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High Salinity Shelf Water (HSSW) formed in the Ross Sea of Antarctica is a precursor to Antarctic Bottom Water (AABW), a water mass that constitutes the bottom limb of the global overturning circulation. HSSW production rates are poorly constrained, as in-situ observations are scarce. Here, we present high-vertical-and-temporal-resolution salinity time series collected in austral winter 2017 from a mooring in Terra Nova Bay (TNB), one of two major sites of HSSW production in the Ross Sea. We calculate an annual-average HSSW production rate of ~0.4 Sv (10 6 m 3 s −1 ), which we use to ground truth additional estimates across 2012–2021 made from parametrized net surface heat fluxes. We find sub-seasonal and interannual variability on the order of 0.1 S v , with a strong dependence on variability in open-water area that suggests a sensitivity of TNB HSSW production rates to changes in the local wind regime and offshore sea ice pack. Antarctic Bottom Water ventilates the deep ocean, but studies of its source regions are limited due to scarce observations. Miller et al. leverage mooring data to quantify the production rate of a key constituent water mass produced in the Ross Sea.

Increasing interest in the deployment of optical oxygen sensors, or optodes, on oceanographic moorings reflects the value of dissolved oxygen (DO) measurements in studies of physical and biogeochemical processes. Optodes are well-suited for moored applications but require careful, multi-step calibrations in the field to ensure data accuracy. Without a standardized set of protocols, this can be an obstacle for science teams lacking expertise in optode data processing and calibration. Here, we provide a set of recommendations for the deployment and in situ calibration of data from moored optodes, developed from our experience working with a set of 60 optodes deployed as part of the Gases in the Overturning and Horizontal circulation of the Subpolar North Atlantic Program (GOHSNAP). In particular, we detail the correction of drift in moored optodes, which occurs in two forms: (i) an irreversible, time-dependent drift that occurs during both optode storage and deployment and (ii) a reversible and pressure-and-time-dependent drift that is detectable in some optodes deployed at depths greater than 1,000 m. The latter is virtually unidentified in the literature yet appears to cause a low-bias in measured DO on the order of 1 to 3 µ mol kg −1 per 1,000 m of depth, appearing as an exponential decay over the first days to months of deployment. Comparisons of our calibrated DO time series against serendipitous mid-deployment conductivity-temperature-depth (CTD)-DO profiles, as well as biogeochemical (BGC)-ARGO float profiles, suggest the protocols described here yield an accuracy in optode-DO of ∼1%, or approximately 2.5 to 3 µ mol kg −1 . We intend this paper to serve as both documentation of the current best practices in the deployment of moored optodes as well as a guide for science teams seeking to collect high-quality moored oxygen data, regardless of expertise.

The upper ocean mediates the transfer of heat and carbon between the atmosphere and ocean interior. The study of this dynamic environment, made possible in part by long-term time series gathered from oceanographic moorings, is therefore crucial to our understanding of Earth’s climate. In this thesis, we use moored datasets from the Southeast Pacific and Southern Oceans to explore two upper-ocean processes relevant to the transfer and eventual sequestration of atmospheric heat and carbon into the deep ocean: wind-, wave-, and buoyancy-forced turbulence and the release of brine in Antarctic polynyas that drives the formation of Antarctic Bottom Water (AABW).In Chapter 1, we use measurements of turbulence kinetic energy (TKE) dissipation rate (ε) collected at 8.4 m depth on the long-established Stratus Mooring in the Southeast Pacific (20° S, 85° W) to assess the applicability of Monin-Obukhov similarity theory (MOST), Law of the Wall (LOW), and other boundary layer similarity scalings to turbulence in the upper ocean. TKE facilitates the mixing of heat, momentum, and solutes within and between the ocean and atmosphere and is generated in the upper ocean primarily by wind, waves, and buoyancy fluxes. Its production can generally be assumed to equal its dissipation, and measurements of ε therefore serve as a means for quantifying turbulence in a system. We present 9 months of ε measurements, a remarkably long time series made possible by the use of a moored pulse-coherent Acoustic Doppler Current Profiler (ADCP), a new methodology for measuring ε that uniquely allows for concurrent surface flux and wave measurements across an extensive length of time and range of conditions. We find that turbulence regimes are quantified similarly using the classic Obukhov length scale (LM=(u*3)/(κB0 ), where u* is ocean-side friction velocity, κ is the von Kármán constant, and B0 is surface buoyancy flux) and the newer Langmuir stability length scale (LL=(〖usu*2〗)/B0 , where us is surface Stokes drift velocity), suggesting that u* implicitly captures the influence of Langmuir turbulence at this site. This is consistent with the strong correlation observed between us and u*, likely promoted by the steady southeast trade winds, and suggests that classic wind and buoyancy-based boundary layer scalings sufficiently describe turbulence in this this region. Accordingly, we find the LOW (ε=(u*3)/κz' where z is instrument depth) and surface buoyancy scaling (ε=B_0, where B_0 is destabilizing surface buoyancy flux) used in classic turbulence scaling studies, such as Lombardo and Gregg (1989), to describe our measurements well, and a newer scaling for Langmuir turbulence scaling based on us and u* to scale ε well at times but to be overall less consistent than (u*3)/κz. The performance of MOST relationships from prior studies in a variety of aquatic and atmospheric settings are also examined, and we find them to largely agree with our data in conditions where both convection and wind-driven current shear act as significant sources of TKE (-1

Dissertation

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