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Abstract. The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changingelement of the Earth system. Analyses of global-scale general circulationmodel (GCM) simulations, including those available through the Coupled ModelIntercomparison Project, Phase 6 (CMIP6), can help reveal the origins ofobserved changes and predict the future evolution of the ACSS. However, anevaluation of ACSS hydrography in GCMs is vital: previous CMIP ensemblesexhibit substantial mean-state biases (reflecting, for example, misplacedwater masses) with a wide inter-model spread. Because the ACSS are also asparely sampled region, grid-point-based model assessments are of limitedvalue. Our goal is to demonstrate the utility of clustering tools foridentifying hydrographic regimes that are common to different source fields(model or data), while allowing for biases in other metrics (e.g., water masscore properties) and shifts in region boundaries. We apply K-meansclustering to hydrographic metrics based on the stratification from one GCM(Community Earth System Model version 2; CESM2) and one observation-basedproduct (World Ocean Atlas 2018; WOA), focusing on the Amundsen,Bellingshausen and Ross seas. When applied to WOA temperature and salinityprofiles, clustering identifies “primary” and “mixed” regimes that havephysically interpretable bases. For example, meltwater-freshened coastalcurrents in the Amundsen Sea and a region of high-salinity shelf waterformation in the southwestern Ross Sea emerge naturally from the algorithm.Both regions also exhibit clearly differentiated inner- and outer-shelfregimes. The same analysis applied to CESM2 demonstrates that, althoughmean-state model biases in water mass T–S characteristics can be substantial,using a clustering approach highlights that the relative differences betweenregimes and the locations where each regime dominates are well representedin the model. CESM2 is generally fresher and warmer than WOA and has a limitedfresh-water-enriched coastal regimes. Given the sparsity of observations ofthe ACSS, this technique is a promising tool for the evaluation of a largermodel ensemble (e.g., CMIP6) on a circum-Antarctic basis.