Best practices for estimating turbulent dissipation from oceanic single-point velocity timeseries observations

Abstract. We provide best practices for estimating the dissipation rate of turbulent kinetic energy, ε, from velocity measurements in an oceanographic context. These recommendations were developed as part of the Scientific Committee on Oceanographic Research (SCOR) Working Group #160 "Analyzing ocean turbulence observations to quantify mixing". The recommendations here focus on velocity measurements that enable fitting the inertial subrange of wavenumber velocity spectra. The method examines the measurable range for this method of dissipation rates in the ocean, seas, and other natural waters. The recommendations are intended to be platform-independent since the velocities may be measured using bottom-mounted platforms, platforms mounted beneath the ice, or platforms directly on mooring lines once the data is motion-decontaminated. The procedure for preparing the data for spectral estimation is discussed in detail, along with the quality control metrics that should accompany each estimate of ε during data archiving. The methods are applied to four 'benchmark' datasets covering different flow regimes and two instrument types (acoustic-Doppler and time of travel). Problems associated with velocity data quality, such as phase-wrapping, spikes, measurement noise, and frame interference, are illustrated with examples drawn from the benchmarks. Difficulties in resolving and identifying the inertial subrange are also discussed, and recommendations on how these issues should be identified and flagged during data archiving are provided.

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Published
2025-09-18
DOI
https://doi.org/10.5194/egusphere-2025-4433
Primary Topic
Oceanographic and Atmospheric Processes
Type
article
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Best practices for estimating turbulent dissipation from oceanic single-point velocity timeseries observations

Danielle Wain, Craig L. Stevens, Cynthia Bluteau, Julia C. Mullarney
Oceanographic and Atmospheric Processes
article

Best practices for estimating turbulent dissipation from oceanic single-point velocity timeseries observations

Danielle Wain, Craig L. Stevens, Cynthia Bluteau, Julia C. Mullarney
article en

Abstract

Abstract. We provide best practices for estimating the dissipation rate of turbulent kinetic energy, ε, from velocity measurements in an oceanographic context. These recommendations were developed as part of the Scientific Committee on Oceanographic Research (SCOR) Working Group #160 "Analyzing ocean turbulence observations to quantify mixing". The recommendations here focus on velocity measurements that enable fitting the inertial subrange of wavenumber velocity spectra. The method examines the measurable range for this method of dissipation rates in the ocean, seas, and other natural waters. The recommendations are intended to be platform-independent since the velocities may be measured using bottom-mounted platforms, platforms mounted beneath the ice, or platforms directly on mooring lines once the data is motion-decontaminated. The procedure for preparing the data for spectral estimation is discussed in detail, along with the quality control metrics that should accompany each estimate of ε during data archiving. The methods are applied to four 'benchmark' datasets covering different flow regimes and two instrument types (acoustic-Doppler and time of travel). Problems associated with velocity data quality, such as phase-wrapping, spikes, measurement noise, and frame interference, are illustrated with examples drawn from the benchmarks. Difficulties in resolving and identifying the inertial subrange are also discussed, and recommendations on how these issues should be identified and flagged during data archiving are provided.

Fisheries and Oceans Canada (CA), Wellington Institute of Technology (NZ), University of Auckland (NZ), Lake County (US), University of Waikato (NZ)
Openalex Percentile: Top 74%
Oceanographic and Atmospheric Processes
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Best practices for estimating turbulent dissipation from oceanic single-point velocity timeseries observations — Danielle Wain, Craig L. Stevens, et al. · (2025) | TGRS Research Map | TGRS