospheric modeling from global reanalysis data or other atmospheric model outputs, without the need for in-situ data. It relies heavily on topographic parameters derived from digital elevation models to be able to scale the input atmospheric forcing to the local topography. It has been tested quite extensively in a variety of environments, including: the Swiss Alps, Svalbard, the California Sierra Nevada, and High Mountain Asia. TopoSCALE is also being used as part of ongoing permafrost reanalysis efforts in the ESA Permafrost_CCI project. The scheme can be coupled to a clustering framework (TopoSUB) which can speed up distributed simulations by orders of magnitude compared to the more traditional gridded approach to land surface modeling. TopoSCALE can also be used together with bias-correction techniques to help downscale future regional climate projections to the hillslope scale with applications to cryospheric climate impact studies. Recent and ongoing applications of TopoSCALE together with snow data assimilation have been particularly fruitful in being able to handle biases in solid precipitation, which has been one of the most challenging problems for downscaling in cryospheric applications. Importantly, TopoSCALE lets modellers shift limited computational resources away from the downscaling exercise to probing uncertainties through ensemble simulations and constraining these with Earth observations.

• Althuizen, Inge; Christiansen, Casper Tai; Michelsen, Anders; Dörsch, Peter; Kjær, Sigrid Trier & Westermann, Sebastian [Vis alle 8 forfattere av denne artikkelen] (2021). Annual ecosystem carbon budgets across an abrupt permafrost thaw gradient in Northern Norway .
• Althuizen, Inge; Christiansen, Casper Tai; Michelsen, Anders; Westermann, Sebastian; Pirk, Norbert & Risk, David [Vis alle 7 forfattere av denne artikkelen] (2021). Annual ecosystem carbon budgets across an abrupt permafrost thaw gradient in Northern Norway .
• Althuizen, Inge; Christiansen, Casper Tai; Dörsch, Peter; Kjær, Sigrid Trier; Michelsen, Anders & Risk, David [Vis alle 8 forfattere av denne artikkelen] (2021). Abrupt thaw enhances annual global warming potential of an actively degrading permafrost peatland.
• Kjær, Sigrid Trier; Nedkvitne, Nora; Westermann, Sebastian; Althuizen, Inge & Dörsch, Peter (2021). Carbon degradation in Subarctic organic permafrost (peat plateaus) after thawing – what constraints CO2 and CH4 production?
• Boike, Julia; Chadburn, Sarah; Martin, Julia; Zwieback, Simon; Althuizen, Inge & Anselm, Norbert [Vis alle 18 forfattere av denne artikkelen] (2021). Standardized monitoring of permafrost thaw: a user-friendly, multiparameter protocol. Arctic Science. ISSN 2368-7460. 8(1). doi: 10.1139/as-2021-0007. Fulltekst i vitenarkiv
• Bryn, Anders; Dalen, Thea Grobstok; Finne, Eirik Aasmo; Heiberg, Hanne; Keetz, Lasse Torben & Nilsen, Irene Brox [Vis alle 30 forfattere av denne artikkelen] (2021). Natur i endring - samspillet mellom klima og økosystemene.
• Althuizen, Inge; Christiansen, Casper Tai; Michelsen, Anders; Pirk, Norbert; Risk, David & Westermann, Sebastian [Vis alle 7 forfattere av denne artikkelen] (2020). Annual ecosystem carbon budgets across an abrupt permafrost thaw gradient in Northern Norway .
• Althuizen, Inge; Christiansen, Casper Tai; Michelsen, Anders; Pirk, Norbert; Risk, David & Westermann, Sebastian [Vis alle 7 forfattere av denne artikkelen] (2020). Annual ecosystem carbon budgets across an abrupt permafrost thaw gradient in Northern Norway .
• Aalstad, Kristoffer & Westermann, Sebastian (2020). ACS_Bayelva_class: 302 high-resolution snow cover maps covering the 2012-2017 snowmelt seasons in the Bayelva catchment (Svalbard, Norway). Vis sammendrag

  The ACS_Bayelva_class dataset contains 302 high-resolution binary snow cover images that were obtained by classifying orthrorectified photographs of a 1.77 km^2 area of interest in the Bayelva catchment. This catchment is close to Ny-Ålesund, the northernmost permanent civilian settlement in the world and a major hub for polar research, in the Norwegian high-Arctic Svalbard archipelago. The imagery has a (roughly) daily temporal resolution and a ground sampling distance (pixel spacing) of 0.5 m. The dataset spans 6 snowmelt seasons, covering the months May-August for the period 2012-2017. The orthophotos were obtained by processing oblique time-lapse photographs taken by a terrestiral automatic camera system (ACS) mounted at 562 m a.s.l. near the summit of Scheteligfjellet (719 m a.s.l.) a few kilometers west of Ny-Ålesund. The orthophotos were manually classified into binary snow cover images (0=no snow, 1=snow) by iteratively selecting a (visually) optimal threshold on the intensity in the blue band for each image. More details are provided in the study of Aalstad et al. (2020) [a copy is available in this repository] where this dataset was created. The ACS was maintained by scientists from the group of Sebastian Westermann at the Section for Physical Geography and Hydrology in the Department of Geosciences at the University of Oslo, Oslo, Norway.

• Aalstad, Kristoffer; Westermann, Sebastian; Fiddes, Joel; Karsten, Logan; McCreight, James & Bertino, Laurent (2020). Testing ensemble-based snow reanalysis in the Lakes basin using the ASO.
• Aalstad, Kristoffer; Westermann, Sebastian; Pirk, Norbert; Fiddes, Joel; Karsten, Logan & McCreight, James [Vis alle 8 forfattere av denne artikkelen] (2020). Constraining land surface models with emerging observations.
• Aalstad, Kristoffer; Westermann, Sebastian; Fiddes, Joel; McCreight, James & Bertino, Laurent (2020). Retrieving, validating, and assimilating fractional snow-covered area from emerging optical satellites for snow reanalysis. Vis sammendrag

  Accurately estimating the snow water equivalent (SWE) that is stored in the worlds mountains remains a challenging and important unsolved problem. The SWE reconstruction approach, where the remotely sensed seasonal depletion of fractional snow-covered area (fSCA) is used with a snow model to build up the snowpack in reverse, has been used for decades to help tackle this problem retrospectively. Despite some success, this deterministic approach ignores uncertainties in the snow model, the meteorological forcing, and the remotely sensed fSCA. A trade-off has also existed between the desired temporal and spatial resolution of the satellite-retrieved fSCA depletion. Recently, ensemble-based data assimilation techniques that can account for the uncertainties inherent in the reconstruction exercise have allowed for probabilistic snow reanalyses. In addition, new higher resolution optical satellite constellations such as Sentinel-2 and the PlanetScope cubesats have been launched into polar orbit, potentially eliminating the aforementioned trade-off. We combine these two developments, namely ensemble-based data assimilation and the emerging remotely sensed data streams, to see if snow reanalyses can be improved at the hillslope (100 m) scale in complex terrain. As a first step, we develop accurate high-resolution binary snow-cover maps using a terrestrial automatic camera system installed on a mountaintop near Ny-Ålesund (Svalbard, Norway). These maps are used to validate fSCA retrieved from various satellite sensors (MODIS, Sentinel-2 MSI, and Landsat 8 OLI) using algorithms ranging from simple thresholding of the normalized difference snow index to spectral unmixing. Through the validation, we demonstrate that the spectral unmixing technique can obtain unbiased fSCA retrievals at the hillslope scale. Next, we move to the Mammoth Lakes basin in the Californian Sierra Nevada, USA, where we have access to independent validation data retrieved from several Airborne Snow Observatory (ASO) and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flights. Using these airborne retrievals as a reference, we show that fSCA can be retrieved at the hillslope scale with reasonable accuracy at an unprecedented near daily revisit period using a combination of the Landsat, Sentinel-2 MSI, RapidEye, and PlanetScope satellite constellations. In a series of data assimilation experiments we show how the combination of these constellations can lead to significant improvements in hillslope scale snow reanalyses as gauged by various evaluation metrics. Furthermore, it is suggested that an iterative ensemble smoother data assimilation scheme can provide more robust SWE estimates than other smoothers that have previously been proposed for snow reanalysis. We briefly conclude with thoughts as to the current impediments to conducting a global hillslope scale snow reanalysis and propose avenues for further research, such as how snow reanalyses can help in the prediction exercise.

• Christiansen, Casper Tai; Michelsen, Anders; Pirk, Norbert; Risk, David; Westermann, Sebastian & Lee, Hanna (2020). Annual ecosystem carbon budgets across an abrupt permafrost thaw gradient in Northern Norway .
• Christiansen, Casper Tai; Michelsen, Anders; Westermann, Sebastian; Pirk, Norbert; Risk, David & Lee, Hanna (2020). Annual ecosystem carbon budgets across an abrupt permafrost thaw gradient in Northern Norway .
• Bryn, Anders; Dalen, Thea Grobstok; Finne, Eirik Aasmo; Heiberg, Hanne; Nilsen, Irene Brox & Parmentier, Frans-Jan W. [Vis alle 22 forfattere av denne artikkelen] (2020). Natur i endring - en vandreutstilling.
• Aalstad, Kristoffer; Westermann, Sebastian; Fiddes, Joel & Bertino, Laurent (2019). Retrieving the depletion of snow-covered area from multiple optical satellite sensors with applications for SWE reanalysis.
• Cai, Lei; Lee, Hanna; Westermann, Sebastian & Aas, Kjetil Schanke (2019). Development of the subgrid excess ground ice framework in the Community Land Model.
• Etzelmüller, Bernd; Patton, Henry; Schomacker, Anders; Hubbard, Alun Lloyd; Czekirda, Justyna & Westermann, Sebastian (2019). Permafrost dynamics in Iceland between 18 ka BP and today – model results and geomorphological implications. Vis sammendrag

  Periglacial processes and the dynamics of permafrost is a decisive factor for slope stability locally, and for understanding landscape development over longer time scales. Iceland has a highly dynamic landscape because of young bedrock and associated high geomorphological process rates, leading to large material production and frequent gravitational processes in the present periglacial realm. At present, permafrost in Iceland is widespread in mountain settings over c. 800 m a.s.l. and sporadically in palsa mires in the central Highlands. However, during the late Pleistocene and Holocene, the periglacial environment in Iceland must have varied strongly in time and space, with subsequent imprint in the landscape. To evaluate the dynamics of permafrost in Iceland since the onset of the last deglaciation, we used the forcing and output of a 3D, time-integrated ice sheet model to run a transient permafrost model (CryoGRID 2) between the onset of the last deglaciation (c. 18 ka BP) until today. The permafrost model was forced by either modeled sub-glacial temperatures if ice-covered, or air temperatures if the area was deglaciated. The results give insights into the possible age of permafrost in Iceland, distinguish areas with wide-spread paleo-permafrost and let us determine the persistence of permafrost in the different areas. The presentation discusses these results in the light of periglacial processes, landforms and landscape development

• Sinitsyn, Anatoly; Arlov, Thor Bjørn; Westermann, Sebastian & Landgren, Oskar Andreas (2022). Case study objects in PCCH-Arctic Selection criteria, list of the structures, and desktop data collection. SINTEF. ISSN 978-82-14-07527-4.
• Aalstad, Kristoffer; Westermann, Sebastian & Bertino, Laurent (2019). Ensemble-based retrospective analysis of the seasonal snowpack. University of Oslo. ISSN 1501-7710. Vis sammendrag

  This thesis presents a satellite-based modeling framework that can estimate how much snow was stored in the terrain. These estimates can help guide climate analysis and prediction. Accurate quantification of Earth’s snow mass is a long-standing problem to which a solution is direly needed with ongoing climate change. Snow plays an essential role in the climate system and snowmelt is a vital source of freshwater for a quarter of the world’s population. The framework combines satellite imagery and historic weather data to remotely estimate snow mass by leveraging enhanced ensemble-based data assimilation algorithms. The result is a retrospective analysis (reanalysis) of the snow mass that can be obtained for any location on Earth. So far, this framework has been successfully implemented in three different environments: Svalbard, the Californian Sierra Nevada, and the Swiss Alps. In the future, snow reanalyses could be used to train algorithms to predict snow mass in near real time. They may also help validate and subsequently improve climate models. Ultimately this would allow us to make even more informed future projections of the possible fate of the environment that sustains us.

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