Seismic imaging of a thermohaline staircase in the western tropical North Atlantic

Fer, Ilker; Nandi, P.; Holbrook, W. S.; Schmitt, Raymond W.; Páramo, Pedro

doi:10.5194/os-6-621-2010

Cited by 47 publications

(48 citation statements)

References 36 publications

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“…The local turbulent dissipation rate can be estimated by combining observations of the internal wave field (finescale measurements) with theoretical models of energy transfer. Finescale parameterizations have been widely used to estimate mixing in the past decade (e.g., Mauritzen et al 2002;Naveira Garabato et al 2004b;Sloyan 2005;Kunze et al 2006;Alford et al 2007;Park et al 2008;Fer et al 2010;Wu et al 2011;Whalen et al 2012;MacKinnon et al 2013). The use of finescale parameterization is high since the observations needed (vertical density and/or velocity measurements) to derive the dissipation rate with these methods are more easily acquired than direct observations of dissipation using microstructure profilers.…”

Section: Observationsmentioning

confidence: 99%

Mixing Variability in the Southern Ocean

Meyer

Sloyan

Polzin

et al. 2015

Journal of Physical Oceanography

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A key remaining challenge in oceanography is the understanding and parameterization of small-scale mixing. Evidence suggests that topographic features play a significant role in enhancing mixing in the Southern Ocean. This study uses 914 high-resolution hydrographic profiles from novel EM-APEX profiling floats to investigate turbulent mixing north of the Kerguelen Plateau, a major topographic feature in the Southern Ocean. A shear-strain finescale parameterization is applied to estimate diapycnal diffusivity in the upper 1600 m of the ocean. The indirect estimates of mixing match direct microstructure profiler observations made simultaneously. It is found that mixing intensities have strong spatial and temporal variability, ranging from O(10 26

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Section: Observationsmentioning

confidence: 99%

Mixing Variability in the Southern Ocean

Meyer

Sloyan

Polzin

et al. 2015

Journal of Physical Oceanography

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“…A recently developed method ''seismic oceanography'' based on the conventional seismic reflection profiling allows us to relate water column acoustic reflections to oceanic finescale structures [e.g., Holbrook et al, 2003;Ruddick et al, 2009]. It has the capability of showing the mesoscale to finescale features simultaneously with a typical vertical and horizontal resolution of 10 m. Numerous oceanographic features can be outlined successfully, such as subsurface eddies [Biescas et al, 2008;Buffett et al, 2009;Menesguen et al, 2012;Papenberg et al, 2010], currents [Tang et al, 2013;Tang and Zheng, 2011;Vsemirnova et al, 2012], internal waves [Holbrook and Fer, 2005;Krahmann et al, 2008], and thermohaline staircases [Biescas et al, 2010;Fer et al, 2010].…”

Section: Citationmentioning

confidence: 99%

Seismic observations from a Yakutat eddy in the northern Gulf of Alaska

2014

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Recent works show that the seismic oceanography technique allows us to relate water column seismic reflections to oceanic finescale structures. In this study, finescale structures of a surface anticyclonic eddy have been unveiled by reprocessing two seismic transects acquired in the northern Gulf of Alaska using an 8 km hydrophone streamer and 6600 cu in linear airgun array in September 2008. The eddy was a typical bowl-like structure with around 55 km width and 700 m depth. It has two fringes around the eddy base and a spiral arm at the NE edge. The in situ sea surface temperature and salinity data from a shipboard thermosalinograph help to confirm our interpretations of a spiral arm shed from the warm eddy and the entrained cold water from elsewhere. Nearby the eddy and offshore the shelf-break, there is a strong frontal feature, probably the Alaska Current. The eddy likely formed offshore Yakutat shelf and transported along the offshore shelf-break by tracking the sea level anomalies. Its equivalent diameter of 65 km was measured using the along-track altimeter and the seismic constraints. It was comparable with results from the representative conventional algorithms of eddy detection. Geostrophic velocities of the eddy were estimated from the dipping seismic reflections under the assumptions of approximate isopycnals and geostrophic balance. Measured water properties including sea surface temperature, salinity, and chlorophyll revealed that eddy translation transports coastal water to the pelagic regions. Structures synthesized from CTD profiles that sampled an earlier eddy suggest that thin striae around the base might be a common feature in Gulf of Alaska eddies.

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“…The physical basis for seismic oceanography has been well established by several studies that combined seismic surveys with simultaneous in situ measurements of temperature, salinity, and density (Nakamura et al 2006;Nandi et al 2004;Sallar es et al 2009): weak, but clear, reflections from within the water column come from vertical changes in (primarily) sound speed and (secondarily) density. Over the past few years, numerous studies have demonstrated the ability of seismic imaging to detect and map major features in the ocean, including fronts (Holbrook et al 2003;Mirshak et al 2010;Sheen et al 2009), internal waves (Holbrook and Fer 2005;Krahmann et al 2008), eddies and warm-core rings (Biescas et al 2008;Ruddick et al 2009;Yamashita et al 2011), thermohaline staircases (Biescas et al 2010;Fer et al 2010), lee waves (Eakin et al 2011), and internal tide beams ). SO has several unique capabilities, including the ability to image fine structure over large sections of the ocean and to full ocean depth, provided that sufficient fine structure is present to produce reflections.…”

Section: Introductionmentioning

confidence: 99%

Estimating Oceanic Turbulence Dissipation from Seismic Images

Holbrook

Fer

Schmitt

et al. 2013

Journal of Atmospheric and Oceanic Technology

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Seismic images of oceanic thermohaline finestructure record vertical displacements from internal waves and turbulence over large sections at unprecedented horizontal resolution. Where reflections follow isopycnals, their displacements can be used to estimate levels of turbulence dissipation, by applying the Klymak-Moum slope spectrum method. However, many issues must be considered when using seismic images for estimating turbulence dissipation, especially sources of random and harmonic noise. This study examines the utility of seismic images for estimating turbulence dissipation in the ocean, using synthetic modeling and data from two field surveys, from the South China Sea and the eastern Pacific Ocean, including the first comparison of turbulence estimates from seismic images and from vertical shear. Realistic synthetic models that mimic the spectral characteristics of internal waves and turbulence show that reflector slope spectra accurately reproduce isopycnal slope spectra out to horizontal wavenumbers of ;0.04 cpm, corresponding to horizontal wavelengths of 25 m. Using seismic reflector slope spectra requires recognition and suppression of shot-generated harmonic noise and restriction of data to frequency bands with signal-to-noise ratios greater than about 4. Calculation of slope spectra directly from Fourier transforms of the seismic data is necessary to determine the suitability of a particular dataset to turbulence estimation from reflector slope spectra. Turbulence dissipation estimated from seismic reflector displacements compares well to those from 10-m shear determined by coincident expendable current profiler (XCP) data, demonstrating that seismic images can produce reliable estimates of turbulence dissipation in the ocean, provided that random noise is minimal and harmonic noise is removed.

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Seismic imaging of a thermohaline staircase in the western tropical North Atlantic

Cited by 47 publications

References 36 publications

Mixing Variability in the Southern Ocean

Mixing Variability in the Southern Ocean

Seismic observations from a Yakutat eddy in the northern Gulf of Alaska

Estimating Oceanic Turbulence Dissipation from Seismic Images

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