Landfast Ice Controls on Turbulence in Antarctic Coastal Seas

Abstract

Knowledge of the ocean surface layer beneath Antarctic landfast ice is sparse. In this article surface layer turbulent and fine structure are quantified with and without landfast ice at the same West Antarctic Peninsula location. Landfast ice reduced turbulence levels locally to an order of magnitude less than ice‐free values, and near‐inertial energy and sub‐inertial tidal energy levels to less than half their ice‐free values. Vertical turbulent heat and nutrient fluxes were, respectively, 6 and 10 times greater than previously estimated. Under‐ice tidal energy dissipation over the entire Antarctic continental shelf due to seasonal landfast ice cover is estimated to be between 788 MW to ∼6 GW. The total rate of wind‐generated turbulence in the surface ocean is greatly reduced by the presence of seasonal landfast ice to an average of 14% of the ice‐free value, but with large sectoral variations. Counter‐intuitively, however, tides and wind contribute approximately equally to the turbulent kinetic energy budget of the upper ocean between the Antarctic coastline and the maximal landfast ice extent, with large sectoral variations, attributed to geographic variations in the strength of the barotropic tide.

Observations of Modified Warm Deep Water Beneath Ronne Ice Shelf, Antarctica, From an Autonomous Underwater Vehicle

“…They are consistently lower than those observed in shear-driven ice shelf-ocean boundary layers (Davis & Nicholls, 2019) or beneath fast ice (Inall et al, 2022), and tend to indicate that despite the tidal forcing, the region of the cavity sampled by ALR is relatively quiescent (at least during neap tides). Over the depth range covered by the vehicle, there is no evidence of ε and χ scaling with the mean flow speed, or of an increase in mixing at the ice front where the flow is required…”

“…The RSI MicroRider package had four microstructure probes sampling at a rate of 512 Hz: two orthogonally positioned shear probes that provide an estimate of the rate of turbulent kinetic energy dissipation (TKE; ε), and two thermistor probes that provide an estimate of the rate of thermal variance dissipation (χ). The microstructure data were processed following standard methods (e.g., Inall et al., 2022; Kimura et al., 2016; Piccolroaz et al., 2021; Scott et al., 2021). Under the assumption of small‐scale isotropy, ε can be estimated as $$${\varepsilon}=\frac{15}{2}\nu \left\langle {\left(\frac{{\partial u}^{\prime }}{\partial z}\right)}^{2}\right\rangle =\frac{15}{2}{\nu}\int \nolimits_{0}^{{k}_{I}}{\psi }_{S}(k)\,dk,$$$ where ν is the temperature‐dependant kinematic viscosity of seawater and $$\left\langle {\left({\partial u}^{\prime }/\partial z\right)}^{2}\right\rangle $$ is the variance of the velocity shear fluctuations perpendicular to ALR's path (Osborn, 1974) derived from integrating the velocity shear spectrum $${\psi }_{S}$$ in wavenumber space $$k$$ up to $${k}_{I}$$.…”

“…The microstructure data were processed following standard methods (e.g. Inall et al, 2022;Kimura et al, 2016;Piccolroaz et al, 2021;Scott et al, 2021).…”

“…The RSI MicroRider package had four microstructure probes sampling at a rate of 512 Hz: two orthogonally positioned shear probes that provide an estimate of the rate of turbulent kinetic energy dissipation (TKE; ε), and two thermistor probes that provide an estimate of the rate of thermal variance dissipation (χ). The microstructure data were processed following standard methods (e.g., Inall et al, 2022;Kimura et al, 2016;Piccolroaz et al, 2021;Scott et al, 2021). Under the assumption of small-scale isotropy, ε can be estimated as…”

Internal tsunamigenesis and ocean mixing driven by glacier calving in Antarctica

“…Buoyancy forcing occurs through heat loss and sea ice production in winter; combined with restratification in summer, this sets the seasonal cycle of water column stability. Winds and tides exert a year-round destratifying influence, modulated by sea ice and influenced by topography ( 18 ). Mixing has been incorporated into ocean and climate models using representations or parameterizations of these processes.…”