Assessing the impact of model formulation and resolution on Arctic sea ice variability and regional predictability

Rapid and dramatic changes that can have profound impacts on human activities and ecosystems have been observed in the Arctic over the past decades. As a result, there has been increased attention into understanding the trend towards decline of Pan-Arctic sea ice. However, there has been very less research into the systematic predictability of the coupled climate system in the Arctic, in particular at regional scales. The goal of this project is to improve our understanding of the dynamical processes controlling seasonal Arctic sea ice variations to identify the processes that are source of predictability on regional scales. More specifically, we seek to identify the dominant sources of Arctic sea ice variability and predictability during both summer and winter and characterize regional differences in the dominant processes. In addition to the year-to-year variability we will investigate regional differences in the character and mechanisms of the multi-year to multidecadal sea-ice changes. We plan to use the latest generation of state-of-the-art climate models developed at GFDL. We will compare models that have overly thin ice in the Arctic (CM2.1, 1o ocean, 2o atmosphere) to more realistic models that simulate thicker sea ice because of an improved atmosphere (FLOR, 1o ocean, 50km atmosphere; CM3, 1o ocean, 2o atmosphere with improved chemistry) or an improved ocean (CM2.5, 0.25o ocean, 50km atmosphere, CM2.6, 0.1o ocean, 50 km atmosphere) or because it assimilates data (ECDA). We will use control simulations of some of these climate models as well as perfect model predictability runs and quasi-operational initialized forecasts based on selected models. These models have significant differences in their mean state and variability, which will allow us to explore the impact of mean state and model configuration on Arctic sea ice variability and predictability, and to better understand the mechanisms of regional Arctic variability.

The proposed work is highly relevant to the CVP competition of the FY 2015 call on Understanding Arctic sea ice mechanisms and predictability. This proposal addresses one of NOAA strategic goals for the Arctic region, to provide forecasts of sea ice and understand and detect climate and ecosystem changes. Because of our close working relationships with the in-house developers of the model and forecast systems we plan to use, support for this proposal would likely have a direct impact on climate simulations and predictions at NOAA.