Abstract
Abstract. We propose a method to reduce the error generated when computing sea ice deformation fields from synthetic aperture radar (SAR)-derived sea ice motion. The method is based on two steps. The first step consists of using a triangulation of the positions taken from the sea ice trajectories to define a mesh on which a first estimate of sea ice deformation is computed. The second step consists of applying a specific smoother to the deformation field to reduce the artificial noise that arises along discontinuities in the sea ice motion field. This method is here applied to RADARSAT Geophysical Processor System (RGPS) sea ice trajectories having a temporal and spatial resolution of about 3 days and 10 km, respectively. From the comparison between unfiltered and filtered fields, we estimate that the artificial noise causes an overestimation of about 60% of opening and closing. The artificial noise also has a strong impact on the statistical distribution of the deformation and on the scaling exponents estimated with multifractal analysis. We also show that a similar noise is present in the deformation fields provided in the widely used four-point deformation RGPS data set. These findings may have serious implications for previous studies as the constant overestimation of the opening and closing could lead to a large overestimation of freezing in leads, salt rejection and sea ice ridging.
Highlights
Sea ice motion can be retrieved from satellite synthetic aperture radar (SAR) images using cross-correlation techniques and feature tracking algorithms (Kwok et al, 1990; Fily et al, 1990; Hollands and Dierking, 2011)
To validate the choice of the method’s parameters (i.e., n and the deformation threshold), we present in Sect. 3 another metric based on a multifractal scaling analysis of the deformation fields
To compare the original RADARSAT Geophysical Processor System (RGPS) deformation data with the unfiltered and filtered deformation data produced by our method, we generate composite pictures of the deformation rates for specific periods
Summary
Sea ice motion can be retrieved from satellite synthetic aperture radar (SAR) images using cross-correlation techniques and feature tracking algorithms (Kwok et al, 1990; Fily et al, 1990; Hollands and Dierking, 2011). Sea ice deformation is estimated by computing the spatial derivatives of the sea ice motion. The most popular data set providing both sea ice motion and deformation is the RADARSAT Geophysical Processor System (RGPS) data set (Kwok, 1998). It covers the western Arctic for the period 1996–2008 at temporal and spatial resolution of about 3 days and 10 km, respectively. Kwok et al (2008) showed that the deformation-related ice production derived from the RGPS data set is up to 2 times higher than the one estimated by numerical models, implying a potential underestimate of the associated sea ice–ocean feedbacks Using the RGPS data set, Kwok (2006) estimated that deformationrelated ice production is about 25–40 % of the winter ice production in both the perennial and seasonal ice zones. Kwok et al (2008) showed that the deformation-related ice production derived from the RGPS data set is up to 2 times higher than the one estimated by numerical models, implying a potential underestimate of the associated sea ice–ocean feedbacks
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