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Abstract. 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. 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. We introduce a time-dependent, one-dimensional model ofearly diagenesis that we term RADI, an acronym accounting for the mainprocesses included in the model: chemical reactions, advection, molecularand bio-diffusion, and bio-irrigation. RADI is targeted for study ofdeep-sea sediments, in particular those containing calcium carbonates(CaCO3). RADI combines CaCO3 dissolution driven by organic matterdegradation with a diffusive boundary layer and integrates state-of-the-artparameterizations of CaCO3 dissolution kinetics in seawater, thusserving as a link between mechanistic surface reaction modeling andglobal-scale biogeochemical models. RADI also includes CaCO3precipitation, providing a continuum between CaCO3 dissolution andprecipitation. RADI integrates components rather than individual chemicalspecies for accessibility and is straightforward to compare againstmeasurements. RADI is the first diagenetic model implemented in Julia, ahigh-performance programming language that is free and open source, and itis also available in MATLAB/GNU Octave. Here, we first describe thescientific background behind RADI and its implementations. Following this, we evaluateits performance in three selected locations and explore other potentialapplications, such as the influence of tides and seasonality on earlydiagenesis in the deep ocean. RADI is a powerful tool to study thetime-transient and steady-state response of the sedimentary system toenvironmental perturbation, such as deep-sea mining, deoxygenation, oracidification events. 

Abstract. The Global Ocean Data Analysis Project (GLODAP) is asynthesis effort providing regular compilations of surface-to-bottom oceanbiogeochemical bottle data, with an emphasis on seawater inorganic carbonchemistry and related variables determined through chemical analysis ofseawater samples. GLODAPv2.2022 is an update of the previous version,GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: datafrom 96 new cruises were added, data coverage was extended until 2021, andfor the first time we performed secondary quality control on all sulfurhexafluoride (SF6) data. In addition, a number of changes were made todata included in GLODAPv2.2021. These changes affect specifically theSF6 data, which are now subjected to secondary quality control, andcarbon data measured on board the RV Knorr in the Indian Ocean in 1994–1995 whichare now adjusted using certified reference material (CRM) measurements made at the time. GLODAPv2.2022includes measurements from almost 1.4 million water samples from the globaloceans collected on 1085 cruises. The data for the now 13 GLODAP corevariables (salinity, oxygen, nitrate, silicate, phosphate, dissolvedinorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4,and SF6) have undergone extensive quality control with a focus onsystematic evaluation of bias. The data are available in two formats: (i) assubmitted by the data originator but converted to World Ocean CirculationExperiment (WOCE) exchange format and (ii) as a merged data product withadjustments applied to minimize bias. For the present annual update,adjustments for the 96 new cruises were derived by comparing those data withthe data from the 989 quality-controlled cruises in the GLODAPv2.2021 dataproduct using crossover analysis. SF6 data from all cruises wereevaluated by comparison with CFC-12 data measured on the same cruises. Fornutrients and ocean carbon dioxide (CO2) chemistry comparisons toestimates based on empirical algorithms provided additional context foradjustment decisions. The adjustments that we applied are intended to removepotential biases from errors related to measurement, calibration, and datahandling practices without removing known or likely time trends orvariations in the variables evaluated. The compiled and adjusted dataproduct 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−1in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % inthe halogenated transient tracers. The other variables included in thecompilation, 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 theOcean 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 themerged data product, which is provided as a single global file and as fourregional ones – the Arctic, Atlantic, Indian, and Pacific oceans –under https://doi.org/10.25921/1f4w-0t92 (Lauvset et al.,2022). These bias-adjusted product files also include significant ancillaryand approximated data, which were obtained by interpolation of, orcalculation from, measured data. This living data update documents theGLODAPv2.2022 methods and provides a broad overview of the secondary qualitycontrol procedures and results. 

Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above. 

Abstract. The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID.