Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology

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 i...

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Bibliographic Details
Published in:The Cryosphere
Main Authors: Chen, Yumeng, Smith, Polly, Carrassi, Alberto, Pasmans, Ivo, Bertino, Laurent, Bocquet, Marc, Sebastian Finn, Tobias, Rampal, Pierre, Dansereau, VĂ©ronique
Format: Article in Journal/Newspaper
Language:English
Published: European Geosciences Union 2024
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Online Access:https://centaur.reading.ac.uk/116449/
https://centaur.reading.ac.uk/116449/9/tc-18-2381-2024.pdf
https://centaur.reading.ac.uk/116449/1/egusphere-2023-1809-manuscript-version4.pdf
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Summary: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.