Description: A well documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly defined criteria. Regional specialists performed the quality control, using state-of-the-art web-based tools, specially developed for accomplishing this global team effort. SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data points from the global oceans and coastal seas, spanning four decades (1968–2007). Three types of data products are available: individual cruise files, a merged complete data set and gridded products. With the rapid expansion of marine CO2 data collection and the importance of quantifying net global oceanic CO2 uptake and its changes, sustained data synthesis and data access are priorities

Description: As a response to public demand for a well-documented, quality controlled, publically available, global surface ocean carbon dioxide (CO2) data set, the international marine carbon science community developed the Surface Ocean CO2 Atlas (SOCAT). The first SOCAT product is a collection of 6.3 million quality controlled surface CO2 data from the global oceans and coastal seas, spanning four decades (1968–2007). The SOCAT gridded data presented here is the second data product to come from the SOCAT project. Recognizing that some groups may have trouble working with millions of measurements, the SOCAT gridded product was generated to provide a robust, regularly spaced CO2 fugacity (fCO2) product with minimal spatial and temporal interpolation, which should be easier to work with for many applications. Gridded SOCAT is rich with information that has not been fully explored yet (e.g., regional differences in the seasonal cycles), but also contains biases and limitations that the user needs to recognize and address (e.g., local influences on values in some coastal regions).

Description: The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO2 (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO2 values) and extended data coverage (from 1968–2007 to 1968–2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore the richness of the data. Applications of SOCAT include process studies, quantification of the ocean carbon sink and its spatial, seasonal, year-to-year and longerterm variation, as well as initialisation or validation of ocean carbon models and coupled climate-carbon models.

Description: Particles sinking out of the euphotic zone are important vehicles of carbon export from the surface ocean. Most of the particles produce heavier aggregates by coagulating with each other before they sink. We implemented an aggregation model into the biogeochemical model of Regional Oceanic Modelling System (ROMS) to simulate the distribution of particles in the water column and their downward transport in the Northwest African upwelling region. Accompanying settling chamber, sediment trap and particle camera measurements provide data for model validation. In situ aggregate settling velocities measured by the settling chamber were around 55 m d(-1). Aggregate sizes recorded by the particle camera hardly exceeded I mm. The model is based on a continuous size spectrum of aggregates, characterised by the prognostic aggregate mass and aggregate number concentration. Phytoplankton and detritus make up the aggregation pool, which has an averaged, prognostic and size dependent sinking. Model experiments were performed with dense and porous approximations of aggregates with varying maximum aggregate size and stickiness as well as with the inclusion of a disaggregation term. Similar surface productivity in all experiments has been generated in order to find the best combination of parameters that produce measured deep water fluxes. Although the experiments failed to represent surface particle number spectra, in the deep water some of them gave very similar slope and spectrum range as the particle camera observations. Particle fluxes at the mesotrophic sediment trap site off Cape Blanc (CB) have been successfully reproduced by the porous experiment with disaggregation term when particle remineralisation rate was 0.2 d(-1). The aggregation-disaggregation model improves the prediction capability of the original biogeochemical model significantly by giving much better estimates of fluxes for both upper and lower trap. The results also point to the need for more studies to enhance our knowledge on particle decay and its variation and to the role that stickiness play in the distribution of vertical fluxes

Description: According to a recent study, C:N ratios of sinking particulate organic matter (POM) in the ocean appear to be higher than Redfield (7.1 instead of 6.6) and depth dependent (increase +0.2/km). Here we investigate the effects of vertically variable C:N element ratios on marine carbon fluxes and the air-sea exchange of CO2 using a global ocean carbon cycle model (AAMOCC). For a steady-state ocean, the results show that models using the constant classical Redfield ratio underestimate both, total inventory and vertical gradients of dissolved inorganic carbon (DIC). While the amount of additional DIC (+150 Gt C) is negligible compared to the high marine carbon inventory, the C:N depth dependence can reduce the ambient atmospheric pCO2 by 20 ppm, permanently. Moreover, the simulation of a future scenario, estimating a possible effect of CO2-dependent C:N ratios of POM on the marine carbon cycle, has shown that even a moderate rise in the C:N element ratio of sinking POM, which is on the order of magnitude of natural variability, yields a considerably higher oceanic uptake of anthropogenic CO2 on timescales of decades to centuries. The assumption is based on a predicted increase in the production of highly carbon enriched transparent exopolymer particles (TEP) caused by rising atmospheric CO2 concentrations and enhanced nutrient limitation. However, counteracting a predicted decrease of the physical (solubility) CO2 pump as a consequence of global change, the effect in our scenario will alleviate further rising atmospheric CO2 concentrations rather than compensate a reduced physical uptake.

Description: Four indirect methods to determine carbon and nutrient regeneration ratios in the ocean are applied to results from a physical-biogeochemical model with prescribed element ratios for organic matter (de-)composition. The aim is to test whether these methods are suitable to reproduce C org :N:P element ratios of organic matter remineralization, which in contrast to the real ocean are exactly known in the model framework. The model experiment is carried out using the classical C:N:P Redfield ratio of 106:16:1 for production and decomposition of organic material under preindustrial atmospheric pCO2. Two methods rely on predefined end member values, while the others do not. The first method is a simple linear regression of two parameters, neglecting mixing effects, and yields remineralization signals biased by isopycnal tracer gradients induced by contributions of different water masses. The second method is based on multiple linear regression of three parameters, includes mixing of three, but not-prescribed end members. It can, in part, reproduce the prescribed remineralization ratios. However, considerable bias appears as a result of water mass mixing. The third method considers isopycnal mixing of three prescribed end member water masses by using temperature/salinity as conservative tracers on the two density surfaces σΘ = 26.8 and σΘ = 27.2. On the basis of a mixing triangle approach, the method is able to reproduce the regeneration rates best in the low latitudes, where the integrated signal of remineralization is high. The fourth method uses the full set of available parameters to derive mixing fractions and remineralization and is applied to the density range from σΘ = 26.8 to σΘ = 27.2, yielding the best reproduction of prescribed remineralization ratios. As expected, results from the last two methods are sensitive to the choice of end member concentrations. In general, best agreement between modeled and reconstructed ratios is found between 20°N and 20°S and deviations occur toward the outcrop regions, which we account to the low amount of remineralized material together with uncertainties in prescribed end member values. Our investigation shows how apparent variability of remineralization ratios can be generated through methodological shortcomings only.