Zhou, L; Stroeve, J; Xu, S; Petty, A; Tilling, R; Winstrup, M; Rostosky, P; ... Nandan, V; + view all Zhou, L; Stroeve, J; Xu, S; Petty, A; Tilling, R; Winstrup, M; Rostosky, P; Lawrence, IR; Liston, GE; Ridout, A; Tsamados, M; Nandan, V; - view fewer (2021) Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval. Cryosphere , 15 (1) pp. 345-367. 10.5194/tc-15-345-2021.

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Abstract

In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March-April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial-temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations.

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