In this study, my colleague Yumeng Chen from the University of Reading, investigates 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 he estimates not only the sea-ice concentration, thickness and velocity, but also its level of damage, internal stress and cohesion. Specifically, he estimates the air drag coefficient and the so-called damage parameter of the MEB model. Mimicking the realistic observation network with different combinations of observations, he demonstrates 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, he shows that, with the current observation network, it is possible to improve both the observed and the unobserved model state forecast and parameter accuracy.

The paper, a contribution to COCO2 project, is entitled Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology, and is published in The Cryosphere.