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Reconstruction of the Rheological Parameters in a Sea Ice Model with Viscoplastic Rheology

Gleb PanteleevaNaval Research Laboratory, Stennis Space Center, Mississippi

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Max YaremchukaNaval Research Laboratory, Stennis Space Center, Mississippi

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Oceana FrancisbUniversity of Hawai‘i at Mānoa, Honolulu, Hawaii

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Online Publication:
27 Jan 2023
Print Publication:
01 Jan 2023
DOI:
https://doi.org/10.1175/JTECH-D-21-0158.1
Page(s):
141–157
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Abstract

We analyzed the feasibility of the reconstruction of the spatially varying rheological parameters through the four-dimensional variational data assimilation of the sea ice velocity, thickness, and concentration into the viscoplastic (VP) sea ice model. The feasibility is assessed via idealized variational data assimilation experiments with synthetic observations configured for a 1-day data assimilation window in a 50 × 40 rectangular basin forced by the open boundaries, winds, and ocean currents and should be viewed as a first step in the developing the similar algorithms which can be applied for the more advanced sea ice models. It is found that “true” spatial variability (∼5.8 kN m−2) of the internal maximum ice strength parameter P* can be retrieved from observations with reasonable accuracy of 2.3–5.3 kN m−2, when an observation of the sea ice state is available daily in each grid point. Similar relative accuracy was achieved for the reconstruction of the compactness strength parameter α. The yield curve eccentricity e is found to be controlled by the data with less efficiency, but the spatial mean value of e could be still reconstructed with a similar degree of confidence. The accuracy of P*, α, and e retrievals is found to increase in regions of stronger ice velocity convergence, providing prospects for better processing of the observations collected during the recent MOSAiC experiment. The accuracy of the retrievals strongly depends on the number of the control variables characterizing the rheological parameter fields.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Gleb Panteleev, gleb.panteleev@nrlssc.navy.mil

Abstract

We analyzed the feasibility of the reconstruction of the spatially varying rheological parameters through the four-dimensional variational data assimilation of the sea ice velocity, thickness, and concentration into the viscoplastic (VP) sea ice model. The feasibility is assessed via idealized variational data assimilation experiments with synthetic observations configured for a 1-day data assimilation window in a 50 × 40 rectangular basin forced by the open boundaries, winds, and ocean currents and should be viewed as a first step in the developing the similar algorithms which can be applied for the more advanced sea ice models. It is found that “true” spatial variability (∼5.8 kN m−2) of the internal maximum ice strength parameter P* can be retrieved from observations with reasonable accuracy of 2.3–5.3 kN m−2, when an observation of the sea ice state is available daily in each grid point. Similar relative accuracy was achieved for the reconstruction of the compactness strength parameter α. The yield curve eccentricity e is found to be controlled by the data with less efficiency, but the spatial mean value of e could be still reconstructed with a similar degree of confidence. The accuracy of P*, α, and e retrievals is found to increase in regions of stronger ice velocity convergence, providing prospects for better processing of the observations collected during the recent MOSAiC experiment. The accuracy of the retrievals strongly depends on the number of the control variables characterizing the rheological parameter fields.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Gleb Panteleev, gleb.panteleev@nrlssc.navy.mil
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