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Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and spatial variability : The surface heat budget of arctic ocen (SHEBA)
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In this article, the evolution and spatial distribution of the snow cover on the sea ice of the Arctic Ocean was observed during the Surface Heat Budget of Arctic Ocean (SHEBA) project, and two basic types of snow were present: depth hoar and wind slab.Abstract:
[1] The evolution and spatial distribution of the snow cover on the sea ice of the Arctic Ocean was observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The snow cover built up in October and November, reached near maximum depth by mid-December, then remained relatively unchanged until snowmelt. Ten layers were deposited, the result of a similar number of weather events. Two basic types of snow were present: depth hoar and wind slab. The depth hoar, 37% of the pack, was produced by the extreme temperature gradients imposed on the snow. The wind slabs, 42% of the snowpack, were the result of two storms in which there was simultaneous snow and high winds (>10 m s -1 ). The slabs impacted virtually all bulk snow properties emphasizing the importance of episodic events in snowpack development. The mean snow depth (n = 21,169) was 33.7 cm with a bulk density of 0.34 g cm -3 (n = 357, r 2 of 0.987), giving an average snow water equivalent of 11.6 cm, 25% higher than the amount record by precipitation gauge. Both depth and stratigraphy varied significantly with ice type, the greatest depth, and the greatest variability in depth occurring on deformed ice (ridges and rubble fields). Across all ice types a persistent structural length in depth variations of ∼20 m was found. This appears to be the result of drift features at the snow surface interacting with small-scale ice surface structures. A number of simple ways of representing the complex temporal and spatial variations of the snow cover in ice-ocean-atmosphere models are suggested.read more
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