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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/tc-2019-167
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-167
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 25 Jul 2019

Submitted as: research article | 25 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

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

Nick Rutter1, Melody J. Sandells2, Chris Derksen3, Joshua King3, Peter Toose3, Leanne Wake1, Tom Watts1, Richard Essery4, Alexandre Roy5, Alain Royer6, Philip Marsh7, Chris Larsen8, and Matthew Sturm8 Nick Rutter et al.
  • 1Department of Geography and Environmental Sciences, Northumbria University, Newcastle upon Tyne, UK
  • 2CORES Science and Engineering Limited, Burnopfield, UK
  • 3Climate Research Division, Environment and Climate Change Canada, Toronto, Canada
  • 4School of GeoSciences, University of Edinburgh, UK
  • 5Département des Sciences de l'Environment, Université du Québec à Trois-Rivières, Canada
  • 6Département de Géomatique Appliquée, Université de Sherbrooke, Canada
  • 7Department of Geography, Wilfrid Laurier University, Canada
  • 8Geophysical Institute, University of Alaska, Fairbanks, USA

Abstract. 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 first guess information of 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 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 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 < 0.6 m, 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 ~ 30 cm, accurate values of representative SSA for depth hoar became critical as retrieval errors were exceeded if the median depth hoar SSA was applied.

Nick Rutter et al.
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Nick Rutter et al.
Data sets

Snow pits and trenches N. Rutter https://doi.org/10.6084/m9.figshare.8397737.v2

Lidar snow depths C. Larsen https://doi.org/10.6084/m9.figshare.8397467.v1

Air temperatures Environment Canada https://doi.org/10.6084/m9.figshare.8397419.v1

Catchment topography and locations of snow pits / trenches P. Toose https://doi.org/10.6084/m9.figshare.8397023.v1

Nick Rutter et al.
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Latest update: 18 Aug 2019
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Short summary
Impact was assessed of natural variability in Arctic tundra snow microstructural characteristics on the capacity to estimate snow water equivalent (SWE) from Ku-band radar. Median values of metrics quantifying snow microstructure adequately characterise differences between snowpack layers. Optimal estimates of SWE required microstructural values slightly less than the measured median, but tolerated natural variability for accurate estimation of SWE in shallow snowpacks.
Impact was assessed of natural variability in Arctic tundra snow microstructural characteristics...
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