Cluster-based ocean model evaluation on the Antarctic continental shelf

A wealth of coupled climate model simulations has recently become available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6) ensemble. Evaluation of the representation of the Antarctic continental shelf seas across CMIP6 models is critical: regional water mass properties are used to drive sea level projections from the Antarctic ice sheet, and previous CMIP ensembles show substantial biases with a wide inter-model and inter-region spread. However, the Antarctic continental shelf seas remain sparsely sampled, posing challenges for model-data comparison.

Here, we employ a new cluster-based, grid-independent, methodology to identify and compare regional water masses, focusing on the Pacific sector of the Antarctic continental shelf seas. We find that temperature is insufficient to differentiate water masses, given the complexity and diversity of hydrographic profiles on the continental shelf. In contrast, clustering approaches applied to World Ocean Atlas 2018 temperature and salinity profiles identify “source” and “mixed” regimes that have a physically interpretable basis. For example, meltwater-freshened coastal currents in the Amundsen Sea, and high salinity shelf water formation regions in the western Ross Sea, emerge naturally from the algorithm. Both regions also exhibit clearly differentiated inner-and outer-shelf water masses.

We then compare the locations and properties of observed regimes to those derived from the modern hydrographic state of the Community Earth System Model, version 2 (CESM2). Although model biases can be substantial, the locations of distinct regimes, and inter-cluster differences in water mass properties, are often well-represented. Differences in the locations and properties of hydrographic regimes between CESM2 and WOA18 are used to discuss the missing or poorly represented physical processes in the Antarctic continental shelf seas of the CESM2. We conclude by demonstrating the application of this method to other CMIP6 historical simulations, as well as the sparsely distributed in-situ profile data in the World Ocean Database.