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  1. Abstract

    Cadmium (Cd) is a trace metal whose distribution in the ocean bears a remarkable resemblance to the nutrient phosphate (PO43−). This resemblance has led to the use of Cd as a proxy for ocean nutrient cycling in paleoceanographic applications, but the processes governing the cycling of Cd in the modern ocean remain unclear. In this study, we use previously published Cd observations and an Artificial Neural Network to produce a dissolved Cd climatology that reproduces the observed subtle deviations between the Cd anddistributions. We use the Cd andclimatologies, along with an ocean circulation inverse model, to diagnose the biogeochemical sources and sinks of dissolved Cd and. Our calculations reveal that dissolved Cd, like, is removed in the surface ocean and has a source in the subsurface, consistent with the simultaneous incorporation of Cd andinto sinking organic particles. However, there are also contrasts between the cycling of dissolved Cd andIn particular, thesurface export ratio varies 8‐fold across latitudes, reaching highest values in the iron‐limited sub‐Antarctic Southern Ocean. This depletes Cd relative toin the low‐latitude thermocline while adding excess Cd to deep waters by the regeneration of Cd‐enriched particles. Also, Cd tends to regenerate slightly deeper thanin the subsurface ocean, and theregeneration ratio reaches a maximum at 700–1,500 m. These contrasts are responsible for a slight concavity in therelationship and should be considered when interpreting paleoceanographic Cd records.

     
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  2. Abstract

    Copper (Cu) is a biologically important trace metal for marine plankton, but it is also toxic at high concentrations. Understanding the global distribution of Cu and the processes controlling its cycling in the ocean is important for understanding how the distribution of this important element can respond to climate change. Here, we use available observations of dissolved copper, an artificial neural network, and an ocean circulation inverse model, to derive a global estimate of the three‐dimensional distribution and cycling of dissolved Cu in the ocean. We find that there is net removal by bio‐assimilation and/or scavenging of dissolved Cu in the surface ocean at a rate of ~1.7 Gmol yr−1and that both the concentration and export of dissolved Cu are highest in the Southern Ocean. In the subsurface above the near‐sediment layer, dissolved Cu is removed at a net rate of ~2.4 Gmol yr−1, consistent with scavenging onto sinking particles, contributing to an increase in the flux of particulate Cu with depth. This removal of Cu by scavenging in the interior ocean is balanced by a net near‐sediment source of dissolved Cu, which sustains a gradual increase in the concentration of dissolved Cu with depth. Globally, this net near‐sediment source is estimated at ~2.6 Gmol yr−1in the deep ocean and ~0.8 Gmol yr−1along continental shelves and slopes. Our results suggest an active oceanic dissolved Cu cycle with a mean internal ocean residence time of ~530 years, highlighting the potential for climate‐driven changes in the marine Cu cycle.

     
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  3. Abstract

    39Ar with its 269‐year half‐life has great potential for constraining ocean ventilation and transport. Here we estimate the distribution of39Ar using a steady ocean circulation inverse model. Our estimates match available39Ar measurements to within an absolute error of ∼9% modern argon without major biases. We find that39Ar traces out the world ocean's ventilation pathways and that the39Ar age ΓArand the ideal mean age have broadly similar large‐scale patterns. At the surface,39Ar is close to saturated except at high latitudes. Undersaturation imparts a finite39Ar age to surface waters relative to the atmosphere, with peak values exceeding 100 years in Antarctic waters. This reservoir age is propagated into the interior with Antarctic Bottom Water, elevating ΓArby ∼50 years in the deep Pacific and Indian oceans. Our estimates identify the large‐scale gradients and uncertainty patterns of39Ar, thus providing guidance for future measurements.

     
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  4. Abstract. Nitrate is a critical ingredient for life in the ocean because, as the mostabundant form of fixed nitrogen in the ocean, it is an essential nutrientfor primary production. The availability of marine nitrate is principallydetermined by biological processes, each having a distinct influence on theN isotopic composition of nitrate (nitrate δ15N) – a propertythat informs much of our understanding of the marine N cycle as well asmarine ecology, fisheries, and past ocean conditions. However, the sparsespatial distribution of nitrate δ15N observations makes itdifficult to apply this useful property in global studies or to facilitaterobust model–data comparisons. Here, we use a compilation of publishednitrate δ15N measurements (n=12 277) and climatological mapsof physical and biogeochemical tracers to create a surface-to-seafloor,1∘ resolution map of nitrate δ15N using an ensembleof artificial neural networks (EANN). The strong correlation (R2>0.87) and small mean difference (<0.05 ‰) between EANN-estimated and observed nitrateδ15N indicate that the EANN provides a good estimate ofclimatological nitrate δ15N without a significant bias. Themagnitude of observation-model residuals is consistent with the magnitude of seasonal to interannual changes in observed nitrate δ15N that are notcaptured by our climatological model. The EANN provides a globally resolved map of mean nitrate δ15Nfor observational and modeling studies of marine biogeochemistry,paleoceanography, and marine ecology. 
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