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. This study assesses the impact of different sea ice thicknessdistribution (ITD) discretizations on the sea ice concentration (SIC)variability in ocean stand-alone NEMO3.6–LIM3 simulations. Three ITDdiscretizations with different numbers of sea ice thickness categories andboundaries are evaluated against three different satellite products(hereafter referred to as “data”). Typical model and data interannual SICvariability is characterized by K-means clustering both in the Arctic andAntarctica between 1979 and 2014. We focus on two seasons, winter(January–March) and summer (August–October), in which correlationcoefficients across clusters in individual months are largest. In theArctic, clusters are computed before and after detrending the series with a second-degree polynomial to separate interannual from longer-term variability.The analysis shows that, before detrending, winter clusters reflect the SICresponse to large-scale atmospheric variability at both poles, while summerclusters capture the negative and positive trends in Arctic and AntarcticSIC, respectively. After detrending, Arctic clusters reflect the SIC responseto interannual atmospheric variability predominantly. The cluster analysisis complemented with a model–data comparison of the sea ice extent and SICanomaly patterns. The single-category discretization shows the worst model–data agreement inthe Arctic summer before detrending, related to a misrepresentation of thelong-term melting trend. Similarly, increasing the number of thin categoriesreduces model–data agreement in the Arctic, due to a poor representation ofthe summer melting trend and an overly large winter sea ice volumeassociated with a net increase in basal ice growth. In contrast, more thincategories improve model realism in Antarctica, and more thick ones improveit in central Arctic regions with very thick ice. In all the analyses wenonetheless identify no optimal discretization. Our results thus suggestthat no clear benefit in the representation of SIC variability is obtainedfrom increasing the number of sea ice thickness categories beyond thecurrent standard with five categories in NEMO3.6–LIM3.

Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model