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Spatial and temporal variability of sea ice deformation rates in the Arctic Ocean observed by RADARSAT-1

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Sea ice deformation parameters are important for elucidation of the properties and characteristics of ice-ocean models. Observations of sea ice motion over 11.5 year period (November 1996–April 2008) are used… Click to show full abstract

Sea ice deformation parameters are important for elucidation of the properties and characteristics of ice-ocean models. Observations of sea ice motion over 11.5 year period (November 1996–April 2008) are used to calculate ice motion divergence and shear rates, and thus, to construct total deformation rate (TDR) estimates with respect to spatial and temporal variability in the Arctic Ocean. Strong sea ice deformation signal (SDS) rates are identified when TDR>0.01 day‒1, and very strong SDS events, when TDR>0.05 day‒1. These calculations are based on measurements made by the RADARSAT-1 Geophysical Processer System (RGPS). Statistical analysis of the SDS data suggest the following features: (1) Mean SDS and the SDS probability distributions are larger in “low latitudes” of the Arctic Ocean (less than 80°N) than in “high latitudes” (above 80°N), in both summer and winter; (2) very high SDS probabilities distributions and mean SDS values occur in coastal areas, e.g. the East Siberian Sea, Chukchi Sea and Beaufort Sea; (3) areas with relatively low TDR values, in the range from 0.01 day‒1 to 0.05 day‒1, cover much of the Arctic Ocean, in summer and winter; (4) of the entire TDR dataset, 45.89% belong to SDS, with summer the SDS percentage, 59.06%, and the winter SDS percentage, 40.50%. Statistically, the summer mean SDS, SDS percentage and very strong SDS are larger than corresponding values in the winter for each year, and show slight increasing tendencies during the years from 1997 to 2007. These results suggest important constraints for accurate simulations of very strong SDS in ice-ocean models.

Keywords: sea ice; sea; deformation; arctic ocean; sds

Journal Title: Science China Earth Sciences
Year Published: 2017

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