Sea ice leads in the Arctic Ocean: Model assessment, interannual variability and trends

Abstract

Sea ice leads in the Arctic are important features that give rise to strong localized atmospheric heating; they provide the opportunity for vigorous biological primary production, and predicting leads may be of relevance for Arctic shipping. It is commonly believed that traditional sea ice models that employ elastic‐viscous‐plastic (EVP) rheologies are not capable of properly simulating sea ice deformation, including lead formation, and thus, new formulations for sea ice rheologies have been suggested. Here we show that classical sea ice models have skill in simulating the spatial and temporal variation of lead area fraction in the Arctic when horizontal resolution is increased (here 4.5 km in the Arctic) and when numerical convergence in sea ice solvers is considered, which is frequently neglected. The model results are consistent with satellite remote sensing data and discussed in terms of variability and trends of Arctic sea ice leads. It is found, for example, that wintertime lead area fraction during the last three decades has not undergone significant trends.

A 4.5 km resolution Arctic Ocean simulation with the global multi-resolution model FESOM 1.4

“…14). At 4.5 km, the sea ice model starts to capture some small-scale features (sea ice leads) with reasonable spatial and temporal variability (Wang et al, 2016c). However, the mean sea ice thickness and concentration are not impacted by whether those small-scale features are represented or not in the model.…”

“…2a). Mesh LOW has been used in the CORE-II model intercomparison studies, and mesh HIGH has been used in a recent study on Arctic sea ice leads (Wang et al, 2016c). Judged by comparing the Rossby radius and grid size (Fig.…”

“…On the mesh, the resolution can vary in space conveniently according to given functions chosen for particular applications. Many ocean process studies have been carried out making use of FESOM in global and regional simulations, for example, with focus on overflows , ice shelf cavities (Timmermann et al, 2012), deep water formation (Scholz et al, 2013), polynyas (Haid and Timmermann, 2013), and Arctic sea ice and ocean dynamics (Wekerle et al, 2013;Wang et al, 2016c;Wekerle et al, 2017b). In global ocean climate simulations, the value of unstructured meshes can be more outstanding.…”

A 4.5 km resolution Arctic Ocean simulation with the global multi-resolution model FESOM1.4

“…14). At 4.5 km the sea ice model starts to capture some small scale features (sea ice leads) with reasonable spatial and temporal variability (Wang et al, 2016c). However, the mean sea ice thickness and concentration is not impacted by whether those small scale features 20 are represented or not in the model.…”

The Finite-volumE Sea ice–Ocean Model (FESOM2)

“…The Finite-Element Sea ice-Ocean circulation Model (FE-SOM, Wang et al, 2014) is the first mature global multiresolution model designed to simulate the large-scale ocean. A number of FESOM-based studies related to the impact of local dynamics on the global ocean (see, e.g., Hellmer et al, 2012;Haid and Timmermann, 2013;Wekerle et al, 2013;Haid et al, 2015;Wang et al, 2016a;Sein et al, 2016;Wekerle et al, 2016) indicate that the multi-resolution approach advocated by FESOM is successful and allows one to explore the impact of local processes on the global ocean with moderate computational effort (see Sein et al, 2016). Other new global multi-resolution models are appearing (see Ringler et al, 2013), and new knowledge on unstructured-mesh modeling has accumulated (for a review, see Danilov, 2013).…”