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Andrew F. Thompson
,
Sarah T. Gille
,
J. A. MacKinnon
, and
Janet Sprintall

Abstract

Temperature and salinity profiles obtained with expendable CTD probes throughout Drake Passage between February 2002 and July 2005 are analyzed to estimate turbulent diapycnal eddy diffusivities to a depth of 1000 m. Diffusivity values are inferred from density/temperature inversions and internal wave vertical strain. Both methods reveal the same pattern of spatial variability across Drake Passage; diffusivity estimates from inversions exceed those from vertical strain by a factor of 3 over most of Drake Passage. The Polar Front (PF) separates two dynamically different regions. Strong thermohaline intrusions characterize profiles obtained north of the PF. South of the PF, stratification is determined largely by salinity, and temperature is typically unstably stratified between 100- and 600-m depth. In the upper 400 m, turbulent diapycnal diffusivities are O(10−3 m2 s−1) north of the PF but decrease to O(10−4 m2 s−1) or smaller south of the PF. Below 400 m diffusivities typically exceed 10−4 m2 s−1. Diffusivities decay weakly with depth north of the PF, whereas diffusivities increase with depth and peak near the local temperature maximum south of the PF. The meridional pattern in near-surface mixing corresponds to local maxima and minima of both wind stress and wind stress variance. Near-surface diffusivities are also found to be larger during winter months north of the PF. Wind-driven near-inertial waves, strong mesoscale eddy activity, and double-diffusive convection are suggested as possible factors contributing to observed mixing patterns.

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Kyla Drushka
,
William E. Asher
,
Janet Sprintall
,
Sarah T. Gille
, and
Clifford Hoang

Abstract

Surface salinity variability on O(1–10) km lateral scales (the submesoscale) generates density variability and thus has implications for submesoscale dynamics. Satellite salinity measurements represent a spatial average over horizontal scales of approximately 40–100 km but are compared to point measurements for validation, so submesoscale salinity variability also complicates validation of satellite salinities. Here, we combine several databases of historical thermosalinograph (TSG) measurements made from ships to globally characterize surface submesoscale salinity, temperature, and density variability. In river plumes; regions affected by ice melt or upwelling; and the Gulf Stream, South Atlantic, and Agulhas Currents, submesoscale surface salinity variability is large. In these regions, horizontal salinity variability appears to explain some of the differences between surface salinities from the Aquarius and SMOS satellites and salinities measured with Argo floats. In other words, apparent satellite errors in highly variable regions in fact arise because Argo point measurements do not represent spatially averaged satellite data. Salinity dominates over temperature in generating submesoscale surface density variability throughout the tropical rainbands, in river plumes, and in polar regions. Horizontal density fronts on 10-km scales tend to be compensated (salinity and temperature have opposing effects on density) throughout most of the global oceans, with the exception of the south Indian and southwest Pacific Oceans between 20° and 30°S, where fronts tend to be anticompensated.

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Lauren Hoffman
,
Matthew R. Mazloff
,
Sarah T. Gille
,
Donata Giglio
, and
Aniruddh Varadarajan

Abstract

Atmospheric rivers (ARs) result in precipitation over land and ocean. Rainfall on the ocean can generate a buoyant layer of freshwater that impacts exchanges between the surface and the mixed layer. These “fresh lenses” are important for weather and climate because they may impact the ocean stratification at all time scales. Here we use in situ ocean data, collocated with AR events, and a one-dimensional configuration of a general circulation model, to investigate the impact of AR precipitation on surface ocean salinity in the California Current System (CCS) on seasonal and event-based time scales. We find that at coastal and onshore locations the CCS freshens through the rainy season due to AR events, and years with higher AR activity are associated with a stronger freshening signal. On shorter time scales, model simulations suggest that events characteristic of CCS ARs can produce salinity changes that are detectable by ocean instruments (≥0.01 psu). Here, the surface salinity change depends linearly on rain rate and inversely on wind speed. Higher wind speeds (U > 8 m s−1) induce mixing, distributing freshwater inputs to depths greater than 20 m. Lower wind speeds (U ≤ 8 m s−1) allow freshwater lenses to remain at the surface. Results suggest that local precipitation is important in setting the freshwater seasonal cycle of the CCS and that the formation of freshwater lenses should be considered for identifying impacts of atmospheric variability on the upper ocean in the CCS on weather event time scales.

Significance Statement

Atmospheric rivers produce large amounts of rainfall. The purpose of this study is to understand how this rain impacts the surface ocean in the California Current System on seasonal and event time scales. Our results show that a greater precipitation over the rainy season leads to a larger decrease in salinity over time. On shorter time scales, these atmospheric river precipitation events commonly produce a surface salinity response that is detectable by ocean instruments. This salinity response depends on the amount of rainfall and the wind speed. In general, higher wind speeds will cause the freshwater input from rain to mix deeper, while lower wind speeds will have reduced mixing, allowing a layer of freshwater to persist at the surface.

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Ana B. Villas Bôas
,
Bruce. D. Cornuelle
,
Matthew. R. Mazloff
,
Sarah. T. Gille
, and
Fabrice Ardhuin

Abstract

Surface gravity waves play a major role in the exchange of momentum, heat, energy, and gases between the ocean and the atmosphere. The interaction between currents and waves can lead to variations in the wave direction, frequency, and amplitude. In the present work, we use an ensemble of synthetic currents to force the wave model WAVEWATCH III and assess the relative impact of current divergence and vorticity in modifying several properties of the waves, including direction, period, directional spreading, and significant wave height H s . We find that the spatial variability of H s is highly sensitive to the nature of the underlying current and that refraction is the main mechanism leading to gradients of H s . The results obtained using synthetic currents were used to interpret the response of surface waves to realistic currents by running an additional set of simulations using the llc4320 MITgcm output in the California Current region. Our findings suggest that wave parameters could be used to detect and characterize strong gradients in the velocity field, which is particularly relevant for the Surface Water and Ocean Topography (SWOT) satellite as well as several proposed satellite missions.

Open access
Momme C. Hell
,
Bruce D. Cornelle
,
Sarah T. Gille
,
Arthur J. Miller
, and
Peter D. Bromirski

Abstract

Strong surface winds under extratropical cyclones exert intense surface stresses on the ocean that lead to upper-ocean mixing, intensified heat fluxes, and the generation of waves, that, over time, lead to swell waves (longer than 10-s period) that travel long distances. Because low-frequency swell propagates faster than high-frequency swell, the frequency dependence of swell arrival times at a measurement site can be used to infer the distance and time that the wave has traveled from its generation site. This study presents a methodology that employs spectrograms of ocean swell from point observations on the Ross Ice Shelf (RIS) to verify the position of high wind speed areas over the Southern Ocean, and therefore of extratropical cyclones. The focus here is on the implementation and robustness of the methodology in order to lay the groundwork for future broad application to verify Southern Ocean storm positions from atmospheric reanalysis data. The method developed here combines linear swell dispersion with a parametric wave model to construct a time- and frequency-dependent model of the dispersed swell arrivals in spectrograms of seismic observations on the RIS. A two-step optimization procedure (deep learning) of gradient descent and Monte Carlo sampling allows detailed estimates of the parameter distributions, with robust estimates of swell origins. Median uncertainties of swell source locations are 110 km in radial distance and 2 h in time. The uncertainties are derived from RIS observations and the model, rather than an assumed distribution. This method is an example of supervised machine learning informed by physical first principles in order to facilitate parameter interpretation in the physical domain.

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Tianyu Wang
,
Sarah T. Gille
,
Matthew R. Mazloff
,
Nathalie V. Zilberman
, and
Yan Du

Abstract

Argo float trajectories are simulated in the southwest Pacific basin (25°–45°S, 170°E–165°W) using velocity fields from a 1/12° Southern Ocean model and a Lagrangian particle tracking model programmed to represent the vertical motions of profiling Argo floats. The system is applied to simulate both core Argo floats (typically parked at 1000-m depth and profiling to 2000-m depth) and Deep Argo floats (parked 500 m above the seafloor). The goal is to estimate probability density functions (PDFs) predicting future float positions. Differences are expected in the trajectory statistics, largely because of limitations in the temporal and spatial resolution of the model fields and uncertainties associated with a random walk component included in the particle advection scheme to represent this unresolved variability. Nonetheless, the core Argo float displacements over ~100-day time intervals are mostly consistent with the derived PDFs, particularly in regions with stable midlayer flows. For the Deep Argo floats, which are released into the open ocean and parked near the bottom, the simulations predict an average total displacement of less than 50 km within 100 days, in good agreement with the Deep Argo floats deployed as part of a pilot study. The study explores both the representativeness and the predictability of float displacements, with an aim to contribute to planning for the float observing system.

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Luke Kachelein
,
Bruce D. Cornuelle
,
Sarah T. Gille
, and
Matthew R. Mazloff

Abstract

A novel tidal analysis package (red_tide) has been developed to characterize low-amplitude non-phase-locked tidal energy and dominant tidal peaks in noisy, irregularly sampled, or gap-prone time series. We recover tidal information by expanding conventional harmonic analysis to include prior information and assumptions about the statistics of a process, such as the assumption of a spectrally colored background, treated as nontidal noise. This is implemented using Bayesian maximum posterior estimation and assuming Gaussian prior distributions. We utilize a hierarchy of test cases, including synthetic data and observations, to evaluate this method and its relevance to analysis of data with a tidal component and an energetic nontidal background. Analysis of synthetic test cases shows that the methodology provides robust tidal estimates. When the background energy spectrum is nearly spectrally white, red_tide results replicate results from ordinary least squares (OLS) commonly used in other tidal packages. When background spectra are red (a spectral slope of −2 or steeper), red_tide’s estimates represent a measurable improvement over OLS. The approach highlights the presence of tidal variability and low-amplitude constituents in observations by allowing arbitrarily configurable fitted frequencies and prior statistics that constrain solutions. These techniques have been implemented in MATLAB in order to analyze tidal data with non-phase-locked components and an energetic background that pose challenges to the commonly used OLS approach.

Open access
Marina Frants
,
Gillian M. Damerell
,
Sarah T. Gille
,
Karen J. Heywood
,
Jennifer MacKinnon
, and
Janet Sprintall

Abstract

Finescale estimates of diapycnal diffusivity κ are computed from CTD and expendable CTD (XCTD) data sampled in Drake Passage and in the eastern Pacific sector of the Southern Ocean and are compared against microstructure measurements from the same times and locations. The microstructure data show vertical diffusivities that are one-third to one-fifth as large over the smooth abyssal plain in the southeastern Pacific as they are in Drake Passage, where diffusivities are thought to be enhanced by the flow of the Antarctic Circumpolar Current over rough topography. Finescale methods based on vertical strain estimates are successful at capturing the spatial variability between the low-mixing regime in the southeastern Pacific and the high-mixing regime of Drake Passage. Thorpe-scale estimates for the same dataset fail to capture the differences between Drake Passage and eastern Pacific estimates. XCTD profiles have lower vertical resolution and higher noise levels after filtering than CTD profiles, resulting in XCTD κ estimates that are, on average, an order of magnitude higher than CTD estimates. Overall, microstructure diffusivity estimates are better matched by strain-based estimates than by estimates based on Thorpe scales, and CTD data appear to perform better than XCTD data. However, even the CTD-based strain diffusivity estimates can differ from microstructure diffusivities by nearly an order of magnitude, suggesting that density-based fine-structure methods of estimating mixing from CTD or XCTD data have real limitations in low-stratification regimes such as the Southern Ocean.

Full access
Veronica Tamsitt
,
Ivana Cerovečki
,
Simon A. Josey
,
Sarah T. Gille
, and
Eric Schulz

Abstract

Wintertime surface ocean heat loss is the key process driving the formation of Subantarctic Mode Water (SAMW), but there are few direct observations of heat fluxes, particularly during winter. The Ocean Observatories Initiative (OOI) Southern Ocean mooring in the southeast Pacific Ocean and the Southern Ocean Flux Station (SOFS) in the southeast Indian Ocean provide the first concurrent, multiyear time series of air–sea fluxes in the Southern Ocean from two key SAMW formation regions. In this work we compare drivers of wintertime heat loss and SAMW formation by comparing air–sea fluxes and mixed layers at these two mooring locations. A gridded Argo product and the ERA5 reanalysis product provide temporal and spatial context for the mooring observations. Turbulent ocean heat loss is on average 1.5 times larger in the southeast Indian (SOFS) than in the southeast Pacific (OOI), with stronger extreme heat flux events in the southeast Indian leading to larger cumulative winter ocean heat loss. Turbulent heat loss events in the southeast Indian (SOFS) occur in two atmospheric regimes (cold air from the south or dry air circulating via the north), while heat loss events in the southeast Pacific (OOI) occur in a single atmospheric regime (cold air from the south). On interannual time scales, wintertime anomalies in net heat flux and mixed layer depth (MLD) are often correlated at the two sites, particularly when wintertime MLDs are anomalously deep. This relationship is part of a larger basin-scale zonal dipole in heat flux and MLD anomalies present in both the Indian and Pacific basins, associated with anomalous meridional atmospheric circulation.

Free access
Jia-Rui Shi
,
Lynne D. Talley
,
Shang-Ping Xie
,
Wei Liu
, and
Sarah T. Gille

Abstract

Observations show that since the 1950s, the Southern Ocean has stored a large amount of anthropogenic heat and has freshened at the surface. These patterns can be attributed to two components of surface forcing: poleward-intensified westerly winds and increased buoyancy flux from freshwater and heat. Here we separate the effects of these two forcing components by using a novel partial-coupling technique. We show that buoyancy forcing dominates the overall response in the temperature and salinity structure of the Southern Ocean. Wind stress change results in changes in subsurface temperature and salinity that are closely related to intensified residual meridional overturning circulation. As an important result, we show that buoyancy and wind forcing result in opposing changes in salinity: the wind-induced surface salinity increase due to upwelling of saltier subsurface water offsets surface freshening due to amplification of the global hydrological cycle. Buoyancy and wind forcing further lead to different vertical structures of Antarctic Circumpolar Current (ACC) transport change; buoyancy forcing causes an ACC transport increase (3.1 ± 1.6 Sv; 1 Sv ≡ 106 m3 s−1) by increasing the meridional density gradient across the ACC in the upper 2000 m, while the wind-induced response is more barotropic, with the whole column transport increased by 8.7 ± 2.3 Sv. While previous research focused on the wind effect on ACC intensity, we show that surface horizontal current acceleration within the ACC is dominated by buoyancy forcing. These results shed light on how the Southern Ocean might change under global warming, contributing to more reliable future projections.

Open access