Spectral attenuation of gravity wave and model calibration in pack ice

We investigate an instance of wave propagation in the fall of 2015 in thin pack ice (<0.3 m) and use the resulting attenuation data to calibrate two viscoelastic wave-in-ice models that describe wave evolution. The study domain is 400 km by 300 km adjacent to a marginal ice zone (MIZ) in the Beau...

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Bibliographic Details
Main Authors: Cheng, Sukun, Stopa, Justin, Ardhuin, Fabrice, Shen, Hayley H.
Format: Text
Language:English
Published: 2019
Subjects:
Online Access:https://doi.org/10.5194/tc-2019-290
https://www.the-cryosphere-discuss.net/tc-2019-290/
Description
Summary:We investigate an instance of wave propagation in the fall of 2015 in thin pack ice (<0.3 m) and use the resulting attenuation data to calibrate two viscoelastic wave-in-ice models that describe wave evolution. The study domain is 400 km by 300 km adjacent to a marginal ice zone (MIZ) in the Beaufort Sea. From Sentinel-1A synthetic aperture radar (SAR) imagery, the ice cover is divided into two regions delineated by the first appearance of leads. According to the quality of SAR retrievals, we focus on a range of wavenumbers corresponding to 9∼15 s waves from the open water dispersion relation. By pairing directional wave spectra from different locations, we obtain wavenumber-dependent attenuation rates, which slightly increase with increasing wavenumber before the first appearance of leads and become lower and more uniform against wavenumber in thicker ice after that. The results are used to calibrate two viscoelastic wave-in-ice models through optimization. For the Wang and Shen (2010) model, the calibrated equivalent shear modulus and viscosity of the pack ice are roughly one order of magnitude greater than that in grease/pancake ice reported in Cheng et al. (2017). These parameters obtained for the extended Fox and Squire model are much larger than laboratory values, as found in Mosig et al. (2015) using data from the Antarctic MIZ. This study shows a promising way of using remote sensing data with large areal coverage to conduct model calibration for various types of ice cover.