Estimating dissipation rates associated with double diffusion
Middleton, L. ORCID: https://orcid.org/0000-0002-2821-6992; Fine, E. C.; MacKinnon, J. A.; Alford, M. H.; Taylor, J.R.. 2021 Estimating dissipation rates associated with double diffusion. Geophysical Research Letters, 48 (15), e2021GL092779. 13, pp. https://doi.org/10.1029/2021GL092779
Before downloading, please read NORA policies.
|
Text (Open Access)
© 2021. The Authors. 2021GL092779.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (1MB) | Preview |
Abstract/Summary
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. 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 hypothesised 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) 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 CTD data.
Item Type: | Publication - Article |
---|---|
Digital Object Identifier (DOI): | https://doi.org/10.1029/2021GL092779 |
ISSN: | 0094-8276 |
Additional Keywords: | Ocean mixing, Double-diffusive convection, Compensated thermohaline variance |
Date made live: | 28 Jun 2021 13:43 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/530576 |
Actions (login required)
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year