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https://doi.org/10.5194/tc-2019-305
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-305
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 03 Feb 2020

Submitted as: research article | 03 Feb 2020

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This preprint is currently under review for the journal TC.

Local-scale variability of snow density on Arctic sea ice

Joshua King1, Stephen Howell1, Mike Brady1, Peter Toose1, Chris Derksen1, Christian Haas2, and Justin Beckers3,4 Joshua King et al.
  • 1Climate Research Division, Environment and Climate Change Canada, Toronto, M3H5T4, Canada
  • 2Alfred Wegner Institute of Polar and Marine Research, Bremerhaven, Germany
  • 3Department of Earth and Space Science and Engineering, York University, Toronto, Ontario, Canada
  • 4Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, T6G2E3, Canada

Abstract. Local-scale variations in snow density and layering on Arctic sea ice were characterized using a combination of traditional snow pit and SnowMicroPen (SMP) measurements. In total, 14 sites were evaluated within the Canadian Arctic Archipelago and Arctic Ocean on both first (FYI) and multi-year (MYI) sea ice. Sites contained multiple snow pits with coincident SMP profiles as well as unidirectional SMP transects. An existing SMP density model was recalibrated using manual density cutter measurements (n = 186) to identify best-fit parameters for the observed conditions. Cross-validation of the revised SMP model showed errors comparable to the expected baseline for manual density measurements (RMSE = 34 kg m−3 or 10.9 %) and strong retrieval skill (R2 = 0.78). The density model was then applied to SMP transect measurements to characterize variations at spatial scales of up to 100 m. A supervised classification trained on snow pit stratigraphy allowed separation of the SMP density estimates by layer-type. The resulting dataset contains 58,882 layer-classified estimates of snow density on sea ice representing 147 m of vertical variation and equivalent to more than 600 individual snow pits. An average bulk density of 310 kg m−3 was estimated with clear separation between FYI and MYI environments. Lower densities on MYI (277 kg m−3) corresponded with increased depth hoar composition (49.2 %), in strong contrast to composition of the thin FYI snowpack (19.8 %). Spatial auto-correlation analysis showed layered composition on FYI snowpack to persist over long distances while composition on MYI rapidly decorrelated at distances less than 16 m. Application of the SMP profiles to determine propagation bias in radar altimetry showed the potential errors of 0.5 cm when climatology is used over known snow density.

Joshua King et al.

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Joshua King et al.

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Latest update: 05 Apr 2020
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Short summary
Measurements of snow on sea ice are sparse, making it difficulty to judge if satellite estimates are correct or if we represent it well in models. Here, we introduce new measurements of snow properties on sea ice to better understand how it changes at distances less than 200 m. Our work shows that similarities in the snow structure are found at longer distances on younger ice than older ice.
Measurements of snow on sea ice are sparse, making it difficulty to judge if satellite estimates...
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