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Analysis of observations and sensitivity experiments with a new three-dimensional global model of stable carbon isotope cycling elucidate processes that control the distribution of δ13C of dissolved inorganic carbon (DIC) in the contemporary and preindustrial ocean. Biological fractionation and the sinking of isotopically light δ13C organic matter from the surface into the interior ocean leads to low δ13CDIC values at depths and in high latitude surface waters and high values in the upper ocean at low latitudes with maxima in the subtropics. Air–sea gas exchange has two effects. First, it acts to reduce the spatial gradients created by biology. Second, the associated temperature-dependent fractionation tends to increase (decrease) δ13CDIC values of colder (warmer) water, which generates gradients that oppose those arising from biology. Our model results suggest that both effects are similarly important in influencing surface and interior δ13CDIC distributions. However, since air–sea gas exchange is slow in the modern ocean, the biological effect dominates spatial δ13CDIC gradients both in the interior and at the surface, in contrast to conclusions from some previous studies. Calcium carbonate cycling, pH dependency of fractionation during air–sea gas exchange, and kinetic fractionation have minor effects on δ13CDIC. Accumulation of isotopically light carbon from anthropogenic fossil fuel burning has decreased the spatial variability of surface and deep δ13CDIC since the industrial revolution in our model simulations. Analysis of a new synthesis of δ13CDIC measurements from years 1990 to 2005 is used to quantify preformed and remineralized contributions as well as the effects of biology and air–sea gas exchange. The model reproduces major features of the observed large-scale distribution of δ13CDIC as well as the individual contributions and effects. Residual misfits are documented and analyzed. Simulated surface and subsurface δ13CDIC are influenced by details of the ecosystem model formulation. For example, inclusion of a simple parameterization of iron limitation of phytoplankton growth rates and temperature-dependent zooplankton grazing rates improves the agreement with δ13CDIC observations and satellite estimates of phytoplankton growth rates and biomass, suggesting that δ13C can also be a useful test of ecosystem models.

We introduce a composite tracer for the marine system, Alk*, that has a global distribution primarily determined by CaCO3 precipitation and dissolution. Alk* is also affected by riverine alkalinity from dissolved terrestrial carbonate minerals. We estimate that the Arctic receives approximately twice the riverine alkalinity per unit area as the Atlantic, and 8 times that of the other oceans. Riverine inputs broadly elevate Alk* in the Arctic surface and particularly near river mouths. Strong net carbonate precipitation results in low Alk* in subtropical gyres, especially in the Indian and Atlantic oceans. Upwelling of dissolved CaCO3-rich deep water elevates North Pacific and Southern Ocean Alk*. We use the Alk* distribution to estimate the variability of the calcite saturation state resulting from CaCO3 cycling and other processes. We show that regional differences in surface calcite saturation state are due primarily to the effect of temperature differences on CO2 solubility and, to a lesser extent, differences in freshwater content and air–sea disequilibria. The variations in net calcium carbonate cycling revealed by Alk* play a comparatively minor role in determining the calcium carbonate saturation state.

Quantifying oceanic anthropogenic carbon uptake by monitoring interior dissolved inorganic carbon (DIC) concentrations is complicated by the influence of natural variability. The \"eMLR method\" aims to address this issue by using empirical regression fits of the data instead of the data themselves, inferring the change in anthropogenic carbon in time by difference between predictions generated by the regressions at each time. The advantages of the method are that it provides in principle a means to filter out natural variability, which theoretically becomes the regression residuals, and a way to deal with sparsely and unevenly distributed data. The degree to which these advantages are realized in practice is unclear, however. The ability of the eMLR method to recover the anthropogenic carbon signal is tested here using a global circulation and biogeochemistry model in which the true signal is known. Results show that regression model selection is particularly important when the observational network changes in time. When the observational network is fixed, the likelihood that co-located systematic misfits between the empirical model and the underlying, yet unknown, true model cancel is greater, improving eMLR results. Changing the observational network modifies how the spatio-temporal variance pattern is captured by the respective datasets, resulting in empirical models that are dynamically or regionally inconsistent, leading to systematic errors. In consequence, the use of regression formulae that change in time to represent systematically best-fit models at all times does not guarantee the best estimates of anthropogenic carbon change if the spatial distributions of the stations emphasize hydrographic features differently in time. Other factors, such as a balanced and representative station coverage, vertical continuity of the regression formulae consistent with the hydrographic context and resiliency of the spatial distribution of the residual field can be used to help guide model selection. The characteristic spatial scales of the modes of inter-annual to decadal variability in relation to the size of the North Atlantic, in concert with the station coverage available, place practical limits on the ability of eMLR to fully account for natural variability. Due to its statistical nature, eMLR only efficiently removes the natural variability whose spatial scales are smaller than the system analyzed.

Here we report on data from an oceanographic cruise on the German research vessel Meteor covering large parts of the Mediterranean Sea during spring of 2011. The main objective of this cruise was to conduct measurements of physical, chemical and biological variables on a section across the Mediterranean Sea with the goal of producing a synoptic picture of the distribution of relevant physical and biogeochemical properties, in order to compare those to historic data sets. During the cruise, a comprehensive data set of relevant variables following the guide lines for repeat hydrography outlined by the GO-SHIP group (http://www.go-ship.org/) was collected. The measurements include salinity and temperature (CTD), an over-determined carbonate system, inorganic nutrients, oxygen, transient tracers (CFC-12, SF6), helium isotopes and tritium, and carbon isotopes. The cruise sampled all major basins of the Mediterranean Sea following roughly an east-to-west section from the coast of Lebanon through to the Strait of Gibraltar, and to the coast of Portugal. Also a south-to-north section from the Ionian Sea to the Adriatic Sea was carried out. Additionally, sampling in the Aegean, Adriatic and Tyrrhenian Seas were carried out. The sections roughly followed lines and positions that have been sampled previously during other programs, thus providing the opportunity for comparative investigations of the temporal development of various parameters.

The original goal of the CARINA (Carbon in Atlantic Ocean) data synthesis project was to create a merged calibrated data set from open ocean subsurface measurements by European scientists that would be generally useful for biogeochemical investigations in the North Atlantic and in particular, studies involving the carbon system. Over time the geographic extent expanded to include the entire Atlantic, the Arctic and the Southern Ocean and the international collaboration broadened significantly. In this paper we give a brief history of the project, a general overview of data included and an outline of the procedures used during the synthesis. The end result of this project was a set of 3 data products, one for each of the listed ocean regions. It is critical that anyone who uses any of the CARINA data products recognize that the data products are not simply concatenations of the originally measured values. Rather, the data have been through an extensive calibration procedure designed to remove measurement bias and bad data. Also a significant fraction of the individual values in the data products were derived either by direct calculation or some means of approximation. These data products were constructed for basin scale biogeochemical investigations and may be inappropriate for investigations involving small areal extent or similar detailed analyses. More information on specific parts of this project can be found in companion articles in this issue. In particular, Tanhua et al. (2010) and Tanhua (2009) describe the procedures and software used to remove measurement bias from the original data. The three data products and a significant volume of supporting information are available from the CARINA web site hosted by the Carbon Dioxide Information Analysis Center (CDIAC: http://cdiac.esd.ornl.gov/oceans/CARINA/Carina_inv.html). Anyone wanting to use the data is advised to get the highest version number of each data product. Incremental versions represent either corrections or additions. The web site documents specifics of the changes.

Data on the carbon and carbon relevant hydrographic and hydrochemical parameters from previously not publicly available cruises in the Arctic, Atlantic and Southern Ocean have been retrieved and merged to a new data base: CARINA (CARbon IN the Atlantic). These data have gone through rigorous quality control (QC) procedures to assure the highest possible quality and consistency. All CARINA data were subject to primary QC; a process in which data are studied in order to identify outliers and obvious errors. Additionally, secondary QC was performed for several of the measured parameters in the CARINA data base. Secondary QC is a process in which the data are objectively studied in order to quantify systematic differences in the reported values. This process involved crossover analysis, and as a second step the offsets derived from the crossover analysis were used to calculate corrections of the parameters measured on individual cruises using least square models. Significant biases found in the data have been corrected in the data products, i.e. three merged data files containing measured, calculated and interpolated data for each of the three regions (i.e. Arctic Mediterranean Seas, Atlantic, and Southern Ocean). Here we report on the technical details of the quality control and on tools that have been developed and used during the project, including procedures for crossover analysis and least square models. Furthermore, an interactive website for uploading of results, plots, comments etc. was developed and was of critical importance for the success of the project, this is also described here.

A three dimensional model of Arctic Ocean circulation and mixing, with a horizontal resolution of 18 km, is overlain by a biogeochemical model resolving the physical, chemical and biological transport and transformations of phosphorus, alkalinity, oxygen and carbon, including the air‐sea exchange of dissolved gases and the riverine delivery of dissolved organic carbon. The model qualitatively captures the observed regional and seasonal trends in surface ocean PO4, dissolved inorganic carbon, total alkalinity, and pCO2. Integrated annually, over the basin, the model suggests a net annual uptake of 59 Tg C a−1, within the range of published estimates based on the extrapolation of local observations (20–199 Tg C a−1). This flux is attributable to the cooling (increasing solubility) of waters moving into the basin, mainly from the subpolar North Atlantic. The air‐sea flux is regulated seasonally and regionally by sea‐ice cover, which modulates both air‐sea gas transfer and the photosynthetic production of organic matter, and by the delivery of riverine dissolved organic carbon (RDOC), which drive the regional contrasts in pCO2 between Eurasian and North American coastal waters. Integrated over the basin, the delivery and remineralization of RDOC reduces the net oceanic CO2 uptake by ∼10%. Key Points A new independent estimate of the CO2 uptake of the Arctic Ocean Sensitivity of CO2 uptake of the Arctic Ocean to RDOC Strong land‐ocean carbon cycle coupling in the Arctic

The paper describes the steps taken for quality controlling chosen parameters within the Arctic Ocean data included in the CARINA data set and checking for offsets between the individual cruises. The evaluated parameters are the inorganic carbon parameters (total dissolved inorganic carbon, total alkalinity and pH), oxygen and nutrients: nitrate, phosphate and silicate. More parameters can be found in the CARINA data product, but were not subject to a secondary quality control. The main method in determining offsets between cruises was regional multi-linear regression, after a first rough basin-wide deep-water estimate of each parameter. Lastly, the results of the secondary quality control are discussed as well as applied adjustments.

Water column data of carbon and carbon-relevant hydrographic and hydrochemical parameters from 188 previously non-publicly available cruise data sets in the Arctic Mediterranean Seas, Atlantic and Southern Ocean have been retrieved and merged into a new database: CARINA (CARbon dioxide IN the Atlantic Ocean). The data have gone through rigorous quality control procedures to assure the highest possible quality and consistency. The data for the pertinent parameters in the CARINA database were objectively examined in order to quantify systematic differences in the reported values, i.e. secondary quality control. Systematic biases found in the data have been corrected in the three data products: merged data files with measured, calculated and interpolated data for each of the three CARINA regions, i.e. the Arctic Mediterranean Seas, the Atlantic and the Southern Ocean. These products have been corrected to be internally consistent. Ninety-eight of the cruises in the CARINA database were conducted in the Atlantic Ocean, defined here as the region south of the Greenland-Iceland-Scotland Ridge and north of about 30° S. Here we present an overview of the Atlantic Ocean synthesis of the CARINA data and the adjustments that were applied to the data product. We also report the details of the secondary QC (Quality Control) for salinity for this data set. Procedures of quality control – including crossover analysis between stations and inversion analysis of all crossover data – are briefly described. Adjustments to salinity measurements were applied to the data from 10 cruises in the Atlantic Ocean region. Based on our analysis we estimate the internal consistency of the CARINA-ATL salinity data to be 4.1 ppm. With these adjustments the CARINA data products are consistent both internally as well as with GLODAP data, an oceanographic data set based on the World Hydrographic Program in the 1990s, and is now suitable for accurate assessments of, for example, oceanic carbon inventories and uptake rates and for model validation.

Water column data of carbon and carbon-relevant parameters have been collected and merged into a new database called CARINA (CARbon IN the Atlantic). In order to provide a consistent data set, all data have been examined for systematic biases and adjusted if necessary (secondary quality control (QC)). The CARINA data set is divided into three regions: the Arctic/Nordic Seas, the Atlantic region and the Southern Ocean. Here we present the CFC data for the Atlantic region, including the chlorofluorocarbons CFC-11, CFC-12 and CFC-113 as well as carbon tetrachloride (CCl4). The methods applied for the secondary quality control, a crossover analyses, the investigation of CFC ratios in the ocean and the CFC surface saturation are presented. Based on the results, the CFC data of some cruises are adjusted by a certain factor or given a \"poor'' quality flag.