The Observed Seasonal Cycle of Macronutrients in Drake Passage: Relationship to Fronts and Utility as a Model Metric
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The Observed Seasonal Cycle of Macronutrients in Drake Passage: Relationship to Fronts and Utility as a Model Metric
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    Journal of Geophysical Research: Oceans, 124, 4763– 4783
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    The Drake Passage Time-series (DPT) is used to quantify the spatial and seasonal variability of historically undersampled, biogeochemically relevant properties across the Drake Passage. From 2004?2017, discrete ship-based observations of surface macronutrients (silicate, nitrate, and phosphate), temperature, and salinity have been collected 5?8 times per year as part of the DPT program. Using the DPT and Antarctic Circumpolar Current (ACC) front locations derived from concurrent expendable bathythermograph data, the distinct physical and biogeochemical characteristics of ACC frontal zones are characterized. Biogeochemical-Argo floats in the region confirm that the near-surface sampling scheme of the DPT robustly captures mixed-layer biogeochemistry. While macronutrient concentrations consistently increase toward the Antarctic continent, their meridional distribution, variability, and biogeochemical gradients are unique across physical ACC fronts, suggesting a combination of physical and biological processes controlling nutrient availability and nutrient front location. The Polar Front is associated with the northern expression of the Silicate Front, marking the biogeographically relevant location between silicate-poor and silicate-rich waters. South of the northern Silicate Front, the silicate-to-nitrate ratio increases, with the sharpest gradient in silicate associated with the Southern ACC Front (i.e., the southern expression of the Silicate Front). Nutrient cycling is an important control on variability in the surface ocean partial pressure of carbon dioxide (pCO2). The robust characterization of the spatiotemporal variability of nutrients presented here highlights the utility of biogeochemical time series for diagnosing and potentially reducing biases in modeling Southern Ocean pCO2 variability, and by inference, air-sea CO2 flux.
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