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

Chen, Yumeng; Smith, Polly; Carrassi, Alberto; Pasmans, Ivo; Bertino, Laurent; Bocquet, Marc; Finn, Tobias Sebastian; Rampal, Pierre; Dansereau, Véronique

doi:https://doi.org/10.5194/tc-18-2381-2024

Articles | Volume 18, issue 5

https://doi.org/10.5194/tc-18-2381-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-18-2381-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 5

Research article

|

14 May 2024

Research article |

| 14 May 2024

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

Yumeng Chen, Polly Smith, Alberto Carrassi, Ivo Pasmans, Laurent Bertino, Marc Bocquet, Tobias Sebastian Finn, Pierre Rampal, and Véronique Dansereau

Model code and software

Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology Yumeng Chen https://doi.org/10.5281/zenodo.8224997

Short summary

We explore multivariate state and parameter estimation using a data assimilation approach through idealised simulations in a dynamics-only sea-ice model based on novel rheology. We identify various potential issues that can arise in complex operational sea-ice models when model parameters are estimated. Even though further investigation will be needed for such complex sea-ice models, we show possibilities of improving the observed and the unobserved model state forecast and parameter accuracy.