This dataset contains observation-based pCO2 data and a derived monthly climatology. The observation-based pCO2 fields were created using a 2-step neural network method extensively described and validated in Landschützer et al. 2013, 2014, 2016. The method first clusters the global ocean into biogeochemical provinces and in a second step reconstructs the non-linear relationship between CO2 driver variables and observations from the v2022 release of the Surface Ocean CO2 Atlas (SOCAT, Bakker et al. 2016). This file contains the resulting monthly pCO2 fields at 1°x1° resolution covering the global ocean for the first time including the Arctic Ocean and few marginal seas (see Landschützer et al 2020). The air-sea CO2 fluxes are computed from the air-sea CO2 partial pressure difference and a bulk gas transfer formulation following Landschützer et al. 2013, 2014, 2016. Furthermore, the monthly climatology is created from the monthly average of the period 1985-present.

This dataset contains reconstructed 'pseudo' wintertime observations of surface pCO2 for the Southern Ocean south of the Antarctic Polar Front from 2004-01-01 to 2018-12-31. The pseudo observations are constructed using subsurface summertime observations of DIC and other tracers in the GLODAP database according to the methods of Mackay and Watson (2021).

This dataset contains continuous monthly maps of sea surface partial pressure of CO2 (pCO2) in the coastal ocean from 1982 to 2020. This product is an updated version of the coastal product of Laruelle et al. (2017) and has been created using a 2-step Self Organizing Maps (SOM) and Feed Forward Network (FFN) method and uses ~ 18 million direct observations from the latest release of the Surface Ocean CO2 database (SOCATv2022, Bakker et al., 2014, 2022). In a first step, the global coastal ocean is divided into 10 biogeochemical provinces using SOM, which group regions with similar environmental properties. Then, for each province, the FFN algorithm reconstructs nonlinear relationships between a set of environmental variables (e.g., sea surface temperature, salinity...) and the observed pCO2. These relationships are then used to perform the spatiotemporal pCO2 extrapolation in regions and time periods where data are lacking. The output consists of continuous monthly pCO2 maps for the coastal ocean, with a spatial resolution of 0.25°, covering the 1982-2020 period. Additionally, this new coastal pCO2 product is used to generate a new coastal air-sea CO2 exchange (FCO2) product for each grid cell at the monthly time scale from 1982 to 2020 using the following equation: FCO2=k∙K0∙∆pCO2∙(1-ice) where FCO2 represents the coastal air-sea CO2 exchange (in mol C m-2 yr-1). By convention a positive FCO2 value corresponds to a CO2 source for the atmosphere. ∆pCO2 represents the difference between the oceanic pCO2 and the atmospheric pCO2 (in atm). K0 (mol C m-3 atm-1) represents the CO2 solubility in sea water which is a function of SST and SSS following the equation of Weiss et al. (1974). k represents the gas exchange transfer velocity (m yr-1) which is a function of the second moment of the wind speed and is calculated using the equation of Ho et al. (2011) and the Schmidt number based on the equation of Wanninkhof et al. (2014). The sea-ice coverage is represented by the term ice and has no units.

ANN-NEPc is a gridded surface ocean pCO2 data product for the Northeast Pacific coastal ocean. It was created using non-linear functional relationships between pCO2 observations from the Surface Ocean CO2 Atlas v2021 as well as additional data from a Fisheries and Oceans Canada February 2019 Line P cruise, a West Coast Ocean Acidification cruise from July and August 2010, and La Perouse cruises from May 2007 and May 2010, and a variety of independent predictor variables (see supplemental information) using an artificial neural network self-organizing-map-feed-forward-network approach described and evaluated in Duke et al. (2024). This file contains monthly pCO2 and air-sea CO2 flux fields from January 1998 to December 2019 at 1/12 degree by 1/12 degree (approximately 9 km by 5km; latitude by longitude) spatial resolution within typically < 6 to 300 km of shore. The air-sea CO2 fluxes are computed from the air-sea CO2 partial pressure difference and a bulk gas transfer formulation following Duke et al. (2024).

The late Taro Takahashi (LDEO/Columbia University) provided the first near-global monthly air-sea CO2 flux climatology in Takahashi et al. (1997), based on available surface water partial pressure of CO2 measurements. This product has been a benchmark for uptake of CO2 in the ocean. Several versions have been provided since, with improvements in procedures and large increases in observations, culminating in the authoritative assessment in Takahashi et al. (2009). Here we provide and document the last iteration using a greatly increased dataset (SOCATv2022) and determining fluxes using air-sea partial pressure differences as a climatological reference for the period 1980-2021. The resulting net flux for the open ocean region is estimated as -1.79 PgC yr-1 which compares well with other global mean flux estimates. While global flux results are consistent, differences in regional means and seasonal amplitudes are discussed. Consistent with other studies, we find the largest differences in the data-sparse southeast Pacific and Southern Ocean.

This dataset consists of the Surface Ocean CO2 Atlas (SOCAT) data product files. SOCAT is a synthesis activity by the international marine carbon research community and has more than 100 contributors worldwide. SOCAT provides access to synthesis and gridded, quality controlled, observational products of surface ocean fCO2 (fugacity of carbon dioxide) for the global oceans and coastal seas. SOCAT version 2019 has 25.7 million quality-controlled surface ocean fCO2 (fugacity of CO2) observations with an estimated accuracy of better than 5 μatm and a WOCE flag of 2 (good) from 1957 to 2017 from 1957 to 2019 for the global oceans and coastal seas. In addition, 1.7 million values with an estimated accuracy of 5 to 10 μatm are available. During quality control, marine scientists assign a flag to each data set, as well as WOCE flags of 2 (good), 3 (questionable) or 4 (bad) to individual fCO2 values. Data sets are assigned flags of A and B for an accuracy of better than 2 μatm, flags of C and D for an accuracy of better than 5 μatm and a flag of E for an accuracy of better than 10 μatm. Bakker et al. (2016) describe the quality control criteria used in SOCAT versions 3, 4, 5, 6 and 2019. Quality control comments for individual data sets can be accessed via the SOCAT Data Set Viewer. All data sets, where data quality has been deemed acceptable, have been made public. The main SOCAT synthesis files and the gridded products contain all data sets with an estimated accuracy of better than 5 µatm (flags of A to D) and fCO2 values with a flag of 2. Access to data sets with an estimated accuracy of 5 to 10 (flag of E) and fCO2 values with flags of 3 and 4 is via additional data products and the Data Set Viewer (Table 8 in Bakker et al., 2016). SOCAT publishes a global gridded product with a 1° longitude by 1° latitude resolution. A second product with a higher resolution of 0.25° longitude by 0.25° latitude is available for the coastal seas. Gridded products are available monthly, per year and per decade. Two powerful, interactive, online viewers, the Data Set Viewer and the Gridded Data Viewer (www.socat.info), enable investigation of the SOCAT synthesis and gridded data products. SOCAT data products can be downloaded. Matlab code is available for reading these files. Ocean Data View also provides access to the SOCAT data products (www.socat.info). SOCAT data products are discoverable, accessible and citable. SOCAT versions 3 to 2019 should be cited as Bakker et al., 2016 (until a publication on versions 4 to 2019 is published). The SOCAT Fair Data Use Statement (www.socat.info) asks users to generously acknowledge the contribution of SOCAT scientists by invitation to co-authorship, especially for data providers in regional studies, and/or reference to relevant scientific articles. The SOCAT website (www.socat.info) provides a single access point for online viewers, downloadable data sets, the Fair Data Use Statement, a list of contributors and an overview of scientific publications on and using SOCAT. Automation of data upload and initial data checks allows annual releases of SOCAT from version 4 onwards. SOCAT enables quantification of the ocean carbon sink and ocean acidification, as well as evaluation of sensor data and ocean biogeochemical models. More than 260 peer-reviewed scientific publications and 80 high-impact reports cite SOCAT. SOCAT represents a milestone in biogeochemical and climate research. SOCAT informs policy and high-profile climate negotiations. Maintenance and annual updates of the SOCAT product require sustained funding and community involvement.

This dataset includes the Surface Ocean CO2 Atlas (SOCAT) version 3. These data include surface underway, chemical, meteorological, navigational and physical data collected from unknown platforms in the world-wide oceans from 1968-11-16 to 2013-12-31. These data include BAROMETRIC PRESSURE, LATITUDE, LONGITUDE, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The Surface Ocean CO2 Atlas (SOCAT) is an international effort, endorsed by the International Ocean Carbon Coordination Project (IOCCP), the Surface Ocean Lower Atmosphere Study (SOLAS) and the Integrated Marine Biogeochemistry and Ecosystem Research program (IMBER), to deliver a uniformly quality-controlled surface ocean CO2 database.

This dataset includes Surface underway, chemical, meteorological and physical data collected from JOHN P. TULLY, PARIZEAU, QUADRA and VANCOUVER in the Arctic Ocean, Beaufort Sea, Bering Sea, Coastal Waters of Southeast Alaska and British Columbia, Gulf of Alaska, Japan Sea, North Pacific Ocean, Olympic Coast National Marine Sanctuary and Sea of Okhotsk from 1973-08-12 to 2003-09-13. These data include ABSOLUTE HUMIDITY, AIR TEMPERATURE - DRY BULB, AIR TEMPERATURE - WET BULB, BAROMETRIC PRESSURE, Partial pressure (or fugacity) of carbon dioxide - atmosphere, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer. These data were collected by C. S. Wong and Sophia C. Johannessen of Fisheries and Oceans Canada; Institute of Ocean Sciences as part of the Station P, Line P dataset. CDIAC associated the following cruise ID(s) with this dataset: Line P and Station P

This dataset consists of the Surface Ocean CO2 Atlas Version 2022 (SOCATv2022) data product files. The ocean absorbs one quarter of the global CO2 emissions from human activity. The community-led Surface Ocean CO2 Atlas (www.socat.info) is key for the quantification of ocean CO2 uptake and its variation, now and in the future. SOCAT version 2022 has quality-controlled in situ surface ocean fCO2 (fugacity of CO2) measurements on ships, moorings, autonomous and drifting surface platforms for the global oceans and coastal seas from 1957 to 2021. The main synthesis and gridded products contain 33.7 million fCO2 values with an estimated accuracy of better than 5 μatm. A further 6.4 million fCO2 sensor data with an estimated accuracy of 5 to 10 μatm are separately available. During quality control, marine scientists assign a flag to each data set, as well as WOCE flags of 2 (good), 3 (questionable) or 4 (bad) to individual fCO2 values. Data sets are assigned flags of A and B for an estimated accuracy of better than 2 μatm, flags of C and D for an accuracy of better than 5 μatm and a flag of E for an accuracy of better than 10 μatm. Bakker et al. (2016) describe the quality control criteria used in SOCAT versions 3 to 2022. Quality control comments for individual data sets can be accessed via the SOCAT Data Set Viewer (www.socat.info). All data sets, where data quality has been deemed acceptable, have been made public. The main SOCAT synthesis files and the gridded products contain all data sets with an estimated accuracy of better than 5 µatm (data set flags of A to D) and fCO2 values with a WOCE flag of 2. Access to data sets with an estimated accuracy of 5 to 10 (flag of E) and fCO2 values with flags of 3 and 4 is via additional data products and the Data Set Viewer (Table 8 in Bakker et al., 2016). SOCAT publishes a global gridded product with a 1° longitude by 1° latitude resolution. A second product with a higher resolution of 0.25° longitude by 0.25° latitude is available for the coastal seas. The gridded products contain all data sets with an estimated accuracy of better than 5 µatm (data set flags of A to D) and fCO2 values with a WOCE flag of 2. Gridded products are available monthly, per year and per decade. Two powerful, interactive, online viewers, the Data Set Viewer and the Gridded Data Viewer (www.socat.info), enable investigation of the SOCAT synthesis and gridded data products. SOCAT data products can be downloaded. Matlab code is available for reading these files. Ocean Data View also provides access to the SOCAT data products (www.socat.info). SOCAT data products are discoverable, accessible and citable. The SOCAT Data Use Statement (www.socat.info) asks users to generously acknowledge the contribution of SOCAT scientists by invitation to co-authorship, especially for data providers in regional studies, and/or reference to relevant scientific articles. The SOCAT website (www.socat.info) provides a single access point for online viewers, downloadable data sets, the Data Use Statement, a list of contributors and an overview of scientific publications on and using SOCAT. Automation of data upload and initial data checks allows annual releases of SOCAT from version 4 onwards. SOCAT is used for quantification of ocean CO2 uptake and ocean acidification and for evaluation of climate models and sensor data. SOCAT products inform the annual Global Carbon Budget since 2013. The annual SOCAT releases by the SOCAT scientific community are a Voluntary Commitment for United Nations Sustainable Development Goal 14.3 (Reduce Ocean Acidification) (#OceanAction20464). More broadly the SOCAT releases contribute to UN SDG 13 (Climate Action) and SDG 14 (Life Below Water), and to the UN Decade of Ocean Science for Sustainable Development. Hundreds of peer-reviewed scientific publications and high-impact reports cite SOCAT. The SOCAT community-led synthesis product is a key step in the value chain based on in situ inorganic