Abstract
AbstractCoupled Model Intercomparison Project phase 5 (CMIP5) climate models simulate a wide range of historical sea ice areas. Even models with areas close to observed values may contain compensating errors, affecting reliability of their projections. This study focuses on the seasonal cycle of sea ice, including analysis of model concentration budgets. Many models have insufficient autumn ice growth, leading to large winter biases. A subset of models accurately represent sea ice evolution year‐round. However, comparing their winter ice concentration budget to observations reveals a range of behaviors. At least one model has an accurate ice budget, which is only possible due to realistic ice drifts. The CMIP5 generation of model physics and resolution is therefore structurally capable of accurately representing processes in Antarctic sea ice. This implies that substantially improved projections of Antarctic dense ocean water formation and ice sheet melting are possible with appropriate subsetting of existing climate models.
Highlights
Antarctic sea ice constitutes a critical part of the global climate system
Coupled Model Intercomparison Project phase 5 (CMIP5) climate models simulate a wide range of historical sea ice areas
Since the ice concentration budget examines the rate of change of sea ice concentration (SIC), dC/dt (HK16), it is helpful to frame biases in terms of the seasonal evolution of ice area
Summary
Antarctic sea ice constitutes a critical part of the global climate system. Over the seasonal cycle, it changes in area by a factor of 6 through highly coupled ice, atmosphere, and ocean processes. Known discrepancies from satellite observations include recent trends ( this may be a result of internal variability; Swart & Fyfe, 2013; Zunz et al, 2013) and the frequency distribution of ice concentration (Roach et al, 2018) It has long been established (Bracegirdle et al, 2015; Raäisaänen, 2007) that there is a relationship between a model's historical sea ice area and how much the Antarctic region warms under greenhouse gas forcing. Uotila et al (2014) applied this technique to assess the CMIP5 models ACCESS1‐0 and ACCESS1‐3 (supporting information Table S1) and the ACCESS‐OM ocean‐sea ice model forced with prescribed atmospheric conditions They found that the models had too strong ice edge advection as a result of ice drift biases, but this was balanced by excessive melting to produce realistic ice evolution. Our key questions are (1) Do models with a realistic annual cycle of ice area have compensating biases in ice processes, and are any models sufficiently realistic to suggest reliability in projections? (2) Where process errors exist, can they be tied to dynamic or thermodynamic processes, and is there a clear link to the sea ice model used, to model resolution, or to forcing from coupled components?
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