Eddy stirring and horizontal diffusivity from Argo float observations: Geographic and depth variability

Abstract

Stirring along isopycnals is a significant factor in determining the distribution of tracers within the ocean. Salinity anomalies on density surfaces from Argo float profiles are used to investigate horizontal stirring and estimate eddy mixing lengths. Eddy mixing length and velocity fluctuations from the ECCO2 global state estimate are used to estimate horizontal diffusivity at a 300 km scale in the upper 2000 m with near‐global coverage. Diffusivity varies by over two orders of magnitude with latitude, longitude, and depth. In all basins, diffusivity is elevated in zonal bands corresponding to strong current regions, including western boundary current extension regions, the Antarctic Circumpolar Current, and equatorial current systems. The estimated mixing lengths and diffusivities provide an observationally based data set that can be used to test and constrain predictions and parameterizations of eddy stirring.

Change of the Global Ocean Vertical Heat Transport over 1993–2010

“…In addition, the global mean of the vertical heat flux that is due to isopycnal mixing shows a subsurface maximum, being close to 1.5 W m 22 , in ECCO v4r1 around 500-m depth. This value is consistent with an independent calculation based on the estimates of isopycnal diffusivity from Cole et al (2015) and the World Ocean Atlas (WOA) climatology. A more detailed comparison between the along-isopycnal heat flux in ECCO v4r1 and that implied by the isopycnal diffusivity from Cole et al (2015) will be presented in a separate study.…”

On the Benefit of Current and Future ALPS Data for Improving Arctic Coupled Ocean-Sea Ice State Estimation

“…For vertical turbulent and molecular mixing, measurements of T, S, and velocities at vertical spatial scales of centimeters are required throughout the entire water column and at horizontal spacing spanning the entire ocean, a suite of measurements not easy to collect (Killworth, 1998). In the absence of direct observations, mixing fields are often inferred from indirect observations and theories (e.g., Kunze et al, 2006;Whalen et al, 2012;Cole et al, 2015). At high latitudes, lack of knowledge in the three-dimensional distribution of these mixing fields is one of the primary reasons the Arctic Ocean's mean horizontal and vertical hydrographic structure is not well reproduced in numerical models (Holloway et al, 2007;Nguyen et al, 2011;Ilicak et al, 2016).…”

Connection between encounter volume and diffusivity in geophysical flows

“…A number of diffusivity estimates other than Okubo's have been made for the Gulf Stream extension region (e.g., Zhurbas and Oh, 2004;LaCasce, 2008;Rypina et al, 2012;Abernathey and Marshall, 2013;Klocker and Abernathey, 2014;or Cole et al, 2015). These estimates are based on surface drifters (Zhurbas and Oh, 2004;LaCasce, 2008;Rypina et al, 2012), satellite-observed velocity fields (Abernathey and Marshall, 2013;Klocker and Abernathey, 2014;Rypina et al, 2012), and Argo float observations (Cole et al, 2015), and they use either the spread of drifters or the evolution of simulated or observed tracer fields to deduce diffusivity.…”

“…These estimates are based on surface drifters (Zhurbas and Oh, 2004;LaCasce, 2008;Rypina et al, 2012), satellite-observed velocity fields (Abernathey and Marshall, 2013;Klocker and Abernathey, 2014;Rypina et al, 2012), and Argo float observations (Cole et al, 2015), and they use either the spread of drifters or the evolution of simulated or observed tracer fields to deduce diffusivity. The resulting diffusivities are spatially varying and span 2 orders of magnitude, from 2 × 10 4 m 2 s −1 in the most energetic regions in the immediate vicinity of the Gulf Stream and its extension, to 10 3 m 2 s −1 in less energetic areas, to 200 m 2 s −1 in the coastal areas of the Slope Sea.…”

“…The diffusivity tensor has also been shown to be anisotropic, with a large anisotropy ratio near the Gulf Stream (Rypina et al, 2012). Data resolution and coverage, as well as the choice of timescales and lengthscales also play a role in defining κ value (Cole at al., 2015). All of these issues complicate the reconciliation of different diffusivity estimates.…”