BUSCADOR RECOLECTA

26 pages, 11 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 data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2020 is an update of the previous version, GLODAPv2.2019. The major changes are data from 106 new cruises added, extension of time coverage to 2019, and the inclusion of available (also for historical cruises) discrete fugacity of CO2 (fCO2) values in the merged product files. GLODAPv2.2020 now includes measurements from more than 1.2 million water samples from the global oceans collected on 946 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 WOCE exchange format and (ii) as a merged data product with adjustments applied to minimize bias. These adjustments were derived by comparing the data from the 106 new cruises with the data from the 840 quality-controlled cruises of the GLODAPv2.2019 data product using crossover analysis. Comparisons to empirical algorithm estimates provided additional context for adjustment decisions; this is new to 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 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 fCO2, were not subjected to bias comparison or adjustments. The original data and their documentation and DOI codes are available at the Ocean Carbon Data System of NOAA NCEI (https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2_2020/, last access: 20 June 2020). 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/10.25921/2c8h-sa89 (Olsen et al., 2020). These bias-adjusted product files also include significant ancillary and approximated data. These were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2020 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 no. 862626). Leticia Cotrim da Cunha was supported by Prociencia/UERJ (grant no. 2019-2021). Marta Álvarez was supported by the IEO RADIALES and RADPROF projects. Peter J. Brown was partially funded by 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. Pérez were supported by the BOCATS2 Project (grant no. PID2019-104279GBC21) co-funded by the Spanish Government and the Fondo Europeo de Desarrollo Regional (FEDER). RikWanninkhof and Brendan R. Carter were supported by the NOAA Global Observations and Monitoring Division (fund reference 100007298) and the Office of Oceanic and Atmospheric Research of NOAA. Henry C. Bittig has been supported by the BONUS INTEGRAL project (grant no. 03F0773A). This research was also funded by the Initiative and
Networking Fund of the Helmholtz Association through the project “Digital Earth” (grant no. ZT-0025), 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

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

11 pages, 2 tables, 4 figures.-- This article is licensed under a Creative Commons Attribution 4.0 International License,, The decreasing seawater pH trend associated with increasing atmospheric carbon dioxide levels is an issue of concern due to possible negative consequences for marine organisms, especially calcifiers. Globally, coastal areas represent important transitional land-ocean zones with complex interactions between biological, physical and chemical processes. Here, we evaluated the pH variability at two sites in the coastal area of the Balearic Sea (Western Mediterranean). High resolution pH data along with temperature, salinity, and also dissolved oxygen were obtained with autonomous sensors from 2018 to 2021 in order to determine the temporal pH variability and the principal drivers involved. By using environmental datasets of temperature, salinity and dissolved oxygen, Recurrent Neural Networks were trained to predict pH and fill data gaps. Longer environmental time series (2012–2021) were used to obtain the pH trend using reconstructed data. The best predictions show a rate of −0.0020±0.00054 pH units year−1, which is in good agreement with other observations of pH rates in coastal areas. The methodology presented here opens the possibility to obtain pH trends when only limited pH observations are available, if other variables are accessible. Potentially, this could be a way to reliably fill the unavoidable gaps present in time series data provided by sensors, 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, 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

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

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

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

19 pages, 14 figures.-- Open Access, The Atlantic Meridional Overturning Circulation entails vigorous thermohaline transformations in the subpolar North Atlantic Ocean (SPNA). There, warm and saline waters originating in the (sub)tropics are converted into cooler and fresher waters by a combination of surface fluxes and sub-surface mixing. Using microstructure measurements and a small-scale variance conservation framework, we quantify the diapycnal and isopycnal contributions –by microscale turbulence and mesoscale eddies, respectively– to thermohaline mixing within the eastern SPNA. Isopycnal stirring is found to account for the majority of thermal (65%) and haline (84%) variance dissipation in the upper 400 m of the eastern SPNA. A simple dimensional analysis suggests that isopycnal stirring could account for (5–10) Sv of diahaline volume flux, suggesting an important role of such stirring in regional water-mass transformations. Our mixing measurements are thus consistent with recent indirect estimates in highlighting the importance of isopycnal stirring for North Atlantic overturning, This research was supported by BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and by EuroGO-SHIP project (Horizon Europe #101094690). BFC is supported by NERC grants NE/W009528/1 and NE/Y002709/1. MF was funded by Juan de La Cierva Formación (FJC2019-038970-I, Ministerio de Ciencia e Innovación, Spanish Government). DFR was supported by a FPU predoctoral fellowship (FPU2021/04749) from the Spanish Ministerio de Universidades, Peer reviewed

This dataset contains the BOCATS2 2023 (A25-Ovide line) pre-qualified measurements of CTD data and qualified microstructure data, BOCATS2, a continuation of the previous BOCATS project (2014-2017), will be a main contribution to the observation of the NA subpolar gyre by continuing the occupation of the biennial section A25-Ovide (2021 and 2023) within the framework of the international GO-SHIP programme. A particular focus will be given to the new challenge of assessing the variability of the deep circulation in the NA, improving the spatial-temporal resolution of deep currents and water mass characteristics by deploying a regional deep-ARGO array and, at a submillenary scale, using paleoceanographic data obtained in sedimentary records from key sites, such as the Bight and Charlie-Gibbs fracture zones. The high-quality observations foreseen in the SPNA will contribute to the early detection of the alteration of the carbon cycle allowing the precise estimation of the heat, CO2 and N2O storage rates and, ultimately, to find the connection between these changes and the variability of the AMOC at different time scales. The natural and anthropogenic fluxes of heat, CO2 and N2O will be evaluated, as well as the present and submillenary scale transport of sediments and biogenic elements, and the impact of acidification on these timescales by means of the analysis of CaCO3 and organic carbon fluxes to the sediment. Besides, the current ocean acidification rates will also be quantified by evaluating the present situation and establishing future projections. These new observation-based estimates will be a valuable result that will be used to validate the predictions from the models (GCMs and ESMs from CMIP5-6) for the 2°C warming scenario. Finally, special attention will be paid to the rates of elevation of aragonite saturation horizons in deep layers, where the impact on the ecosystems sustained by calcareous organisms is potentially imminent, The Spanish project BOCATS2 with the number PID2019-104279GB-C21 was funded by MCIN/AEI/10.13039/501100011033. The French contribution was funded by Ifremer, and is a contribution to the European project Euro GO-SHIP (Grant agreement n°101094690), 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, 5 figures, 2 tables, Increased oceanic uptake of CO2 due to rising anthropogenic emissions has caused lowered pH levels (ocean acidification) that are hypothesized to diminish biotic calcification and reduce the export of total alkalinity (AT) as carbonate minerals from the surface ocean or their burial in coastal sediments. This “CO2-biotic calcification feedback” is a negative feedback on atmospheric CO2, as elevated levels of surface AT increase the ocean's capacity to uptake CO2. We detect signatures of this feedback in the global ocean for the first time using repeat hydrographic measurements and seawater property prediction algorithms. Over the course of the past 30 years, we find an increase in global surface AT of 0.072 ± 0.023 μmol kg−1 yr−1, which would have caused approximately 20 Tmol of additional AT to accumulate in the surface ocean. This finding suggests that anthropogenic CO2 emissions are measurably perturbing the cycling of carbon on a planetary scale by disrupting biological patterns. More observations of AT would be required to understand the effects of this feedback on a regional basis and to fully characterize its potential to reduce the efficiency of marine carbon dioxide removal technolog, RCB and BRC thank the National Oceanographic Partnership Program (NOPP) for support through the Inflation Reduction Act under the National Oceanic and Atmospheric Administration's Ocean Acidification Program award NA23OAR0170515 to University of Washington. Analyses used to explore uncertainties in ESPER estimates and measurements were enabled by support from the Global Ocean Monitoring and Observing program of NOAA through funding the Carbon Data Management and Synthesis Program (Fund Ref. 100007298, program officer: Kathy Tedesco). AJF was supported by NOAA's Pacific Marine Environmental Laboratory (PMEL). BT was supported by CSIRO Environment and the Australian Antarctic Program Partnership. RJW was supported by the National Science Foundation Division of Ocean Sciences (OCE-2148468). KAS was supported by the Atlantic Zone Offshore Monitoring Programme (AZOMP) and the Aquatic Climate Change Adaptation Services Program (ACCASP) of Fisheries and Oceans, Canada. MI was supported by the Environmental Research and Technology Development Fund (JPMEERF24S12200) of the Environmental Restoration and Conservation Agency provided by the Ministry of the Environment of Japan. FFP was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033 and by the European Union under grant agreement no. 101094690 (EuroGO-SHIP), 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