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Abstract Marine net community production (NCP), a metric of ecosystem functionality, is often estimated as the residual term in a mass balance equation that aims to describe upper ocean variations in the time series of a chemical tracer. The advent of biogeochemical (BGC) Argo profiling floats equipped with nitrate, pH, and oxygen sensors has enabled such NCP estimation across vast ocean regions. Floats typically drift at 1,000 m depth between profiling from ∼2,000 m to the surface every 10 days, resulting in quasi‐Lagrangian time series that can reflect different upper ocean water masses over time. However, limited information about real‐time horizontal tracer gradients often leads to lateral processes being omitted during tracer budget closure, which can bias the residual‐term NCP estimates. To determine the potential magnitude of such biases, we developed a method to quantify and adjust for the impact of lateral float movement across horizontal tracer gradients using dissolved inorganic carbon (DIC) as our case study. We evaluated the method by extracting artificial float profiles from a depth‐resolved observation‐based DIC product to generate an artificial DIC time series. We then estimated NCP before and after accounting for horizontal gradient effects and compared the results to NCP estimates from an artificial DIC time series extracted at a fixed location along the float trajectory. Testing 10 biogeographical domains with moderate to substantial horizontal DIC gradients, our method significantly improved the precision (by ∼50 to ∼80%) and accuracy (by ∼10 to ∼100%) of regional NCP estimates. This method can be applied to other tracers with multi‐month‐long residence times. 

Abstract The strength and variability of the Southern Ocean carbon sink is a significant source of uncertainty in the global carbon budget. One barrier to reconciling observations and models is understanding how synoptic weather patterns modulate air-sea carbon exchange. Here, we identify and track storms using atmospheric sea level pressure fields from reanalysis data to assess the role that storms play in driving air-sea CO₂exchange. We examine the main drivers of CO₂fluxes under storm forcing and quantify their contribution to Southern Ocean annual air-sea CO₂fluxes. Our analysis relies on a forced ocean-ice simulation from the Community Earth System Model, as well as CO₂fluxes estimated from Biogeochemical Argo floats. We find that extratropical storms in the Southern Hemisphere induce CO₂outgassing, driven by CO₂disequilibrium. However, this effect is an order of magnitude larger in observations compared to the model and caused by different reasons. Despite large uncertainties in CO₂fluxes and storm statistics, observations suggest a pivotal role of storms in driving Southern Ocean air-sea CO₂outgassing that remains to be well represented in climate models, and needs to be further investigated in observations. 

Abstract Profiles of oxygen measurements from Argo profiling floats now vastly outnumber shipboard profiles. To correct for drift, float oxygen data are often initially adjusted to deployment casts, ship‐based climatologies, or, recently, measurements of atmospheric oxygen for in situ calibration. Air calibration enables accurate measurements in the upper ocean but may not provide similar accuracy at depth. Using a quality controlled shipboard data set, we find that the entire Argo oxygen data set is offset relative to shipboard measurements (float minus ship) at pressures of 1,450–2,000 db by a median of −1.9 μmol kg⁻¹(mean ± SD of −1.9 ± 3.9, 95% confidence interval around the mean of {−2.2, −1.6}) and air‐calibrated floats are offset by −2.7 μmol kg⁻¹(−3.0 ± 3.4 (CI_95%{−3.7, −2.4}). The difference between float and shipboard oxygen is likely due to offsets in the float oxygen data and not oxygen changes at depth or biases in the shipboard data set. In addition to complicating the calculation of long‐term ocean oxygen changes, these float oxygen offsets impact the adjustment of float nitrate and pH measurements, therefore biasing important derived quantities such as the partial pressure of CO₂(pCO₂) and dissolved inorganic carbon. Correcting floats with air‐calibrated oxygen sensors for the float‐ship oxygen offsets alters float pH by a median of 3.0 mpH (3.1 ± 3.7) and float‐derived surfacepCO₂by −3.2 μatm (−3.2 ± 3.9). This adjustment to floatpCO₂represents half, or more, of the bias in float‐derivedpCO₂reported in studies comparing floatpCO₂to shipboardpCO₂measurements. 

Abstract We use observations from the Southern Ocean (SO) biogeochemical profiling float array to quantify the meridional pattern of particle export efficiency (PE_eff) during the austral productive season. Float estimates reveal a pronounced latitudinal gradient of PE_eff, which is quantitatively supported by a compilation of existing ship‐based measurements. Relying on complementary float‐based estimates of distinct carbon pools produced through biological activity, we find that PE_effpeaks near the region of maximum particulate inorganic carbon sinking flux in the polar antarctic zone, where net primary production (NPP) is the lowest. Regions characterized by intermediate NPP and low PE_eff, primarily in the subtropical and seasonal ice zones, are generally associated with a higher fraction of dissolved organic carbon production. Our study reveals the critical role of distinct biogenic carbon pool production in driving the latitudinal pattern of PE_effin the SO. 

Abstract Seawater carbonate chemistry observations are increasingly necessary to study a broad array of oceanographic challenges such as ocean acidification, carbon inventory tracking, and assessment of marine carbon dioxide removal strategies. The uncertainty in a seawater carbonate chemistry observation comes from unknown random variations and systematic offsets. Here, we estimate the magnitudes of these random and systematic components of uncertainty for the discrete open‐ocean carbonate chemistry measurements in the Global Ocean Data Analysis Project 2022 update (GLODAPv2.2022). We use both an uncertainty propagation approach and a carbonate chemistry measurement “inter‐consistency” approach that quantifies the disagreement between measured carbonate chemistry variables and calculations of the same variables from other carbonate chemistry measurements. Our inter‐consistency analysis reveals that the seawater carbonate chemistry measurement community has collected and released data with a random uncertainty that averages about 1.7 times the uncertainty estimated by propagating the desired “climate‐quality” random uncertainties. However, we obtain differing random uncertainty estimates for subsets of the available data, with some subsets seemingly meeting the climate‐quality criteria. We find that seawater pH measurements on the total scale do not meet the climate‐quality criteria, though the inter‐consistency of these measurements improves (by 38%) when limited to the subset of measurements made using purified indicator dyes. We show that GLODAPv2 adjustments improve inter‐consistency for some subsets of the measurements while worsening it for others. Finally, we provide general guidance for quantifying the random uncertainty that applies for common combinations of measured and calculated values.