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Ocean alkalinity enhancement (OAE) is a promising approach to marine carbon dioxide removal (mCDR) that leverages the large surface area and carbon storage capacity of the oceans to sequester atmospheric CO2 as dissolved bicarbonate (HCO3-). One OAE method involves the conversion of salt in seawater into aqueous alkalinity (NaOH), which is returned to the ocean. The resulting increase in seawater pH and alkalinity causes a shift in dissolved inorganic carbon (DIC) speciation toward carbonate and a decrease in the surface ocean p CO2. The shift in the p CO2 results in enhanced uptake of atmospheric CO2 by the seawater due to gas exchange. In this study, we systematically test the efficiency of CO2 uptake in seawater treated with NaOH at aquarium (15 L) and tank (6000 L) scales to establish operational boundaries for safety and efficiency in advance of scaling up to field experiments. CO2 equilibration occurred on the order of weeks to months, depending on circulation, air forcing, and air bubbling conditions within the test tanks. An increase of ∼0.7 –0.9 mol DIC per mol added alkalinity (in the form of NaOH) was observed through analysis of seawater bottle samples and pH sensor data, consistent with the value expected given the values of the carbonate system equilibrium calculations for the range of salinities and temperatures tested. Mineral precipitation occurred when the bulk seawater pH exceeded 10.0 and Ωaragonite exceeded 30.0. This precipitation was dominated by Mg(OH)2 over hours to 1 d before shifting to CaCO3,aragonite precipitation. These data, combined with models of the dilution and advection of alkaline plumes, will allow the estimation of the amount of carbon dioxide removal expected from OAE pilot studies. Future experiments should better approximate field conditions including sediment interactions, biological activity, ocean circulation, air–sea gas exchange rates, and mixing zone dynamics. [ABSTRACT FROM AUTHOR]

Climatologies, which depict mean fields of oceanographic variables on a regular geographic grid, and atlases, which provide graphical depictions of specific areas, play pivotal roles in comprehending the societal vulnerabilities linked to ocean acidification (OA). This significance is particularly pronounced in coastal regions where most economic activities, such as commercial and recreational fisheries and aquaculture industries, occur. In this paper, we unveil a comprehensive data product featuring coastal ocean acidification climatologies and atlases, encompassing the fugacity of carbon dioxide, pH on the total scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle factor, total dissolved inorganic carbon content, and total alkalinity content. These variables are provided on 1° × 1° spatial grids at 14 standardized depth levels, ranging from the surface to a depth of 500 m, along the North American ocean margins, defined as the region between the coastline and a distance of 200 nautical miles (∼370 km) offshore. The climatologies and atlases were developed using the World Ocean Atlas (WOA) gridding methods of the NOAA National Centers for Environmental Information (NCEI) based on the recently released Coastal Ocean Data Analysis Product in North America (CODAP-NA), along with the 2021 update to the Global Ocean Data Analysis Project version 2 (GLODAPv2.2021) data product. The relevant variables were adjusted to the index year of 2010. The data product is available in NetCDF (https://doi.org/10.25921/g8pb-zy76 , Jiang et al., 2022b) on the NOAA Ocean Carbon and Acidification Data System: https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0270962.html (last access: 15 July 2024). It is recommended to use the objectively analyzed mean fields (with "_an" suffix) for each variable. The atlases can be accessed at https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/synthesis/nacoastal.html (last access: 15 July 2024). [ABSTRACT FROM AUTHOR]

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, CCl 4 , and SF 6) 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. SF 6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO 2), 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 µ mol kg -1 in dissolved inorganic carbon, 4 µ mol 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 CO 2 fugacity (f CO 2), 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 National Centers for Environmental Information (NCEI), which also provides access to the merged data product. This 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/zyrq-ht66 (Lauvset et al., 2023). 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 GLODAPv2.2023 methods and provides a broad overview of the secondary quality control procedures and results. [ABSTRACT FROM AUTHOR]

Climatologies, which depict mean fields of oceanographic variables on a regular geographic grid, and atlases, which provide graphical depictions of specific areas, play pivotal roles in comprehending the societal vulnerabilities linked to ocean acidification (OA). This significance is particularly pronounced in coastal regions where most economic activities related to commercial and recreational fisheries as well as aquaculture industries occur. In this paper, we unveil a comprehensive data product featuring coastal climatologies and atlases for ten OA indicators, including fugacity of carbon dioxide, pH on the total scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle Factor, total dissolved inorganic carbon content, and total alkalinity content. These indicators are provided on 1°×1° degree spatial grids at 14 standardized depth levels, ranging from the surface to a depth of 500 meters, along the North American ocean margins – defined as the region between the coastline and a distance of 200 nautical miles (∼370 km) offshore. The climatologies and atlases were developed using the World Ocean Atlas (WOA) gridding methods of the NOAA National Centers for Environmental Information (NCEI), based on the recently released Coastal Ocean Data Analysis Product in North America (CODAP-NA), along with the 2021 update to the Global Ocean Data Analysis Project version 2 (GLODAPv2.2021) data product. The relevant variables were adjusted to the index year of 2010. The data product is available in NetCDF (DOI: 10.25921/g8pb-zy76) at the NOAA Ocean Carbon and Acidification Data System: https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0270962.html. It is recommended to use the objectively analyzed mean fields (with '_an' suffix) for each variable. The atlases can be accessed at: https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/synthesis/nacoastal.html. [ABSTRACT FROM AUTHOR]

Ocean alkalinity enhancement (OAE) is a promising approach to marine carbon dioxide removal (mCDR) that leverages the large surface area and carbon storage capacity of the oceans to sequester atmospheric CO2 as dissolved bicarbonate (HCO3-). The SEA MATE (S afe E levation of A lkalinity for the M itigation of A cidification T hrough E lectrochemistry) process uses electrochemistry to convert some of the salt (NaCl) in seawater or brine into aqueous acid (HCl), which is removed from the system, and base (NaOH), which is returned to the ocean with the remaining seawater. The resulting increase in seawater pH and alkalinity causes a shift in dissolved inorganic carbon (DIC) speciation toward carbonate and a decrease in the surface-ocean p CO2. The shift in the p CO-2 results in enhanced CO2 uptake or reduced CO2 loss by the seawater due to gas exchange. The net result of this process is the increase of surface-ocean DIC, where it is durably stored as mostly bicarbonate and some carbonate. In this study, we systematically test the efficiency of CO2 uptake in seawater treated with NaOH at beaker (1 L), aquaria (15 L), and tank (6000 L) scales to establish operational boundaries for safety and efficiency in scaling up to field experiments. Preliminary results show CO2 equilibration occurred on order of weeks to months, depending on circulation, air forcing, and air bubbling conditions within the test tanks. An increase of ~0.7–0.9 mol DIC/ mol added alkalinity (in the form of NaOH) was observed through analysis of seawater bottle samples and pH sensor data, consistent with the value expected given the values of the carbonate system equilibrium calculations for the range of salinities and temperatures tested. Mineral precipitation occurred when the bulk seawater pH exceeded 10.0 and Ωaragonite exceeded 30.0. This precipitation was dominated by Mg(OH)2 over hours to 1 day before shifting to CaCO3, aragonite precipitation. These data, combined with models of the dilution and advection of alkaline plumes, will allow for estimation of the amount of carbon dioxide removal expected from OAE pilot studies. Future experiments should better approximate field conditions including sediment interactions, biological activity, ocean circulation, air-sea gas exchange rates, and mixing-zone dynamics. [ABSTRACT FROM AUTHOR]

Ocean alkalinity enhancement (OAE) is a promising approach to marine carbon dioxide removal (mCDR) that leverages the large surface area and carbon storage capacity of the oceans to sequester atmospheric CO2 as dissolved bicarbonate (HCO3-). The SEA MATE (Safe Elevation of Alkalinity for the Mitigation of Acidification Through Electrochemistry) process uses electrochemistry to convert some of the salt (NaCl) in seawater or brine into aqueous acid (HCl), which is removed from the system, and base (NaOH), which is returned to the ocean with the remaining seawater. The resulting increase in seawater pH and alkalinity causes a shift in dissolved inorganic carbon (DIC) speciation toward carbonate and a decrease in the surface-ocean pCO2. The shift in the pCO2 results in enhanced CO2 uptake or reduced CO2 loss by the seawater due to gas exchange. The net result of this process is the increase of surface-ocean DIC, where it is durably stored as mostly bicarbonate and some carbonate. In this study, we systematically test the efficiency of CO2 uptake in seawater treated with NaOH at beaker (1L), aquaria (15L), and tank (6000L) scales to establish operational boundaries for safety and efficiency in scaling up to field experiments. Preliminary results show CO2 equilibration occurred on order of weeks to months, depending on circulation, air forcing, and air bubbling conditions within the test tanks. An increase of -0.7-0.9 mol DIC/ mol added alkalinity (in the form of NaOH) was observed through analysis of seawater bottle samples and pH sensor data, consistent with the value expected given the values of the carbonate system equilibrium calculations for the range of salinities and temperatures tested. Mineral precipitation occurred when the bulk seawater pH exceeded 10.0 and Ωaragonite exceeded 30.0. This precipitation was dominated by Mg(OH)2 over hours to 1 day before shifting to CaCO3, aragonite precipitation. These data, combined with models of the dilution and advection of alkaline plumes, will allow for estimation of the amount of carbon dioxide removal expected from OAE pilot studies. Future experiments should better approximate field conditions including sediment interactions, biological activity, ocean circulation, air-sea gas exchange rates, and mixing-zone dynamics. [ABSTRACT FROM AUTHOR]

For about 2 decades, oceanographers have been installing oxygen sensors on Argo profiling floats to be deployed throughout the world ocean, with the stated objective of better constraining trends and variability in the ocean's inventory of oxygen. Until now, measurements from these Argo-float-mounted oxygen sensors have been mainly used for localized process studies on air–sea oxygen exchange, upper-ocean primary production, biological pump efficiency, and oxygen minimum zone dynamics. Here, we present a new four-dimensional gridded product of ocean interior oxygen, derived via machine learning algorithms trained on dissolved oxygen observations from Argo-float-mounted sensors and discrete measurements from ship-based surveys and applied to temperature and salinity fields constructed from the global Argo array. The data product is called GOBAI- O2 , which stands for Gridded Ocean Biogeochemistry from Artificial Intelligence – Oxygen (Sharp et al., 2022; 10.25921/z72m-yz67); it covers 86 % of the global ocean area on a 1 ∘ × 1 ∘ (latitude × longitude) grid, spans the years 2004–2022 with a monthly resolution, and extends from the ocean surface to a depth of 2 km on 58 levels. Two types of machine learning algorithms – random forest regressions and feed-forward neural networks – are used in the development of GOBAI- O2 , and the performance of those algorithms is assessed using real observations and simulated observations from Earth system model output. Machine learning represents a relatively new method for gap filling ocean interior biogeochemical observations and should be explored along with statistical and interpolation-based techniques. GOBAI- O2 is evaluated through comparisons to the oxygen climatology from the World Ocean Atlas, the mapped oxygen product from the Global Ocean Data Analysis Project and to direct observations from large-scale hydrographic research cruises. Finally, potential uses for GOBAI- O2 are demonstrated by presenting average oxygen fields on isobaric and isopycnal surfaces, average oxygen fields across vertical–meridional sections, climatological seasonal cycles of oxygen averaged over different pressure layers, and globally integrated time series of oxygen. GOBAI- O2 indicates a declining trend in the oxygen inventory in the upper 2 km of the global ocean of 0.79 ± 0.04 % per decade between 2004 and 2022. [ABSTRACT FROM AUTHOR]

The deliberate increase in ocean alkalinity (referred to as ocean alkalinity enhancement, or OAE) has been proposed as a method for removing CO 2 from the atmosphere. Before OAE can be implemented safely, efficiently, and at scale several research questions have to be addressed, including (1) which alkaline feedstocks are best suited and the doses in which they can be added safely, (2) how net carbon uptake can be measured and verified, and (3) what the potential ecosystem impacts are. These research questions cannot be addressed by direct observation alone but will require skilful and fit-for-purpose models. This article provides an overview of the most relevant modelling tools, including turbulence-, regional-, and global-scale biogeochemical models and techniques including approaches for model validation, data assimilation, and uncertainty estimation. Typical biogeochemical model assumptions and their limitations are discussed in the context of OAE research, which leads to an identification of further development needs to make models more applicable to OAE research questions. A description of typical steps in model validation is followed by proposed minimum criteria for what constitutes a model that is fit for its intended purpose. After providing an overview of approaches for sound integration of models and observations via data assimilation, the application of observing system simulation experiments (OSSEs) for observing system design is described within the context of OAE research. Criteria for model validation and intercomparison studies are presented. The article concludes with a summary of recommendations and potential pitfalls to be avoided. [ABSTRACT FROM AUTHOR]

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 (SF 6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF 6 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, CCl 4 , and SF 6) 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. SF 6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO 2) 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 CO 2 fugacity (f CO 2), 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%5f2022/ , 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. [ABSTRACT FROM AUTHOR]

Over a decade ago, oceanographers began installing oxygen sensors on Argo floats to be deployed throughout the world ocean with the express objective of better constraining trends and variability in the ocean's inventory of oxygen. Until now, measurements from these Argo-mounted oxygen sensors have been mainly used for localized process studies on air-sea oxygen exchange, biological pump efficiency, upper ocean primary production, and oxygen minimum zone dynamics. Here we present a four-dimensional gridded product of ocean interior oxygen, derived via machine learning algorithms trained on dissolved oxygen observations from Argo-mounted sensors and discrete measurements from ship-based surveys, and applied to temperature and salinity fields constructed from the global Argo array. The data product is called GOBAI-O2 for Gridded Ocean Biogeochemistry from Artificial Intelligence - Oxygen (Sharp et al., 2022; https://doi.org/10.25921/z72m-yz67; last access: 30 Aug. 2022); it covers 86% of the global ocean area on a 1° latitude by 1° longitude grid, spans the years 2004-2021 with monthly resolution, and extends from the ocean surface to two kilometers in depth on 58 levels. Two machine learning algorithms -- random forest regressions and feed-forward neural networks -- are used in the development of GOBAI-O2, and the performance of those algorithms is assessed using real observations and Earth system model output. GOBAI-O2 is evaluated through comparisons to the World Ocean Atlas and to direct observations from large-scale hydrographic research cruises. Finally, potential uses for GOBAI-O2 are demonstrated by presenting average oxygen fields on isobaric and isopycnal surfaces, average oxygen fields across vertical-meridional sections, climatological cycles of oxygen averaged over different pressure intervals, and a globally integrated oxygen inventory time series. [ABSTRACT FROM AUTHOR]

A common strategy for calculating the direction and rate of carbon dioxide gas (CO 2) exchange between the ocean and atmosphere relies on knowledge of the partial pressure of CO 2 in surface seawater (p CO 2(sw)), a quantity that is frequently observed by autonomous sensors on ships and moored buoys, albeit with significant spatial and temporal gaps. Here we present a monthly gridded data product of p CO 2(sw) at 0.25 ∘ latitude by 0.25 ∘ longitude resolution in the northeastern Pacific Ocean, centered on the California Current System (CCS) and spanning all months from January 1998 to December 2020. The data product (RFR-CCS; Sharp et al., 2022; 10.5281/zenodo.5523389) was created using observations from the most recent (2021) version of the Surface Ocean CO 2 Atlas (Bakker et al., 2016). These observations were fit against a variety of collocated and contemporaneous satellite- and model-derived surface variables using a random forest regression (RFR) model. We validate RFR-CCS in multiple ways, including direct comparisons with observations from sensors on moored buoys, and find that the data product effectively captures seasonal p CO 2(sw) cycles at nearshore sites. This result is notable because global gridded p CO 2(sw) products do not capture local variability effectively in this region, suggesting that RFR-CCS is a better option than regional extractions from global products to represent p CO 2(sw) in the CCS over the last 2 decades. Lessons learned from the construction of RFR-CCS provide insight into how global p CO 2(sw) products could effectively characterize seasonal variability in nearshore coastal environments. We briefly review the physical and biological processes – acting across a variety of spatial and temporal scales – that are responsible for the latitudinal and nearshore-to-offshore p CO 2(sw) gradients seen in the RFR-CCS reconstruction of p CO 2(sw). RFR-CCS will be valuable for the validation of high-resolution models, the attribution of spatiotemporal carbonate system variability to physical and biological drivers, and the quantification of multiyear trends and interannual variability of ocean acidification. [ABSTRACT FROM AUTHOR]

In the deep trenches, i.e., areas deeper than HT ht 6000 HT ht , both number and density of observations are low. Finally, while questionable (WOCE flag HT ht 3) and bad (WOCE flag HT ht 4) data have been excluded from the product files, some may have gone unnoticed through our analyses. When bottom depths were not given, they were approximated as the deepest sample pressure HT ht 10 HT ht or extracted from ETOPO1 (Amante and Eakins, 2009), whichever was greater. The oceans mitigate climate change by absorbing both atmospheric HT ht corresponding to a significant fraction of anthropogenic HT ht emissions (Friedlingstein et al., 2019; Gruber et al., 2019) and most of the excess heat in the Earth system caused by the enhanced greenhouse effect (Cheng et al., 2020, 2017). [Extracted from the article]

To calculate the direction and rate of carbon dioxide gas (CO2) exchange between the ocean and atmosphere, it is critical to know the partial pressure of CO2 in surface seawater (pCO2(sw)). Over the last decade, a variety of data products of global monthly pCO2(sw) have been produced, primarily for the open ocean on 1° latitude by 1° longitude grids. More recently, monthly products of pCO2(sw) that are more finely spatially resolved in the coastal ocean have been made available. A remaining challenge in the development of pCO2(sw) products is the robust characterization of seasonal variability, especially in nearshore coastal environments. Here we present a monthly data product of pCO2(sw) at 0.25° latitude by 0.25° longitude resolution in the Northeast Pacific Ocean, centered around the California Current System (CCS). The data product (RFR-CCS; Sharp et al., 2021; https://doi.org/10.5281/zenodo.5523389) was created using the most recent (2021) version of the Surface Ocean CO2 Atlas (Bakker et al., 2016) from which pCO2(sw) observations were extracted and fit against a variety of satellite- and model-derived surface variables using a random forest regression (RFR) model. We validate RFR-CCS in multiple ways, including direct comparisons with observations from moored autonomous surface platforms, and find that the data product effectively captures seasonal pCO2(sw) cycles at nearshore mooring sites. This result is notable because alternative global products for the coastal ocean do not capture local variability effectively in this region. We briefly review the physical and biological processes — acting across a variety of spatial and temporal scales — that are responsible for the latitudinal and nearshore-to-offshore pCO2(sw) gradients seen in RFR-CCS reconstructions of pCO2(sw). [ABSTRACT FROM AUTHOR]

Internally consistent, quality-controlled (QC) data products play an important role in promoting regional-to-global research efforts to understand societal vulnerabilities to ocean acidification (OA). However, there are currently no such data products for the coastal ocean, where most of the OA-susceptible commercial and recreational fisheries and aquaculture industries are located. In this collaborative effort, we compiled, quality-controlled, and synthesized 2 decades of discrete measurements of inorganic carbon system parameters, oxygen, and nutrient chemistry data from the North American continental shelves to generate a data product called the Coastal Ocean Data Analysis Product in North America (CODAP-NA). There are few deep-water (> 1500 m) sampling locations in the current data product. As a result, crossover analyses, which rely on comparisons between measurements on different cruises in the stable deep ocean, could not form the basis for cruise-to-cruise adjustments. For this reason, care was taken in the selection of data sets to include in this initial release of CODAP-NA, and only data sets from laboratories with known quality assurance practices were included. New consistency checks and outlier detections were used to QC the data. Future releases of this CODAP-NA product will use this core data product as the basis for cruise-to-cruise comparisons. We worked closely with the investigators who collected and measured these data during the QC process. This version (v2021) of the CODAP-NA is comprised of 3391 oceanographic profiles from 61 research cruises covering all continental shelves of North America, from Alaska to Mexico in the west and from Canada to the Caribbean in the east. Data for 14 variables (temperature; salinity; dissolved oxygen content; dissolved inorganic carbon content; total alkalinity; pH on total scale; carbonate ion content; fugacity of carbon dioxide; and substance contents of silicate, phosphate, nitrate, nitrite, nitrate plus nitrite, and ammonium) have been subjected to extensive QC. CODAP-NA is available as a merged data product (Excel, CSV, MATLAB, and NetCDF; 10.25921/531n-c230, https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0219960.html , last access: 15 May 2021) (Jiang et al., 2021a). The original cruise data have also been updated with data providers' consent and summarized in a table with links to NOAA's National Centers for Environmental Information (NCEI) archives (https://www.ncei.noaa.gov/access/ocean-acidification-data-stewardship-oads/synthesis/NAcruises.html). [ABSTRACT FROM AUTHOR]

Internally-consistent, quality-controlled data products play a very important role in promoting regional to global research efforts to understand societal vulnerabilities to ocean acidification (OA). However, there are currently no such data products for the coastal ocean where most of the OA-susceptible commercial and recreational fisheries and aquaculture industries are located. In this collaborative effort, we compiled, quality controlled (QC), and synthesized two decades of discrete measurements of inorganic carbon system parameters, oxygen, and nutrient chemistry data from the U.S. North American continental shelves, to generate a data product called the Coastal Ocean Data Analysis Product for North America (CODAP-NA). There are few deep-water (> 1500 m) sampling locations in the current data product. As a result, cross-over analyses, which rely on comparisons between measurements on different cruises in the stable deep ocean, could not form the basis for cruise-to-cruise adjustments. For this reason, care was taken in the selection of data sets to include in this initial release of CODAP-NA, and only data sets from laboratories with known quality assurance practices were included. New consistency checks and outlier detections were used to QC the data. Future releases of this CODAP-NA product will use this core data product as the basis for secondary QC. We worked closely with the investigators who collected and measured these data during the QC process. This version of the CODAP-NA is comprised of 3,292 oceanographic profiles from 61 research cruises covering all continental shelves of North America, from Alaska to Mexico in the west and from Canada to the Caribbean in the east. Data for 14 variables (temperature; salinity; dissolved oxygen concentration; dissolved inorganic carbon concentration; total alkalinity; pH on the Total Scale; carbonate ion concentration; fugacity of carbon dioxide; and concentrations of silicate, phosphate, nitrate, nitrite, nitrate plus nitrite, and ammonium) have been subjected to extensive QC. CODAP-NA is available as a merged data product (Excel, CSV, MATLAB, and NetCDF, https://doi.org/10.25921/531n-c230, https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0219960.html) (Jiang et al., 2020). The original cruise data have also been updated with data providers' consent and summarized in a table with links to NOAA's National Centers for Environmental Information (NCEI) archives (https://www.ncei.noaa.gov/access/ocean-acidification-data-stewardship-oads/synthesis/NAcruises.html). [ABSTRACT FROM AUTHOR]

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%5f2020/ , 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 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. [ABSTRACT FROM AUTHOR]

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 water samples. GLODAPv2.2020 is an update of the previous version, GLODAPv2.2019. The major changes are: data from 106 more cruises added, extension of time coverage until 2019, and the inclusion of available discrete fugacity of CO2 (fCO2) values in the merged product files. GLODAPv2.2020 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, especially 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. They correct for errors related to measurement, calibration, and data handling practices, while taking into account any 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, depending on region, in pH, 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, their documentation and doi codes are available at the Ocean Carbon Data System of NOAA NCEI (https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2%5F2020/, last access: 22 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). The bias corrected 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. [ABSTRACT FROM AUTHOR]