Spatial and Temporal Variability of Diapycnal Mixing in the Indian Ocean

Abstract

The rate of turbulent kinetic energy dissipation and diapycnal diffusivity are estimated along 10 hydrographic sections across the Indian Ocean from a depth of 500 m to the seabed. Six sections were occupied twice. On the meridional section, which is nominally along 95°E, spatial patterns were observed to persist throughout the three occupations. Since the variability in diffusivity exceeds the variability in the vertical gradients of temperature and salinity, we conclude that the diffusive diapycnal fluxes vary mostly with diffusivity. In high latitudes, diapycnal diffusions of both temperature and salinity contribute almost equally to density diffusion, particularly across isopycnals just above the salinity maximum, while mainly temperature contributes in other latitudes. The known zonal difference in turbulence is reproduced. Diffusivity from the seabed to 4,000 m above the seabed has an exponential profile with a mode value of 4 × 10−4 m2s−1 at 1,000 m above the seabed and is positively correlated with topographic roughness as reported previously. It is found that the diffusivity also correlates with wind power injected through the surface at near‐inertial frequencies 10–80 days before the observations. These correlations were used to interpolate the observation‐based turbulence quantities to the entire Indian Ocean. Although the dissipation averaged along selected neutral‐density surfaces is less than the dissipation needed to explain the meridional overturning circulation evaluated across 32°S latitude, this may be explained by effects not captured by the ship‐based observations and parameterization. These effects likely include unobserved high‐mixing events, near bottom processes (e.g., hydraulic jumps), and deep equatorial jets.

Turbulence Across the Antarctic Circumpolar Current in the Indian Southern Ocean: Micro‐Temperature Measurements and Finescale Parameterizations

“…The present large h 0 is consistent with the averaged vertical profiles of K ρ inferred from strain‐based finescale parameterizations (Kunze, 2017) and the empirical model based on finescale parameterizations (Katsumata et al., 2021) and from the FP07 observation (Goto et al., 2021). This could be partly because the present empirical model does not involve the data near the bottom between seafloor and the 160 m above bottom, and the vertical average of 320 m might erase the structure near the bottom and instead emphasize the large vertical scale impact from fine horizontal scale rough bottom topography.…”

“…By summarizing the relationships between above‐mentioned variables ($${\overline{N}}^{2}$$, var(bH), ( U ) mean ) and ε FP 07 or K ρ , we here attempt to empirically formulate the observed ε FP 07 or K ρ as a function of those variables ($${\overline{N}}^{2}$$, var(bH), ( U ) mean ), focusing here on the bottom topographic influence as previously attempted (e.g., Decloedt & Luther, 2010; Katsumata et al., 2021). In the present study, the observed diffusivity K ρ is almost independent on $${\overline{N}}^{2}$$ ( R = −0.10) as assumed in the previous study (Decloedt & Luther, 2010), which is consistent with the model of Henyey et al.…”

“…First purpose of the present study is to map the spatial variability of turbulent mixing estimated from the microstructure measurements with the CTD‐attached FP07 across the ACC in the Indian Ocean from the subantarctic to the polar regions (Section 3.1). To date, the turbulence distribution covering the wide range of the Southern Ocean across the ACC have been inferred mainly from the finescale parameterizations (e.g., Katsumata et al., 2021; Kunze, 2017; Kunze et al., 2006; Naveira Garabato et al., 2004). Those previous studies reported that spatial patterns of turbulent dissipation rates are associated with density stratification N 2 , bottom topographic roughness, and depth‐averaged current speed U .…”

“…Those previous studies reported that spatial patterns of turbulent dissipation rates are associated with density stratification N 2 , bottom topographic roughness, and depth‐averaged current speed U . Long vertical influence of the bottom roughness (exponential decay scale >1000 m) from the finescale parameterizations (Katsumata et al., 2021; Kunze, 2017) contradicts with the decay scale of 500 m implemented in the most widely used parameterization, which assumed localized mixing generated from the tide‐topography interaction (Jayne & St. Laurent, 2001). We examine this issue by using both turbulence data from micro‐temperature and finescale parameterizations.…”

Response of Internal Wave‐Induced Turbulent Dissipation to ENSO in the Western Pacific Warm Pool

“…This scheme provides a reliable basis for calculating the turbulent mixing below the mixing layer by using the temperature and salinity profiles obtained from Argo floats. This parameterization scheme was successfully applied in various regions, such as the Northwestern Pacific (Whalen et al., 2018) and the Indian Ocean (Katsumata et al., 2021), to accurately describe the spatial and temporal distributions of turbulent mixing and was found to be consistent with the observations from microstructure data. Therefore, the finescale parameterization scheme can reasonably derive diapycnal turbulent mixing.…”