Multivariate State And Parameter Estimation With Data Assimilation Applied To Sea-Ice Models Using A Maxwell Elasto-Brittle Rheology
International audience In this study, we investigate the fully multivariate state and parameter estimation through idealised simulations of a dynamics-only model that uses the novel Maxwell elasto-brittle (MEB) sea-ice rheology and in which we estimate not only the sea-ice concentration, thickness a...
Published in: | The Cryosphere |
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Main Authors: | , , , , , , , , |
Other Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2024
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Subjects: | |
Online Access: | https://insu.hal.science/insu-04604398 https://insu.hal.science/insu-04604398/document https://insu.hal.science/insu-04604398/file/tc-18-2381-2024.pdf https://doi.org/10.5194/tc-18-2381-2024 |
Summary: | International audience In this study, we investigate the fully multivariate state and parameter estimation through idealised simulations of a dynamics-only model that uses the novel Maxwell elasto-brittle (MEB) sea-ice rheology and in which we estimate not only the sea-ice concentration, thickness and velocity, but also its level of damage, internal stress and cohesion. Specifically, we estimate the air drag coefficient and the so-called damage parameter of the MEB model. Mimicking the realistic observation network with different combinations of observations, we demonstrate that various issues can potentially arise in a complex sea-ice model, especially in instances for which the external forcing dominates the model forecast error growth. Even though further investigation will be needed using an operational (a coupled dynamics–thermodynamics) sea-ice model, we show that, with the current observation network, it is possible to improve both the observed and the unobserved model state forecast and parameter accuracy. |
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