In this study, we use observations and numerical simulations to investigate the effect of meteorological parameters such as wind and atmospheric pressure on harbour water exchanges. The modelled information is obtained from the SAMOA (Sistema de Apoyo Meteorológico y Oceanográfico de la Autoridad Portuaria) forecasting system, which is a high-resolution numerical model for coastal and port-scale forecasting. Based on the observations, six events with high renewal times have been proposed for analysis using the SAMOA model. Therefore, the conclusions of this study have been possible due to the combination of observed data from the measurement campaigns and the information provided by the model. The results show that days with higher renewal times coincide with favourable wind-direction events or increases in atmospheric pressure. After analysing these events using model results, it was observed that during these episodes, water inflows were generated, and in some cases, there was a negative difference in levels between inside and outside the harbour produced by atmospheric pressure variations. The latter may be due to the fact that the water in the harbour (having a lower volume) descends faster and, therefore, generates a difference in level between the exterior and the interior and, consequently, inflow currents that imply an increase in the renewal time. These results are a demonstration of how meteorological information (normally available in ports) can be used to estimate currents and water exchanges between ports and their outer harbour area., This research received funding from the EuroSea project, under agreement with the European Social Fund (ESF) through a grant from FI AGAUR 2020 (Agency for the Management of University and Research Grants). This research has received funding from EuroSea project GA862626 funder H2020-EU.3.2.5.1 The authors want to acknowledge the ECO-BAYS research project (PID2020-115924RB-I00, financed by MCIN/AEI/10.13039/501100011033). The lead author has been financed by the Secretaria d’Universitats i Recerca de la Generalitat de Catalunya and the European Social Fund (ESF)., Peer Reviewed, Postprint (published version)

As the resolution of observations and models improves, emerging evidence indicates that ocean variability on 1–200‐km scales is of fundamental importance to ocean circulation, air‐sea interaction, and biogeochemistry. In many regions, salinity variability dominates over thermal effects in forming density fronts. Unfortunately, current satellite observations of sea surface salinity (SSS) only resolve scales ≥40 km (or larger, depending on the product). In this study, we investigate small‐scale variability (≲25 km) by reconstructing gridded SSS observations made by the Soil Moisture Active Passive (SMAP) satellite in the northwest Atlantic Ocean. Using altimetric geostrophic currents, we numerically advect SMAP SSS fields to produce a Lagrangian reconstruction that represents small scales. Reconstructed fields are compared to in‐situ salinity observations made by a ship‐board thermosalinograph, revealing a marked improvement in small‐scale salinity variability when compared to the original SMAP fields, particularly from the continental shelf to the Gulf Stream. In the Sargasso Sea, however, both SMAP and the reconstructed fields contain higher variability than is observed in situ. Enhanced small‐scale salinity variability is concentrated in two bands: a northern band aligned with the continental shelfbreak and a southern band aligned with the Gulf Stream mean position. Seasonal differences in the small‐scale variability appear to covary with the seasonal cycle of the large‐scale SSS gradients resulting from the freshening of the coastal waters during periods of elevated river outflow., This study has been developed in the framework of the (Sub)mesoscale Salinity Variability at Fronts project (NNX17AK04G) funded by the National Aeronautics and Space Administration (NASA). https://doi.org/10.20350/digitalCSIC/12830 (Barceló‐Llull et al., 2020). During the revision of the manuscript, Bàrbara Barceló‐Llull was working at IMEDEA (CSIC‐UIB, Spain) in the framework of the EuroSea project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 862626., Peer reviewed

The COVID-19 pandemic has resulted in unparalleled global impacts on human mobility. In the ocean, ship-based activities are thought to have been impacted due to severe restrictions on human movements and changes in consumption. Here, we quantify and map global change in marine traffic during the first half of 2020. There were decreases in 70.2% of Exclusive Economic Zones but changes varied spatially and temporally in alignment with confinement measures. Global declines peaked in April, with a reduction in traffic occupancy of 1.4% and decreases found across 54.8% of the sampling units. Passenger vessels presented more marked and longer lasting decreases. A regional assessment in the Western Mediterranean Sea gave further insights regarding the pace of recovery and long-term changes. Our approach provides guidance for large-scale monitoring of the progress and potential effects of COVID-19 on vessel traffic that may subsequently influence the blue economy and ocean health., D.M. and J.T. acknowledge support from the European Union’s Horizon 2020 research and innovation programme (Marie Skłodowska‐Curie grant agreement no. 794938, EuroSea grant agreement no. 862626 and JERICO-S3 grant agreement no. 871153). B.J.G. is supported by NERC Grant NE/V009354/1. K.M. is supported by the Waterloo Foundation, and the Darwin Initiative (Project 26-014) through funding from the Department for Environment, Food & Rural Affairs (Defra) in the UK., Peer reviewed

The increasing science and society requests for ocean monitoring from global to regional and local scales, the need for integration and convergence into a globally consistent ocean observing system as well as the need for improvement of access to information are now internationally recognized goals to progress toward the sustainable management of a healthy ocean. To respond to these challenges at regional level, the Balearic Islands Coastal Observing and Forecasting System (SOCIB) is developing a comprehensive set of ocean indicators in the Mediterranean Sea and around the Balearic Islands, key environments that are strongly affected by climate change and human pressure. This new SOCIB value-added product addresses the sub-regional ocean variability from daily (events) to interannual/decadal (climate) scales. A user-friendly interface has been implemented to monitor, visualize and communicate ocean information that is relevant for a wide range of sectors, applications and regional end-users. These sub-regional indicators allowed us to detect specific events in real time. Remarkable events and features identified include marine heat waves, atmospheric storm, extreme river discharge, mesoscale eddy, deep convection among others, all of them being oceanic phenomena that directly impact the ocean circulation and marine ecosystems. The long-term variations, in response to climate change, are also addressed highlighting and quantifying trends in physical and biogeochemical components of the ocean as well as sub-regional differences. At both (sub-) regional, national and international levels, a society-aligned science will have stronger impact on policy decision-makings and will support society to implement specific actions to address worldwide environmental challenges., Part of this work was supported by the JERICO-S3 and EuroSea projects. These projects have received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement Nos. 871153 and 862626, respectively.

Search and rescue (SAR) modeling applications, mostly based on Lagrangian tracking particle algorithms, rely on the accuracy of met-ocean forecast models. Skill assessment methods are therefore required to evaluate the performance of ocean models in predicting particle trajectories. The Skill Score (SS), based on the Normalized Cumulative Lagrangian Separation (NCLS) distance between simulated and satellite-tracked drifter trajectories, is a commonly used metric. However, its applicability in coastal areas, where most of the SAR incidents occur, is difficult and sometimes unfeasible, because of the high variability that characterizes the coastal dynamics and the lack of drifter observations. In this study, we assess the performance of four models available in the Ibiza Channel (Western Mediterranean Sea) and evaluate the applicability of the SS in such coastal risk-prone regions seeking for a functional implementation in the context of SAR operations. We analyze the SS sensitivity to different forecast horizons and examine the best way to quantify the average model performance, to avoid biased conclusions. Our results show that the SS increases with forecast time in most cases. At short forecast times (i.e., 6 h), the SS exhibits a much higher variability due to the short trajectory lengths observed compared to the separation distance obtained at timescales not properly resolved by the models. However, longer forecast times lead to the overestimation of the SS due to the high variability of the surface currents. Findings also show that the averaged SS, as originally defined, can be misleading because of the imposition of a lower limit value of zero. To properly evaluate the averaged skill of the models, a revision of its definition, the so-called SS∗, is recommended. Furthermore, whereas drifters only provide assessment along their drifting paths, we show that trajectories derived from high-frequency radar (HFR) effectively provide information about the spatial distribution of the model performance inside the HFR coverage. HFR-derived trajectories could therefore be used for complementing drifter observations. The SS is, on average, more favorable to coarser-resolution models because of the double-penalty error, whereas higher-resolution models show both very low and very high performance during the experiments., This work was supported by the IBISAR project funded by Mercator Ocean International User Uptake Program under the contract 67-UU-DO-CMEMS-DEM4_LOT7, and the EuroSea European Union’s Horizon 2020 Research and Innovation Program (grant agreement ID 862626). IBISAR was developed in close collaboration with the Spanish Maritime Safety and Rescue Agency and the Spanish Port System. IH-C was supported by the Vicenç Mut grant funded by the Government of the Balearic Island and the European Social Fund. We are also very grateful for the MEDCLIC project (LCF/PR/PR14/11090002) supported by La Caixa Foundation, contributing to the development of the WMOP model., Peer reviewed

The impact of the assimilation of HFR (high-frequency radar) observations in a high-resolution regional model is evaluated, focusing on the improvement of the mesoscale dynamics. The study area is the Ibiza Channel, located in the western Mediterranean Sea. The resulting fields are tested against trajectories from 13 drifters. Six different assimilation experiments are compared to a control run (no assimilation). The experiments consist of assimilating (i) sea surface temperature, sea level anomaly, and Argo profiles (generic observation dataset); the generic observation dataset plus (ii) HFR total velocities and (iii) HFR radial velocities. Moreover, for each dataset, two different initialization methods are assessed: (a) restarting directly from the analysis after the assimilation or (b) using an intermediate initialization step applying a strong nudging towards the analysis fields. The experiments assimilating generic observations plus HFR total velocities with the direct restart provide the best results, reducing by 53 % the average separation distance between drifters and virtual particles after the first 48 h of simulation in comparison to the control run. When using the nudging initialization step, the best results are found when assimilating HFR radial velocities with a reduction of the mean separation distance by around 48 %. Results show that the integration of HFR observations in the data assimilation system enhances the prediction of surface currents inside the area covered by both antennas, while not degrading the correction achieved thanks to the assimilation of generic data sources beyond it. The assimilation of radial observations benefits from the smoothing effect associated with the application of the intermediate nudging step., This research has been supported by the the EU Horizon 2020 JERICO-NEXT (grant agreement no. 654410) and EuroSea (grant agreement no. 862626) projects as well as MEDCLIC, a joint project between SOCIB and the “La Caixa” Foundation.

25 pages, 10 figures, 7 tables.-- This work is distributed under the Creative Commons Attribution 4.0 License, The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2021 is an update of the previous version, GLODAPv2.2020 (Olsen et al., 2020). The major changes are as follows: data from 43 new cruises were added, data coverage was extended until 2020, all data with missing temperatures were removed, and a digital object identifier (DOI) was included for each cruise in the product files. In addition, a number of minor corrections to GLODAPv2.2020 data were performed. GLODAPv2.2021 includes measurements from more than 1.3 million water samples from the global oceans collected on 989 cruises. The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have undergone extensive quality control with a focus on
systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but updated to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For this annual update, adjustments for the 43 new cruises were derived by comparing those data with the data from the 946 quality controlled cruises in the GLODAPv2.2020 data product using crossover analysis. Comparisons to estimates of nutrients and ocean CO2 chemistry based on empirical algorithms provided additional context for adjustment decisions in this version. The adjustments are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent with to better than 0.005 in salinity, 1% in oxygen, 2% in nitrate, 2% in silicate, 2% in phosphate, 4 μmolkg-1 in dissolved inorganic carbon, 4 μmolkg-1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5% in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments., The original data, their documentation, and DOI codes are available at the Ocean Carbon Data System of NOAA NCEI (https://www.ncei.noaa.gov/access/ocean-carbon-data-system/oceans/GLODAPv2_2021/, last access: 7 July 2021). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under https://doi.org/10.25921/ttgq-n825 (Lauvset et al., 2021). These bias-adjusted product files also include significant ancillary and approximated data and can be accessed via https://www.glodap.info (last access: 29 June 2021). These were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2021 methods and provides a broad overview of the secondary quality control procedures and results, This research has been supported by EU Horizon 2020 through the EuroSea action (grant no. 862626), internal strategic funding from NORCE Climate, Prociencia/UERJ (grant 2019–2021), IEO RADIALES and RADPROF projects, the UK Climate Linked Atlantic Sector Science (CLASS) NERC National Capability Long-term Single Centre Science Programme(grant no. NE/R015953/1), the BOCATS2 (PID2019-104279GBC21) project funded by MCIN/AEI/10.13039/501100011033 and contributing toWATER:iOS CSIC PTI, the NOAA Global Observations and Monitoring Division (fund reference 100007298), the Office of Oceanic and Atmospheric Research of NOAA Global Observations and Monitoring Division (fund reference 100007298), the Office of Oceanic and Atmospheric Research of NOAA, the BONUS INTEGRAL project (grant no. 03F0773A), the Australian Antarctic Program Partnership and the Integrated Marine Observing System, EU Horizon 2020 action SO-CHIC (grant no. 821001), and the Initiative and Networking Fund of the Helmholtz Association through the project “Digital Earth” (grant no. ZT-0025), Peer reviewed

Understanding and sustainably managing complex environments such as marine ecosystems benefits from an integrated approach to ensure that information about all relevant components and their interactions at multiple and nested spatiotemporal scales are considered. This information is based on a wide range of ocean observations using different systems and approaches. An integrated approach thus requires effective collaboration between areas of expertise in order to improve coordination at each step of the ocean observing value chain, from the design and deployment of multi-platform observations to their analysis and the delivery of products, sometimes through data assimilation in numerical models. Despite significant advances over the last two decades in more cooperation across the ocean observing activities, this integrated approach has not yet been fully realized. The ocean observing system still suffers from organizational silos due to independent and often disconnected initiatives, the strong and sometimes destructive competition across disciplines and among scientists, and the absence of a well-established overall governance framework. Here, we address the need for enhanced organizational integration among all the actors of ocean observing, focusing on the occidental systems. We advocate for a major evolution in the way we collaborate, calling for transformative scientific, cultural, behavioral, and management changes. This is timely because we now have the scientific and technical capabilities as well as urgent societal and political drivers. The ambition of the United Nations Decade of Ocean Science for Sustainable Development (2021–2030) and the various efforts to grow a sustainable ocean economy and effective ocean protection efforts all require a more integrated approach to ocean observing. After analyzing the barriers that currently prevent this full integration within the occidental systems, we suggest nine approaches for breaking down the silos and promoting better coordination and sharing. These recommendations are related to the organizational framework, the ocean science culture, the system of recognition and rewards, the data management system, the ocean governance structure, and the ocean observing drivers and funding. These reflections are intended to provide food for thought for further dialogue between all parties involved and trigger concrete actions to foster a real transformational change in ocean observing., This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 862626, project EuroSea (Improving and Integrating European Ocean Observing and Forecasting Systems for Sustainable Use of the Oceans)., Peer reviewed

Special issue “Advances in interdisciplinary studies at multiple scales in the Mediterranean Sea”. It is a result of the 8th MONGOOS Meeting & Workshop, Trieste, Italy, 3–5 December 2019.-- 57 pages, 9 figures, 1 table, 1 appendix, supplement https://doi.org/10.5194/os-18-997-2022-supplement.-- Data availability: Access to sea level data presented in this review is provided through national and international data portals and repositories quoted in Sects. 2 and 3 and in the Supplement, Employed for over a century, the traditional way of monitoring sea level variability by tide gauges – in combination with modern observational techniques like satellite altimetry – is an inevitable ingredient in sea level studies over the climate scales and in coastal seas. The development of the instrumentation, remote data acquisition, processing, and archiving in the last decades has allowed the extension of the applications to a variety of users and coastal hazard managers. The Mediterranean and Black seas are examples of such a transition – while having a long tradition of sea level observations with several records spanning over a century, the number of modern tide gauge stations is growing rapidly, with data available both in real time and as a research product at different time resolutions. As no comprehensive survey of the tide gauge networks has been carried out recently in these basins, the aim of this paper is to map the existing coastal sea level monitoring infrastructures and the respective data availability. The survey encompasses a description of major monitoring networks in the Mediterranean and Black seas and their characteristics, including the type of sea level sensors, measuring resolutions, data availability, and existence of ancillary measurements, altogether collecting information about 240 presently operational tide gauge stations. The availability of the Mediterranean and Black seas sea level data in the global and European sea level repositories has been also screened and classified following their sampling interval and level of quality check, pointing to the necessity of harmonization of the data available with different metadata and series in different repositories. Finally, an assessment of the networks' capabilities for their use in different sea level applications has been done, with recommendations that might mitigate the bottlenecks and ensure further development of the networks in a coordinated way, a critical need in the era of human-induced climate changes and sea level rise, This research has been partially supported by Horizon 2020 (EuroSea (grant no. 862626) and JERICO-S3 (grant no. 871153)), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

Society is facing climate-related challenges and impacts, such as marine heat wave (MHW) events that adversely affect ecosystems, threaten economies and strengthen storms by warming ocean waters. MHWs are substantially increasing in intensity, duration and frequency worldwide, particularly in the Mediterranean Sea, which responds rapidly to climate change. This study proposes a comprehensive analysis of MHWs in the different sub-regions of the Mediterranean, where the strong spatial variability requires focused attention, from surface to sub-surface and from open to coastal oceans. At surface, the MHW indices have dramatically increased over the last four decades from 1982 to 2020, with an unprecedented acceleration rate in recent years in all sub-regions. Besides the sub-regional features of surface MHWs, the propagation of such events into the ocean interior is also examined highlighting sub-regional and seasonal variability in the sub-surface ocean response. The resulting upper-ocean density stratification to these extreme events is enhanced in all sub-regions which would increase the degree of decoupling between surface and deep oceans causing changes in water masses and marine life. Finally, extremely warm events in coastal waters are also addressed through a case study in the Balearic Islands showing their higher intensity and occurrence in near-shore environment as well as the different response from surface to sub-surface that strongly depends on local features. In addition to this study, the Balearic Islands Coastal Observing and Forecasting System (SOCIB) has implemented a smart platform to monitor, visualize and share timely information on sub-regional MHWs, from event detection in real-time to long-term variations in response to global warming, to diverse stakeholders. Society-aligned ocean information at sub-regional scale will support the policy decision-making and the implementation of specific actions at local, national and regional scales, and thus contribute to respond to societal and worldwide environmental challenges., Part of this work was supported by the EuroSea project (www.eurosea.eu), which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 862626.

The Mediterranean Sea is a prominent climate-change hot spot, with many socioeconomically vital coastal areas being the most vulnerable targets for maritime safety, diverse met-ocean hazards and marine pollution. Providing an unprecedented spatial and temporal resolution at wide coastal areas, high-frequency radars (HFRs) have been steadily gaining recognition as an effective land-based remote sensing technology for continuous monitoring of the surface circulation, increasingly waves and occasionally winds. HFR measurements have boosted the thorough scientific knowledge of coastal processes, also fostering a broad range of applications, which has promoted their integration in coastal ocean observing systems worldwide, with more than half of the European sites located in the Mediterranean coastal areas. In this work, we present a review of existing HFR data multidisciplinary science-based applications in the Mediterranean Sea, primarily focused on meeting end-user and science-driven requirements, addressing regional challenges in three main topics: (i) maritime safety, (ii) extreme hazards and (iii) environmental transport process. Additionally, the HFR observing and monitoring regional capabilities in the Mediterranean coastal areas required to underpin the underlying science and the further development of applications are also analyzed. The outcome of this assessment has allowed us to provide a set of recommendations for future improvement prospects to maximize the contribution to extending science-based HFR products into societally relevant downstream services to support blue growth in the Mediterranean coastal areas, helping to meet the UN's Decade of Ocean Science for Sustainable Development and the EU's Green Deal goals., Publication fees are provided by EuroSea (EU Horizon 2020 research and innovation program, grant agreement ID no. 862626) and JERICO-S3 (EU Horizon 2020 research and innovation program, grant agreement ID no. 871153). Research was supported by the following projects: CMEMS-INSTAC phase II, which provides the context of the activities for HFR data harmonization, standardization and distribution; the IBISAR CMEMS User-Uptake project (67-UU-DO-CMEMS-DEM4_LOT7); MEDCLIC project (LCF/PR/PR14/11090002, supported by La Caixa Foundation) that contributed to the development of the WMOP model; the CARTHE III project (Prime Award no. SA 18-14, subcontract agreement SPC-000649) and CALYPSO Departmental Research Initiative (grant no. N00014-18-1-2782), which supported the development of the methodology for extreme event monitoring in the Ligurian Sea (Sect. 2.2.1); the IMPACT project (EU funded, PC Interreg VA IFM 2014–2020, Prot. ISMAR no. 0002269) that funded the HFR network in the Ligurian Sea; the JERICO-NEXT project (EU Horizon 2020, grant agreement no. 654410) under which the assimilation of HFR data in WMOP (Sect. 2.1.2) and the biological connectivity application in the Gulf of Manfredonia (Sect. 2.3.3) have been developed; the COCONET project (EU FP7, grant agreement no. 287844) and the Italian national projects SSDPESCA and RITMARE; and the SICOMAR-PLUS EU Interreg Marittimo project, which funded the recent upgrades to the HFR installations of the MIO in Toulon.

The population dynamics of small and middle-sized pelagic fish are subject to considerable interannual and interdecadal fluctuations in response to fishing pressure and natural factors. However, the impact of environmental forcing on these stocks is not well documented. The Moroccan Atlantic coast is characterized by high environmental variability due to the upwelling phenomenon, resulting in a significant abundance and variation in the catches of small and middle-sized pelagic species. Therefore, understanding the evolution of stock abundance and its relationship with different oceanographic conditions is a key issue for fisheries management. However, because of the limited availability of independent-fishery data along the Moroccan Atlantic coast, there is a lack of knowledge about the population dynamics. The main objective of this study is to test the correlation between the environment conditions and the stock fluctuations trends estimated by a stock assessment model that does not need biological information on growth, reproduction, and length or age structure as input. To achieve this objective, the fishery dynamics are analyzed with a stochastic surplus production model able to assimilate data from surveys and landings for a biomass trend estimation. Then, in a second step, the model outputs are correlated with different environmental (physical and biogeochemical) variables in order to assess the influence of different environmental drivers on population dynamics. This two-step procedure is applied for chub mackerel along the Moroccan coast, where all these available datasets have not been used together before. The analysis performed showed that larger biomass estimates are linked with periods of lower salinity, higher chlorophyll, higher net primary production, higher nutrients, and lower subsurface oxygen, i.e., with an enhanced strength of the upwelling. In particular, acute anomalies of these environmental variables are observed in the southern part presumably corresponding to the wintering area of the species in the region. The results indicate that this is a powerful procedure, although with important limitations, to deepen our understanding of the spatiotemporal relationships between the population and the environment in this area. Moreover, once these relationships have been identified, they could be used to generate a mathematical relationship to simulate future population trends in diverse environmental scenarios., The FarFish project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 727891. The EuroSea project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626., Peer reviewed

30 pages, 11 figures, 10 tables.-- This work is distributed under the Creative Commons Attribution 4.0 License, The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2022 is an update of the previous version, GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: data from 96 new cruises were added, data coverage was extended until 2021, and for the first time we performed secondary quality control on all sulfur hexafluoride (SF6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF6 data, which are now subjected to secondary quality control, and carbon data measured on board the RV Knorr in the Indian Ocean in 1994-1995 which are now adjusted using certified reference material (CRM) measurements made at the time. GLODAPv2.2022 includes measurements from almost 1.4 million water samples from the global oceans collected on 1085 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 96 new cruises were derived by comparing those data with the data from the 989 quality-controlled cruises in the GLODAPv2.2021 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2) chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1% in oxygen, 2% in nitrate, 2% in silicate, 2% in phosphate, 4μmolkg-1 in dissolved inorganic carbon, 4μmolkg-1 in total alkalinity, 0.01-0.02 in pH (depending on region), and 5% in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA NCEI (https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/GLODAPv2-2022/, last access: 15 August 2022). This site also provides access to the merged data product, which is provided as a single global file and as four regional ones - the Arctic, Atlantic, Indian, and Pacific oceans - under 10.25921/1f4w-0t92 (Lauvset et al., 2022). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2022 methods and provides a broad overview of the secondary quality control procedures and results., Nico Lange was funded by EU Horizon 2020 through the EuroSea action (grant agreement 862626). Siv K. Lauvset acknowledges internal strategic funding from NORCE Climate. Leticia Cotrim da Cunha was supported by Prociencia/UERJ 2022-2024 and CNPq/PQ2 309708/2021-4 grants. Marta Álvarez was supported by IEO RADPROF project. Peter J. Brown was partly funded by the UK Climate Linked Atlantic Sector Science (CLASS) NERC National Capability Long-term Single Centre Science Programme (grant NE/R015953/1). Anton Velo and Fiz F. Pérez were supported by BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and contributing to WATER:iOS CSIC PTI. Funding for Li-Qing Jiang and the CODAP-NA development team (Simone R. Alin, Leticia Barbero, Richard A. Feely, Brendan R. Carter) comes from the NOAA Ocean Acidification Program (OAP, project number: OAP 1903-1903) and NOAA National Centers for Environmental Information (NCEI). Brendan R. Carter thanks the Global Ocean Monitoring and Observing (GOMO) program of the National Oceanic and Atmospheric Administration (NOAA) for funding their contributions (project no. 100007298) through the Cooperative Institute for Climate, Ocean, & Ecosystem Studies (CIOCES) under NOAA Cooperative Agreement NA20OAR4320271, contribution no. 2022-2012. Richard A. Feely and Simone R. Alin acknowledge the NOAA GOMO (project no. 100007298) and the NOAA Pacific Marine Environmental Laboratory. Henry C. Bittig gratefully acknowledges financial support by the BONUS INTEGRAL project (grant no. 03F0773A). Bronte Tilbrook was supported through the Australian Antarctic Program Partnership and the Integrated Marine Observing System. Matthew P. Humphreys acknowledges EU Horizon 2020 action SO-CHIC (grant no. 821001). Adam Ulfsbo was supported by the Swedish Research Council FORMAS (grant no. 2018-01398). Jens Daniel Müller acknowledges support from the European Union's Horizon 2020 research and innovation program under grant agreement no. 821003 (project 4C). Alex Kozyr and Li-Qing Jiang were supported by NOAA grant NA19NES4320002 (Cooperative Institute for Satellite Earth System Studies – CISESS) at the University of Maryland/ESSIC. GLODAP also acknowledge funding from the Initiative and Networking Fund of the Helmholtz Association through the project “Digital Earth” (ZT-0025) and from the United States National Science Foundation grant OCE-2140395 to the Scientific Committee on Oceanic Research (SCOR, United States) for International Ocean Carbon Coordination Project. The contribution of Leticia Barbero was carried out under the auspices of CIMAS and NOAA, cooperative agreement no. NA20OAR4320472, Peer reviewed

Surface Water & Ocean Topography (SWOT) is the first satellite altimetry mission to measure the elevation of nearly all water on Earth’s surface. SWOT will provide high-resolution maps of the water surface topography over the open and coastal oceans, lakes rivers and reservoirs. After two decades of preparation , SWOT was launched on December 2022. For approximately the first 180 days of the mission, SWOT is in a 1-day repeat orbit for cal/val. This document represents the cruise plan of the FaSt-SWOT field campaigns co-led by IMEDEA(CSIC-UIB) and SOCIB as a contribution to the SWOT Science Team and SWOT-AdAC consortium. FaSt-SWOT multi-platform experiments took place in the Balearic Sea in April-May 2023 during the SWOT satellite mission fast-sampling phase. The generals objectives of these experiments were (1) to validate the first observations provided by the new altimeter mission during the calibration/validation phase and (2) to improve the characterization of oceanic fine scales through the combined use of in-situ multi-platform and satellite data in synergy with numerical models and innovative computational techniques. The campaigns have assessed the actual capability to map SSH variability over a range of scales (30-100 km) traditionally not resolved by conventional altimeters. A unique aspect of the FaSt-SWOT experiments is the combination of concurrent multi-scale ship-based instruments, autonomous platforms, and satellite observations with ad hoc modeling simulations, enabling the evaluation of underlying mechanisms. FaSt-SWOT federates two multiplatform in situ experiments, combining glider, drifter, ship observations together with satellite observations and high-resolution data-assimilative numerical simulations. Advanced Observing System Simulation Experiments (OSSEs) and new tools of artificial intelligence have been performed to optimize the sampling strategies. This document includes the plans for the cruises and it will be complemented with the cruise reports., The FaSt-SWOT project is funded by the Spanish Research Agency and the European Regional Development Fund (AEI/FEDER, UE) under Grant Agreement (PID2021-122417NB-I00). The present research is conducted within the framework of the activities of the Spanish Government through the "María de Maeztu Centre of Excellence'' accreditation to IMEDEA (CSIC-UIB) (CEX2021-001198). The Spanish
Ministry of Science and Innovation, the Regional Government of the Balearic Islands and the Spanish Research Council (CSIC) are acknowledged for their support to the ICTS SOCIB. A. P., B. M. and B. B. L. thank the European Union funding through the EuroSea project an Horizon 2020 research and innovation programme under grant agreement No 862626., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001198)., Peer reviewed

28 pages, 2 tables, 8 figures.-- This is an open access article under the terms of the Creative Commons Attribution License, The oceanic uptake and resulting storage of the anthropogenic CO2 (Cant) that humans have emitted into the atmosphere moderates climate change. Yet our knowledge about how this uptake and storage has progressed in time remained limited. Here, we determine decadal trends in the storage of Cant by applying, the eMLR(C*) regression method to ocean interior observations collected repeatedly since the 1990s. We find that the global ocean storage of Cant grew from 1994 to 2004 by 29 ± 3 Pg C dec−1 and from 2004 to 2014 by 27 ± 3 Pg C dec−1 (±1σ). The storage change in the second decade is about 15 ± 11% lower than one would expect from the first decade and assuming proportional increase with atmospheric CO2. We attribute this reduction in sensitivity to a decrease of the ocean buffer capacity and changes in ocean circulation. In the Atlantic Ocean, the maximum storage rate shifted from the Northern to the Southern Hemisphere, plausibly caused by a weaker formation rate of North Atlantic Deep Waters and an intensified ventilation of mode and intermediate waters in the Southern Hemisphere. Our estimates of the Cant accumulation differ from cumulative net air-sea flux estimates by several Pg C dec−1, suggesting a substantial and variable, but uncertain net loss of natural carbon from the ocean. Our findings indicate a considerable vulnerability of the ocean carbon sink to climate variability and change, JDM and NG acknowledge support from the European Union's Horizon 2020 research and innovation programme under grant agreements no. 821003 (project 4C) and no. 821001 (SO-CHIC). FFP was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and contributed to WATER:iOS CSIC PTI. AO and SKL were supported by the project N-ICOS-2 (Research Council of Norway Grant 296012). SKL also acknowledges internal funding support from NORCE. MI was supported by JPMEERF21S20810. RW, RAF, and BC were supported by the Office of Ocean and Atmospheric Research (OAR) of NOAA, including the Global Observation and Monitoring Program (GOMO), FundRef 100018302. BC and RAF contributions are PMEL contribution 5454 and CICOES contribution 2022-1244. TT acknowledges support by EU Horizon 2020 through the EuroSea action (grant agreement 862626), Peer reviewed

The study of marine heat waves as extreme temperature events has a wide range of applications, from a gauge for ecological and socioeconomic impact to a climate change indicator. Various definitions of marine heat waves as extreme sea temperature events exist to account for its broad applicability, with statistical definitions based on percentile based thresholds being widespread in its use. Using satellite and model data of the Mediterranean Sea, we analyze the statistical implications of choosing baseline climatological periods for threshold delineation, which are either fixed in the past or shifted in time. We show that in the context of a warming Mediterranean Sea, using a fixed baseline leads to a saturation of marine heat wave days that compromises the significance of this marine indicator, with 90% of climate models analyzed predicting an average above 189 marine heat wave days per year by 2050 even for the lowest emission scenario. We argue that only with a moving baseline, can we reach a definition for marine heat waves which yield consistently rare extreme events., This work has been funded by the JAE-Intro scholarships issued by the Spanish National Research Council (CSIC), the Mediterranean Institute for Advanced Studies (IMEDEA), and the University of Balearic islands (UIB). Part of this work was supported by the EuroSea project (www.eurosea.eu), which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 862626., VC also acknowledges the support from the Ramón y Cajal Program (RYC2020-029306-I) and from the European Social Fund/Universitat de les Illes Balears/Spanish State Research Agency (AEI - 10.13039/501100011033)., With funding from the Spanish government through the ‘María de Maeztu Unit of Excelence’ accreditation (CEX2021- 001198), Peer reviewed

12 pages, 6 tables, 4 figures.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), The assessment of the saturation state (Ω) for calcium carbonate minerals (aragonite and calcite) in the ocean is important to determine if calcifying organisms have favourable or unfavourable conditions to synthesize their carbonated structures. This parameter is largely affected by ocean acidification, as the decline in seawater pH causes a decrease in carbonate ion concentration, which in turn, lowers Ω. This work examines temporal trends of seawater pH, ΩAragonite and ΩCalcite in major Atlantic and Mediterranean water masses that exchange in the Strait of Gibraltar: North Atlantic Central Water (NACW), Levantine Intermediate Water (LIW) and Western Mediterranean Deep Water (WMDW) using accurate measurements of carbonate system parameters collected in the area from 2005-2021. Our analysis evidences a gradual reduction in pH in the three water mases during the monitoring period, which is accompanied by a decline in Ω for both minerals. The highest and lowest decreasing trends were found in the NACW and LIW, respectively. Projected long-term changes of Ω for future increases in atmospheric CO2 under the IPCC AR6 Shared Socio-economic Pathway "fossil-fuel-rich development" (SSP5-8.5) indicate that critical conditions for calcifiers with respect to aragonite availability will be reached in the entire water column of the region before the end of the current century, with a corrosive environment (undersaturation of carbonate) expected after 2100, This work was supported by the European projects CARBOOCEAN (FP6-511176), CARBOCHANGE (FP7-264879), PERSEUS (FP7-287600), Eurosea and COMFORT. The EuroSea (Improving and integrating the European Ocean Observing and Forecasting System) and COMFORT (Our common future ocean in the Earth system - quantifying coupled cycles of carbon, oxygen, and nutrients for determining and achieving safe operating spaces with respect to tipping points) projects have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No 862626 and 820989, respectively. Funding from the Junta de Andalucia through the TECADE grant (PY20_00293) is also acknowledged. SA-V was supported by a pre-doctoral grant FPU19/04338 from the Spanish Ministry of Science, Innovation and Universities. FP was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033. This work is a contribution to the CSIC Interdisciplinary Thematic Platform OCEANS+, funded by the European Union-Next Generation EU Agreement between MITECO, CSIC, AZTI, SOCIB, and the universities of Vigo and Cadiz, to promote research and generate scientific knowledge in the field of marine sustainability. SF acknowledges the financial support of a “Vicenç Munt Estabilitat” postdoctoral contract from the Balearic Islands Government and the PTA2018–015585-I funded by the Spanish Ministry of Science and Innovation, Peer reviewed

© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)., Coastal circulation influences the distribution of European anchovy (Engraulis encrasicolus) at early life stages (ELS) in the Bay of Biscay (BoB). However, how this happens is not yet fully understood. In this work, further insight is provided by performing Lagrangian diagnostics based on observations of ELS anchovies' initial distributions and currents. Surface diagnostics were obtained by using high-frequency radar (HFR) currents and were applied to analyse multiyear variability and detect the coastal processes that affect the distribution. Since ELS anchovies are also located at subsurface levels, subsurface diagnostics were obtained by using currents reconstructed from HFR and ADCP observations with a reduced order optimal interpolation (ROOI) method. The analyses included transport computations as well as the analysis of flow properties by Lagrangian Coherent Structures and chlorophyll-a satellite images. Results suggest that ELS anchovies are mostly retained over the shelf and slope, and that transport patterns highly vary across different periods. Mesoscale structures such as eddies, fronts and along-slope currents within the slope and the Capbreton canyon area, as well as strong and persistent winds, could significantly impact the distribution of ELS anchovies. In some periods, the resulting distribution might be due to a combination of these processes. Circulation can also play a key role in ELS anchovy aggregation within short time scales (20 days). This work showcases the potential of observation-based approaches and emphasizes the relevance of coastal observatories for integrated studies., We thank the Emergencies and Meteorology Directorate (Security department) of the Basque Government for public data provision from the Basque Operational Oceanography System EuskOOS. This study has been conducted using EU Copernicus Marine Service information. Wind data were obtained from the meteorological agency of Galicia (MeteoGalicia). The processing of HFR data was supported by JERICO-S3 project, funded by the European Union's Horizon 2020 Research and Innovation Program under grant agreement no. 871153. This study has also been undertaken with the financial support of the "Departamento de Medio Ambiente, Ordenación del Territorio, Agricultura y Pesca" of the Basque Government (MarcoProgram). This work has been done partially with financial support from the project LAMARCA (PID2021-123352OB-C31; PID2021-123352OB-C33) funded by MICIN/AEI /10.13039/501100011033/ and by FEDER (UE), the project Tech2Coast (TED2021-130949B-I00) funded by MCIN/AEI/ 10.13039/501100011033 and by EU “NextGenerationEU/PRTR” and the project EuroSea funded by he European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No.862626. This study is a contribution to the IM22MPDH project, funded by the EMFF (European Maritime Fishing Funds) Data collection framework, the “Departamento de Desarrollo Económico y Competitividad” of the Basque Government and the "Secretaría General de Pesca" of the Spanish Government providing the oceanographic vessels Emma Bardán. Ivan Manso-Narvarte was supported by a PhD fellowship from the "Departamento de Medio Ambiente, Ordenación del Territorio, Agricultura y Pesca" of the Basque Government. Ismael Hernández-Carrasco acknowledges financial support from the project TRITOP (grant\# UIB2021-PD06) funded by University of the Balearic Islands and by FEDER(EU). This is contribution number 1183 of the Marine Research Division of AZTI-BRTA., Peer reviewed

12 pages, 5 figures.-- This article is licensed under a Creative Commons Attribution 4.0 International License, The subpolar North Atlantic (SPNA) is a region of high anthropogenic CO2 (Cant) storage per unit area. Although the average Cant distribution is well documented in this region, the Cant pathways towards the ocean interior remain largely unresolved. We used observations from three Argo-O2 floats spanning 2013-2018 within the SPNA, combined with existing neural networks and back-calculations, to determine the Cant evolution along the float pathways from a quasi-lagrangian perspective. Our results show that Cant follows a stepwise deepening along its way through the SPNA. The upper subtropical waters have a stratified Cant distribution that homogenizes within the winter mixed layer by Subpolar Mode Water formation in the Iceland Basin. In the Irminger and Labrador Basins, the high-Cant footprint (> 55 μmol kg−1) is mixed down to 1400 and 1800 dbar, respectively, by deep winter convection. As a result, the maximum Cant concentration is diluted (<45 μmol kg−1). Our study highlights the role of water mass transformation as a first-order mechanism for Cant penetration into the ocean. It also demonstrates the potential of Argo-O2 observations, combined with existing methods, to obtain reliable Cant estimates, opening ways to study the oceanic Cant content at high spatio-temporal resolution, R.A. has received funding, as part of the EuroSea project, from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 862626. L.I.C., V.T., and R.B. acknowledge support from Ifremer. H.M. was supported by CNRS. F.F.P. was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033. This work is a contribution to CSIC’s Thematic Interdisciplinary Platform PTI WATER:iOS. The authors gratefully acknowledge financial support by the Brittany Region for the CPER Bretagne ObsOcean 2021-2027 and from the French government within the framework of the “Investissements d’avenir” program integrated in France 2030 and managed by the Agence Nationale de la Recherche (ANR) under grant agreement no ANR-21-ESRE-0019 for the Equipex+ Argo-2030 project, Peer reviewed

© 2024 Pereiro, Belyaev, Dunbar, Conway, Dabrowski, Graves, Navarro, Nolan, Pearlman, Simpson and Cusack. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms., This work presents the steps followed in the design and implementation of a marine observatory that provides the current state and forecast of oceanic conditions relevant to the aquaculture sector. Examples of successful implementation of these guidelines are presented in the framework of the EuroSea project (H2020 grant agreement No. 862626) for two aquaculture sites: Deenish Island in Ireland and El Campello in Spain. In-situ essential ocean measurements, remote-sensing observations and modelled forecasts are jointly provided to the aquaculture end users. The process begins with stakeholder interaction to understand their main needs and concerns, followed by software architecture design and development to facilitate data acquisition, post-processing and visualization on an open-access web platform. User input regarding the development of the observatory and web platform content and frequent feedback are of paramount importance during the whole process to ensure that the services offered match the needs of the aquaculture sector., This study was supported by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 862626., Peer reviewed

The new Surface Water and Ocean Topography (SWOT) satellite mission aims to provide sea surface height (SSH) measurements in two dimensions along a wide-swath altimeter track with an expected effective resolution down to 15–30 km. In this context our goal is to optimize the design of in situ experiments aimed to reconstruct fine-scale ocean currents (~20 km), such as those that will be conducted to validate the first available tranche of SWOT data. A set of Observing System Simulation Experiments are developed to evaluate different sampling strategies and their impact on the reconstruction of fine-scale sea level and surface ocean velocities. The analysis focuses (i) within a swath of SWOT on the western Mediterranean Sea and (ii) within a SWOT crossover on the subpolar northwest Atlantic. From this evaluation we provide recommendations for the design of in situ experiments that share the same objective. In both regions of study distinct strategies provide reconstructions similar to the ocean truth, especially those consisting of rosette Conductivity Temperature Depth (CTD) casts down to 1000 m and separated by a range of distances between 5 and 15 km. A good compromise considering the advantages of each configuration is the reference design, consisting of CTD casts down to 1000 m and 10 km apart. Faster alternative strategies in the Mediterranean comprise: (i) CTD casts down to 500 m and separated by 10 km and (ii) an underway CTD with a horizontal spacing between profiles of 6 km and a vertical extension of 500 m. In the Atlantic, the geostrophic velocities reconstructed from strategies that only sample the upper 500 m depth have a maximum magnitude ~50% smaller than the ocean truth. A configuration not appropriate for our objective in both regions is the strategy consisting of an underway CTD sampling one profile every 2.5 km and down to 200 m. This suggests that the thermocline and halocline need to be sampled to reconstruct the geostrophic flow at the upper layer. Concerning seasonality, the reference configuration is a design that provides reconstructions similar to the ocean truth in both regions for the period evaluated in summer and also in winter in the Mediterranean., We thank the interest, support and engagement of the main stakeholders of this research: the SWOT Science Team, the SWOT Adopt-A-Crossover Consortium and the FaSt-SWOT project (funded by the Spanish Research Agency and the European Regional Development Fund (AEI/FEDER, UE) under Grant Agreement (PID2021-122417NB-I00)). The present research was carried out within the framework of the activities of the Spanish Government through the "María de Maeztu Centre of Excellence" accreditation to IMEDEA (CSIC-UIB) (CEX2021-001198)., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001198)., This study was developed in the framework of the EuroSea project, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626., Peer reviewed

[Dataset generated in Subtask 2.3.1 of the H2020 EuroSea project] H2020 EuroSea project:
The H2020 EuroSea project aims at improving and integrating the European Ocean Observing and Forecasting System (see official website: https://eurosea.eu/). It has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626).

Task 2.3:
Task 2.3 has the objective to improve the design of multi-platform experiments aimed to validate the Surface Water and Ocean Topography (SWOT) satellite observations with the goal to optimize the utility of these observing platforms. Observing System Simulation Experiments (OSSEs) have been conducted to evaluate different configurations of the in situ observing system, including rosette and underway CTD, gliders, conventional satellite nadir altimetry and velocities from drifters. High-resolution models have been used to simulate the observations and to represent the “ocean truth”. Several methods of reconstruction have been tested: spatio-temporal optimal interpolation, machine-learning techniques, model data assimilation and the MIOST tool. The planned OSSEs are detailed in this public report Barceló-Llull et al. (2020) and the complete analysis is available here Barceló-Llull et al. (2022). Contributors to Task 2.3 are CSIC (Spain), CLS (France), SOCIB (Spain), IMT-Atlantique (France) and Ocean-Next (France).

Subtask 2.3.1:
Subtask 2.3.1 aims to evaluate different in situ sampling strategies to reconstruct fine-scale ocean currents (~20 km) in the context of SWOT. An advanced version of the classic optimal interpolation used in field experiments, which considers the spatial and temporal variability of the observations, has been applied to reconstruct different configurations with the objective to evaluate the best sampling strategy to validate SWOT.

Where?
The analysis focuses on two regions of interest: (i) the western Mediterranean Sea and (ii) the Subpolar North West Atlantic. In the western Mediterranean Sea, the target area is located within a swath of SWOT, while in the North West Atlantic the region of study includes a crossover of SWOT during the fast-sampling phase.

[Report with the full analysis] The complete analysis can be found in this report: Barceló-Llull et al. (2022).

[Codes for the analysis] The codes generated to develop Subtask 2.3.1 can be found on GitHub: https://github.com/bbarcelollull/EuroSea_subTask_2.3.1, The dataset includes:

1) Model outputs used to simulate the observations in different configurations in both regions of study. The folder "2D_model_outputs" contains 2D data used to simulate SSH observations for the analysis of the temporal correlation scale (Barceló-Llull et al., 2022, p. 28-42). The folder "3D_model_outputs" contains 3D model outputs used to simulate observations of temperature and salinity. Note that eNATL60 outputs have been interpolated onto a new regular grid.

2) Simulated configurations (or sampling strategies) in each region (PKL file format).

3) Observations simulated in each configuration in both regions of study. The observations simulated are temperature and salinity. ADCP horizontal velocities are also simulated, however for eNATL60 they will be corrected in the future to account for the rotated original axes. File format: region_configuration_period_model.nc. The folder "SSH" includes the simulated SSH observations for the analysis of the temporal correlation scale (Barceló-Llull et al., 2022, p. 28-42).

4) Reconstructed fields with the spatio-temporal optimal interpolation. File format: region_configuration_period_model_stOI_Lx_Lt_cd_YYYYMMDDhhmm_var.nc (stOI = spatio-temporal optimal interpolation, Lx = spatial correlation scale, Lt = temporal correlation scale, cd = map on the central date of the sampling, YYYYMMDDhhmm = date and time of the map, var = variable interpolated (temperature and salinity) or the derived variables (dynamic height, geostrophic velocities and the Rossby number)).

5) Compared fields (ocean truth from model outputs vs. reconstructed fields) for each region and model (PKL file format)., EuroSea – Improving and Integrating European Ocean Observing and Forecasting Systems for Sustainable use of the Oceans 862626. European Commission., Peer reviewed

[Codes generated in Subtask 2.3.1 of the H2020 EuroSea project] H2020 EuroSea project:
The H2020 EuroSea project aims at improving and integrating the European Ocean Observing and Forecasting System (see official website: https://eurosea.eu/). It has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626).

Task 2.3:
Task 2.3 has the objective to improve the design of multi-platform experiments aimed to validate the Surface Water and Ocean Topography (SWOT) satellite observations with the goal to optimize the utility of these observing platforms. Observing System Simulation Experiments (OSSEs) have been conducted to evaluate different configurations of the in situ observing system, including rosette and underway CTD, gliders, conventional satellite nadir altimetry and velocities from drifters. High-resolution models have been used to simulate the observations and to represent the “ocean truth”. Several methods of reconstruction have been tested: spatio-temporal optimal interpolation, machine-learning techniques, model data assimilation and the MIOST tool. The planned OSSEs are detailed in this public report Barceló-Llull et al. (2020) and the complete analysis is available here Barceló-Llull et al. (2022). Contributors to Task 2.3 are CSIC (Spain), CLS (France), SOCIB (Spain), IMT-Atlantique (France) and Ocean-Next (France).

Subtask 2.3.1:
Subtask 2.3.1 aims to evaluate different in situ sampling strategies to reconstruct fine-scale ocean currents (~20 km) in the context of SWOT. An advanced version of the classic optimal interpolation used in field experiments, which considers the spatial and temporal variability of the observations, has been applied to reconstruct different configurations with the objective to evaluate the best sampling strategy to validate SWOT.

Where?
The analysis focuses on two regions of interest: (i) the western Mediterranean Sea and (ii) the Subpolar North West Atlantic. In the western Mediterranean Sea, the target area is located within a swath of SWOT, while in the North West Atlantic the region of study includes a crossover of SWOT during the fast-sampling phase.

[Report with the full analysis] The complete analysis can be found in this report: Barceló-Llull et al. (2022)., Codes

The codes are organized into 3 folders:

1_simulate_observations
2_reconstruct_observations_spatiotemporal_OI
3_evaluation

Here there is a step-by-step description with the corresponding codes.

1_simulate_observations

Objective: Simulate CTD observations from different platforms (rosette, underway CTD, gliders) and ADCP observations to evaluate different in situ sampling strategies

(1) Step00a_interpolate_eNATL60_4D_outputs.py

Interpolate eNATL60 model outputs onto a regular grid with a horizontal resolution of 1/60º for each time step and at each depth layer. Before starting the interpolation, we mask the 0 unreal values in the original data to exclude them from the interpolation. Then, we save the interpolated model data in a netcdf file for each variable (T, S, U and V), for each region (Atlantic or Mediterranean) and for each period (January or September). We use the interpolated data to extract the corresponding pseudo-observations in Step 2. NOTE: U and V are not zonal and meridional velocities. They are velocities along the original x and y axis. Then, if the objective is to extract ADCP velocity, they need to be rotated.

(2) Define sampling strategies:

Step01_define_sampling_strategy_CTD_ADCP.py

Define sampling strategy with rosette CTD: get (time, lon, lat, dep) of each cast. Valid for reference configuration and configurations 1, 2 and 4. MedSea and Atlantic.

Step01_define_sampling_strategy_gliders.py

Define sampling strategy with gliders: get (time, lon, lat, dep) of each profile. Valid for configuration 5. MedSea and Atlantic.

Step01_define_sampling_strategy_uCTD.py

Define sampling strategy with underway CTD: get (time, lon, lat, dep) of each profile. Valid for configuration 3. MedSea and Atlantic.

(3) Step02_extract_pseudo-obs_from_models.py

Extract pseudo-observations of temperature, salinity and ADCP horizontal velocities.

(4) Step03_plot_pseudo-obs.py

Plot pseudo-observations.

(5) Step31_simulate_pseudo-obs_error.py

Simulate random error for CTD and ADCP pseudo-observations, following a Gaussian distribution with a standard deviation defined by the instrumental error. Different (uncorrelated) for each observations. Following Gasparin et al., 2019.

Toolbox: EuroSea_toolbox.py

2_reconstruct_observations_spatiotemporal_OI

Objective: Reconstruct observations with the spatio-temporal optimal interpolation

(1) Step05b_spatio-temporal_optimal_interpolation_T_and_S.py

Reconstruct pseudo-observations of T and S applying linear interpolation on the vertical and the spatio-temporal optimal interpolation horizontally. For all configurations, in the Atlantic and Mediterranean, for all models.

For T and S: noise-to-signal error 3%, Lx = Ly = 20 km, Lt = 10 days. Not done for U and V but the code is ready.

Time of the resulting OI map: central date of each configuration.

(2) Step07b_calculate_dh_vgeo_spatio-temporal_OI.py

From the reconstructed T and S 3D fields: compute DH, (ug, vg), and Rog. For all configurations, in the Atlantic and Mediterranean, for all models.

(3) Step08b_figures_to_check_reconstructed_fields_spatio-temporal_OI.py

Plot figures to check reconstructed fields with the spatio-temporal OI.

Plot for each configuration: T (with observations) + S (with observations) + dh+vgeo

Toolboxes: EuroSea_toolbox.py, deriv_tools.py, Tools_OI.py

3_evaluation

Objective: Compare reconstructed fields to the ocean truth and find the best sampling strategies

(1) Step00b_interpolate_eNATL60_2D_outputs.py

Interpolate eNATL60 2D (surface) fields onto a regular grid.

(1) Step09b_extract_reconstructed_data_for_comparison_spatio-temporal_OI.py

Extract reconstructed data at the upper layer to do comparisons in Step 12. Save data with the same format as the ocean truth .pkl file.

(2) Step09c_figures_reconstructed_fields_all_spatio-temporal_OI.py

Reconstructed fields: Plot 1 figure for each region, model and variable, including all configurations. Variables: dh, geostrophic velocity magnitude and geostrophic Ro. For comparison between configurations and with the ocean truth. [Figures published in D2.3]

(3) Step10b_extract_model_data_for_figures_spatio-temporal_OI.py

Extract 2D model data (ocean truth) within the configuration domain and linearly interpolate model fields to the time of the OI map. Save fields.

(4) Step11b_figures_model_SSH_speed_Ro_spatio-temporal_OI.py

Ocean truth: Plot 1 figure for each region, model and variable, including all configurations. Variables: SSH, total horizontal velocity magnitude (speed) and Ro computed from total horizontal velocity. For comparison with reconstructed fields. [Figures published in D2.3]

(5) Step10c_extract_model_data_for_comparison_spatio-temporal_OI_bigger_domain.py

Extract 2D model data within a domain bigger than the corresponding configuration and linearly interpolate model fields to the time of the OI map. Save fields, to be used in Step12f.

(6) Step12f_compute_statistics_spatio-temporal_OI_limit_domain.py

This codes does:

Open reconstructed and model fields (saved in a bigger domain than the corresponding configuration in Step10c).
Interpolate model fields (ssh, ut, vt, speed, Ro) onto the reconstruction grid.
Limit model and reconstructed data within the configuration 2a domain.
Compute DH anomaly and SSH anomaly. Spatial average over configuration 2a domain.
Calculate RMSE-based score between reconstructed and model fields. https://github.com/ocean-data-challenges/2020a_SSH_mapping_NATL60/blob/master/notebooks/example_data_eval.ipynb
Save RMSE-based score in a .pkl file for each field.
Plot table and figure of the RMSE-based score. (Only plot figures for DH and geostrophic velocity magnitude.)

(7) Step13a_comparison_statistics_spatio-temporal_OI_best_configurations_ranking_all.py

Leaderboard based on the RMSEs calculated in Step12f for the Mediterranean and Atlantic [D2.3].

Toolboxes: EuroSea_toolbox.py, deriv_tools.py, EuroSea – Improving and Integrating European Ocean Observing and Forecasting Systems for Sustainable use of the Oceans 862626., Peer reviewed

26 pages, 11 figures, 8 tables.-- This work is distributed under the Creative Commons Attribution 4.0 License, The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major changes are as follows: data from 23 new cruises were added. In addition, a number of changes were made to the data included in GLODAPv2.2022. GLODAPv2.2023 includes measurements from more than 1.4 million water samples from the global oceans collected on 1108 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on the systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 23 new cruises were derived by comparing those data with the data from the 1085 quality-controlled cruises in the GLODAPv2.2022 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2), chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data-handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 4 µmol kg−1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments, Nico Lange has been funded by EU Horizon 2020 through the EuroSea action (grant no. 862626). Siv K. Lauvset has received internal strategic funding from NORCE Climate. Are Olsen, Nico Lange, and Siv K. Lauvset have received funding from the EU Horizon Europe project OceanICU (grant no. 101083922). Leticia Cotrim da Cunha has been supported by the Prociencia 2022–2024 grant from Universidade do Estado do Rio de Janeiro (UERJ, Brazil) and the PQ2 309708/2021-4 grant from the National Council for Scientific and Technological Development (CNPq, Brazil). Marta Álvarez has been supported by an Instituto Español de Oceanografía (IEO) RADPROF project. Peter J. Brown has received partial funding from the UK Climate Linked Atlantic Sector Science (CLASS) NERC National Capability Long-term Single Centre Science Programme (grant no. NE/R015953/1). Anton Velo and Fiz F. Perez have been supported by the BOCATS2 (grant no. PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and the Horizon Europe project EuroGO-SHIP (grant no. 101094690). Brendan R. Carter has received funding from the Global Ocean Monitoring and Observing (GOMO) program of the National Oceanic and Atmospheric Administration (NOAA) through contributions (project no. 100007298) via the Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CIOCES) under a NOAA Cooperative Agreement (grant no. NA20OAR4320271; contribution no. 2022–2012). Mario Hoppema has received funding from the EU Horizon 2020 Action SO-CHIC (grant no. 821001). Adam Ulfsbo has been supported by the Swedish Research Council Formas (grant no. 2018-01398). Jens Daniel Müller has received support from the European Union's Horizion 2020 research and innovation program for project 4C (grant no. 821003). Alex Kozyr has been supported by NOAA (grant no. NA19NES4320002; Cooperative Institute for Satellite Earth System Studies – CISESS) at the University of Maryland/ESSIC. Ryan J. Woosley has been supported by NSF grants (grant nos. OCE-1923312 and OCE-2148468). Masao Ishii has been supported by the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency of Japan (grant no. JPMEERF21S20810). GLODAP also acknowledges funding from the Initiative and Networking Fund of the Helmholtz Association through the project “Digital Earth” (grant no. ZT-0025), Peer reviewed

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)., Extreme events are increasing in frequency and severity due to climate change, making the littoral zone even more vulnerable and requiring continuous monitoring for its optimized management. The low-lying Ebro Delta ecosystem, located in the NW Mediterranean, was subject to Storm Gloria in the winter of 2020, the most severe coastal storm registered in the area in decades and one of the most intense ever recorded in the Mediterranean. This event caused intense rainfall, severe flooding, the erosion of beaches, and the destruction of coastal infrastructures. In this study, the Landsat-8 and Sentinel-2 satellites were used to monitor the flooding impact and water quality status, including chlorophyll-a, suspended particulate matter, and turbidity, to evaluate the pre-, syn-, and post-storm scenarios. Image processing was carried out using the ACOLITE software and the on-the-cloud Google Earth Engine platform for the water quality and flood mapping, respectively, showing a consistent performance for both satellites. This cost-effective methodology allowed us to characterize the main water quality variation in the coastal environment during the storm and detect a higher flooding impact compared to the one registered three days later by the Copernicus Emergency Service for the same area. Moreover, the time series revealed how the detrimental impact on the water quality and turbidity conditions was restored two weeks after the extreme weather event. While transitional plumes of sediment discharge were formed, no phytoplankton blooms appeared during the study period in the delta. These results demonstrate that the workflow implemented is suitable for monitoring extreme coastal events using open satellite imagery at 10–30 m spatial resolution, thus providing valuable information for early warning to facilitate timely assistance and hazard impact evaluation. The integration of these tools into ecological disaster management can significantly improve current monitoring strategies, supporting decision-makers from the local to the national level in prevention, adaptation measures, and damage compensation., This research was funded by Grant CNS2023-143630 funded by MICIU/AEI/10.13039/501100011033 and by European Union NextGenerationEU/PRTR, by PIE-CSIC (grant number 202030E277), and by the European Union’s Horizon 2020 research and innovation programme, EuroSea project (gran number 862626). The study was supported by the Spanish Ministry of Science, Innovation, and Universities through Programa Estatal Juan de la Cierva Incorporación-2019 (grant number IJC2019-039382-I) and FPU Programme (grant number FPU20/01294). This research has been financially supported by the agreement between the Spanish Ministry for Ecological Transition and Demographic Challenge and CSIC, funded by the European Union-Next Generation Program to contribute to the MSFD., Peer reviewed

17 pages, 2 figures.-- Open Access, Seagrass meadows provide numerous ecosystem services including biodiversity, coastal protection, and carbon sequestration. In Europe, seagrasses can be found in shallow sheltered waters along coastlines, in estuaries & lagoons, and around islands, but their distribution has declined. Factors such as poor water quality, coastal modification, mechanical damage, overfishing, land-sea interactions, climate change and disease have reduced the coverage of Europe’s seagrasses necessitating their recovery. Research, monitoring and conservation efforts on seagrass ecosystems in Europe are mostly uncoordinated and biased towards certain species and regions, resulting in inadequate delivery of critical information for their management. Here, we aim to identify the 100 priority questions, that if addressed would strongly advance seagrass monitoring, research and conservation in Europe. Using a Delphi method, researchers, practitioners, and policymakers with seagrass experience from across Europe and with diverse seagrass expertise participated in the process that involved the formulation of research questions, a voting process and an online workshop to identify the final list of the 100 questions. The final list of questions covers areas across nine themes: Biodiversity & Ecology; Ecosystem services; Blue carbon; Fishery support; Drivers, Threats, Resilience & Response; Monitoring & Assessment; Conservation & Restoration; Governance, Policy & Management; and Communication. Answering these questions will fill current knowledge gaps and place European seagrass onto a positive trajectory of recovery, This project was initiated and carried out under the EuroSea project using funding from the United Nations Educational, Scientific and Cultural Oragnisation. Additional support was from the UK Natural Environment Research Council RESOW grant to Swansea University (NE/V016385/1). The EuroSea project is funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No 862626. Thanks to Toste Tanhua and Emma Heslop for their supporting this process. Thanks are due to FCT/MCTES for the financial support to CESAM (UIDB/50017/2020 + UIDP/50017/2020 + LA/P/0094/2020), through PT national funds. Financial support from Fundacao para a Ciencia e a Technologia was also provided through the research contract to A.I. Sousa (CEECIND/00962/2017), Peer reviewed

19 pages, 11 figures, 4 tables.-- This work is distributed under the Creative Commons Attribution 4.0 License, The Atlantic Meridional Overturning Circulation (AMOC) is a key component of the Earth's climate. However, there are few long time series of observations of the AMOC, and the study of the mechanisms driving its variability depends mainly on numerical simulations. Here, we use four ocean circulation estimates produced by different data-driven approaches of increasing complexity to analyse the seasonal to decadal variability of the subpolar AMOC across the Greenland–Portugal OVIDE (Observatoire de la Variabilité Interannuelle à DÉcennale) line since 1993. We decompose the MOC strength variability into a velocity-driven component due to circulation changes and a volume-driven component due to changes in the depth of the overturning maximum isopycnal. We show that the variance of the time series is dominated by seasonal variability, which is due to both seasonal variability in the volume of the AMOC limbs (linked to the seasonal cycle of density in the East Greenland Current) and to seasonal variability in the transport of the Eastern Boundary Current. The decadal variability of the subpolar AMOC is mainly caused by changes in velocity, which after the mid-2000s are partly offset by changes in the volume of the AMOC limbs. This compensation means that the decadal variability of the AMOC is weaker and therefore more difficult to detect than the decadal variability of its velocity-driven and volume-driven components, which is highlighted by the formalism that we propose, This work received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 862626 (EUROSEA), the French national programme Les Enveloppes Fluides et l'Environnement (LEFE) and Ifremer. Herlé Mercier was supported by the Centre National de La Recherche Scientifique (CNRS). Fiz F. Pérez and Antón Velo were supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and, together with Pascale Lherminier, by the EuroGO-SHIP project (Horizon Europe #101094690). Marcos Fontela was supported by grant PTA2022-021307-I funded by MCIN/AEI/10.13039/501100011033, by European Social Fund Plus, and by the Portuguese Foundation for Science and Technology through projects UIDB/04326/2020, UIDP/04326/2020, LA/P/0101/2020, and CEECINST/00114/2018, Peer reviewed

[Description of methods used for collection/generation of data] See Pascual et al. (2023, https://doi.org/10.20350/digitalCSIC/15276) and Mourre et al. (2024, https://doi.org/10.20350/digitalCSIC/16077)., This dataset includes all raw observations (mostly in native instrument format) collected during the FaSt-SWOT oceanographic campaign (R/V SOCIB) carried out in the Balearic Sea (Western Mediterranean) between 25 April and 10 May 2023 (Leg 1 from 25 to 28 April and Leg 2 from 7 to 10 May). This experiment was part of the FaSt-SWOT project (PID2021-122417NB-I00 funded by MCIN/AEI/10.13039/501100011033/FEDER,UE), with the objectives to improve the characterization and understanding of small-scale ocean structures and contribute to SWOT satellite cal/val activities during its initial fast-sampling phase., Observations were collected both by ship-based instruments (CTD, Moving Vessel Profiler, thermosalinograph, ADCP and weather station) and autonomous platforms (surface drifters and gliders). They include measurements of both physical (temperature, salinity, currents) and biogeochemical (oxygen, chlorophyll, turbidity, photosynthetically active radiation) ocean variables., The data collection was mainly supported by the FaSt-SWOT project, funded by the Spanish Ministry of Science and Innovation, the Spanish Research Agency and the European Regional Development Fund (MCIN/AEI/10.13039/501100011033/FEDER, UE) under Grant Agreement PID2021-122417NB-I00. The project is conducted within the framework of the activities of the Spanish Government through the ”María de Maeztu Centre of Excellence” accreditation to IMEDEA (CSIC-UIB) (CEX2021-001198). The Spanish Ministry of Science and Innovation, the Regional Government of the Balearic Islands and the Spanish Research Council (CSIC) are also acknowledged for their support to the ICTS SOCIB. AP, BM and BBL thank the European Union funding through the EuroSea project, an Horizon 2020 research and innovation programme under grant agreement No 862626. LGN acknowledges funding of her Margarita Salas fellowship by European UnionNextGenerationEU, Ministry of Universities and Recovery, Transformation and Resilience Plan, through a call from the University of the Balearic Islands (Palma, Spain)., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001198)., ADCP: Leg 1, Leg2.-- CTD: Leg 1, Leg2.-- Drifters: carthe, hereon.-- Gliders: sdeep01, sdeep09.-- GPS: Leg1, Leg2.-- Meteo: Leg1, Leg2.-- MVP: Leg1, Leg2.-- salinity_water_samples.-- Thermosalinograph: Leg1, Leg2., Peer reviewed

All information regarding the SPOTS pilot and the collaborative NSF EarthCube-funded Marine Ecological Time Series Research Coordination Network (METS-RCN) can be accessed at https://www2.whoi.edu/site/mets-rcn/ (METS-RCN, METS-RCN, 2024). The SPOTS web page (https://www2.whoi.edu/site/mets-rcn/ts-data-product/, METS-RCN, 2024)., The supplement related to this article is available online at: https://doi.org/10.5194/essd-16-1901-2024-supplement., The presented pilot for the Synthesis Product for Ocean Time Series (SPOTS) includes data from 12 fixed ship-based time-series programs. The related stations represent unique open-ocean and coastal marine environments within the Atlantic Ocean, Pacific Ocean, Mediterranean Sea, Nordic Seas, and Caribbean Sea. The focus of the pilot has been placed on biogeochemical essential ocean variables: dissolved oxygen, dissolved inorganic nutrients, inorganic carbon (pH, total alkalinity, dissolved inorganic carbon, and partial pressure of CO2), particulate matter, and dissolved organic carbon. The time series used include a variety of temporal resolutions (monthly, seasonal, or irregular), time ranges (10-36 years), and bottom depths (80-6000ĝ€¯m), with the oldest samples dating back to 1983 and the most recent one corresponding to 2021. Besides having been harmonized into the same format (semantics, ancillary data, units), the data were subjected to a qualitative assessment in which the applied methods were evaluated and categorized. The most recently applied methods of the time-series programs usually follow the recommendations outlined by the Bermuda Time Series Workshop report (Lorenzoni and Benway, 2013), which is used as the main reference for "method recommendations by prevalent initiatives in the field". However, measurements of dissolved oxygen and pH, in particular, still show room for improvement. Additional data quality descriptors include precision and accuracy estimates, indicators for data variability, and offsets compared to a reference and widely recognized data product for the global ocean: The GLobal Ocean Data Analysis Project (GLODAP). Generally, these descriptors indicate a high level of continuity in measurement quality within time-series programs and a good consistency with the GLODAP data product, even though robust comparisons to the latter are limited. The data are available as (i) a merged comma-separated file that is compliant with the World Ocean Circulation Experiment (WOCE) exchange format and (ii) a format dependent on user queries via the Environmental Research Division's Data Access Program (ERDDAP) server of the Global Ocean Observing System (GOOS). The pilot increases the data utility, findability, accessibility, interoperability, and reusability following the FAIR philosophy, enhancing the readiness of biogeochemical time series. It facilitates a variety of applications that benefit from the collective value of biogeochemical time-series observations and forms the basis for a sustained time-series living data product, SPOTS, complementing relevant products for the global interior ocean carbon data (GLobal Ocean Data Analysis Project), global surface ocean carbon data (Surface Ocean CO2 Atlas; SOCAT), and global interior and surface methane and nitrous oxide data (MarinE MethanE and NiTrous Oxide product). Aside from the actual data compilation, the pilot project produced suggestions for reporting metadata, implementing quality control measures, and making estimations about uncertainty. These recommendations aim to encourage the community to adopt more consistent and uniform practices for analysis and reporting and to update these practices regularly. The detailed recommendations, links to the original time-series programs, the original data, their documentation, and related efforts are available on the SPOTS website. This site also provides access to the data product (DOI: 10.26008/1912/bco-dmo.896862.2, Lange et al., 2024) and ancillary data., The authors acknowledge funding from the United States National Science Foundation (grant no. OCE-2140395) to the Scientific Committee on Oceanic Research (SCOR, United States) for the International Ocean Carbon Coordination Project (IOCCP)., Nico Lange was funded by EU Horizon 2020 through the EuroSea Innovation Action (grant agreement no. 862626) and by iAtlantic (grant agreement no. 818123). Björn Fiedler was funded by the WASCAL MRP-CCMS project from the German Federal Ministry of Education and Research (BMBF; grant agreement no. 01LG1805A). The work of Sólveig R. Ólafsdóttir was supported by the European Union's Horizon 2020 research and innovation program under grant agreement no. 820989 (COMFORT). Frank Muller-Karger and Digna Rueda-Roa from the CARIACO time-series project were supported financially by the National Science Foundation (grant no. OCE-1259043). The work of Ingunn Skjelvan was supported by the Norwegian Environment Agency under grant agreement nos. 14078029, 15078033, 16078007, 17018007, and 21087110. The work of K2 and KNOT was partly supported by a Grant-in-Aid for Scientific Research (grant no. 20H04349) from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) KAKENHI. The DYFAMED ship-based time series is supported by the MOOSE program (Mediterranean Ocean Observing System for the Environment) coordinated by CNRS-INSU and the Research Infrastructure ILICO (CNRS-IFREMER). GIFT has been supported by the European projects CARBOOCEAN, CARBOCHANGE, SESAME, PERSEUS, and COMFORT, the Spanish Ministry of Science, through the grant nos. CTM2005/01091-MAR and CTM2008-05680-C02-01 and the Junta de Andalucia through the TECADE project (grant no. PY20_00293). The work of HOT is supported by the NSF (grant no. OCE-0926766). The METS RCN is supported by grant no. NSF 2028291. The RADIALES program is a structural program funded by Centro Nacional Instituto Español de Oceanografía (IEO-CSIC)., Peer reviewed

The EU funded project EuroSea brought together key actors of the European ocean observing and forecasting communities with key users of the ocean observing products and services in order to better integrate existing ocean observation systems and tools, and to improve the delivery of ocean information to users. EuroSea was constructed around the ocean observing value chain that connects observations to users of ocean information, and, just as intended, the value chain concept was a useful prism to improve the system. In this article, we summarize some of the main take-home messages from EuroSea on the needs for developing the European Ocean Observing System and its links with modeling and forecasting systems. During the project, the challenges and gaps in the design and coordination of the European ocean observing and forecasting system were identified and mapped. Many gaps and challenges related to the observations of physical, chemical and biological Essential Ocean Variables were identified. Some of these gaps are related to technological developments, while others are caused by insufficient and short-term funding leading to a not sustainable system, management, and cooperation between different entities, as well as limitations in foresight activities, policies and decisions. This article represents a compilation of the broader needs for advancing the observing and forecasting system, and is meant as a guide for the community, and to funders and investors to advance ocean observing and the delivery of ocean information in Europe. To enhance the sustainability of ocean observations, which is paramount for a reliable provision of quality oceanographic data and services, several recommendations were compiled for ocean observing networks, frameworks, initiatives, as well as the ocean observing funders within the European nations, and the European Commission., The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was fully funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626, as part of the EuroSea project., Peer reviewed

This time-series data synthesis pilot product includes data from 12 fixed ship-based time-series programs with
a focus on biogeochemical essential ocean variables., Methods & Sampling.
Oceanographic data from twelve fixed ship-based time-series programs were synthesized into a pilot product
with focus on biogeochemical essential ocean variables (BGC-EOV). Measurements of dissolved oxygen,
dissolved inorganic nutrients, inorganic carbon (pH, TALK, DIC, pCO2), particulate matter, and DOC were
compiled from the time series programs listed below.
Methods, Sampling, and Instruments are dependent on individual time-series programs, and often vary within a
single time series program from cruise-to-cruise.
Instruments are listed in the section below, with detailed metadata available at ODIS
(https://oceaninfohub.org/odis/).
Additional details may be found by viewing the related datasets and publications sections below., The presented time-series data synthesis pilot product includes data from 12 fixed ship-based time-series programs. The related stations represent unique marine environments within the Atlantic Ocean, Pacific Ocean, Mediterranean Sea, Nordic Seas, and Caribbean Sea. The focus of the pilot has been placed on biogeochemical essential ocean variables: dissolved oxygen, dissolved inorganic nutrients, inorganic carbon (pH, total alkalinity, dissolved inorganic carbon, and partial pressure of CO2), particulate matter, and dissolved organic carbon. The time-series used include a variety of temporal resolutions (monthly, seasonal, or irregular), time ranges (10 to 36 years), and bottom depths (80 to 6000 meters), with the oldest samples dating back to 1983 and the most recent one corresponding to 2021. Besides having been harmonized into the same format (semantics, ancillary data, units), the data were subjected to a qualitative assessment in which the applied methods were evaluated and categorized. Additional data-quality descriptors include precision and accuracy estimates. This data product pilot facilitates a variety of applications that benefit from the collective value of biogeochemical time-series observations and forms the basis for a sustained time-series living data product, complementing relevant products for the global interior ocean carbon data (GLobal Ocean Data Analysis Project), global surface ocean carbon data (Surface Ocean CO2 Atlas; SOCAT), and global interior and surface methane and nitrous oxide data (MarinE MethanE and NiTrous Oxide product)., This time-series data synthesis pilot product includes data from 12 fixed ship-based time-series programs with a focus on biogeochemical essential ocean variables. Data used in this synthesis product were made possible with funding through the following:
EU Horizon 2020 through the EuroSea Innovation Action (grant agreement 862626)
EU Horizon 2020 iAtlantic programme (grant agreement 818123)
European Union’s Horizon 2020 research and innovation program (grant agreement 820989; COMFORT).
WASCAL MRP-CCMS project from the German Federal Ministry of Education and Research (BMBF; grant agreement no. 01LG1805A).
National Science Foundation (OCE-1259043, OCE-175651, and RISE-2028291).
Norwegian Environment Agency under grant agreement nos. 14078029, 15078033, 16078007, 17018007, and 21087110.
Grant-in-Aid for Scientific Research (20H04349) from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) KAKENHI.
Mediterranean Ocean Observing System for the Environment program (MOOSE) coordinated by CNRS-INSU and the Research Infrastructure ILICO (CNRS-IFREMER).
The European projects CARBOOCEAN, CARBOCHANGE, SESAME, PERSEUS and COMFORT
The Spanish Ministry of Science through the grants CTM2005/01091-MAR and CTM2008-05680-C02-01 and the Junta de Andalucía through the TECADE project (PY20_00293)
Centro Nacional Instituto Español de Oceanografía (IEO-CSIC), Peer reviewed

Ocean observing systems in coastal, shelf and marginal seas collect diverse oceanographic information supporting a wide range of socioeconomic needs, but observations are necessarily sparse in space and/or time due to practical limitations. Ocean analysis and forecast systems capitalize on such observations, producing data-constrained, four-dimensional oceanographic fields. Here we review efforts to quantify the impact of ocean observations, observing platforms, and networks of platforms on model products of the physical ocean state in coastal regions. Quantitative assessment must consider a variety of issues including observation operators that sample models, error of representativeness, and correlated uncertainty in observations. Observing System Experiments, Observing System Simulation Experiments, representer functions and array modes, observation impacts, and algorithms based on artificial intelligence all offer methods to evaluate data-based model performance improvements according to metrics that characterize oceanographic features of local interest. Applications from globally distributed coastal ocean modeling systems document broad adoption of quantitative methods, generally meaningful reductions in model-data discrepancies from observation assimilation, and support for assimilation of complementary data sets, including subsurface in situ observation platforms, across diverse coastal environments., CE acknowledges support by the Simons Foundation through the Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems (CBIOMES) grant ID 549949. Parts of this work were originally supported by two European Union (EU)-funded initiatives: (1) the Copernicus Marine Service and their Service Evolution program; (2) the JERICO-Next project (Joint European Research Infrastructure Network for Coastal Observatories) funded by the EU’s Horizon 2020 research and innovation program (2015-2019). The contribution of PD is supported by Centre National de la Recherche Scientifique (CNRS). The contribution of VV is supported by the Copernicus Marine Service Evolution projects SCRUM/2 and MULTICAST. The contribution of GC is supported by Institut Français de Recherche pour l’Exploitation de la Mer (Ifremer). The contribution of CS is supported by the JERICO-Next project. MR and CK acknowledge support of the Australian Research Council for model development through grants DP140102337, LP170100498, LP220100515. BB-L and AP acknowledge fundings from the EuroSea project, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626. GH acknowledges support by the National Oceanographic and Atmospheric Administration Atlantic Oceanographic and Meteorological Laboratory. BB-L is supported by the Balearic Islands Government Vicenç Mut program, grant PD/008/2022. B-JC is supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), the Ministry of Education (2020R1A2C1014678)., Peer reviewed

The European Ocean Observing Community (EOOC) integrates inputs from diverse entities dedicated to comprehensively monitoring and forecasting oceanic phenomena in European Seas. With increasing climate and anthropogenic pressures, the urgency of ensuring the EOOC’s preparedness to observe Essential Ocean Variables (EOVs) is evident. This paper advocates for the adoption of a scoring approach designed to evaluate the readiness of the EOOC in observing and forecasting key ocean phenomena. The proposed scoring methodology can be applied at both European and potentially regional and/or national levels, and emerges as a transformative tool for scrutinizing the EOOC’s capability to predict and monitor key ocean phenomena. Our findings, based on the application of the scoring approach, suggest that while the community demonstrates commendable readiness levels for certain oceanic phenomena, 83% remain in developing stages, oscillating between “Idea” and “Trial” readiness levels. A closer examination exposes critical shortages predominantly in the coordination and observational facets (Process), and data management and information products (Output). The implications of these identified gaps reach far beyond academic realms, profoundly affecting diverse sectors and societal resilience (e.g., energy sector). The suggested scoring approach serves as a clear call for strategic investments and heightened support for the European observing community. By adopting a regular and systematic scoring methodology, we not only measure progress at present but also pave the way for a resilient and future-ready EOOC., The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work has been supported by the European Union, through the EuroSea project, in the context of the Horizon 2020 research and innovation programme under grant agreement No 862626., Peer reviewed

61 pages, 13 figures, 4 tables, appendixes, For over a decade, countries and territories in the Gulf of Mexico, South Florida, Wider Caribbean and West Africa have experienced an unprecedented Transatlantic Triple Threat, the influxes of holopelagic Sargassum spp., resulting in significant social, economic and environmental impacts. These impacts have caused challenges to already strained climate-sensitive socio-economic and environmental sectors. Emerging impacts recently reported in the energy and water sectors further highlight the need for adaptive management strategies to address this triple threat.
The magnitude and complexity of the Sargassum issue has inspired scientists to investigate many aspects associated with this phenomenon, including the source and causes of bloom events. There has been considerable debate about the root cause(s) of unprecedented Sargassum spp. influx events, but it is generally agreed that the post-2011 Sargassum phenomenon in the tropical Atlantic can be considered a ‘wicked problem’. A wicked problem can be defined as a social or cultural problem that is difficult or impossible to solve because of its complex and interconnected nature (Rittel and Webber, 1973). Sargassum influxes are influenced by a complex interplay of both natural and anthropogenic factors, and the social dynamics associated with response planning and management are subject to real-world constraints which hinder (risk-free) attempts to find a solution. [...], This White Paper was funded by UNESCO-IOC and the EU H2020 project ‘EuroSea’ (grant agreement No 862626), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

We present an impact assessment of temperature and salinity glider observations on physical analysis and forecasting systems operating in the Western Mediterranean Sea through one-year-long coordinated experiments. A unique set of glider observations including data from several endurance lines provided by different institutions is assimilated in the three systems. Results are compared against an assimilation-free run and an assimilative-run that with each systems’ default configuration. Moreover, an additional biogeochemical analysis system is forced by two physical runs with and without the assimilation of glider observations. First of all, we demonstrate that glider data assimilation has an overall positive impact on the state estimation of the Western Mediterranean Sea, independently of the system employed and the pre-processing approach used to ingest the glider measurements. Secondly, we show that it helps improve the representation of mesoscale structures, in particular the location and size of an intense anticyclonic eddy observed in the Balearic Sea. Thirdly, the geostrophic currents and transport of Winter Intermediate Water in the Ibiza Channel are also improved. Finally, the adjustment of the mixing after glider data assimilation in the physical system translated to a better estimate of chlorophyll distribution in the upper layer of the biogeochemical system. Leading to the same order of magnitude of improvement in the different forecasting systems, this intercomparison exercise provides robustness of the obtained impact assessment estimates. It also allows us to identify relative strengths and weaknesses of these systems, which are useful to identify future ways of improvement. Overall, this study demonstrates the value of repeated glider observations collected along endurance lines for regional ocean prediction., This study is conducted within the EuroSea project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626., Peer reviewed

The ocean plays an essential role in regulating Earth’s climate, influencing weather conditions, providing sustenance for large populations, moderating anthropogenic climate change, encompassing massive biodiversity, and sustaining the global economy. Human activities are changing the oceans, stressing ocean health, threatening the critical services the ocean provides to society, with significant consequences for human well-being and safety, and economic prosperity. Effective and sustainable monitoring of the physical, biogeochemical state and ecosystem structure of the ocean, to enable climate adaptation, carbon management and sustainable marine resource management is urgently needed. The Argo program, a cornerstone of the Global Ocean Observing System (GOOS), has revolutionized ocean observation by providing real-time, freely accessible global temperature and salinity data of the upper 2,000m of the ocean (Core Argo) using cost-effective simple robotics. For the past 25 years, Argo data have underpinned many ocean, climate and weather forecasting services, playing a fundamental role in safeguarding goods and lives. Argo data have enabled clearer assessments of ocean warming, sea level change and underlying driving processes, as well as scientific breakthroughs while supporting public awareness and education. Building on Argo’s success, OneArgo aims to greatly expand Argo’s capabilities by 2030, expanding to full-ocean depth, collecting biogeochemical parameters, and observing the rapidly changing polar regions. Providing a synergistic subsurface and global extension to several key space-based Earth Observation missions and GOOS components, OneArgo will enable biogeochemical and ecosystem forecasting and new long-term climate predictions for which the deep ocean is a key component. Driving forward a revolution in our understanding of marine ecosystems and the poorly-measured polar and deep oceans, OneArgo will be instrumental to assess sea level change, ocean carbon fluxes, acidification and deoxygenation. Emerging OneArgo applications include new views of ocean mixing, ocean bathymetry and sediment transport, and ecosystem resilience assessment. Implementing OneArgo requires about $100 million annually, a significant increase compared to present Argo funding. OneArgo is a strategic and cost-effective investment which will provide decision-makers, in both government and industry, with the critical knowledge needed to navigate the present and future environmental challenges, and safeguard both the ocean and human wellbeing for generations to come., The author(s) declare that financial support was received for the research and/or publication of this article. VT gratefully acknowledges financial support from the following projects and grants: the Equipex+ Argo-2030 project supported by the French government under the “Investissements d’avenir” program within France 2030 and managed by the Agence Nationale de la Recherche (ANR) under grant agreement no. ANR-21-ESRE-0019; the CPER Obsocean, co-funded by the European Union, Région Bretagne, Département du Finistère, Brest Métropole, and Ifremer; and the Euro-Argo ONE project funded by the European Union's Horizon Europe research and innovation programme under grant agreement no. 101188133. HC acknowledges financial support from the European Research Council (ERC) for the “REFINE—Robots Explore Plankton-drive Fluxes in the Marine Twilight Zone” project (grant agreement 834177) and from the Centre National d’Étude Spatiale (CNES) for the BGC-Argo TOSCA project. NZ acknowledges support from the NOAA Global Ocean Monitoring and Observing Program through Award NA20OAR4320278, and additional support from NSF (OCE-2242742) and Seabed2030 (UNH2042102). MS acknowledges support from the NOAA Global Ocean Monitoring and Observing Program (NA20OAR4320278) and Seabed2030 (UNH2042102). SRJ, WBO, and SEW were supported by the NOAA Global Ocean Monitoring and Observing Program through CINAR Award grant #NA19OAR4320074. KJ acknowledges support from US National Science Foundation projects Southern Ocean Carbon and Climate Observations and Modeling (NSF PLR-1425989, OPP-1936222, and OPP-2332379) and the Global Ocean Biogeochemical Array (NSF OCE-1946578), and support from the David and Lucile Packard Foundation. NK was supported by the Service National d'Observation (SNO) Argo France (INSU/CNRS/UBO). XX is supported by Laoshan Laboratory (LSKJ202201500). SS was supported National Centre for Earth Observation (UK). DR, JS, and MS acknowledge support from the NOAA Global Ocean Monitoring and Observing Program (NA20OAR4320278), with MS also receiving support from Seabed2030 (UNH2042102). GCJ and JML were funded by the NOAA Global Ocean Monitoring and Observation Program and NOAA Research. AJF was supported by the NOAA Pacific Marine Environmental Laboratory, and both AJF and RRR received support from the NOAA National Marine Fisheries Service Essential Data Acquisition Strategic Initiative on Remote Sensing through the Inflation Reduction Act. MSL acknowledges support from the Physical Oceanography Program of the U.S. National Science Foundation through grant OCE-1948335. The work of P.J.D. from Lawrence Livermore National Laboratory (LLNL) is supported by the Regional and Global Model Analysis (RGMA) program area under the Earth and Environmental System Modeling (EESM) program within the Earth and Environmental Systems Sciences Division (EESSD) of the U.S. Department of Energy’s (DOE) Office of Science (OSTI). This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344 (LLNL IM Release#: LLNL-JRNL-2003708). RC and NP received support from the GEORGE project funded by the European Union’s Horizon Europe programme (grant agreement no. 101094716) and from the Euro-Argo ONE project (grant agreement no. 101188133). PMEL Contribution Number 5699. ELM was supported by the European Union under grant agreement no. 101094690 (EuroGO-SHIP). EVW was supported by the Australian Antarctic Program Partnership (funded by the Australian Government Department of Climate Change, Energy, the Environment and Water through the Antarctic Science Collaboration Initiative) and Australia’s Integrated Marine Observing System (IMOS), enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). HH received support from the Met Office Hadley Centre Climate Programme funded by DSIT. AGS acknowledges support from the Spanish National Research Council (CSIC) infrastructure call (INFRA24017). WL acknowledges support from the GREAT project funded by CNES through the Ocean Surface Topography Science Team (OSTST) and from the ESA Sea Level Budget Closure project under the Climate Change Initiative phase 2. OS was supported by NASA award S0-RRNES20-0051 and 80NSSC20K1518. APM received support from the NERC Atlantis project (NE/Y005589/1). D.D. was supported by the French ANR project no. ANR-21-CE01-0011-01—CROSSROAD and the Horizon Europe project 101059547—EPOC. MAB, KM, and HZ received funding from the European Union's Horizon 2020 research and innovation programme (grant agreement no. 862626, EuroSea) and from Horizon Europe (grant agreement no. 101081460, ASPECT Project)., Peer reviewed

Ocean mesoscale variability, including meanders and eddies, is a crucial component of the global ocean circulation. The Eddy Kinetic Energy (EKE) of these features accounts for about 90% of the ocean's total kinetic energy. This study investigates if the global ocean mesoscale variability is becoming more energetic by analyzing 30 years of satellite altimetric observations. We use two observational products: one constructed from a consistent pair of altimeters and another including all available missions. Our results reveal a significant global EKE strengthening of 1-3% per decade. The intensification is concentrated in energetic regions, particularly in the Kuroshio Extension and the Gulf Stream, which show EKE increases of ~ 50% and ~ 20%, respectively, over the last decade. These observations raise new questions about the impact of the Gulf Stream strengthening on the Atlantic meridional overturning circulation (AMOC) and challenge existing climate models, emphasizing the need for improved representation of small-scale ocean processes., B. B.-L. and A. P. acknowledge funding from the EuroSea project, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862626. B. B.-L. is funded by the Balearic Government Vicenç Mut program (Grant number PD/008/2022) and acknowledges support from the METARAOR project (Grant number PID2022-139349OB-I00) funded by MCIN/AEI/10.13039/501100011033/FEDER, EU. A. P., B. B.-L., and V. C. acknowledge support from the FaSt-SWOT project (Grant number PID2021-122417NB-I00) funded by the Spanish Ministry of Science, Innovation, and Universities, the Spanish Research Agency, and the European Regional Development Fund (MCIN/AEI/10.13039/501100011033/FUE). P. R. was supported by a JAE-Intro scholarship issued by the Spanish National Research Council (CSIC). V. C. acknowledges support from the Ramón y Cajal Program (RYC2020-029306-I) and from the European Social Fund/Universitat de les Illes Balears/Spanish State Research Agency (AEI—https://doi.org/10.13039/501100011033). All authors acknowledge funding from the "Copernicus Marine Service Sea Level Thematic Assembly Center" (SL-TAC) project, funded by the Copernicus Marine Service (CMEMS), and from the “Ocean observations and indicators for climate and assessments” (ObsSea4Clim) project, funded by the European Union, Grant Agreement number 101136548, DOI: 10.3030/101136548, contribution nr. 2. This study was carried out within the framework of the activities of the Spanish Government through the “María de Maeztu Centre of Excellence” accreditation to IMEDEA (CSIC-UIB) (CEX2021-001198)., With funding from the Spanish government through the "Maria de Maeztu Centre of Excellence" accreditation (CEX2021-001198)., Peer reviewed

In this study, we use observations and numerical simulations to investigate the effect of meteorological parameters such as wind and atmospheric pressure on harbour water exchanges. The modelled information is obtained from the SAMOA (Sistema de Apoyo Meteorológico y Oceanográfico de la Autoridad Portuaria) forecasting system, which is a high-resolution numerical model for coastal and port-scale forecasting. Based on the observations, six events with high renewal times have been proposed for analysis using the SAMOA model. Therefore, the conclusions of this study have been possible due to the combination of observed data from the measurement campaigns and the information provided by the model. The results show that days with higher renewal times coincide with favourable wind-direction events or increases in atmospheric pressure. After analysing these events using model results, it was observed that during these episodes, water inflows were generated, and in some cases, there was a negative difference in levels between inside and outside the harbour produced by atmospheric pressure variations. The latter may be due to the fact that the water in the harbour (having a lower volume) descends faster and, therefore, generates a difference in level between the exterior and the interior and, consequently, inflow currents that imply an increase in the renewal time. These results are a demonstration of how meteorological information (normally available in ports) can be used to estimate currents and water exchanges between ports and their outer harbour area., This research received funding from the EuroSea project, under agreement with the European Social Fund (ESF) through a grant from FI AGAUR 2020 (Agency for the Management of University and Research Grants). This research has received funding from EuroSea project GA862626 funder H2020-EU.3.2.5.1 The authors want to acknowledge the ECO-BAYS research project (PID2020-115924RB-I00, financed by MCIN/AEI/10.13039/501100011033). The lead author has been financed by the Secretaria d’Universitats i Recerca de la Generalitat de Catalunya and the European Social Fund (ESF)., Peer Reviewed