BUSCADOR RECOLECTA

10 pages, 5 figures.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), In the North Atlantic, there are two main western boundary currents related to the Atlantic Meridional Overturning Circulation (AMOC): the Gulf Stream flowing northward and the Deep Western Boundary Current (DWBC) flowing southward. Here we analyze data from the OVIDE section (GO-SHIP A25 Portugal-Greenland 40–60°N) that crosses the DWBC and the northward extension of the Gulf Stream, the North Atlantic Current. We show that North Atlantic western boundary currents play a key role in the transport of dissolved organic matter, specifically dissolved organic carbon (DOC). Revisited transports and budgets of DOC with new available data identify the eastern Subpolar North Atlantic (eSPNA) as an important source of locally produced organic matter for the North Atlantic and a key region in the supply of bioavailable DOC to the deep ocean. The East Greenland Current, and its upstream source the East Reykjanes Ridge Current on the eastern flank of the mid-Atlantic ridge, are export pathways of bioavailable DOC toward subtropical latitudes. The fast overturning and subsequent remineralization of DOC produced in the autotrophic eSPNA explains up to 38% of the total oxygen consumption in the deep North Atlantic between the OVIDE section and 24°N. Carbon budgets that do not take into account this organic remineralization process overestimates the natural uptake of carbon dioxide (CO2) from the atmosphere by one third. The inclusion of DOC transports in regional carbon budgets reconciles the estimates of CO2 uptake in the North Atlantic between model and observations, For this work MF was funded by the Spanish Ministry of Economy and Competitiveness (BES-2014-070449) supported by the Spanish Government and co-funded by the Fondo Europeo de Desarrollo Regional 2007–2012 (FEDER) and by Portuguese national funds from FCT – Foundation for Science and Technology through project UID/Multi/04326/2019 and CEECINST/00114/2018. FP was supported by the BOCATS2 Project (PID2019-104279GB-C21) and ARIOS project (CTM2016-76146-C3-1-R) both co-funded by the Spanish Government and the Fondo Europeo de Desarrollo Regional (FEDER). This project has received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement no. 820989 (project 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). HM was supported by the French Centre National de la Recherche Scientifique, Peer reviewed

12 pages, 6 figures, 1 table.-- Under a Creative Commons license, The net uptake of carbon dioxide (CO2) from the atmosphere is changing the ocean's chemical state. Such changes, commonly known as ocean acidification, include a reduction in pH and the carbonate ion concentration ([CO32−]), which in turn lowers oceanic saturation states (Ω) for calcium carbonate (CaCO3) minerals. The Ω values for aragonite (Ωaragonite; one of the main CaCO3 minerals formed by marine calcifying organisms) influence the calcification rate and geographic distribution of cold-water corals (CWCs), important for biodiversity. Here, high-quality measurements, collected on thirteen cruises along the same track during 1991–2018, are used to determine the long-term changes in Ωaragonite in the Irminger and Iceland Basins of the North Atlantic Ocean, providing the first trends of Ωaragonite in the deep waters of these basins. The entire water column of both basins showed significant negative Ωaragonite trends between −0.0014 ± 0.0002 and −0.0052 ± 0.0007 per year. The decrease in Ωaragonite in the intermediate waters, where nearly half of the CWC reefs of the study region are located, caused the Ωaragonite isolines to rapidly migrate upwards at a rate between 6 and 34 m per year. The main driver of the decline in Ωaragonite in the Irminger and Iceland Basins was the increase in anthropogenic CO2. But this was partially offset by increases in salinity (in Subpolar Mode Water), enhanced ventilation (in upper Labrador Sea Water), and increases in alkalinity (in classical Labrador Sea Water, cLSW; and overflow waters). We also found that water mass aging reinforced the Ωaragonite decrease in cLSW. Based on these Ωaragonite trends over the last three decades, we project that the entire water column of the Irminger and Iceland Basins will likely be undersaturated for aragonite when in equilibrium with an atmospheric mole fraction of CO2 (xCO2) of ~880 ppmv, corresponding to climate model projections for the end of the century based on the highest CO2 emission scenarios. However, intermediate waters will likely be aragonite undersaturated when in equilibrium with an atmospheric xCO2 exceeding ~630 ppmv, an xCO2 level slightly above that corresponding to 2 °C global warming, thus exposing CWCs inhabiting the intermediate waters to undersaturation for aragonite, The research leading to these results was supported through the EU FP7 project CARBOCHANGE “Changes in carbon uptake and emissions by oceans in a changing climate”, which received funding from the European Commission's Seventh Framework Programme under grant agreement No 264879. For this work, M.I. García-Ibáñez and A. Velo were supported by the BOCATS2 Project (PID2019-104279GB-C21) co-funded by the Spanish Government and the Fondo Europeo de Desarrollo Regional (FEDER). M.I. Garcia-Ibanez was also supported by the UK's Natural Environment Research Council CUSTARD grant [NE/P021263/1], part of the RoSES programme. N.R. Bates was funded by National Science Foundation award (OCE–1258622). M. Fontela was funded by Portuguese national funds from the FCT–Foundation for Science and Technology through project UID/Multi/04326/2019 and CEECINST/00114/2018. This project has also received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 820989 (project 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), Peer reviewed

16 pages, 2 tables, 5 figures.-- This article is licensed under a Creative Commons Attribution 4.0 International License, The processes of warming, anthropogenic CO2 (Canth) accumulation, decreasing pHT (increasing [H+]T; concentration in total scale) and calcium carbonate saturation in the subarctic zone of the North Atlantic are unequivocal in the time-series measurements of the Iceland (IS-TS, 1985–2003) and Irminger Sea (IRM-TS, 1983–2013) stations. Both stations show high rates of Canth accumulation with different rates of warming, salinification and stratification linked to regional circulation and dynamics. At the IS-TS, advected and stratified waters of Arctic origin drive a strong increase in [H+]T, in the surface layer, which is nearly halved in the deep layer (44.7 ± 3.6 and 25.5 ± 1.0 pmol kg−1 yr−1, respectively). In contrast, the weak stratification at the IRM-TS allows warming, salinification and Canth uptake to reach the deep layer. The acidification trends are even stronger in the deep layer than in the surface layer (44.2 ± 1.0 pmol kg−1 yr−1 and 32.6 ± 3.4 pmol kg−1 yr−1 of [H+]T, respectively). The driver analysis detects that warming contributes up to 50% to the increase in [H+]T at the IRM-TS but has a small positive effect on calcium carbonate saturation. The Canth increase is the main driver of the observed acidification, but it is partially dampened by the northward advection of water with a relatively low natural CO2 content, FFP was founded by the Ministerio Ciencia, Innovación y Universidades (Grant No. PRX18/00312) for visiting Dr. Taro Takahashi in LDEO in 2019. FFP were also supported by the BOCATS2 Project (PID2019-104279GB-C21) co-funded by the Spanish Government and the Fondo Europeo de Desarrollo Regional (FEDER). FFP and SRO were supported by the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 820989 (project 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, Peer reviewed

14 pages, 4 tables, 4 figures.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY), Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above., Funding for L-QJ and AK was from NOAA Ocean Acidification Program (OAP, Project ID: 21047) and NOAA National Centers for Environmental Information (NCEI) through NOAA grant NA19NES4320002 [Cooperative Institute for Satellite Earth System Studies (CISESS)] at the University of Maryland/ESSIC. BT was in part supported by the Australia’s Integrated Marine Observing System (IMOS), enabled through the National Collaborative Research Infrastructure Strategy (NCRIS). AD was supported in part by the United States National Science Foundation. AV and FP were supported by BOCATS2 Project (PID2019-104279GB-C21/AEI/10.13039/501100011033) funded by the Spanish Research Agency and contributing to WATER:iOS CSIC interdisciplinary thematic platform. MH was partly funded by the European Union’s Horizon 2020 Research and Innovation Program under grant agreement N°821001 (SO-CHIC), Peer reviewed

The database provides discrete measurements of carbon system parameters in water samples collected at 3 stations that form the marine time series GIFT during 33 oceanographic campaigns conducted over 2005–2021. Geographic coordinates of sampling stations are provided. Some physical data (i.e. pressure, temperature and salinity) are also included. Moreover, pH data obtained with a SAMI-pH sensor (Sunburst Sensors, LLC)) attached to a mooring line deployed in the Strait of Gibraltar for the years 2016 and 2017 are provided.
During the cruises, a temperature and salinity profile was obtained with a Seabird 911Plus CTD probe. Seawater was subsequently collected for biogeochemical analysis using Niskin bottles immersed in an oceanographic rosette platform at variable depths (from 5 to 8 levels) depending on the instant position of the interface between the Atlantic and Mediterranean flows that was identified by CTD profiles. The biogeochemical variables shown in the database are pH in total scale at 25 °C (pHT25), total alkalinity (AT), and inorganic nutrients (phosphate, PO43and Silicate, SiO44−). pHT25 data were obtained by the spectrophotometric method with m-cresol purple as the indicator (Clayton & Byrne 1993). Samples were taken directly from the oceanographic bottles in 10 cm path-length optical glass cells and measurements were carried out with a Shimadzu UV-2401PC spectrophotometer containing a 25 °C-thermostated cells holder. Samples for AT analysis were collected in 500-ml borosilicate bottles, and poisoned with 100 μl of HgCl2-saturated aqueous solution and stored until measurement in the laboratory. AT was measured by potential titration according to Mintrop et al. (2000) with a Titroprocessor (model Metrohm 794 from 2005-2020 and model Metrothm 888 for 2021). Water samples (5 mL, two replicates) for inorganic nutrients determination were taken, filtered immediately (Whatman GF/F, 0.7 μm) and stored frozen for later analyses in the shore-based laboratory. Nutrients concentrations were measured with a continuous flow auto-analyzer using standard colorimetric techniques (Hansen & Koroleff 1999).

2. Methods for processing the data:
3. Instrument- or software-specific information needed to interpret/reproduce the data, please indicate their location:
4. Standards and calibration information, if appropriate:
5. Environmental/experimental conditions:
6. Describe any quality-assurance procedures performed on the data:
7. People involved with sample collection, processing, analysis and/or submission, please specify using CREDIT roles https://casrai.org/credit/:

Chief Scientists -I.Emma Huertas/Susana Flecha;
Hydro: Who -Susana Flecha/David Roque/Silvia Amaya-Vías/Angélica Enrique;
Nuts: Who -Manuel Arjonilla/ Status - final;
Silicate and Phosphate Autoanalizer Hansen and Koroleff (1999), This research was supported by the COMFORT project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 820989 (project 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).” Funding was also provided by the European projects CARBOOCEAN (FP6-511176), CARBOCHANGE (FP7-264879), PERSEUS (FP7-287600) and the Junta de Andalucía TECADE project (PY20_00293). The dataset is subject to a Creative Commons License Attribution-ShareAlike 4.0 International. F.F.P. was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033. SAV was supported by a pre-doctoral grant FPU19/04338 from the Spanish Ministry of Science, Innovation and Universities., Peer reviewed

10 pages, 5 figures.-- Under a Creative Commons license.-, Understanding the ocean carbon sink and its future acidification-derived changes requires accurate and precise measurements with good spatiotemporal coverage. In addition, a deep knowledge of the thermodynamics of the seawater carbonate system is key to interconverting between measured and calculated variables. To gain insights into the remaining inconsistencies in the seawater carbonate system, we assess discrete water column measurements of carbon dioxide fugacity (fCO2), dissolved inorganic carbon (DIC), total alkalinity (TA), and pH measured with unpurified indicators, from hydrographic cruises in the Atlantic, Pacific, and Southern Oceans included in GLODAPv2.2020 (19,013 samples). An agreement of better than ± 3% between fCO2 measured and calculated from DIC and pH is obtained for 94% of the compiled dataset, while when considering fCO2 measured and calculated from DIC and TA, the agreement is better than ± 4% for 88% of the compiled dataset, with a poorer internal consistency for high-CO2 waters. Inspecting all likely sources of uncertainty from measured and calculated variables, we conclude that the seawater carbonate system community needs to (i) further refine the thermodynamic model of the seawater carbonate system, especially K2, including the impact of organic compounds and other acid-base systems on TA; (ii) update the standard operating procedures for the seawater carbonate system measurements following current technological and analytical advances, paying particular attention to the pH methodology that is the one that evolved the most; (iii) encourage measuring discrete water column fCO2 to further check the internal consistency of the seawater carbonate system, especially given the new era of sensor-based seawater measurements; and (iv) develop seawater Certified Reference Materials (CRMs) for fCO2 and pH together with seawater CRMs for TA and DIC over the range of values encountered in the global ocean. Our conclusions also suggest the need for a re-evaluation of the adjustments applied by GLODAPv2 to pH, which were based on DIC and TA consistency checks but not supported by fCO2 and DIC consistency, The research leading to these results was supported through NOAA's Ocean Acidification Program (OAP) via Award #NA17OAR0170332; through NERC via project NE/P021263/1; through the Spanish Research Agency via project PID2019-104279GB-C21/AEI/10.13039/501100011033; and through GAIN via grant IN607A2018/2, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

[Description of methods used for collection/generation of data] In both stations a SAMI-pH (Sunburst Sensors LCC) was attached, at 1 m in the Bay of Palma and at 4 m depth in Cabrera. The pH sensors were measuring pH, in the total scale (pH𝑇T), hourly since December 2018 in the Bay of Palma and since November 2019 in Cabrera. The sensor precision and accuracy are < 0.001 pH and ± 0.003 pH units, respectively. Monthly maintenance of the sensors was performed including data download and surface cleaning. Temperature and salinity for the Cabrera mooring line was obtained starting November 2019 with a CT SBE37 (Sea-Bird Scientific©). Accuracy of the CT is ± 0.002 ∘C for temperature and ± 0.003 mS cm−1−1 for conductivity. Additionally, oxygen data from a SBE 63 (Sea-Bird Scientific ©) sensor attached to the CT in Cabrera were used. Accuracy of oxygen sensors is ± 2% for the SBE 63., [Methods for processing the data] Periodically water samplings for dissolved oxygen (DO), pH in total scale at 25 ∘C (pH𝑇25) and total alkalinity (TA) were obtained during the sensor maintenance campaigns. DO and (pH𝑇25) samples were collected in order to validate the data obtained by the sensors.
DO concentrations were evaluated with the Winkler method modified by Benson and Krause by potentiometric titration with a Metrohm 808 Titrando with a accuracy of the method of ± 2.9 μmol kg−1μmol kg−1 and with an obtained standard deviation from the sensors data and the water samples collected of ± 5.9 μmol kg−1μmol kg−1.
pH𝑇25T25 data was obtained by the spectrophotometric method with a Shimadzu UV-2501 spectrophotometer containing a 25 ∘C-thermostated cells with unpurified m-cresol purple as indicator following the methodology established by Clayton and Byrne by using Certified Reference Material (CRM Batch #176 supplied by Prof. Andrew Dickson, Scripps Institution of Oceanography, La Jolla, CA, USA). The accuracy obtained from the CRM Batch was of ± 0.0051 pH units and the precision of the method of ± 0.0034 pH units. The mean difference between the SAMI-pH and discrete samples was of 0.0017 pH units., Funding for this work was provided by the projects RTI2018-095441-B-C21 (SuMaEco) and, the BBVA Foundation project Posi-COIN and the Balearic Islands Government projects AAEE111/2017 and SEPPO (2018). SF was supported by a “Margalida Comas” postdoctoral scholarship, also from the Balearic Islands Government.
FFP 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., Peer reviewed

[Description of methods used for collection/generation of data] Data was acquired in both stations using a SAMI-pH (Sunburst Sensors LCC) was attached, at 1 m in the Bay of Palma and at 4 m depth in Cabrera. The pH sensors were measuring pH, in the total scale (pH𝑇), hourly since December 2018 in the Bay of Palma and since November 2019 in Cabrera. The sensor precision and accuracy are < 0.001 pH and ± 0.003 pH units, respectively. Monthly maintenance of the sensors was performed including data download and surface cleaning. Temperature and salinity for the Cabrera mooring line was obtained starting November 2019 with a CT SBE37 (Sea-Bird Scientific©). Accuracy of the CT is ± 0.002 ∘C for temperature and ± 0.003 mS cm−1−1 for conductivity. Additionally, oxygen data from a SBE 63 (Sea-Bird Scientific ©) sensor attached to the CT in Cabrera were used. Accuracy of oxygen sensors is ± 2% for the SBE 63., [Methods for processing the data] Once data (available at https://doi.org/XXX/DigitalCSIC/XXX) was validated, several processing steps were performed to ensure an optimal training process for the neural network models. First, all the data of the time series were re-sampled by averaging the data points obtaining a daily frequency. Afterwards, a standard feature-scaling procedure (min-max normalization) was applied to every feature (temperature, salinity and oxygen) and to pHT. Finally, we built our training and validations sets as tensors with dimensions (batchsize, windowsize, 𝑁features), where batchsize is the number of examples to train per iteration, windowsize is the number of past and future points considered and 𝑁features is the number of features used to predict the target series. Temperature values below 𝑇=12.5T=12.5 °C were discarded as they are considered outliers in sensor data outside the normal range in the study area.
A BiDireccional Long Short-Term Memory (BD-LSTM) neural network was selected as the best architecture to reconstruct the pHT time series, with no signs of overfitting and achieving less than 1% error in both training and validation sets. Data corresponding to the Bay of Palma were used in the selection of the best neural network architecture. The code and data used to determine the best neural network architecture can be found in a GitHub repository mentioned in the context information., Funding for this work was provided by the projects RTI2018-095441-B-C21, RTI2018-095441-B-C22 (SuMaEco) and Grant MDM-2017-0711 (María de Maeztu Excellence Unit) funded by MCIN/AEI/10.13039/501100011033 and by the “ERDF A way of making Europe", the BBVA Foundation project Posi-COIN and the Balearic Islands Government projects AAEE111/2017 and SEPPO (2018). SF was supported by a “Margalida Comas” postdoctoral scholarship, also from the Balearic Islands Government.
FFP 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 (https://pti-waterios.csic.es/)., Peer reviewed

20 pages, 5 figures.-- Open access, The change in anthropogenic CO2 (Canth) in the Atlantic Ocean is linked to the Atlantic Meridional Overturning Circulation (AMOC), that redistributes Canth meridionally and in depth. We have employed direct biogeochemical measurements and hydrographic data from the last 30 years, adjusted using inverse models for each decade with both physical and biogeochemical constraints. We then have computed the meridional transports and the vertical transports between two sections at the interphases by advection and diffusion. We have focused on the repeated sections at three latitudes—30°S, 24, and 55°N, dividing the Atlantic into two boxes. We have divided the net transport into upper, deep and abyssal layers, with an upper and abyssal northward transport of Canth and a southward component in deep layers. The change in time in the net transports of Canth appears to be mainly due to modifications in the transport of upper layers. The lower layer of the AMOC, a combination of deep and abyssal waters, maintain more consistent transports in time. Vertical advection plays an important role in the North Atlantic, exporting Canth from upper to deep layers. In the South Atlantic, the newly formed Antarctic Bottom Water exports Canth from abyssal to deep layers. The strong gradient in Canth concentration at the interphase of upper and deep layers results in a strong vertical diffusion, V.C. acknowledges the Agencia Canaria de Investigación, Innovación y Sociedad de la Información (ACIISI) grant program of “Apoyo al personal investigador en formación” TESIS2019010015. V.C. and A.H-G. were supported by the SAGA project (RTI2018-100844-B-C31) funded by the Ministerio de Ciencia, Innovación y Universidades of the Spanish Government. F.F.P. and A.V. were supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and contributing to WATER:iOS CSIC PTI, 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

34 pages, 13 figures, 6 tables.-- This is an open access article under the terms of the Creative Commons Attribution License, The seasonal cycle is the dominant mode of variability in the air-sea CO2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO2 and air-sea CO2 flux seasonality from models and observation-based estimates, focusing on both a present-day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation-based estimates (pCO2 products) of surface pCO2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO2 has increased in amplitude over the last three decades in both pCO2 products and GOBMs. Third, decadal increases in pCO2 seasonal cycle amplitudes in subtropical biomes for both pCO2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO2 (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO2 products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome-aggregated decadal changes in the amplitude of pCO2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high-quality seasonally resolved measurements over these regions, We would like to thank the financial sponsors of the original kickoff meeting for RECCAP2 in Gotemba Japan in March 2019, which facilitated not only this paper but the broader RECCAP2 synthesis project. The Japanese sponsors of the kickoff meeting were the National Institute for Environmental Studies (NIES) and the Japan Agency for Marine-Earth Science and Technology (JAMSTEC). The international sponsors of the meeting were the Global Carbon Project (GCP), the European Space Agency (ESA), and the International Ocean Carbon Coordination Program (IOCCP). We also acknowledge the support of KREONET. KBR, KS, JK, and SSH were supported by the Institute for Basic Science in Korea (Grant IBS-R028-D1). JS acknowledges support from the Research Council of Norway (Grant 270061). PV, JT and NGo acknowledge funding from the Research Council of Norway (COLUMBIA-275268 and CE2COAST-318477). AJF was supported by NOAA’s Pacific Marine Environmental Laboratory (PMEL). PL acknowledges support for the VLIZ ICOS carbon data collection work from Research Foundation Flanders (FWO) contract I001821N. The contribution of HF was funded by support from the Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CICOES) under NOAA Cooperative Agreement NA20OAR4320271, Contribution No. 2023-1266. JDM, MG, LGr and NGr acknowledge support from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 821003 (project 4C) and no. 820989 (project COMFORT). MG and TTTC acknowledge funding from the European Copernicus Marine Environment Monitoring Service (no. 83-CMEMSTAC-MOB). JH was supported by the Initiative and Networking Fund of the Helmholtz Association (Helmholtz Young Investigator Group Marine Carbon and Ecosystem Feedbacks in the Earth System [MarESys], Grant number VH-NG-1301). MI, KT, and YI were supported by the Environment Research and Technology Development Fund (JPMEERF21S20803) of the Environmental Restoration and Conservation Agency provided by the Ministry of the Environment of Japan. MI and KT were additionally supported by MEXT KAKENHI Grant Number JP19H05700. LK was supported by NSF’s Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project under the NSF Awards PLR-1425989 and OPP-1936222, with additional support from NOAA and NASA. A. Velo was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033. S.S. acknowledges support by NSF’s Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project under the NSF Award PLR-1425989, with additional support from NOAA and NASA. SB was supported by NASA Carbon Cycle Science (80NSSC22K0156), NOAA Climate Program Office's Climate Observations and Monitoring, Climate Variability and Predictability, and Global Ocean Monitoring and Observation programs (NA21OAR4310260), and NSF (OCE-2049631), Peer reviewed

32 pages, 3 tables, 7 figures.-- This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, This contribution to the RECCAP2 (REgional Carbon Cycle Assessment and Processes) assessment analyzes the processes that determine the global ocean carbon sink, and its trends and variability over the period 1985–2018, using a combination of models and observation-based products. The mean sea-air CO2 flux from 1985 to 2018 is −1.6 ± 0.2 PgC yr−1 based on an ensemble of reconstructions of the history of sea surface pCO2 (pCO2 products). Models indicate that the dominant component of this flux is the net oceanic uptake of anthropogenic CO2, which is estimated at −2.1 ± 0.3 PgC yr−1 by an ensemble of ocean biogeochemical models, and −2.4 ± 0.1 PgC yr−1 by two ocean circulation inverse models. The ocean also degasses about 0.65 ± 0.3 PgC yr−1 of terrestrially derived CO2, but this process is not fully resolved by any of the models used here. From 2001 to 2018, the pCO2 products reconstruct a trend in the ocean carbon sink of −0.61 ± 0.12 PgC yr−1 decade−1, while biogeochemical models and inverse models diagnose an anthropogenic CO2-driven trend of −0.34 ± 0.06 and −0.41 ± 0.03 PgC yr−1 decade−1, respectively. This implies a climate-forced acceleration of the ocean carbon sink in recent decades, but there are still large uncertainties on the magnitude and cause of this trend. The interannual to decadal variability of the global carbon sink is mainly driven by climate variability, with the climate-driven variability exceeding the CO2-forced variability by 2–3 times. These results suggest that anthropogenic CO2 dominates the ocean CO2 sink, while climate-driven variability is potentially large but highly uncertain and not consistently captured across different methods, TD acknowledges support from the US National Science Foundation through Grant OCE-1948955. RW and BR are supported by funding from NOAA's Global Ocean Monitoring and Observations (GOMO) Program. The CICOES and PMEL contributions to this work are numbers 2023-1260 and 5497, respectively. JDM, LG, and NG acknowledge support from the European Union's Horizon 2020 research and innovation programme under Grant agreement no. 821003 (project 4C) and no. 820989 (project COMFORT). JH acknowledges funding from the Initiative and Networking Fund of the Helmholtz Association (Helmholtz Young Investigator Group Marine Carbon and Ecosystem Feedbacks in the Earth System (MarESys), Grant VH-NG-1301) and from ERC-2022-STG OceanPeak, Grant agreement 101077209. DC acknowledges support from the NASA Carbon Cycle and Ecosystems (CCE) program under Grant 80NSSC22K0154. SCD acknowledges support from the NSF Center for Chemical Currencies of a Microbial Planet (C-CoMP) (NSF Award 2019589). SAH was supported by a European Research Council Consolidator Grant (GOCART, agreement number 724416). PL was supported by Research Foundation Flanders (FWO) contract I001821N. CN acknowledges funding from the European Union's Horizon 2020 research and innovation programme under Grant agreement No 820989 (project COMFORT). LP acknowledges funding from the project PA 3075/2-1 by the German Research Foundation and the North German Supercomputing Alliance (HLRN) for providing computing power for the experiments. FFP was supported by the BOCATS2 project (PID2019-104279GB-C21) funded by MCIN/AEI/10.13039/501100011033. KBR was supported by the Institute for Basic Sciences (IBS), Republic of Korea, under IBS-R028-D1. JS acknowledges funding from the Research Council of Norway (Grant 270061) and computational/storage resources provided by UNINET/sigma2 (nn/ns2980k). JTH was funded by the Woods Hole Oceanographic Institution Postdoctoral Scholar Program, the European Union's Horizon 2020 research and innovation program under grant agreement 821003 (project 4C, Climate-Carbon Interactions in the Current Century), and the Swiss National Science Foundation under Grant 200020_200511. CLQ acknowledges funding from the European Union project 4C (Grant 821003) and the Royal Society (Grant RP\R1\191063), and support from UEA’s High Performance Computing services. TTTC and MG acknowledge financial support by the European Copernicus Marine Environment Monitoring Service (CMEMS) MOB-TAC project for the joint development with F. Chevallier of the CMEMS-LSCE-FFNN model, 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

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

32 pages, 10 figures, 2 tables.-- Open Access, The ocean is a major carbon sink and takes up 25%–30% of the anthropogenically emitted CO2. A state-of-the-art method to quantify this sink are global ocean biogeochemistry models (GOBMs), but their simulated CO2 uptake differs between models and is systematically lower than estimates based on statistical methods using surface ocean pCO2 and interior ocean measurements. Here, we provide an in-depth evaluation of ocean carbon sink estimates from 1980 to 2018 from a GOBM ensemble. As sources of inter-model differences and ensemble-mean biases our study identifies (a) the model setup, such as the length of the spin-up, the starting date of the simulation, and carbon fluxes from rivers and into sediments, (b) the simulated ocean circulation, such as Atlantic Meridional Overturning Circulation and Southern Ocean mode and intermediate water formation, and (c) the simulated oceanic buffer capacity. Our analysis suggests that a late starting date and biases in the ocean circulation cause a too low anthropogenic CO2 uptake across the GOBM ensemble. Surface ocean biogeochemistry biases might also cause simulated anthropogenic fluxes to be too low, but the current setup prevents a robust assessment. For simulations of the ocean carbon sink, we recommend in the short-term to (a) start simulations at a common date before the industrialization and the associated atmospheric CO2 increase, (b) conduct a sufficiently long spin-up such that the GOBMs reach steady-state, and (c) provide key metrics for circulation, biogeochemistry, and the land-ocean interface. In the long-term, we recommend improving the representation of these metrics in the GOBMs, J. Terhaar acknowledges funding from the Woods Hole Oceanographic Institution Postdoctoral Scholar Program, and the Swiss National Science Foundation under Grants PZ00P2_209044 and 200020_200511. N. Goris acknowledges funding from the Norwegian Research Council through the project COLUMBIA (Grant 275268). J. Terhaar, J.D. Müller, and N. Gruber acknowledge funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 821003 (project 4C, Climate–Carbon Interactions in the Current Century). F.F. Pérez was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and contributed to WATER:iOS CSIC PTI. N. Gruber acknowledges further support from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 821001 (SO-CHIC). T. DeVries acknowledges support from NSF Grant OCE-1948955. J. Hauck and R. Seferian were supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 820989 (project COMFORT). J. Hauck acknowledges funding from the Initiative and Networking Fund of the Helmholtz Association (Helmholtz Young Investigator Group Marine Carbon and Ecosystem Feedbacks in the Earth System [MarESys], Grant VH-NG-1301) and from ERC-2022-STG OceanPeak (Grant 101077209). R. Seferian thanks the ESM2025 project under the grant agreement No. 101003536, Peer reviewed

31 pages, 8 figures, 1 table.-- This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, As part of the second phase of the Regional Carbon Cycle Assessment and Processes project (RECCAP2), we present an assessment of the carbon cycle of the Atlantic Ocean, including the Mediterranean Sea, between 1985 and 2018 using global ocean biogeochemical models (GOBMs) and estimates based on surface ocean carbon dioxide (CO2) partial pressure (pCO2 products) and ocean interior dissolved inorganic carbon observations. Estimates of the basin-wide long-term mean net annual CO2 uptake based on GOBMs and pCO2 products are in reasonable agreement (−0.47 ± 0.15 PgC yr−1 and −0.36 ± 0.06 PgC yr−1, respectively), with the higher uptake in the GOBM-based estimates likely being a consequence of a deficit in the representation of natural outgassing of land derived carbon. In the GOBMs, the CO2 uptake increases with time at rates close to what one would expect from the atmospheric CO2 increase, but pCO2 products estimate a rate twice as fast. The largest disagreement in the CO2 flux between GOBMs and pCO2 products is found north of 50°N, coinciding with the largest disagreement in the seasonal cycle and interannual variability. The mean accumulation rate of anthropogenic CO2 (Cant) over 1994–2007 in the Atlantic Ocean is 0.52 ± 0.11 PgC yr−1 according to the GOBMs, 28% ± 20% lower than that derived from observations. Around 70% of this Cant is taken up from the atmosphere, while the remainder is imported from the Southern Ocean through lateral transport, F. F. Pérez and A. Velo were supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and by European Union under grant agreement no. 101094690 (EuroGO-SHIP), and with E. Huertas contributed to WATER:iOS CSIC PTI. M. Becker acknowledges funding from the Research Council of Norway through N-ICOS-2 (Grant 296012), and Nansen Legacy, Grant 276730. N. Goris was supported by the strategic project DYNASOR (DYnamics of the North Atlantic Surface and Overturning ciRculation) of the Bjerknes Centre for Climate Research. M. López-Mozos was supported by the Grant PRE2020-093138 funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future.” J. Tjiputra acknowledges funding from EU funded H2020 projects TRIATLAS (no. 817578) and OceanICU (no. 101083922). A. Olsen appreciates support from the Research Council of Norway through N-ICOS-2 (Grant 296012), and Horizon Europe through Grant 101083922 (OceanICU Improving Carbon Understanding). J.D. Müller and N. Gruber acknowledge support from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 821003 (project 4C) and no. 820989 (project COMFORT). M. Gehlen acknowledges support from the European Union’s Horizon 2020 research and innovation program under grant agreements no. 820989 (project COMFORT) and no. 862923 (project AtlantECO), as well as from Horizon Europe through Grant 101083922 (OceanICU). T. Chau and M. Gehlen appreciate funding through the European Copernicus Marine Environment Monitoring Service (CMEMS) Grant 83-CMEMSTAC-MOB. J. Hauck acknowledges funding from the Initiative and Networking Fund of the Helmholtz Association (Helmholtz Young Investigator Group Marine Carbon and Ecosystem feedback in the Earth System [MarESys], Grant VH-NG-1301) and from ERC-2022-STG OceanPeak, Grant agreement 101077209. R. Wanninkof acknowledges funding from the NOAA/OAR Global Ocean Monitoring and Observation Program (GOMO), 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

29 pages, 4 tables, 7 figures, The CO2–carbonate system dynamics in the North Atlantic subpolar gyre (NASPG) were evaluated between 2009 and 2019. Data were collected aboard eight summer cruises through the Climate and Ocean: Variability, Predictability and Change (CLIVAR) 59.5° N section. The ocean acidification (OA) patterns and the reduction in the saturation state of calcite (ΩCa) and aragonite (ΩArag) in response to the increasing anthropogenic CO2 (Cant) were assessed within the Irminger, Iceland, and Rockall basins during a poorly assessed decade in which the physical patterns reversed in comparison with previous well-known periods. The observed cooling, freshening, and enhanced ventilation increased the interannual rate of accumulation of Cant in the interior ocean by 50 %–86 % and the OA rates by close to 10 %. The OA trends were 0.0013–0.0032 units yr−1 in the Irminger and Iceland basins and 0.0006–0.0024 units yr−1 in the Rockall Trough, causing a decline in ΩCa and ΩArag of 0.004–0.021 and 0.003–0.0013 units yr−1, respectively. The Cant-driven rise in total inorganic carbon (CT) was the main driver of the OA (contributed by 53 %–68 % in upper layers and > 82 % toward the interior ocean) and the reduction in ΩCa and ΩArag (> 64 %). The transient decrease in temperature, salinity, and AT collectively counteracts the CT-driven acidification by 45 %–85 % in the upper layers and in the shallow Rockall Trough and by < 10 % in the interior ocean. The present investigation reports the acceleration of the OA within the NASPG and expands knowledge about the future state of the ocean, This research has been supported by the Ministerio de Ciencia e Innovación (grant nos. CTM2008-05255, CTM2010-09514-E, CTM2011-12984-E, CTM2014-52342-P, CTM2017-83476-P, and PID2019-104279GB-C21); the HORIZON EUROPE Research Infrastructures (grant no. 101094690); the Universidad de Las Palmas de Gran Canaria (grant no. PIFULPGC-2020-2 ARTHUM-2); and the Shirshov Institute of Oceanology, Russian Academy of Sciences (grant no. FMWE-2023-0002), Peer reviewed

15 pages, 7 figures, The subpolar North Atlantic (SPNA) is crucial in the global ocean circulation system and one of the few regions where deep convection occurs. The intermediate and deep waters formed in the SPNA have long been investigated, yet their sources and pathways are not fully understood. In this study, we employ a combination of two radionuclide tracers, namely, 129I and 236U, to understand water mass provenance and mixing in the SPNA. The concentrations measured between Portugal and Greenland and across the Labrador Sea in 2020/2021 agreed with previously observed tracer distributions. The highest tracer concentrations were measured in the East Greenland Current (EGC), Denmark Strait Overflow Water (DSOW), and, to a lesser extent, in the eastward-flowing Labrador Sea Water (LSW). In contrast, waters of southern origin such as the North East Antarctic Bottom Water and North East Atlantic Central Water (ENACW) carried comparably smaller amounts of 129I. By using a binary mixing model, we estimated that the EGC contains about 29%–32% of the Polar Surface Water outflowing the Fram Strait. DSOW was mainly derived from 20% to 35% Return Atlantic Water and mixed with LSW. The Iceland Scotland Overflow Water (ISOW) evolved into North East Atlantic Deep Water in the Irminger and Labrador seas primarily by mixing with LSW and, to a lesser extent, with DSOW. The 129I and 236U binary mixing approach was less conclusive for LSW, reaching the current limitation of the model. This study suggests potential benefits and limitations of using 129I and 236U to investigate the mixing and provenance of water masses in the SPNA, This work was mainly funded by the European Research Council grant TITANICA awarded to NC (Grant agreement 101001451). Additional funds came from the Swiss National Science Foundation (Grant number PR00P2_193091) awarded to NC and the ETH Career SEED Grant (SEED-06 19-2) awarded to MCa as well as the consortium partners of the ETH Zurich Laboratory of Ion Beam Physics (EAWAG, EMPA, and PSI). Statement: Open access funding is provided by Swiss National Science Foundation (SNSF). This work has been supported by BOCATS2 (PID2019-104279GB-C21) project funded by MICIU/AEI/10.13039/501100011033, Peer reviewed

19 pages, 5 figures, Over the last decades, back-calculation (BC) techniques for ocean anthropogenic carbon (Cant) estimation have improved and evolved into different methodologies that are not exempt from various assumptions and limitations. No single optimal BC method exists to date for computing Cant; therefore, it is necessary to continue advancing the broad range of approaches. Here, we present a novel method based on the BC fundamentals that combines marine-carbonate-system (MCS) data and the Total Matrix Intercomparison (TMI) framework. This MCS-TMI approach differs from other BC methods by using the TMI to reconstruct deep-ocean biogeochemical properties and their preformed conditions. It also incorporates a global sea-air oxygen disequilibrium term, and a dynamic stoichiometric carbon-to-oxygen ratio that depends on the water-mass ideal time. The MCS-TMI yields a total Cant inventory of 124 ± 7 Pg C (referred to 1995), in good agreement with previous global Cant climatologies. The MCS-TMI method uncertainty (±5.6 μmol kg−1) is controlled by input-data errors that, nonetheless, have a minimal impact on the total Cant inventory. In contrast, our total Cant inventory uncertainty is governed by methodological errors, specifically those related to the TMI's boundary conditions. Our study demonstrates the effectiveness of MCS data-based climatologies in reconstructing a 3D gridded Cant climatology, and the validity of ocean circulation transport operators for obtaining BC preformed conditions, M. López-Mozos was supported by the grant PRE2020-093138 funded by MICIU/AEI/10.13039/501100011033 and by “ESF Investing in your future”. F. F Pérez was supported by the FICARAM+ project (PID2023-148924OB-l00). A. Velo was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MICIU/AEI/10.13039/501100011033, and by EuroGO-SHIP project (Horizon Europe #101094690). L.I. Carracedo was supported by Ifremer, Peer reviewed

8 files, Dataset of "The Unaccounted Oceanic Sink of Anthropogenic Nitrous Oxide and its Relationship with Anthropogenic Carbon Dioxide"

Following files are provided:

- column_inventory_cant_molm2_n2oant_mmolm2.csv: Stands for the integrated values of Cant and N2Oant for each method and for the full water column in the WOA 1deg x 1deg grid
- 3D_global_inventory_cant_n2oant.nc: Stands for the concentration values of Cant and N2Oant for each method and for the full WOA 1deg x 1deg x 33 levels grid
- TTD_ files: mat files for cant and n2oant for the Glodapv2 (2016) dataset, and for Atlantic, Pacific and Indian Ocean, Agencia Estatal de Investigación, BOCATS2, funded by MICIU/AEI/10.13039/501100011033, PID2019‐104279GB‐C21; Agencia Estatal de Investigación, PTA 2019 funded by MCIN/AEI/10.13039/501100011033 PTA2019-017983-I; European Commission, Euro GO-SHIP – Euro GO-SHIP: developing a Research Infrastructure concept to support European hydrography, Peer reviewed