Leads and ridges in Arctic sea ice from RGPS data and a new tracking algorithm

Abstract

Abstract. Leads and pressure ridges are dominant features of the Arctic sea ice cover. Not only do they affect heat loss and surface drag, but they also provide insight into the underlying physics of sea ice deformation. Due to their elongated shape they are referred to as linear kinematic features (LKFs). This paper introduces two methods that detect and track LKFs in sea ice deformation data and establish an LKF data set for the entire observing period of the RADARSAT Geophysical Processor System (RGPS). Both algorithms are available as open-source code and applicable to any gridded sea ice drift and deformation data. The LKF detection algorithm classifies pixels with higher deformation rates compared to the immediate environment as LKF pixels, divides the binary LKF map into small segments, and reconnects multiple segments into individual LKFs based on their distance and orientation relative to each other. The tracking algorithm uses sea ice drift information to estimate a first guess of LKF distribution and identifies tracked features by the degree of overlap between detected features and the first guess. An optimization of the parameters of both algorithms, as well as an extensive evaluation of both algorithms against handpicked features in a reference data set, is presented. A LKF data set is derived from RGPS deformation data for the years from 1996 to 2008 that enables a comprehensive description of LKFs. LKF densities and LKF intersection angles derived from this data set agree well with previous estimates. Further, a stretched exponential distribution of LKF length, an exponential tail in the distribution of LKF lifetimes, and a strong link to atmospheric drivers, here Arctic cyclones, are derived from the data set. Both algorithms are applied to output of a numerical sea ice model to compare the LKF intersection angles in a high-resolution Arctic sea ice simulation with the LKF data set.

Simulating intersection angles between conjugate faults in sea ice with different viscous–plastic rheologies

“…Hutter et al (2019) present an LKF tracking algorithm and show that fracture angles (half of the intersection angles) between LKFs in RGPS data follow a broad distribution that peaks around 20 • , in line with previous assessments (e.g., Walter and Overland, 1993). Hutter et al (2019) also show that the distribution of fracture angles in a VP simulation with 2 km grid spacing is biased, with a high modal value of 45 • and with too few small intersection angles between 15 and 25 • . The observed bias motivates the present investigation of the dependence of fracture angles in different VP rheologies and model settings, that is, scale, resolution, boundary conditions, model geometry, and variability in initial ice thickness field.…”

“…1), and c is the cohesion value (the value of σ II for σ I = 0) defined relative to the tensile strength by c = µ • T , where T is defined as a fraction of P . The theoretical angle of fracture θ can be calculated from the Mohr's circle of stress and yield curve written in the local (reference) coordinate system (Ip et al, 1991;Pritchard, 1988;Hibler and Schulson, 2000). Details are described in Appendix B.…”

“…The finite size of the grid spacing widens the deformation line, and the fracture spreads over several pixels because of the obliquity of the fracture. Automatic algorithms for measuring LKF intersection angles are described in Linow and Dierking (2017) and Hutter et al (2019). We solve the nonlinear sea ice momentum equations with a Picard or fixed point iteration with 1500 nonlinear or outerloop iterations.…”

“…This mechanism introduces an anisotropy in high-resolution simulations that is similar to observations with comparable spatial resolution. Lead characteristics, including intersection angles between LKFs, were studied a number of times (Lindsay and Rothrock, 1995;Hutchings et al, 2005;Wilchinsky et al, 2010;Bröhan and Kaleschke, 2014;Wang et al, 2016;Hutter et al, 2019). These studies show that VP models produce LKFs with various confinements, scales, resolutions, and forcings.…”

“…From observations with different instruments (Landsat, Seasat/SAR, areal photographs, AVHRR), typical fracture angles between intersecting LKFs of (15 ± 15) • emerge at scales from 1 to 100 km (Erlingsson, 1988;Walter and Overland, 1993). Hutter et al (2019) present an LKF tracking algorithm and show that fracture angles (half of the intersection angles) between LKFs in RGPS data follow a broad distribution that peaks around 20 • , in line with previous assessments (e.g., Walter and Overland, 1993). Hutter et al (2019) also show that the distribution of fracture angles in a VP simulation with 2 km grid spacing is biased, with a high modal value of 45 • and with too few small intersection angles between 15 and 25 • .…”