Articles | Volume 16, issue 1
https://doi.org/10.5194/tc-16-1-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-1-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jan 2022
Research article |
| 03 Jan 2022
| 03 Jan 2022
Assessing volumetric change distributions and scaling relations of retrogressive thaw slumps across the Arctic
Philipp Bernhard
CORRESPONDING AUTHOR
Institute of Environmental Engineering, ETH Zurich, 8093 Zurich, Switzerland
Simon Zwieback
Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Nora Bergner
Institute of Environmental Engineering, ETH Zurich, 8093 Zurich, Switzerland
Irena Hajnsek
Institute of Environmental Engineering, ETH Zurich, 8093 Zurich, Switzerland
Microwaves and Radar Institute, German Aerospace Center (DLR) e.V., 82234 Weßling, Germany
Related authors
Kathrin Maier, Zhuoxuan Xia, Lin Liu, Mark J. Lara, Jurjen van der Sluijs, Philipp Bernhard, and Irena Hajnsek
EGUsphere, https://doi.org/10.5194/egusphere-2025-2187, https://doi.org/10.5194/egusphere-2025-2187, 2025
Short summary
Short summary
Our study explores how thawing permafrost on the Qinghai-Tibet Plateau triggers landslides, mobilising stored carbon. Using satellite data from 2011 to 2020, we measured soil erosion, ice loss, and carbon mobilisation. While current impacts are modest, increasing landslide activity suggests future significance. This research underscores the need to understand permafrost thaw's role in carbon dynamics and climate change.
Shiyi Li, Lanqing Huang, Philipp Bernhard, and Irena Hajnsek
The Cryosphere, 19, 1621–1639, https://doi.org/10.5194/tc-19-1621-2025, https://doi.org/10.5194/tc-19-1621-2025, 2025
Short summary
Short summary
This work presents an improved method for seasonal wet snow mapping in Karakoram using synthetic aperture radar (SAR) data and topographic data. This method enables robust wet snow classification in complex mountainous terrain. Large-scale wet snow maps were generated using the proposed method, covering three major water basins in Karakoram over 4 years (2017–2021). Crucial snow variables were further derived from the maps and provided valuable insights on regional snow melting dynamics.
Philipp Bernhard, Simon Zwieback, and Irena Hajnsek
The Cryosphere, 16, 2819–2835, https://doi.org/10.5194/tc-16-2819-2022, https://doi.org/10.5194/tc-16-2819-2022, 2022
Short summary
Short summary
With climate change, Arctic hillslopes above ice-rich permafrost are vulnerable to enhanced carbon mobilization. In this work elevation change estimates generated from satellite observations reveal a substantial acceleration of carbon mobilization on the Taymyr Peninsula in Siberia between 2010 and 2021. The strong increase occurring in 2020 coincided with a severe Siberian heatwave and highlights that carbon mobilization can respond sharply and non-linearly to increasing temperatures.
Kathrin Maier, Zhuoxuan Xia, Lin Liu, Mark J. Lara, Jurjen van der Sluijs, Philipp Bernhard, and Irena Hajnsek
EGUsphere, https://doi.org/10.5194/egusphere-2025-2187, https://doi.org/10.5194/egusphere-2025-2187, 2025
Short summary
Short summary
Our study explores how thawing permafrost on the Qinghai-Tibet Plateau triggers landslides, mobilising stored carbon. Using satellite data from 2011 to 2020, we measured soil erosion, ice loss, and carbon mobilisation. While current impacts are modest, increasing landslide activity suggests future significance. This research underscores the need to understand permafrost thaw's role in carbon dynamics and climate change.
Shiyi Li, Lanqing Huang, Philipp Bernhard, and Irena Hajnsek
The Cryosphere, 19, 1621–1639, https://doi.org/10.5194/tc-19-1621-2025, https://doi.org/10.5194/tc-19-1621-2025, 2025
Short summary
Short summary
This work presents an improved method for seasonal wet snow mapping in Karakoram using synthetic aperture radar (SAR) data and topographic data. This method enables robust wet snow classification in complex mountainous terrain. Large-scale wet snow maps were generated using the proposed method, covering three major water basins in Karakoram over 4 years (2017–2021). Crucial snow variables were further derived from the maps and provided valuable insights on regional snow melting dynamics.
Sara-Patricia Schlenk, Georg Fischer, Matteo Pardini, and Irena Hajnsek
EGUsphere, https://doi.org/10.5194/egusphere-2024-3474, https://doi.org/10.5194/egusphere-2024-3474, 2025
Short summary
Short summary
Synthetic Aperture Radar (SAR) revealed ice features of unknown glaciological origin in southwest Greenland’s ablation zone. Using SAR techniques, we identified low-backscatter areas with surface scattering, in contrast to surrounding high-backscatter areas with scattering from the subsurface. Our first theory relates the low backscatter to residual liquid water in a weathering crust and the surrounding to bare glacier ice. These findings may deepen our understanding of ablation zone properties.
Lanqing Huang and Irena Hajnsek
The Cryosphere, 18, 3117–3140, https://doi.org/10.5194/tc-18-3117-2024, https://doi.org/10.5194/tc-18-3117-2024, 2024
Short summary
Short summary
Interferometric synthetic aperture radar can measure the total freeboard of sea ice but can be biased when radar signals penetrate snow and ice. We develop a new method to retrieve the total freeboard and analyze the regional variation of total freeboard and roughness in the Weddell and Ross seas. We also investigate the statistical behavior of the total freeboard for diverse ice types. The findings enhance the understanding of Antarctic sea ice topography and its dynamics in a changing climate.
Joanmarie Del Vecchio, Emma R. Lathrop, Julian B. Dann, Christian G. Andresen, Adam D. Collins, Michael M. Fratkin, Simon Zwieback, Rachel C. Glade, and Joel C. Rowland
Earth Surf. Dynam., 11, 227–245, https://doi.org/10.5194/esurf-11-227-2023, https://doi.org/10.5194/esurf-11-227-2023, 2023
Short summary
Short summary
In cold regions of the Earth, thawing permafrost can change the landscape, impact ecosystems, and lead to the release of greenhouse gases. In this study we used many observational tools to better understand how sediment moves on permafrost hillslopes. Some topographic change conforms to our understanding of slope stability and sediment transport as developed in temperate landscapes, but much of what we observed needs further explanation by permafrost-specific geomorphic models.
Marcel Stefko, Silvan Leinss, Othmar Frey, and Irena Hajnsek
The Cryosphere, 16, 2859–2879, https://doi.org/10.5194/tc-16-2859-2022, https://doi.org/10.5194/tc-16-2859-2022, 2022
Short summary
Short summary
The coherent backscatter opposition effect can enhance the intensity of radar backscatter from dry snow by up to a factor of 2. Despite widespread use of radar backscatter data by snow scientists, this effect has received notably little attention. For the first time, we characterize this effect for the Earth's snow cover with bistatic radar experiments from ground and from space. We are also able to retrieve scattering and absorbing lengths of snow at Ku- and X-band frequencies.
Philipp Bernhard, Simon Zwieback, and Irena Hajnsek
The Cryosphere, 16, 2819–2835, https://doi.org/10.5194/tc-16-2819-2022, https://doi.org/10.5194/tc-16-2819-2022, 2022
Short summary
Short summary
With climate change, Arctic hillslopes above ice-rich permafrost are vulnerable to enhanced carbon mobilization. In this work elevation change estimates generated from satellite observations reveal a substantial acceleration of carbon mobilization on the Taymyr Peninsula in Siberia between 2010 and 2021. The strong increase occurring in 2020 coincided with a severe Siberian heatwave and highlights that carbon mobilization can respond sharply and non-linearly to increasing temperatures.
Lanqing Huang, Georg Fischer, and Irena Hajnsek
The Cryosphere, 15, 5323–5344, https://doi.org/10.5194/tc-15-5323-2021, https://doi.org/10.5194/tc-15-5323-2021, 2021
Short summary
Short summary
This study shows an elevation difference between the radar interferometric measurements and the optical measurements from a coordinated campaign over the snow-covered deformed sea ice in the western Weddell Sea, Antarctica. The objective is to correct the penetration bias of microwaves and to generate a precise sea ice topographic map, including the snow depth on top. Excellent performance for sea ice topographic retrieval is achieved with the proposed model and the developed retrieval scheme.
Simon Zwieback and Franz J. Meyer
The Cryosphere, 15, 2041–2055, https://doi.org/10.5194/tc-15-2041-2021, https://doi.org/10.5194/tc-15-2041-2021, 2021
Short summary
Short summary
Thawing of ice-rich permafrost leads to subsidence and slumping, which can compromise Arctic infrastructure. However, we lack fine-scale maps of permafrost ground ice, chiefly because it is usually invisible at the surface. We show that subsidence at the end of summer serves as a
fingerprintwith which near-surface permafrost ground ice can be identified. As this can be done with satellite data, this method may help improve ground ice maps and thus sustainably steward the Arctic.
Cited articles
Bachmann, M., Borla Tridon, D., Martone, M., Sica, F., Buckreuss, S., and
Zink, M.: How to update a global DEM – acquisition concepts for TanDEM-X and
Tandem-L, in: Proceedings of the European Conference on Synthetic Aperture
Radar, Aachen, Germany, 4–7 June 2018, 1–5, 2018. a
Bak, P. and Tang, C.: Earthquakes as a self-organized critical phenomenon,
J. Geophys. Res.-Sol. Ea., 94, 15635–15637, 1989. a
Balser, A. W., Jones, J. B., and Gens, R.: Timing of retrogressive thaw slump
initiation in the Noatak Basin, northwest Alaska, USA, J. Geophys. Res.-Earth, 119, 1106–1120, https://doi.org/10.1002/2013JF002889, 2014. a
Bennett, G., Molnar, P., Eisenbeiss, H., and McArdell, B.: Erosional power in
the Swiss Alps: characterization of slope failure in the Illgraben, Earth Surf. Proc. Land., 37, 1627–1640, https://doi.org/10.1002/esp.3263,
2012. a
Bernhard, P.: Dataset for Assessing volumetric change distributions and scaling relations of thaw slumps across the Arctic, ETH Zurich [data set], https://doi.org/10.3929/ethz-b-000482449, 2021. a
Bernhard, P., Zwieback, S., Leinss, S., and Hajnsek, I.: Mapping
Retrogressive Thaw Slumps Using Single-Pass TanDEM-X Observations, IEEE J. Sel. Top. Appl., 13, 3263–3280, https://doi.org/10.1109/JSTARS.2020.3000648, 2020. a, b, c, d
Boggs, P. T. and Rogers, J. E.: Orthogonal Distance Regression, Statistical
analysis of measurement error models and applications: proceedings of the
AMS-IMS-SIAM joint summer research conference held June 10–16, 1989, Humboldt State University, Arcata, California, USA, 112,
186, 1990. a
Brown, J., Ferrians, O., Heginbottom, J. A., and Melnikov, E.: Circum-Arctic
Map of Permafrost and Ground-Ice Conditions, Version 2, National Snow and Ice Data Center (NSIDC), Boulder, Colorado, USA, https://doi.org/10.7265/skbg-kf16, 2002. a, b, c
Burn, C. R. and Lewkowicz, A.: Canadian landform examples-17 retrogressive thaw
slumps, Can. Geogr., 34, 273–276, https://doi.org/10.1111/j.1541-0064.1990.tb01092.x, 1990. a
Burn, C. R., Michel, F. A., and Smith, M. W.: Stratigraphic, isotopic, and
mineralogical evidence for an early Holocene thaw unconformity at Mayo, Yukon
Territory, Can. J. Earth Sci., 23, 794–803,
https://doi.org/10.1139/e86-081, 1986. a
Clauset, A., Shalizi, C. R., and Newman, M. E.: Power-law distributions in
empirical data, SIAM Rev., 51, 661–703, 2009. a
Dai, C., Jones, M., Howat, I., Liljedahl, A., Lewkowicz, A., and Freymueller, J.: Using ArcticDEM to identify and quantify pan-Arctic retrogressive thaw slump activity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12142, https://doi.org/10.5194/egusphere-egu2020-12142, 2020. a
European Space Agency (ESA): Copernicus Open Access Hub, ESA [data set], available at: https://scihub.copernicus.eu, last access: 22 December 2021. a
Fritz, T., Rossi, C., Yague-Martinez, N., Rodriguez-Gonzalez, F., Lachaise, M.,
and Breit, H.: Interferometric processing of TanDEM-X data, in: 2011 Int. Geosci. Remote Se., Vancouver, BC, Canada, 24–29 July 2011, 2428–2431,
https://doi.org/10.1109/IGARSS.2011.6049701, 2011. a
German Space Agency (DLR): DLR EOWEB GeoPortal, DLR [data set], available at: https://eoweb.dlr.de, last access: 22 December 2021. a
Gooseff, M. N., Balser, A., Bowden, W. B., and Jones, J. B.: Effects of
hillslope thermokarst in northern Alaska, Eos, 90, 29–30, 2009. a
Grosse, G., Harden, J., Turetsky, M., McGuire, A. D., Camill, P., Tarnocai, C.,
Frolking, S., Schuur, E. A., Jorgenson, T., Marchenko, S., Romanovsky, V.,
Wickland, K. P., French, N., Waldrop, M., Bourgeau-Chavez, L., and Striegl,
R. G.: Vulnerability of high-latitude soil organic carbon in North America
to disturbance, J. Geophys. Res.-Biogeo., 116, G4,
https://doi.org/10.1029/2010JG001507, 2011. a
Jones, M. K. W., Pollard, W. H., and Jones, B. M.: Rapid initialization of
retrogressive thaw slumps in the Canadian high Arctic and their response to
climate and terrain factors, Environ. Res. Lett., 14, 055006, https://doi.org/10.1088/1748-9326/ab12fd
2019. a, b, c
Kang-tsung, C. and Bor-wen, T.: The Effect of DEM Resolution on Slope and
Aspect Mapping, Cartogr. and Geogr. Inform., 18, 69–77,
https://doi.org/10.1559/152304091783805626, 1991. a
Kaplan, G. and Avdan, U.: Object-based water body extraction model using
Sentinel-2 satellite imagery, Eur. J. Remote Sens., 50, 1, https://doi.org/10.1080/22797254.2017.1297540, 2017. a
Kaufman, D., Ager, T., Anderson, N., Anderson, P., Andrews, J., Bartlein, P.,
Brubaker, L., Coats, L., Cwynar, L., Duvall, M., Dyke, A., Edwards, M.,
Eisner, W., Gajewski, K., Geirsdóttir, A., Hu, F., Jennings, A., Kaplan, M.,
Kerwin, M., Lozhkin, A., MacDonald, G., Miller, G., Mock, C., Oswald, W.,
Otto-Bliesner, B., Porinchu, D., Rühland, K., Smol, J., Steig, E., and
Wolfe, B.: Holocene thermal maximum in the western Arctic (0–180∘ W),
Quaternary Sci. Rev., 23, 529–560,
https://doi.org/10.1016/j.quascirev.2003.09.007, 2004. a
Klar, A., Aharonov, E., Kalderon-Asael, B., and Katz, O.: Analytical and
observational relations between landslide volume and surface area, J. Geophys. Res.-Earth, 116, F2, https://doi.org/10.1029/2009JF001604, 2011. a, b
Kokelj, S. V. and Jorgenson, M. T.: Advances in thermokarst research,
Permafrost Periglac., 24, 108–119, https://doi.org/10.1002/ppp.1779,
2013. a
Kokelj, S. V., Lantz, T. C., Kanigan, J., Smith, S. L., and Coutts, R.: Origin
and polycyclic behaviour of tundra thaw slumps, Mackenzie Delta region,
Northwest Territories, Canada, Permafrost Periglac., 20,
173–184, https://doi.org/10.1002/ppp.642, 2009. a, b, c
Kokelj, S. V., Lantz, T. C., Tunnicliffe, J., Segal, R., and Lacelle, D.:
Climate-driven thaw of permafrost preserved glacial landscapes, northwestern
Canada, Geology, 45, 371–374, https://doi.org/10.1130/G38626.1, 2017. a, b
Kokelj, S. V., Kokoszka, J., van der Sluijs, J., Rudy, A. C. A., Tunnicliffe, J., Shakil, S., Tank, S. E., and Zolkos, S.: Thaw-driven mass wasting couples slopes with downstream systems, and effects propagate through Arctic drainage networks, The Cryosphere, 15, 3059–3081, https://doi.org/10.5194/tc-15-3059-2021, 2021. a
Krieger, G., Moreira, A., Fiedler, H., Hajnsek, I., Werner, M., Younis, M., and
Zink, M.: TanDEM-X: A satellite formation for high-resolution SAR
interferometry, IEEE T. Geosci. Remote, 45, 3317–3340, https://doi.org/10.1109/TGRS.2007.900693, 2007. a
Lacelle, D., Bjornson, J., Lauriol, B., Clark, I., and Troutet, Y.:
Segregated-intrusive ice of subglacial meltwater origin in retrogressive
thaw flow headwalls, Richardson Mountains, NWT, Canada, Quaternary Sci. Rev., 23, 681–696, https://doi.org/10.1016/j.quascirev.2003.09.005, 2004. a
Lacelle, D., Bjornson, J., and Lauriol, B.: Climatic and geomorphic factors
affecting contemporary (1950–2004) activity of retrogressive thaw slumps on
the Aklavik plateau, Richardson mountains, NWT, Canada, Permafrost
Periglac., 21, 1–15, https://doi.org/10.1002/ppp.666, 2010. a, b
Lacelle, D., Brooker, A., Fraser, R. H., and Kokelj, S. V.: Distribution and
growth of thaw slumps in the Richardson Mountains-Peel Plateau region,
northwestern Canada, Geomorphology, 235, 40–51,
https://doi.org/10.1016/j.geomorph.2015.01.024, 2015. a, b
Lantuit, H. and Pollard, W. H.: Fifty years of coastal erosion and
retrogressive thaw slump activity on Herschel Island, southern Beaufort Sea,
Yukon Territory, Canada, Geomorphology, 95, 84–102,
https://doi.org/10.1016/j.geomorph.2006.07.040, 2008. a, b
Lantuit, H., Pollard, W. H., Couture, N., Fritz, M., Schirrmeister, L., Meyer,
H., and Hubberten, H.-W.: Modern and Late Holocene Retrogressive Thaw Slump
Activity on the Yukon Coastal Plain and Herschel Island, Yukon Territory,
Canada, Permafrost Periglac., 23, 39–51,
https://doi.org/10.1002/ppp.1731, 2012. a
Lantz, T. C. and Kokelj, S. V.: Increasing rates of retrogressive thaw slump
activity in the Mackenzie Delta region, N. W. T., Canada, Geophys. Res. Lett., 35, 6, https://doi.org/10.1029/2007GL032433, 2008. a, b
Lewkowicz, A. G.: Headwall retreat of ground-ice slumps, Banks Island,
Northwest Territories, Can. J. Earth Sci., 24, 6, https://doi.org/10.1139/e87-105, 1987a. a
Lewkowicz, A. G.: Nature and Importance of Thermokarst Processes, Sand Hills
Moraine, Banks Island, Canada, Geogr. Ann. A, 69, 321–327, https://doi.org/10.1080/04353676.1987.11880218,
1987b. a
Lewkowicz, A. G. and Way, R. G.: Extremes of summer climate trigger thousands
of thermokarst landslides in a High Arctic environment, Nat. Commun., 10, 1, https://doi.org/10.1038/s41467-019-09314-7, 2019. a, b
Malamud, B. D., Turcotte, D. L., Guzzetti, F., and Reichenbach, P.: Landslide
inventories and their statistical properties, Earth Surf. Proc. Land., 29, 687–711, https://doi.org/10.1002/esp.1064, 2004. a
Markovsky, I. and Van Huffel, S.: Overview of total least-squares methods,
Signal Process., 87, 2283–2302, https://doi.org/10.1016/j.sigpro.2007.04.004, 2007. a
Martone, M., Bräutigam, B., Rizzoli, P., Gonzalez, C., Bachmann, M., and
Krieger, G.: Coherence evaluation of TanDEM-X interferometric data, ISPRS J. Photogramm., 73, 21–29,
https://doi.org/10.1016/j.isprsjprs.2012.06.006, 2012. a
McFeeters, S. K.: The use of the Normalized Difference Water Index (NDWI) in
the delineation of open water features, Int. J. Remote Sens., 17, 7, https://doi.org/10.1080/01431169608948714, 1996. a
Millan, R., Dehecq, A., Trouvé, E., Gourmelen, N., and Berthier, E.: Elevation
changes and X-band ice and snow penetration inferred from TanDEM-X data of
the Mont-Blanc area, in: 2015 8th International Workshop on the Analysis of
Multitemporal Remote Sensing Images (Multi-Temp), Annecy, France, 22–24 July 2015, 1–4,
https://doi.org/10.1109/Multi-Temp.2015.7245753, 2015. a
Nesterova, N., Khomutov, A., Kalyukina, A., and Leibman, M.: The specificity
of thermal denudation feature distribution on Yamal and Gydan peninsulas
Russia, in: EGU General Assembly 2020 Online, 4–8 May 2020, EGU2020-746,
https://doi.org/10.5194/egusphere-egu2020-746, 2020. a, b
Nicu, I. C., Lombardo, L., and Rubensdotter, L.: Preliminary assessment of thaw
slump hazard to Arctic cultural heritage in Nordenskiöld Land, Svalbard,
Landslides, 18, 1–13, https://doi.org/10.1007/s10346-021-01684-8, 2021. a
Nitze, I., Grosse, G., Jones, B. M., Arp, C. D., Ulrich, M., Fedorov, A., and
Veremeeva, A.: Landsat-based trend analysis of lake dynamics across Northern
Permafrost Regions, Remote Sens.-Basel, 9, 640, https://doi.org/10.3390/rs9070640, 2017. a
Nitze, I., Grosse, G., Jones, B., Romanovsky, V., and Boike, J.: Remote
sensing quantifies widespread abundance of permafrost region disturbances
across the Arctic and Subarctic, Nat. Commun., 9, 1–11, 2018. a
Obu, J.: How Much of the Earth's Surface is Underlain by Permafrost?, J. Geophys. Res.-Earth, 126, e2021JF006123,
https://doi.org/10.1029/2021JF006123, 2021. a
Ohtani, K.: Bootstrapping R2 and adjusted R2 in regression analysis, Econ. Model., 17, 473–483, https://doi.org/10.1016/S0264-9993(99)00034-6, 2000. a
Parker, R., Hancox, G., Petley, D., Massey, C., Densmore, A., and Rosser, N.:
Spatial distributions of earthquake-induced landslides and hillslope
preconditioning in northwest South Island, New Zealand, Earth Surf. Dynam., 3, 501–525, 2015. a
Planet-Team: Planet Application Program Interface: In Space for Life on Earth, available at: https://api.planet.com (last access: 22 December 2021), 2018. a
Ramage, J. L., Irrgang, A. M., Herzschuh, U., Morgenstern, A., Couture, N., and
Lantuit, H.: Terrain Controls on the Occurrence of Coastal Retrogressive
Thaw Slumps along the Yukon Coast, Canada, J. Geophys. Res.-Earth, 122, 9, https://doi.org/10.1002/2017JF004231, 2017. a, b
Rudy, A. C., Lamoureux, S. F., Kokelj, S. V., Smith, I. R., and England, J. H.:
Accelerating Thermokarst Transforms Ice-Cored Terrain Triggering a
Downstream Cascade to the Ocean, Geophys. Res. Lett., 44, 21,
https://doi.org/10.1002/2017GL074912, 2017. a
Schuur, E. A. G., McGuire, A. D., Schädel, C., Grosse, G., Harden, J. W.,
Hayes, D. J., Hugelius, G., Koven, C. D., Kuhry, P., Lawrence, D. M., Natali,
S. M., Olefeldt, D., Romanovsky, V. E., Schaefer, K., Turetsky, M. R., Treat,
C. C., and Vonk, J. E.: Climate change and the permafrost carbon feedback,
Nature, 520, 171–179, https://doi.org/10.1038/nature14338, 2015. a
Segal, R. A., Lantz, T. C., and Kokelj, S. V.: Acceleration of thaw slump
activity in glaciated landscapes of the Western Canadian Arctic,
Environ. Rese. Lett., 11, 034025,
https://doi.org/10.1088/1748-9326/11/3/034025, 2016. a
Swanson, D. K. and Nolan, M.: Growth of retrogressive thaw slumps in the
Noatak Valley, Alaska, 2010–2016, measured by airborne photogrammetry,
Remote Sens., 10, 983, https://doi.org/10.3390/rs10070983, 2018. a, b
Tanyaş, H., Allstadt, K. E., and van Westen, C. J.: An updated method for
estimating landslide-event magnitude, Earth Surf. Proc. Land.,
43, 1836–1847, https://doi.org/10.1002/esp.4359, 2018. a, b
Tebbens, S. F.: Landslide Scaling: A Review, Earth Space Sci., 7,
e2019EA000662, https://doi.org/10.1029/2019EA000662,
2020. a, b
Turcotte, D. L.: Self-organized criticality, Rep. Prog. Phys.,
62, 1377–1429, 1999. a
Turetsky, M. R., Abbott, B. W., Jones, M. C., Anthony, K. W., Olefeldt, D., Schuur, E. A., Grosse, G., Kuhry, P., Hugelius, G., Koven, C., Lawrence, D. M., Gibson, C., Sannel, B., and McGuire, D.: Carbon
release through abrupt permafrost thaw, Nat. Geosci., 13, 138–143,
2020. a
Van der Sluijs, J., Kokelj, S. V., Fraser, R. H., Tunnicliffe, J., and Lacelle,
D.: Permafrost terrain dynamics and infrastructure impacts revealed by UAV
photogrammetry and thermal imaging, Remote Sens., 10, 1734, https://doi.org/10.3390/rs10111734, 2018. a
Wang, B., Paudel, B., and Li, H.: Retrogression characteristics of landslides
in fine-grained permafrost soils, Mackenzie Valley, Canada, Landslides, 6,
121–127, 2009. a
Wang, B., Paudel, B., and Li, H.: Behaviour of retrogressive thaw slumps in
northern Canada – three-year monitoring results from 18 sites, Landslides,
13, 1–8, https://doi.org/10.1007/s10346-014-0549-y, 2016. a
Werner, C., Wegmueller, U., Strozzi, T., and Wiesmann, A.: GAMMA SAR and
interferometric processing software, in: European Space Agency (Special
Publication) ESA SP, 461, 211–219, 2000. a
Zwieback, S., Kokelj, S. V., Günther, F., Boike, J., Grosse, G., and Hajnsek, I.: Sub-seasonal thaw slump mass wasting is not consistently energy limited at the landscape scale, The Cryosphere, 12, 549–564, https://doi.org/10.5194/tc-12-549-2018, 2018. a, b
Zwieback, S., Boike, J., Marsh, P., and Berg, A.: Debris cover on thaw slumps
and its insulative role in a warming climate, Earth Surf. Proc. Land., 45, 2631–2646, https://doi.org/10.1002/esp.4919, 2020. a
Short summary
We present an investigation of retrogressive thaw slumps in 10 study sites across the Arctic. These slumps have major impacts on hydrology and ecosystems and can also reinforce climate change by the mobilization of carbon. Using time series of digital elevation models, we found that thaw slump change rates follow a specific type of distribution that is known from landslides in more temperate landscapes and that the 2D area change is strongly related to the 3D volumetric change.
We present an investigation of retrogressive thaw slumps in 10 study sites across the Arctic....
