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Toward Optimization of Rheology in Sea Ice Models through Data Assimilation

Toward Optimization of Rheology in Sea Ice Models through Data Assimilation AbstractSea ice models that allow for deformation are primarily based on rheological formulations originally developed in the 1970s. In both the original viscoplastic (VP) and elastic-VP schemes, the internal pressure term is modeled as a function of variable sea ice thickness and concentration with spatially and temporally constant empirical parameters for ice strength. This work considers a spatially variable extension of the rheology parameters as well as wind stress in a one-dimensional VP sea ice data assimilation system. In regions of total ice cover, experiments that assimilate synthetic ice-state observations using variable rheological parameters show larger improvements than equivalent experiments using homogeneous parameters. For partially ice-covered regions where internal ice stresses are relatively unimportant, experiments assimilating synthetic sea ice velocity observations demonstrate reasonable reconstruction of spatially variable wind stresses. These results suggest practical benefits for sea ice–state reconstruction and forecasts by using sea ice velocity, thickness, and concentration observations to optimize spatially varying rheological parameters and to improve wind stress forcing. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

Toward Optimization of Rheology in Sea Ice Models through Data Assimilation

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References (65)

Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
eISSN
1520-0426
DOI
10.1175/JTECH-D-18-0239.1
Publisher site
See Article on Publisher Site

Abstract

AbstractSea ice models that allow for deformation are primarily based on rheological formulations originally developed in the 1970s. In both the original viscoplastic (VP) and elastic-VP schemes, the internal pressure term is modeled as a function of variable sea ice thickness and concentration with spatially and temporally constant empirical parameters for ice strength. This work considers a spatially variable extension of the rheology parameters as well as wind stress in a one-dimensional VP sea ice data assimilation system. In regions of total ice cover, experiments that assimilate synthetic ice-state observations using variable rheological parameters show larger improvements than equivalent experiments using homogeneous parameters. For partially ice-covered regions where internal ice stresses are relatively unimportant, experiments assimilating synthetic sea ice velocity observations demonstrate reasonable reconstruction of spatially variable wind stresses. These results suggest practical benefits for sea ice–state reconstruction and forecasts by using sea ice velocity, thickness, and concentration observations to optimize spatially varying rheological parameters and to improve wind stress forcing.

Journal

Journal of Atmospheric and Oceanic Technology – American Meteorological Society

Published: Dec 23, 2019

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