Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

Research output: Contribution to journalArticlepeer-review



  • Nick Rutter
  • Melody Sandells
  • Chris Derksen
  • Josh King
  • Peter Toose
  • Leanne Wake
  • Tom Watts
  • Richard Essery
  • Alexandre Roy
  • Alain Royer
  • Philip Marsh
  • Chris Larsen
  • Matthew Sturm

External departments

  • Cores Science and Engineering Ltd.
  • Environment and Climate Change Canada
  • University of Alaska Fairbanks
  • University of Edinburgh
  • Université de Sherbrooke
  • Université du Québec à Trois-Rivières
  • Wilfrid Laurier University


Original languageEnglish
Pages (from-to)3045-3059
JournalThe Cryosphere
Issue number11
Publication statusPublished - 19 Nov 2019
Publication type

Research output: Contribution to journalArticlepeer-review


Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across 9 trenches) collected over two winters at Trail Valley Creek, NWT, Canada, were applied in synthetic radiative transfer experiments. This allowed robust assessment of the impact of estimation accuracy of unknown snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer thickness varied over the shortest horizontal distances, controlled by subnivean vegetation and topography, while variability of total snowpack thickness approximated that of wind slab layers. Mean horizontal correlation lengths of layer thickness were sub-metre for all layers. Depth hoar was consistently ~30% of total depth, and with increasing total depth the proportion of wind slab increased at the expense of the decreasing surface snow layer. Distinct differences were evident between distributions of layer properties; a single median value represented density and specific surface area (SSA) of each layer well. Spatial variability in microstructure of depth hoar layers dominated SWE retrieval errors. A depth hoar SSA estimate of around 7% under the median value was needed to accurately retrieve SWE. In shallow snowpacks <0.6m, depth hoar SSA estimates of ±5-10% around the optimal retrieval SSA allowed SWE retrievals within a tolerance of ±30 mm. Where snowpacks were deeper than ~30cm, accurate values of representative SSA for depth hoar became critical as retrieval errors were exceeded if the median depth hoar SSA was applied.

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