Abstract
Abstract. A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous–plastic (VP) sea-ice rheology are compared with synthetic aperture radar (SAR) satellite observations (RGPS, RADARSAT Geophysical Processor System) for the time period 1996–2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs) are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs) of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous–plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.
Highlights
The Arctic sea ice in many respects is an important component of the Earth’s climate system, e.g., sea ice governs the ocean-to-atmosphere heat flux, freezing and melting influences the upper ocean salinity and density, and sea-ice dynamics act as a latent energy transport (Barry et al, 1993)
Sea-ice deformations from coupled Arctic Ocean and seaice simulations with horizontal grid spacing of 18, 9, and 4.5 km were compared to RADARSAT Geophysical Processor System (RGPS) satellite observations during the 1992–2008 period
Lagrangian sea-ice drift was reconstructed from the three model solutions for a direct comparison with the RGPS data (Sect. 2.3), and noise related to the sampling of the Lagrangian data points was removed by an anisotropic filter (Sect. 2.4)
Summary
The Arctic sea ice in many respects is an important component of the Earth’s climate system, e.g., sea ice governs the ocean-to-atmosphere heat flux, freezing and melting influences the upper ocean salinity and density, and sea-ice dynamics act as a latent energy transport (Barry et al, 1993). Detailed comparisons between satellite remote sensing data with model results, reveal big differences in certain aspects of the sea-ice cover, e.g., for fracture zones and for small-scale dynamic processes (Kwok et al, 2008; Girard et al, 2009) It remains unclear whether current model physics are suited to reproduce these observed sea-ice deformation features (Coon et al, 2007) or if new sea-ice rheologies (e.g., Bouillon and Rampal, 2015b; Girard et al, 2011; Sulsky et al, 2007) have to be used. It contains an evaluation of the representation of sea-ice deformation dependencies on horizontal grid spacing, both spatially and as time series, and shows the power-law scaling behavior of the modeled and observed sea-ice deformation fields.
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