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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.

Marine dissolved organic matter (DOM) presents key thermodynamic properties that are not yet fully constrained. Here, we report the distribution of binding sites occupied by protons (i.e., proton affinity spectra) and parametrize the median intrinsic proton binding affinities (log K̅H) and heterogeneities (m), for DOM samples extracted from the North Atlantic. We estimate that 11.4 ± 0.6% of C atoms in the extracted marine DOM have a functional group with a binding site for ionic species. The log K̅H of the most acidic groups was larger (4.01–4.02 ± 0.02) than that observed in DOM from coastal waters (3.82 ± 0.02), while the chemical binding heterogeneity parameter increased with depth to values (m1= 0.666 ± 0.009) ca. 10% higher than those observed in surface open ocean or coastal samples. On the contrary, the log K̅H for the less acidic groups shows a difference between the surface (10.01 ± 0.08) and deep (9.22 ± 0.35) samples. The latter chemical groups were more heterogeneous for marine than for terrestrial DOM, and m2 decreased with depth to values of 0.28 ± 0.03. Binding heterogeneity reflects aromatic carbon compounds’ persistence and accumulation in diverse, low-abundance chemical forms, while easily degradable low-affinity groups accumulate more uniformly in the deep ocean.

This dataset consists of the GLODAPv2.2023 data product composed of data from 1108 scientific cruises covering the global ocean between 1972 and 2021. It includes full depth discrete bottle measurements of salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon (TCO2), total alkalinity (TAlk), CO2 fugacity (fCO2), pH, chlorofluorocarbons (CFC-11, CFC-12, CFC-113, and CCl4), SF6, and various isotopes and organic compounds. It was created by appending data from 23 cruises to GLODAPv2.2022 (Lauvset et al., 2022, NCEI Accession 0257247). The data for salinity, oxygen, nitrate, silicate, phosphate, TCO2, TAlk, pH, CFC-11, CFC-12, CFC-113, CCl4, and SF6 were subjected to primary and secondary quality control. Severe biases in these data have been corrected for, and outliers removed. However, differences in data related to any known or likely time trends or variations have not been corrected for. These data are believed to be accurate to 0.005 in salinity, 1% in oxygen, 2% in nitrate, 2% in silicate, 2% in phosphate, 4 µmol kg-1 in TCO2, 4 µmol kg-1 in TAlk, and for the halogenated transient tracers and SF6: 5%

Oceanic dissolved inorganic carbon (T-C) is the largest pool of carbon that substantially interacts with the atmosphere on human timescales. Oceanic T-C is increasing through uptake of anthropogenic carbon dioxide (CO2), and seawater pH is decreasing as a consequence. Both the exchange of CO2 between the ocean and atmosphere and the pH response are governed by a set of parameters that interact through chemical equilibria, collectively known as the marine carbonate system. To investigate these processes, at least two of the marine carbonate system's parameters are typically measured - most commonly, two from T-C, total alkalinity (A(T)), pH, and seawater CO2 fugacity (f(CO2); or its partial pressure, p(CO2), or its dry-air mole fraction, x(CO2)) - from which the remaining parameters can be calculated and the equilibrium state of seawater solved. Several software tools exist to carry out these calculations, but no fully functional and rigorously validated tool written in Python, a popular scientific programming language, was previously available. Here, we present PyCO2SYS, a Python package intended to fill this capability gap. We describe the elements of PyCO2SYS that have been inherited from the existing CO2SYS family of software and explain subsequent adjustments and improvements. For example, PyCO2SYS uses automatic differentiation to solve the marine carbonate system and calculate chemical buffer factors, ensuring that the effect of every modelled solute and reaction is accurately included in all its results. We validate PyCO2SYS with internal consistency tests and comparisons against other software, showing that PyCO2SYS produces results that are either virtually identical or different for known reasons, with the differences negligible for all practical purposes. We discuss insights that guided the development of PyCO2SYS: for example, the fact that the marine carbonate system cannot be unambiguously solved from certain pairs of parameters. Finally, we consider p

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 sulphur 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 onboard the RV Knorr in the Indian Ocean in 1994–1995 which are now adjusted using 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, 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 contex

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 b

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 b

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.

Anthropogenic carbon dioxide (CO2) emissions drive climate change and pose one of the major challenges of our century. The effects of increased CO2 in the form of ocean acidification (OA) on the communities of marine planktonic eukaryotes in tropical regions such as the Timor Sea are barely understood. Here, we show the effects of high CO2 (mean ± SD pCO2 = 1823 ± 161 μatm and pHT = 7.46 ± 0.05) versus in situ CO2 (504 ± 42 µatm, 7.95 ± 0.04) seawater on the community composition of marine planktonic eukaryotes after 3 and 48 h of treatment exposure in a shipboard microcosm experiment. Illumina sequencing of the V9 hypervariable region of 18S rRNA (gene) was used to study the eukaryotic community composition. Increased CO2 significantly suppressed the relative abundances of different eukaryotic operational taxonomic units (OTUs), including important primary producers, although the chlorophyll a concentration remained constant. OA effects on eukaryotes were consistent between total (DNA-based) and active (cDNA-based) taxa after 48 h, e.g. for the diatoms Trieres chinensis and Stephanopyxis turris. Effects of OA on the relative abundances of OTUs were often species- or even ecotype-specific, and the incubation selectively allowed for detection of the OA-sensitive OTUs that benefitted the most from incubation in a closed bottle, as containment effects on the community structure were evident after 48 h. Many OTUs were adversely affected by sudden decreases of seawater pH, suggesting high sensitivity to OA at the base of the tropical marine biodiversity and difficult-to-predict outcomes for food-web functioning in the future ocean.

We report on a pilot study using a CO2 optode deployed on a Seaglider in the Norwegian Sea from March to October 2014. The optode measurements required drift and lag correction and in situ calibration using discrete water samples collected in the vicinity. We found that the optode signal correlated better with the concentration of CO2, c(CO2), than with its partial pressure, p(CO2). Using the calibrated c(CO2) and a regional parameterisation of total alkalinity (AT) as a function of temperature and salinity, we calculated total dissolved inorganic carbon content, c(DIC), which had a standard deviation of 11 µmol kg−1 compared with in situ measurements. The glider was also equipped with an oxygen (O2) optode. The O2 optode was drift corrected and calibrated using a c(O2) climatology for deep samples. The calibrated data enabled the calculation of DIC- and O2-based net community production, N(DIC) and N(O2). To derive N, DIC and O2 inventory changes over time were combined with estimates of air– sea gas exchange, diapycnal mixing and entrainment of deeper waters. Glider-based observations captured two periods of increased Chl a inventory in late spring (May) and a second one in summer (June). For the May period, we found N(DIC) = (21±5) mmol m−2 d−1, N(O2) = (94± 16) mmol m−2 d−1 and an (uncalibrated) Chl a peak concentration of craw(Chl a) = 3 mg m−3. During the June period, craw(Chl a) increased to a summer maximum of 4 mg m−3, associated with N(DIC) = (85±5) mmol m−2 d−1 and N(O2) = (126±25) mmol m−2 d−1. The high-resolution dataset allowed for quantification of the changes in N before, during and after the periods of increased Chl a inventory. After the May period, the remineralisation of the material produced during the period of increased Chl a inventory decreased N(DIC) to (−3 ± 5) mmol m−2 d−1 and N(O2) to (0 ± 2) mmol m−2 d−1. The survey area was a source of O2 and a sink of CO2 for most of the summer. The deployment captured two different surface waters infl