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The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort that provides high-quality, quality-controlled ocean biogeochemical bottle data with annual-updates, playing a crucial role in advancing our understanding of the Earth's oceans and their complex biogeochemical processes. This deliverable covers the GLODAP annual updates under the EuroSea funding, as well as the automatization of the quality control process of the data. Under the EuroSea funding, GLODAP has received three updates (GLODAPv2.2020, GLODAPv2.2021 and GLODAPv2.2022) with a total number of 245 cruises added, and in addition, a new version release (GLODAPv3) is planned. These updates were possible as a result of the large degree of automatization of the quality control process that ensures the accuracy of the data. The core of the quality control process is the crossover analysis that is currently performed via the 2nd QC Matlab toolbox from Lauvset and Tanhua (2015). However, following Eurosea’s vision of a user-focused, truly interdisciplinary, and responsive European ocean observing and forecasting system, this deliverable aims to migrate from the Matlab toolbox to an online web application based on the open-source software Django and Python. This will allow the user to simply upload the data file to be quality controlled and the web application performs the secondary quality control through the deep water crossover analysis just as in Matlab, and offers similar graphics for visualization. Because the crossover analysis is partially automated on this online tool, the users do not need to possess any programming knowledge in order to quality control their data. In addition, this online tool can be part of a fully automated GLODAP quality control process, without need for manual intervention.

Recent work suggests that Oxygen Minimum Zones (OMZs) are sustained by the supply of oxygen-poor waters rather than the export of organic matter from the local surface layer and its subsequent remineralization inside OMZs. However, the mechanisms that form and maintain OMZs are not well constrained, such as the origin of the oxygen that oxygenates OMZs, and the locations where oxygen consumption occurs. Here we use an observation-based transport matrix to determine the origins of open ocean OMZs in terms of (a) OMZ volume, (b) oxygen that survives remineralization and oxygenates OMZs, and (c) oxygen utilization in the interior ocean that contributes to the oxygen-deficit of OMZs. We also determine where the utilization of oxygen occurs along the pathways that ventilate the OMZs. Our results show that about half of the volume of OMZ waters originate in high-latitude regions, but most of their oxygen is utilized for remineralization before they reach OMZs. Instead, OMZs are mostly oxygenated by tropical, subtropical and intermediate waters formed in nearby regions. More than half of the utilization of oxygen occurs in the tropics and subtropics, while less than a third occurs within the OMZs themselves. We therefore suggest that, in steady-state, OMZs are primarily set by ocean circulation pathways that high-latitude deep and old water upwards, with relatively low oxygen content.

About a quarter of the total anthropogenic CO2 emissions during the industrial era has been absorbed by the ocean. The rate limiting step for this uptake is the transport of the anthropogenic carbon (Cant) from the ocean mixed layer where it is absorbed to the interior ocean where it is stored. While it is generally known that deep water formation sites are important for vertical carbon transport, the exact magnitude of the fluxes across the base of the mixed layer in different regions is uncertain. Here, we determine where, when, and how much Cant has been injected across the mixed-layer base and into the interior ocean since the start of the industrialized era. We do this by combining a transport matrix derived from observations with a time-evolving boundary condition obtained from already published estimates of ocean Cant. Our results show that most of the Cant stored below the mixed layer are injected in the subtropics (40.1%) and the Southern Ocean (36.0%), while the Subpolar North Atlantic has the largest fluxes. The Subpolar North Atlantic is also the most important region for injecting Cant into the deep ocean with 81.6% of the Cant reaching depths greater than 1,000 m. The subtropics, on the other hand, have been the most efficient in transporting Cant across the mixed-layer base per volume of water ventilated. This study shows how the oceanic Cant uptake relies on vertical transports in a few oceanic regions and sheds light on the pathways that fill the ocean Cant reservoir.

Submesoscale processes have a determinant role in the dynamics of oceans by transporting momentum, heat, mass, and particles. Furthermore, they can define niches where different phytoplankton species flourish and accumulate not only by nutrient provisioning but also by modifying the water column structure or active gathering through advection. In coastal areas, however, submesoscale oceanic processes act together with coastal ones, and their effect on phytoplankton distribution is not straightforward. The present study brings the relevance of hydrodynamic variables, such as vorticity, into consideration in the study of phytoplankton distribution, via the analysis of in situ and remote multidisciplinary data. In situ data were obtained during the ETOILE oceanographic cruise, which surveyed the Capbreton Canyon area in the southeastern part of the Bay of Biscay in early August 2017. The main objective of this cruise was to describe the link between the occurrence and distribution of phytoplankton spectral groups and mesoscale to submesoscale ocean processes. In situ discrete hydrographic measurements and multi-spectral chlorophyll a (chl a) fluorescence profiles were obtained in selected stations, while temperature, conductivity, and in vivo chl a fluorescence were also continuously recorded at the surface. On top of these data, remote sensing data available for this area, such as high-frequency radar and satellite data, were also processed and analysed. From the joint analysis of these observations, we discuss the relative importance and effects of several environmental factors on phytoplankton spectral group distribution above and below the pycnocline and at the deep chlorophyll maximum (DCM) by performing a set of generalized additive models (GAMs). Overall, salinity is the most important parameter modulating not only total chl a but also the contribution of the two dominant spectral groups of phytoplankton, brown and green algae groups. However, at the DCM, among