The Kuroshio occasionally carries warm and salty North Pacific Water into fresher waters of the South China Sea, forming a front with a complex temperature-salinity (T-S) structure to the west of the Luzon Strait. In this study, we examine the T-S interleavings formed by alternating layers of North Pacific water with South China Sea water in a front formed during the winter monsoon season of 2014. Using observations from a glider array following a free-floating wave-powered vertical profiling float to calculate the fine-scale parameters Turner angle, Tu, and Richardson number, Ri, we identified areas favorable to double diffusion convection and shear instability observed in a T-S interleaving. We evaluated the contribution of double diffusion convection and shear instabilities to the thermal variance diffusivity, X, using microstructure data and compared it with previous parameterization schemes based on fine-scale properties. We discover that turbulent mixing is not accurately parameterized when both Tu and Ri are within critical ranges (Tu > 60, Ri < 1/4). In particular, X associated with salt finger processes was an order of magnitude higher (6.7 x 10^-7 K² s^-1) than in regions where only velocity shear was likely to drive mixing (8.7 x 10^-8 K² s^-1).

Over the last two decades, autonomous sensing of ocean turbulence has progressed from a niche endeavor to one where commercial off-the-shelf hardware is available broadly to the community. This advancement has opened new sampling possibilities, for example, direct observation of turbulence in tropical cyclones, extended observational records much longer than those afforded by ship-based programs, and co-location of multiple platforms for statistical assessment of the natural variation in mixing. The reality of real-time data delivery of turbulence quantities has also introduced challenges for onboard processing, data compression, and quality control of quantities that naturally vary by many magnitudes within short temporal and spatial scales. Developments within autonomous sensing of ocean turbulence continue through advances in software design for efficient and accurate data delivery and hardware design of multiple form factors and sensor combinations. In May 2022, a small group of US scientists convened a two-day workshop focused on Microstructure Sensing from Autonomous Platforms in Lake Arrowhead, California. Workshop attendees were sponsored by ONR for engineering development in this topic area, and, in the spirit of past ONR workshops, the participants shared results and discussed recent innovations. Conversations ranged from a historical perspective of ocean turbulence measurement, to new hardware integration of turbulence sensors with autonomous platforms, to algorithms for onboard processing and real-time data delivery. Participants were tasked with developing short synopses of their presentations – nominally three pages and a few figures – for wider distribution.

The observed development of deep mixed layers and the dependence of intense, deep-mixing events on wind and wave conditions are studied using an ocean LES model with and without an imposed Stokes-drift wave forcing. Model results are compared to glider measurements of the ocean vertical temperature, salinity and turbulence kinetic energy (TKE) dissipation rate structure collected in the Icelandic Basin. Observed wind stress reached 0.8 N m^-2 with significant wave height of 4–6 m, while boundary layer depths reached 180 m. We find that wave forcing, via the commonly used Stokes drift vortex force parameterization, is crucial for accurate prediction of boundary layer depth as characterized by measured and predicted TKE dissipation rate profiles. Analysis of the boundary layer kinetic energy (KE) budget using a modified total Lagrangian-mean energy equation, derived for the wave averaged Boussinesq equations by requiring that the rotational inertial terms vanish identically as in the standard energy budget without Stokes forcing, suggests that wind work should be calculated using both the surface current and surface Stokes drift. A large percentage of total wind energy is transferred to model TKE via regular and Stokes drift shear production and dissipated. However, resonance by clockwise rotation of the winds can greatly enhance the generation of inertial current mean KE (MKE). Without resonance, TKE production is about 5 times greater than MKE generation, whereas with resonance this ratio decreases to roughly 2. The results have implications for the problem of estimating the global kinetic energy budget of the ocean.

The ocean surface boundary layer is a gateway of energy transfer into the ocean. Wind-driven shear and meteorologically forced convection inject turbulent kinetic energy into the surface boundary layer, mixing the upper ocean and transforming its density structure. In the absence of direct observations or the capability to resolve sub-grid scale 3D turbulence in operational ocean models, the oceanography community relies on surface boundary layer similarity scalings (BLS) of shear and convective turbulence to represent this mixing. Despite their importance, near-surface mixing processes (and ubiquitous BLS representations of these processes) have been under-sampled in high energy forcing regimes such as the Southern Ocean. With the maturing of autonomous sampling platforms, there is now an opportunity to collect high-resolution spatial and temporal measurements in the full range of forcing conditions. Here, we characterize near-surface turbulence under strong wind forcing using the first long-duration glider microstructure survey of the Southern Ocean. We leverage these data to show that the measured turbulence is significantly higher than standard shear-convective BLS in the shallower parts of the surface boundary layer and lower than standard shear-convective BLS in the deeper parts of the surface boundary layer; the latter of which is not easily explained by present wave-effect literature. Consistent with the CBLAST (Coupled Boundary Layers and Air Sea Transfer) low winds experiment, this bias has the largest magnitude and spread in shallowest 10% of the actively mixing layer under low-wind and breaking wave conditions, when relatively low levels of turbulent kinetic energy (TKE) in surface regime are easily biased by wave events.

Finescale strain parameterization (hereafter, FSP) of turbulent kinetic energy dissipation rate has become a widely used method for observing ocean mixing, solving a coverage problem where direct turbulence measurements are absent but CTD profiles are available. This method can offer significant value, but there are limitations in its broad application to the global ocean. FSP often fails to produce reliable results in frontal zones where temperature-salinity (T/S) intrusive features contaminate the CTD strain spectrum, as well as where the aspect ratio of the internal wave spectrum is known to vary greatly with depth, as frequently occurs in the Southern Ocean. In this study we use direct turbulence measurements from DIMES (Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean) and glider microstructure measurements from AUSSOM (Autonomous Sampling of Southern Ocean Mixing) to show that FSP can have large biases (compared to direct turbulence measurement) below the mixed layer when physics associated with T/S fronts are meaningfully present. We propose that the FSP methodology be modified to (1) include a density ratio (R_p)-based data exclusion rule to avoid contamination by double diffusive instabilities in frontal zones such as the Antarctic Circumpolar Current, the Gulf Stream, and the Kuroshio, and (2) conduct (or leverage available) microstructure measurements of the depth-varying shear-to-strain ratio R_w(Z) prior to performing FSP in each dynamically-unique region of the global ocean.

Upper-ocean turbulence is central to the exchanges of heat, momentum, and gases across the air–sea interface and therefore plays a large role in weather and climate. Current understanding of upper-ocean mixing is lacking, often leading models to misrepresent mixed layer depths and sea surface temperature. In part, progress has been limited by the difficulty of measuring turbulence from fixed moorings that can simultaneously measure surface fluxes and upper-ocean stratification over long time periods. Here we introduce a direct wavenumber method for measuring turbulent kinetic energy (TKE) dissipation rates ϵ from long-enduring moorings using pulse-coherent ADCPs. We discuss optimal programming of the ADCPs, a robust mechanical design for use on a mooring to maximize data return, and data processing techniques including phase-ambiguity unwrapping, spectral analysis, and a correction for instrument response. The method was used in the Salinity Processes Upper-Ocean Regional Study (SPURS) to collect two year-long datasets. We find that the mooring-derived TKE dissipation rates compare favorably to estimates made nearby from a microstructure shear probe mounted to a glider during its two separate 2-week missions for O(10^-8) ≤ ε ≤ O(10^-5) m² s^-3. Periods of disagreement between turbulence estimates from the two platforms coincide with differences in vertical temperature profiles, which may indicate that barrier layers can substantially modulate upper-ocean turbulence over horizontal scales of 1–10 km. We also find that dissipation estimates from two different moorings at 12.5 and at 7 m are in agreement with the surface buoyancy flux during periods of strong nighttime convection, consistent with classic boundary layer theory.

Mixing efficiency is an important turbulent flow property in fluid dynamics, whose variability potentially affects the large‐scale ocean circulation. However, there are several confusing definitions. Here we compare and contrast patch‐wise versus bulk estimates of mixing efficiency in the abyss by revisiting data from previous extensive field surveys in the Brazil Basin. Observed patch‐wise efficiency is highly variable over a wide range of turbulence intensity. Bulk efficiency is dominated by rare extreme turbulence events. In the case where enhanced near‐bottom turbulence is thought to be driven by breaking of small‐scale internal tides, the estimated bulk efficiency is 20%, close to the conventional value of 17%. On the other hand, where enhanced near‐bottom turbulence appears to be convectively driven by hydraulic overflows, bulk efficiency is suggested to be as large as 45%, which has implications for a further significant role of overflow mixing on deep‐water mass transformation.

Using a combination of models and observations, the US Office of Naval Research Flow Encountering Abrupt Topography (FLEAT) initiative examines how island chains and submerged ridges affect open ocean current systems, from the hundreds of kilometer scale of large current features to the millimeter scale of turbulence. FLEAT focuses on the western Pacific, mainly on equatorial currents that encounter steep topography near the island nation of Palau. Wake eddies and lee waves as small as 1 km were observed to form as these currents flowed around or over the steep topography. The direction and vertical structure of the incident flow varied over tidal, inertial, seasonal, and interannual timescales, with implications for downstream flow. Models incorporated tides and had grids with resolutions of hundreds of meters to enable predictions of flow transformations as waters encountered and passed around Palau’s islands. In addition to making scientific advances, FLEAT had a positive impact on the local Palauan community by bringing new technology to explore local waters, expanding the country’s scientific infrastructure, maintaining collaborations with Palauan partners, and conducting outreach activities aimed at elementary and high school students, US embassy personnel, and Palauan government officials.

The interaction of flow with steep island and ridge topography at the Palau island chain leads to rich vorticity fields that generate a cascade of motions. The energy transfer to small scales removes energy from the large-scale mean flow of the equatorial current systems and feeds energy to the fine and microstructure scales where instability mechanisms lead to turbulence and dissipation. Until now, direct assessments of the turbulence associated with island wakes have received only minimal attention. Here, we examine data collected from an ocean glider equipped with microstructure sensors that flew in the island wake of Palau. We use a combination of submesoscale modeling and direct observation to quantify the relationship between vorticity and turbulence levels. We find that direct wind-driven mixing only accounts for about 10% of the observed turbulence levels, suggesting that most of the energy for mixing is extracted from the shear associated with the vorticity field in the island’s wake. Below the surface layer, enhanced turbulence correlates with the phase and magnitude of the relative vorticity and strain levels of the mesoscale flow.