Dataset for Assessing volumetric change distributions and scaling relations of thaw slumps across the Arctic

Bernhard, Philipp; Zwieback, Simon; Bergner, Nora; and Hajnsek, Irena

Arctic ice-rich permafrost is becoming increasingly vulnerable to terrain-altering thermokarst, and among the most rapid and dramatic of these changes are retrogressive thaw slumps (RTSs). They initiate when ice-rich soils are exposed and thaw, leading to the formation of a steep headwall which retreats during the summer months. The impacts and the distribution and scaling laws governing RTS changes within and between regions are unknown. Using TanDEM-X-derived digital elevation models, we estimated RTS volume and area changes over a 5-year time period from winter 2011/12 to winter 2016/17 and used for the first time probability density functions to describe their distributions. We found that over this time period all 1853 RTSs mobilized a combined volume of 17×10⁶ m³ yr⁻¹, corresponding to a volumetric change density of 77 m³ yr⁻¹ km⁻². Our remote sensing data reveal inter-regional differences in mobilized volumes, scaling laws, and terrain controls. The distributions of RTS area and volumetric change rates follow an inverse gamma function with a distinct peak and an exponential decrease for the largest RTSs. We found that the distributions in the high Arctic are shifted towards larger values than at other study sites We observed that the area-to-volume scaling was well described by a power law with an exponent of 1.15 across all study sites; however the individual sites had scaling exponents ranging from 1.05 to 1.37, indicating that regional characteristics need to be taken into account when estimating RTS volumetric changes from area changes. Among the terrain controls on RTS distributions that we examined, which included slope, adjacency to waterbodies, and aspect, the latter showed the greatest but regionally variable association with RTS occurrence. Accounting for the observed regional differences in volumetric change distributions, scaling relations, and terrain controls may enhance the modelling and monitoring of Arctic carbon, nutrient, and sediment cycles.

Citation

In order to use these data, you must cite this data set with the following citation:

Bernhard, P., Zwieback, S., Bergner, N., and Hajnsek, I.: Assessing volumetric change distributions and scaling relations of retrogressive thaw slumps across the Arctic, The Cryosphere, 16, 1–15, https://doi.org/10.5194/tc-16-1-2022, 2022.

Kontakt

Bernhard, Philipp

Metadaten-Zugang

DCAT in RDF/XML-Format

DCAT in Turtle-Format

DCAT in JSON-LD-Format

APGC Dataset Metadata in JSON-Format

Daten und Ressourcen

Zusätzliche Informationen

Feld Wert
Identifikator DOI:10.3929/ethz-b-000482449
Projekt(e)
Institut ETH Zürich
Quelle https://doi.org/10.3929/ethz-b-000482449
Publikationsdatum 2021-05-04
Version 1.0
Produkt retrogressive thaw slumps dataset
Sensor(en) TanDEM-X
Dateien
  1. Readme.txt
  2. RTS_data_Inventory.csv
  3. RTS_data_Location.kml
Variablen [Einheiten]
  1. Area: Study region name
  2. RTSID: Numbers of RTS starting from 1 in each study region
  3. location_center_lat: Latitude degree of RTS location
  4. location_center_lon: Longitude degree of RTS location
  5. change_vol_year: yearly average volumetric change rate [m² yr⁻¹]
  6. change_area_year: yearly average area change rate [m² yr⁻¹]
  7. dem_avg_slope: mean slope in degree
  8. dem_aspect: Aspect of RTS (0° (=East), 90° (North), 180° (=West), 270° (=South))
  9. dem_elevation: Elevation from DEM
  10. location: lakeshore or hillslope
Region Circum-Arctic
Räumlicher Bezug EPSG:4326 WGS 84
Räumliche Auflösung
Räumliche Abdeckung Latitude 65.87 to 80.00 Longitude -178.84 to 100.24
Zeitliche Abdeckung 2011-2017
Zeitliche Auflösung winter period
Format Shapefile, CSV
Is Supplement To

Bernhard, P., Zwieback, S., Bergner, N., and Hajnsek, I.: Assessing volumetric change distributions and scaling relations of retrogressive thaw slumps across the Arctic, The Cryosphere, 16, 1–15, https://doi.org/10.5194/tc-16-1-2022, 2022.

Zusammenhang mit

Ausdehnung des Datensatzes