Regime-dependence when constraining a sea ice model with observations: lessons from a single-column perspective

Abstract

A substantial body of work has explored the use of sea ice concentration (SIC) and sea ice thickness (SIT) observations to initialize modeled estimates of the unobserved Arctic sea ice state via data assimilation (DA). While many recent studies have highlighted the particular value of incorporating SIT observations to this end, the influence of local sea ice conditions on the efficacy of assimilating various observation types has not been sufficiently evaluated. This work utilizes a single-column sea ice model to represent three common Arctic sea ice regimes: pack ice, seasonal ice, and first-year ice. An ensemble data assimilation framework is then used to assimilate synthetic observations of SIC, SIT, and two types of sea ice freeboard in each regime. Results demonstrate substantial variation in observation efficacy across observation types and sea ice conditions. In particular, SIT and laser altimeter freeboard observations are found to have a broadly positive impact in thick ice regimes, while SIC effectively constrains thinner, more marginal sea ice regimes. A need for regime-tailored DA strategies and further experimentation with underutilized sea ice observation types is strongly implied.