A description of model intercomparison processes and techniques for ocean forecasting

<strong class="journal-contentHeaderColor">Abstract.</strong> The availability of numerical simulations for ocean dynamics past estimates or future forecast worldwide at multiple scales is opening new challenges in assessing their realism and predictive capacity through an intercomparison exercise. This requires a huge effort in designing and implementing a proper assessment of models' performances, as already demonstrated by the atmospheric community that was pioneering in that sense. Historically, the ocean community has only recently launched dedicated actions aimed at identifying robust patterns in eddy-permitting simulations: it required definition of modelling configurations, execution of dedicated experiments that also deal with the storing of the outputs and the implementation of evaluation frameworks. Starting from this baseline, numerous initiatives like WCRP/Climate Variability and Predictability (CLIVAR) for climate research and the Global Ocean Data Assimilation Experiment (GODAE) for operational systems have arisen and are actively promoting best practice through specific intercomparison tasks, aimed at demonstrating the efficient use of the Global Ocean Observing System and its operational capabilities, sharing expertise, and increasing the scientific quality of the numerical systems. Examples, like the Ocean Reanalysis Intercomparison Project (ORA-IP) or the Class 4 near-real-time GODAE intercomparison, are introduced and commented on, also discussing ways forward for making this kind of analysis more systematic using artificial intelligence approaches for addressing monitoring of ocean state in operations or facilitating in-house routine verification in ocean forecasting centres.