Preprints
https://doi.org/10.5194/egusphere-2023-2509
https://doi.org/10.5194/egusphere-2023-2509
15 Nov 2023
 | 15 Nov 2023

Snow Depth Estimation on Lead-less Landfast ice using Cryo2Ice satellite observations

Monojit Saha, Julienne Stroeve, Dustin Isleifson, John Yackel, Vishnu Nandan, Jack Christopher Landy, and Hoi Ming Lam

Abstract. Observations of snow on Arctic sea ice are vitally important for sea ice thickness estimation as well as for understanding bio-physical processes and human-activities. This study is the first assessment of the potential for near-coincident ICESat-2 and Cryosat-2 (Cryo2Ice) snow depth retrievals in a lead-less region of the Canadian Arctic Archipelago. Snow depths are retrieved using the absolute difference in surface height from a near-coincident ICESat-2 and Cryosat-2 after applying an ocean tide correction between satellite passes 77 minutes apart. Both the absolute mean snow depths and snow depth distributions retrieved from Cryo2Ice compare favourably to in-situ measurements. All four in-situ sites had snow with saline basal layers and different levels of roughness/ridging. The retrieved Cryo2Ice snow depths were underestimated by an average of 20.7 % which is slightly higher than the tidal adjustment applied. Differences in the Cryo2Ice and in-situ snow depth distributions reflected the different sampling resolutions between the sensors and the in-situ measurements, with more heavily ridged areas producing larger mean underestimation of the snow depth. Results suggest the possibility of estimating snow depth over lead-less landfast sea ice but attributing 2–3 cm biases to differences in sampling resolution, snow salinity, density, surface roughness and/or errors in altimeter’s tidal corrections require further investigation.

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Short summary
Snow on sea ice is vital for near-shore sea ice geophysical and biological processes. Past...