Novel methods to study sea ice deformation, linear kinematic features and coherent dynamic elements from imaging remote sensing data

Abstract. Satellite Synthetic Aperture Radar (SAR) data are commonly utilized for calculating sea ice displacements and, consequently, sea ice deformation strain rates. However, strain rate calculations often suffer from a poor signal-to-noise ratio, especially for products with a spatial resolution higher than 1 km. In this study, we applied a new filtering method to strain rate calculations derived from Sentinel-1 SAR image pairs with a spatial resolution of 800 m. Subsequently, we employed a power law to evaluate the deformation rates at decreasing spatial resolutions, assessing the quality of the filtered data. Upon positive evaluation of the filtered data, we introduced two innovative methods for sea ice deformation assessment. The first method, named 'damage parcels' (DP) tracking, involved the combined analysis of displacements and deformation strain rates to monitor divergence and convergence within the sea ice cover. Additionally, we proposed a new term to describe the behavior of the winter pack: 'Coherent Dynamic Elements' (CDE). CDEs are cohesive clusters of ice plates within the pack ice that move coherently along Linear Kinematic Features (LKFs). The second novel method developed in this study focused on exploring the geometrical properties of these CDEs. Both methods were applied to the winter collection of Sentinel-1 SAR imagery available during the N-ICE2015 campaign. Our results revealed a cyclically changing winter sea ice cover, marked by synoptic events and transitions from pack ice to the marginal ice zone. The DP were continuously tracked over a period of three weeks, including a major storm, revealing a remarkably slow healing process of existing LKFs. Furthermore, the CDE analysis demonstrated the presence of elongated CDEs with a density ranging from 5 to 20 per 100 km by 100 km, and the shortest distance between LKFs was found to be 5–10 km.