Abstract
AbstractDouble diffusion refers to a variety of turbulent processes in which potential energy is released into kinetic energy, made possible in the ocean by the difference in molecular diffusivities between salinity and temperature. Here, we present a new method for estimating the kinetic energy dissipation rates forced by double‐diffusive convection using temperature and salinity data alone. The method estimates the up‐gradient diapycnal buoyancy flux associated with double diffusion, which is hypothesized to balance the dissipation rate. To calculate the temperature and salinity gradients on small scales we apply a canonical scaling for compensated thermohaline variance (or ‘spice’) on sub‐measurement scales with a fixed buoyancy gradient. Our predicted dissipation rates compare favorably with microstructure measurements collected in the Chukchi Sea. Fine et al. (2018), https://doi.org/10.1175/jpo-d-18-0028.1, showed that dissipation rates provide good estimates for heat fluxes in this region. Finally, we show the method maintains predictive skill when applied to a sub‐sampling of the Conductivity, Temperature, Depth (CTD) data.
Highlights
Recent decades have seen a decline in Arctic sea-ice thickness and extent (E. Carmack et al, 2015)
Double diffusion refers to a variety of turbulent processes in which potential energy is released into kinetic energy, made possible in the ocean by the difference in molecular diffusivities between salinity and temperature
In the second section we describe the method for estimating turbulent dissipation rates associated with double-diffusive convection
Summary
Recent decades have seen a decline in Arctic sea-ice thickness and extent (E. Carmack et al, 2015). Recent decades have seen a decline in Arctic sea-ice thickness and extent Sea-ice melting is influenced by vertical ocean heat transport (Timmermans & Marshall, 2020). A doubling of the Beaufort Gyre halocline heat content has influenced sea-ice extent (Shimada et al, 2006; Timmermans et al, 2018). The most direct measurements of turbulent mixing require high-resolution measurements (microstructure) which are costly and difficult to obtain across large spatial scales. A natural solution is to parameterize turbulence based on properties measured on the finescale (e.g., Polzin et al, 2014; Whalen et al, 2015). Common shear and strain based parameterisations for internal wave breaking do not apply well to areas of double-diffusive convection (Gregg, 1989)
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