In this article, Part 1 of a two-part series, we run and evaluate the skill of a regional physical–biogeochemical stochastic ocean model based on NEMO. The domain covers the Bay of Biscay at 1/36° resolution, as a case study for open-ocean and coastal shelf dynamics. We generate model ensembles based on assumptions about errors in the atmospheric forcing, the ocean model parameterizations and in the sources and sinks of the biogeochemical variables. The resulting errors are found to be mainly driven by the wind forcing uncertainties, with the rest of the perturbed forcing and parameters locally influencing the ensemble spread. Biogeochemical uncertainties arise from intrinsic ecosystem model errors and from errors in the physical state. Uncertainties in physical forcing and parameterization are found to have a larger impact on chlorophyll spread than uncertainties in ecosystem sources and sinks. The ensembles undergo quantitative verification with respect to observations, focusing on upper-ocean properties. Despite a tendency for ensembles to be generally under-dispersive, they appear to be reasonably consistent with respect to sea surface temperature data. The largest statistical sea-level biases are observed in coastal regions. These biases hint at the presence of high-frequency error sources currently unaccounted for, and suggest that the ensemble-based uncertainties are unfit to model error covariances for assimilation. Model ensembles for chlorophyll appear to be consistent with ocean colour data only at times. The stochastic model is qualitatively evaluated by analysing its ability at generating consistent multivariate incremental model corrections. Corrections to physical properties are associated with large-scale biases between model and data, with diverse characteristics in the open-ocean and the shelves. Mesoscale features imprint their signature on temperature and sea-level corrections, as well as on chlorophyll corrections due to the vertical velocities associated with vortices. Small scale local corrections are visible over the shelves. Chlorophyll information has measurable impact on physical variables.

In this Part 2 article of a two-part series, observations based on satellite missions were used to evaluate the empirical consistency of model ensembles generated via stochastic modelling of ocean physics and biogeochemistry. A high-resolution Bay of Biscay configuration was used as a case study to explore the model error subspace in both the open and coastal ocean. In Part 1 of this work, three experiments were carried out to generate model ensembles by perturbing only physics, only biogeochemistry, and both of them simultaneously. In Part 2 of this work, empirical consistency was checked, first by means of rank histograms projecting the data onto the model ensemble classes, and second, by pattern-selective consistency criteria in the space of “array modes” defined as eigenvectors of the representer matrix. Rank histograms showed large dependency on geographical region and on season for sea surface temperature (SST), sea-level anomaly (SLA), and phytoplankton functional types (PFT), shifting from consistent model-data configurations to large biases because of model ensemble underspread. Consistency for SST array modes was found to be verified at large, small and coastal scales soon after the ensemble spin-up. Array modes for the along-track sea-level showed useful consistent information at large scales and at the mesoscale; for the gridded SLA was verified only at large scale. Array modes showed that biogeochemical model uncertainties generated by stochastic physics, were effectively detected by PFT measurements at large scales, as well as at mesoscale and small-scale. By contrast, perturbing only biogeochemistry, with an identical physical forcing across the ensemble, limits the potential of PFT measurements at detecting and possibly correcting small-scale biogeochemical model errors. When an ensemble was found to be inconsistent with observations along a particular direction (here, an array mode), a plausible reason is that other error processes must have been active in the model, in addition to the ones at work across the ensemble.

A rich data set on particulate matter optical properties and parameters (beam attenuation coefficient, volume concentration, particle size and PSD slope), accompanied by measurements of biochemical indices (particulate organic carbon, particulate nitrogen and their stable isotopic composition) was obtained from the surface to deep waters across the Mediterranean Sea, in March-April 2018. A decrease of beam attenuation coefficients, total particle volume concentrations, particulate organic carbon and nitrogen concentrations was noted towards the eastern Mediterranean Sea (EMed) in comparison to the western Mediterranean Sea (WMed). LISST-derived optical properties were significantly correlated with water mass characteristics. Overall, the most turbid water mass identified in the Mediterranean Sea was the Surface Atlantic water (AW), and the most transparent was the Transitional Mediterranean Water (TMW) in the Cretan Sea, whereas a general decrease in particulate matter concentration is observed from the WMed towards the EMed. Relatively depleted δ13C-POC values in the particle pool of the open Mediterranean Sea can be attributed to contribution from terrestrial inputs, mainly via atmospheric deposition. Throughout the entire water column, a significant positive correlation between particle beam attenuation coefficient and particulate organic carbon concentration is observed in the open Mediterranean Sea. Such relationship suggests the predominance of organic particles with biogenic origin. POC concentration and particle median diameter D50 are significantly and negatively correlated both in the WMed and the EMed Sea, confirming that small particles are POC-rich. At depth, a prominent decrease of most measured parameters was observed, with the exception of particle median diameter that increased substantially in the EMed towards the deep sea, suggesting potentially enhanced aggregation processes. The low particle size distribution slope ξ observed in the EMed, corresponding to larger particle populations, supports the above notion. Basin-wide Rayleigh-type isotopic fractionation in vertical profiles of δ15N-PN across the Mediterranean Sea, underlines the differences in the trophic characters of the two sub-basins and highlights the role of circulation changes on biogeochemical parameters and the redistribution of particulate matter as a source of nutrients in the water column.