Sebastian Westermann

• Schmidt, Juditha; Etzelmüller, Bernd; Schuler, Thomas; Magnin, Florence; Boike, Julia & Langer, Moritz [Show all 7 contributors for this article] (2021). Surface temperatures and their influence on the permafrost thermal regime in high-Arctic rock walls on Svalbard. The Cryosphere. ISSN 1994-0416. 15, p. 2491–2509. doi: 10.5194/tc-15-2491-2021.
• Boike, Julia; Chadburn, Sarah; Martin, Julia; Zwieback, Simon; Althuizen, Inge & Anselm, Norbert [Show all 18 contributors for this article] (2021). Standardized monitoring of permafrost thaw: a user-friendly, multi-parameter protocol. Arctic Science. ISSN 2368-7460. doi: 10.1139/as-2021-0007.
• Zweigel, Robin Benjamin; Westermann, Sebastian; Nitzbon, Jan; Langer, M; Boike, Julia & Etzelmüller, Bernd [Show all 7 contributors for this article] (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.
• Stuenzi, Simone Maria; Boike, Julia; Cable, William; Herzschuh, Ulrike; Kruse, Stefan & Pestryakova, Luidmila A. [Show all 10 contributors for this article] (2021). Variability of the surface energy balance in permafrost-underlain boreal forest. Biogeosciences. ISSN 1726-4170. doi: 10.5194/bg-18-343-2021.
• 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. doi: 10.5194/tc-15-1399-2021.
• Chaudhary, Nitin; Westermann, Sebastian; Lamba, Shubhangi; Shurpali, Narasinha J.; Sannel, A. Britta K. & Schurgers, Guy [Show all 8 contributors for this article] (2020). Modelling past and future peatland carbon dynamics across the pan‐Arctic. Global Change Biology. ISSN 1354-1013. 26(7), p. 4119–4133. doi: 10.1111/gcb.15099. Full text in Research Archive
• Angelopoulos, Michael; Overduin, Pier Paul; Westermann, Sebastian; Tronicke, Jens; Strauss, Jens & Schirrmeister, Lutz [Show all 11 contributors for this article] (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. Full text in Research Archive
• Nitzbon, Jan; Westermann, Sebastian; Langer, Moritz; Martin, Leo Celestin Paul; Strauss, Jens & Laboor, Sebastian [Show all 7 contributors for this article] (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. Full text in Research Archive
• Sayedi, Sayedeh Sara; Abbott, Benjamin W.; Thornton, Brett F.; Frederick, Jennifer M.; Vonk, Jorien E. & Overduin, Paul [Show all 32 contributors for this article] (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. Full text in Research Archive
• 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), p. 4611–4626. doi: 10.5194/tc-14-4611-2020. Full text in Research Archive Show summary

  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 [Show all 25 contributors for this article] (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. Full text in Research Archive
• Pastorello, Gilberto; Trotta, Carlo; Canfora, Eleonora; Chu, Housen; Christianson, Danielle & Cheah, You-Wei [Show all 287 contributors for this article] (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. Full text in Research Archive
• Etzelmüller, Bernd; Patton, Henry; Schomacker, Anders; Czekirda, Justyna; Girod, Luc Maurice Ramuntcho & Hubbard, Alun Lloyd [Show all 8 contributors for this article] (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. Full text in Research Archive
• Obu, Jaroslav; Westermann, Sebastian; Vieira, Gonçalo; Abramov, Andrey; Balks, Megan Ruby & Bartsch, Annett [Show all 9 contributors for this article] (2020). Pan-Antarctic map of near-surface permafrost temperatures at 1 km2 scale. The Cryosphere. ISSN 1994-0416. 14(2), p. 497–519. doi: 10.5194/tc-14-497-2020. Full text in Research Archive
• 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. Full text in Research Archive
• 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, p. 1–14. doi: 10.3389/feart.2019.00192. Full text in Research Archive
• 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), p. 1019–1040. doi: 10.5194/esurf-7-1019-2019. Full text in Research Archive
• Fiddes, Joel; Aalstad, Kristoffer & Westermann, Sebastian (2019). Hyper-resolution ensemble-based snow reanalysis in mountain regions using clustering. Hydrology and Earth System Sciences. ISSN 1027-5606. 23(11), p. 4717–4736. doi: 10.5194/hess-23-4717-2019. Full text in Research Archive
• 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), p. 705–719. doi: 10.1029/2018JF004945. Full text in Research Archive
• Overduin, PP; Schneider von Deimling, T; Miesner, F; Grigoriev, Mikhail N; Ruppel, Carolyn & Vasiliev, Alexander [Show all 9 contributors for this article] (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), p. 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), p. 1089–1123. doi: 10.5194/tc-13-1089-2019. Full text in Research Archive
• Angelopoulos, Michael; Westermann, Sebastian; Overduin, Paul; Faguet, Alexey; Olenchenko, Vladimir & Grosse, Guido [Show all 7 contributors for this article] (2019). Heat and Salt Flow in Subsea Permafrost Modeled with CryoGRID2. Journal of Geophysical Research (JGR): Earth Surface. ISSN 2169-9003. 124, p. 920–937. doi: 10.1029/2018JF004823. Full text in Research Archive
• 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), p. 1814–1832. doi: 10.1029/2018WR023247.
• Karjalainen, Olli; Aalto, Juha; Luoto, Miska; Westermann, Sebastian; Romanovsky, Vladimir E & Nelson, Frederick E. [Show all 8 contributors for this article] (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. Full text in Research Archive
• 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. Full text in Research Archive
• Obu, Jaroslav; Westermann, Sebastian; Bartsch, Annett; Berdnikov, Nikolai M.; Christiansen, Hanne H & Dashtseren, Avirmed [Show all 21 contributors for this article] (2019). Northern Hemisphere permafrost map based on TTOP modelling for 2000–2016 at 1 km2 scale. Earth-Science Reviews. ISSN 0012-8252. 193, p. 299–316. doi: 10.1016/j.earscirev.2019.04.023. Full text in Research Archive
• Aas, Kjetil Schanke; Martin, Leo Celestin Paul; Nitzbon, Jan; Langer, Moritz; Boike, Julia & Lee, Hanna [Show all 8 contributors for this article] (2019). Thaw processes in ice-rich permafrost landscapes represented with laterally coupled tiles in a land surface model. The Cryosphere. ISSN 1994-0416. 13(2), p. 591–609. doi: 10.5194/tc-13-591-2019. Full text in Research Archive
• Hjort, Jan; Karjalainen, Olli; Aalto, Juha; Westermann, Sebastian; Romanovsky, Vladimir E & Nelson, Frederick E. [Show all 8 contributors for this article] (2018). Degrading permafrost puts Arctic infrastructure at risk by mid-century. Nature Communications. ISSN 2041-1723. 9. doi: 10.1038/s41467-018-07557-4. Full text in Research Archive
• Strozzi, Tazio; Antonova, Sofia; Günther, Frank; Mätzler, Eva; Vieira, Gonçalo & Wegmüller, Urs [Show all 8 contributors for this article] (2018). Sentinel-1 SAR interferometry for surface deformation monitoring in low-land permafrost areas. Remote Sensing. ISSN 2072-4292. 10(9). doi: 10.3390/rs10091360. Full text in Research Archive
• Westergaard-Nielsen, Andreas; Karami, Mojtaba; Hansen, Birger Ulf; Westermann, Sebastian & Elberling, Bo (2018). Contrasting temperature trends across the ice-free part of Greenland. Scientific Reports. ISSN 2045-2322. 8. doi: 10.1038/s41598-018-19992-w. Full text in Research Archive
• Kjellman, Sofia E.; Axelsson, Pia E.; Etzelmüller, Bernd; Westermann, Sebastian & Sannel, A. Britta K. (2018). Holocene development of subarctic permafrost peatlands in Finnmark, northern Norway. The Holocene. ISSN 0959-6836. 28(12), p. 1855–1869. doi: 10.1177/0959683618798126. Full text in Research Archive Show summary

  Subarctic permafrost peatlands are important soil organic carbon pools, and improved knowledge about peat properties and peatland sensitivity to past climate change is essential when predicting future response to a warmer climate and associated feedback mechanisms. In this study, Holocene peatland development and permafrost dynamics of four subarctic peat plateaus in Finnmark, northern Norway have been investigated through detailed analyses of plant macrofossils and geochemical properties. Peatland inception occurred around 9800 cal. yr BP and 9200 cal. yr BP at the two continental sites Suossjavri and Iskoras. Younger basal peat ages were found at the two coastal locations Lakselv and Karlebotn, at least partly caused by the time lag between deglaciation and emergence of land by isostatic uplift. Here, peatland development started around 6150 cal. yr BP and 5150 cal. yr BP, respectively. All four peatlands developed as wet fens throughout most of the Holocene. Permafrost aggradation, causing frost heave and a shift in the vegetation assemblage from wet fen to dry bog species, probably did not occur until during the last millennium, ca. 950 cal. yr BP in Karlebotn and ca. 800 cal. yr BP in Iskoras, and before ca. 150 cal. yr BP in Lakselv and ca. 100 cal. yr BP in Suossjavri. In Karlebotn, there are indications of a possible earlier permafrost phase around 2200 cal. yr BP due to climatic cooling at the late Subboreal to early Subatlantic transition. The mean long-term Holocene carbon accumulation rate at all four sites was 12.3 +/- 4.1 gC m-2 yr-1 (+/- SD) and the mean soil organic carbon storage was 97 +/- 46 kgC m-2.

• Boike, Julia; Juszak, Inge; Lange, Stephan; Chadburn, Sarah; Burke, Eleanor & Paul Overduin, Pier [Show all 13 contributors for this article] (2018). A 20-year record (1998-2017) of permafrost, active layer and meteorological conditions at a high Arctic permafrost research site (Bayelva, Spitsbergen). Earth System Science Data. ISSN 1866-3508. 10(1), p. 355–390. doi: 10.5194/essd-10-355-2018. Full text in Research Archive
• Aalstad, Kristoffer; Westermann, Sebastian; Schuler, Thomas; Boike, Julia & Bertino, Laurent (2018). Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites. The Cryosphere. ISSN 1994-0416. 12(1), p. 247–270. doi: 10.5194/tc-12-247-2018. Full text in Research Archive Show summary

  With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain en- vironments. However, estimating the snow water equiva- lent (SWE) is challenging in remote-sensing applications al- ready at medium spatial resolutions of 1km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1km scale by assimilating fractional snow-covered area (fSCA) satel- lite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be log- normally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previ- ous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimi- lation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Reso- lution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79◦ N, Svalbard, Norway) where field measure- ments of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20%, re- spectively, when compared to the prior, yielding RMSEs of 0.01, 0.09m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least nearly matches the performance of other ensemble-based batch smoother schemes with regards to various evaluation metrics. Given the modularity of the method, it could prove valuable for a range of satellite-era hydrometeorological reanalyses.

• Kepski, Daniel; Luks, Bartek; Migala, K.; Wawrzyniak, Tomasz; Westermann, Sebastian & Wojtun, B. (2017). Terrestrial Remote Sensing of Snowmelt in a Diverse High-Arctic Tundra Environment Using Time-Lapse Imagery. Remote Sensing. ISSN 2072-4292. 9(7). doi: 10.3390/rs9070733. Full text in Research Archive
• Trofaier, Anna Maria; Westermann, Sebastian & Bartsch, Annett (2017). Progress in space-borne studies of permafrost for climate science: towards a multi-ECV approach. Remote Sensing of Environment. ISSN 0034-4257. 203, p. 55–70. doi: 10.1016/j.rse.2017.05.021. Full text in Research Archive
• Chadburn, Sarah E.; Burke, Eleanor J.; Cox, Peter M.; Friedlingstein, Pierre; Hugelius, Gustaf & Westermann, Sebastian (2017). An observation-based constraint on permafrost loss as a function of global warming. Nature Climate Change. ISSN 1758-678X. 7(5), p. 340–344. doi: 10.1038/nclimate3262.
• Westermann, Sebastian; Peter, Maria; Langer, Moritz; Schwamborn, Georg; Schirrmeister, Lutz & Etzelmüller, Bernd [Show all 7 contributors for this article] (2017). Transient modeling of the ground thermal conditions using satellite data in the Lena River delta, Siberia. The Cryosphere. ISSN 1994-0416. 11(3), p. 1441–1463. doi: 10.5194/tc-11-1441-2017. Full text in Research Archive
• Chadburn, Sarah E.; Krinner, Gerhard; Porada, Philipp; Bartsch, Annett; Beer, Christian & Belelli Marchesini, Luca [Show all 23 contributors for this article] (2017). Carbon stocks and fluxes in the high latitudes: Using site-level data to evaluate Earth system models. Biogeosciences. ISSN 1726-4170. 14(22), p. 5143–5169. doi: 10.5194/bg-14-5143-2017. Full text in Research Archive
• Magnin, Florence; Westermann, Sebastian; Pogliotti, Paolo; Ravanel, Ludovico; Deline, Phillip & Malet, Eric (2017). Snow control on active layer thickness in steep alpine rock walls (Aiguille du Midi, 3842 m a.s.l., Mont Blanc massif). CATENA. ISSN 0341-8162. 149(Part 2), p. 648–662. doi: 10.1016/j.catena.2016.06.006.
• Gisnås, Kjersti; Etzelmüller, Bernd; Lussana, Cristian; Hjort, Jan; Sannel, Britta & Isaksen, Ketil [Show all 11 contributors for this article] (2017). Permafrost Map for Norway, Sweden and Finland. Permafrost and Periglacial Processes. ISSN 1045-6740. 28(2), p. 359–378. doi: 10.1002/ppp.1922.
• Borge, Amund Frogner; Westermann, Sebastian; Solheim, Ingvild & Etzelmüller, Bernd (2017). Strong degradation of palsas and peat plateaus in northern Norway during the last 60 years. The Cryosphere. ISSN 1994-0416. 11(1), p. 1–16. doi: 10.5194/tc-11-1-2017. Full text in Research Archive Show summary

  Solheim, Ingvild og Etzelmuller, Bernd er ikke (P)-personer. Fikset ms 26/9

• Aas, Kjetil Schanke; Gisnås, Kjersti; Westermann, Sebastian & Berntsen, Terje Koren (2017). A Tiling Approach to Represent Subgrid Snow Variability in Coupled Land Surface–Atmosphere Models. Journal of Hydrometeorology. ISSN 1525-755X. 18(1), p. 49–63. doi: 10.1175/JHM-D-16-0026.1. Full text in Research Archive
• Myhra, Kristin Sæterdal; Westermann, Sebastian & Etzelmuller, Bernd (2017). Modelled Distribution and Temporal Evolution of Permafrost in Steep Rock Walls Along a Latitudinal Transect in Norway by CryoGrid 2D. Permafrost and Periglacial Processes. ISSN 1045-6740. 28(1), p. 172–182. doi: 10.1002/ppp.1884.
• Steiger, Céline; Etzelmüller, Bernd; Westermann, Sebastian & Myhra, Kristin Sæterdal (2016). Modelling the permafrost distribution in steep rock walls in Norway. Norsk Geologisk Tidsskrift. ISSN 0029-196X. 96(4), p. 1–13. doi: 10.17850/njg96-4-04.
• Antonova, Sonya; Duguay, Claude R.; Kääb, Andreas; Heim, Birgit; Langer, Moritz & Westermann, Sebastian [Show all 7 contributors for this article] (2016). Monitoring ice phenology and bedfast ice in lakes of the Lena River Delta using TerraSAR-X backscatter and coherence time series. Remote Sensing. ISSN 2072-4292. 8(11). doi: 10.3390/rs8110903.
• Langer, Moritz; Westermann, Sebastian; Boike, Julia; Kirillin, Sergej; Grosse, Guido & Peng, Shushi [Show all 7 contributors for this article] (2016). Rapid degradation of permafrost underneath waterbodies in tundra landscapes - Toward a representation of thermokarst in land surface models. Journal of Geophysical Research (JGR): Earth Surface. ISSN 2169-9003. 121(12), p. 2446–2470. doi: 10.1002/2016JF003956.
• Wawrzyniak, Tomasz; Osuch, Marzena; Napiorkowski, Jaroslaw & Westermann, Sebastian (2016). Modelling of the thermal regime of permafrost during 1990-2014 in Hornsund, Svalbard. Polish Polar Research. ISSN 0138-0338. 37(2), p. 219–242. doi: 10.1515/popore-2016-0013.
• Bartsch, Annett; Grosse, Guido; Kääb, Andreas; Westermann, Sebastian; Strozzi, Tazio & Wiesmann, Andreas [Show all 10 contributors for this article] (2016). GlobPermafrost - How space-based earth observation supports understanding of permafrost. ESA SP. ISSN 0379-6566. SP-740.
• Gisnås, Kjersti; Westermann, Sebastian; Schuler, Thomas; Melvold, Kjetil & Etzelmüller, Bernd (2016). Small-scale variation of snow in a regional permafrost model. The Cryosphere. ISSN 1994-0416. 10(3), p. 1201–1215. doi: 10.5194/tc-10-1201-2016.
• Westermann, Sebastian; Langer, Moritz; Boike, Julia; Heikenfeld, Max; Peter, Maria & Etzelmuller, Bernd [Show all 7 contributors for this article] (2016). Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3. Geoscientific Model Development. ISSN 1991-959X. 9(2), p. 523–546. doi: 10.5194/gmd-9-523-2016.
• Gisnås, Kjersti; Westermann, Sebastian; Schuler, Thomas; Melvold, Kjetil & Etzelmuller, Bernd (2015). Small-scale variation of snow in a regional permafrost model. The Cryosphere Discussions. ISSN 1994-0432. 9, p. 6661–6696. doi: 10.5194/tcd-9-6661-2015.
• Aas, Kjetil Schanke; Berntsen, Terje Koren; Boike, Julia; Etzelmuller, Bernd; Kristjansson, Jon Egill & Maturilli, Marion [Show all 9 contributors for this article] (2015). A comparison between simulated and observed surface energy balance at the Svalbard Archipelago. Journal of Applied Meteorology and Climatology. ISSN 1558-8424. 54(5), p. 1102–1119. doi: 10.1175/JAMC-D-14-0080.1.

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• Sinitsyn, Anatoly; Sand, Gunnar; Arlov, Thor Bjørn; Landgren, Oskar Andreas & Westermann, Sebastian (2022). Kan vi redde Taubanestasjonen i Hiorthhamn? Svalbardposten.
• Salzano, Roberto; Aalstad, Kristoffer; Boldrini, Enrico; Gallet, Jean-Charles; Kepski, Daniel & Luks, Bartlomiej [Show all 9 contributors for this article] (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. p. 236–251. doi: 10.5281/zenodo.4294084.
• Salzano, Roberto; Aalstad, Kristoffer; Boldrini, Enrico; Gallet, Jean-Charles; Kȩpski, Daniel & Luks, Bartlomiej [Show all 9 contributors for this article] (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. p. 236–251. doi: 10.5281/zenodo.4294084.
• Aalstad, Kristoffer; Alonso-Gonzalez, Esteban; Bazilova, Varvara; Bertino, Laurent; Fiddes, Joel & Filhol, Simon [Show all 9 contributors for this article] (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 [Show all 8 contributors for this article] (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. Show summary

  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 [Show all 7 contributors for this article] (2021). Leveraging emerging Earth observations using data assimilation. Show summary

  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 [Show all 7 contributors for this article] (2021). Workshop on downscaling with TopoSCALE for cryospheric applications. Show summary

  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 [Show all 8 contributors for this article] (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 [Show all 7 contributors for this article] (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 [Show all 8 contributors for this article] (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?
• Bryn, Anders; Dalen, Thea Grobstok; Finne, Eirik Aasmo; Heiberg, Hanne; Keetz, Lasse Torben & Nilsen, Irene Brox [Show all 30 contributors for this article] (2021). Natur i endring - samspillet mellom klima og økosystemene.
• Althuizen, Inge; Christiansen, Casper Tai; Michelsen, Anders; Pirk, Norbert; Risk, David & Westermann, Sebastian [Show all 7 contributors for this article] (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 [Show all 7 contributors for this article] (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). Show summary

  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 [Show all 8 contributors for this article] (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. Show summary

  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. [Show all 22 contributors for this article] (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. Show summary

  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

• Aalstad, Kristoffer; Westermann, Sebastian; Karsten, Logan; Gutmann, Ethan; McCreight, James & Fiddes, Joel [Show all 7 contributors for this article] (2018). Ensemble-based reanalysis of the seasonal montane snowpack: Lessons from the ASO.
• Aalstad, Kristoffer; Westermann, Sebastian; Karsten, Logan; Fiddes, Joel & Bertino, Laurent (2018). Snow history matching in mountainous terrain.
• Aalstad, Kristoffer; Westermann, Sebastian; Bertino, Laurent; Schuler, Thomas; Boike, Julia & Karsten, Logan (2018). Towards high-resolution Bayesian snow reconstruction in permafrost regions.
• Christiansen, Casper Tai; Westermann, Sebastian; Risk, David & Lee, Hanna (2018). Advancing permafrost carbon climate feedback – improvements and evaluations of the Norwegian Earth System Model with observations.
• Lee, Hanna; Ekici, Altug; Robson, Benjamin Aubrey; Fan, Yuanchao; Westermann, Sebastian & Langer, Moritz (2018). Vulnerability of permafrost thaw and the emerging risks for the Arctic infrastructure.
• Aalstad, Kristoffer; Westermann, Sebastian; Schuler, Thomas; Boike, Julia & Bertino, Laurent (2017). Ensemble-based subgrid snow data assimilation.
• Aalstad, Kristoffer; Westermann, Sebastian; Schuler, Thomas; Boike, Julia & Bertino, Laurent (2017). Towards High-Resolution SWE Mapping in Permafrost Regions.
• Aalstad, Kristoffer; Westermann, Sebastian; Schuler, Thomas; Boike, Julia & Bertino, Laurent (2017). Towards High-Resolution SWE Mapping in Permafrost Regions.
• Aas, Kjetil Schanke; Westermann, Sebastian; Martin, Leo Celestin Paul & Berntsen, Terje Koren (2017). Degrading Palsa Mires in Northern Norway Simulated with a Regional Climate Model with a Subgrid Snow Scheme.
• Lee, Hanna; Christiansen, Casper Tai & Westermann, Sebastian (2017). Advancing permafrost carbon climate feedback – improvements and evaluations of the Norwegian Earth System Model with observations (FEEDBACK).
• Aalstad, Kristoffer; Westermann, Sebastian & Bertino, Laurent (2016). An ensemble-based subgrid snow data assimilation framework applied to the southern Swiss alps.
• Aalstad, Kristoffer; Westermann, Sebastian & Bertino, Laurent (2016). An ensemble-based subgrid snow data assimilation framework.
• Aalstad, Kristoffer; Westermann, Sebastian & Bertino, Laurent (2016). An ensemble-based snow data assimilation framework.
• Aalstad, Kristoffer; Westermann, Sebastian; Boike, Julia; Bertino, Laurent & Aas, Kjetil Schanke (2016). An ensemble-based snow data assimilation framework with applications to permafrost modeling.
• Hilger, Paula; Hermanns, Reginald; Etzelmüller, Bernd; Westermann, Sebastian; Krautblatter, Michael & Gosse, John C. [Show all 8 contributors for this article] (2016). Evaluation of rock-slope failures in steep permafrost slopes in Norway - first insights in the geological history of the Mannen unstable rock slope in Møre og Romsdal.
• Schuler, Thomas; Aalstad, Kristoffer; Aas, Kjetil Schanke; Burkhart, John; Dunse, Thorben & Filhol, Simon [Show all 9 contributors for this article] (2016). Towards real-time snow products for Svalbard.
• Aalstad, Kristoffer; Bertino, Laurent & Westermann, Sebastian (2016). An ensemble-based subgrid snow data assimilation framework.
• Obu, Jaroslav; Westermann, Sebastian; Kääb, Andreas & Bartsch, Annett (2016). Mapping the Thermal State of Permafrost Through Modelling and Remote Sensing in ESA GlobPermafrost Project.
• Nuth, Christopher; Kääb, Andreas; Westermann, Sebastian & Winsvold, Solveig Havstad (2016). Climate Change from Global Monitoring of Glaciers and Permafrost.
• Westermann, Sebastian; Langer, Moritz; Østby, Torbjørn Ims; Peter, Maria; Boike, Julia & Gisnås, Kjersti [Show all 12 contributors for this article] (2016). Mapping the thermal state of permafrost through modeling and remote sensing .
• Myhra, Kristin Sæterdal; Etzelmuller, Bernd & Westermann, Sebastian (2016). The Influence of Steep Rock Walls on the Thermal Regime of Talus Slopes.
• Aalstad, Kristoffer; Westermann, Sebastian & Bertino, Laurent (2019). Ensemble-based retrospective analysis of the seasonal snowpack. University of Oslo. ISSN 1501-7710.
• Bilt, Willem van der; Bakke, Jostein; Smedsrud, Lars H.; Sund, Monica; Schuler, Thomas & Westermann, Sebastian [Show all 47 contributors for this article] (2019). Climate in Svalbard 2100 . Norsk klimaservicesenter. ISSN 2387-3027. Full text in Research Archive

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