Preprints
https://doi.org/10.5194/npg-2018-48
https://doi.org/10.5194/npg-2018-48
10 Dec 2018
 | 10 Dec 2018
Status: this preprint has been withdrawn by the authors.

Estimating vertically averaged energy dissipation rate

Nozomi Sugiura, Shinya Kouketsu, Shuhei Masuda, Satoshi Osafune, and Ichiro Yasuda

Abstract. The energy dissipation rate is an important characteristic of turbulence; however, its magnitude in observational profiles can be misidentified owing to its erratic evolution. By analysing observed data from oceanic turbulence, we show that the vertical sequences of depth-averaged energy dissipation rates have a scaling property, and propose a method to suitably estimate the vertically averaged value by utilizing that property. For scaling in the observed profiles, we found that averaging neighbouring points increases the expected value of its logarithm proportionally to the logarithm of the averaging interval. Furthermore, the population mean can be estimated for the logarithm of the vertically averaged energy dissipation rate from a single observation profile, by scaling up and promoting the observed value at each depth to one that corresponds to the whole profile. The estimate allows to distinguish whether an observational profile exhibits a momentarily high value by intermittency or maintains high energy dissipation on average.

This preprint has been withdrawn.

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Nozomi Sugiura, Shinya Kouketsu, Shuhei Masuda, Satoshi Osafune, and Ichiro Yasuda

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Nozomi Sugiura, Shinya Kouketsu, Shuhei Masuda, Satoshi Osafune, and Ichiro Yasuda
Nozomi Sugiura, Shinya Kouketsu, Shuhei Masuda, Satoshi Osafune, and Ichiro Yasuda

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Short summary
The observed profiles of the turbulent energy dissipation rate look so erratic that we can hardly identify them as continuous curves. However, we found that each sequence has the striking feature of self-similarity. Using this, we can efficiently take ensemble statistics of the vertically averaged energy dissipation rate from a single observation profile, by scaling up and promoting the observed value at each depth to one that corresponds to the whole profile.