Estimating the population mean for a vertical profile of energy dissipation rate

Abstract Energy dissipation rates are an important characteristic of turbulence; however, their magnitude in observational profiles can be incorrectly determined owing to their irregular appearance during vertical evolution. By analysing the data obtained from oceanic turbulence measurements, we dem...

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Main Authors:	Nozomi Sugiura, Shinya Kouketsu, Shuhei Masuda, Satoshi Osafune, Ichiro Yasuda
Format:	article
Language:	EN
Published:	Nature Portfolio 2020
Subjects:	Medicine R Science Q
Online Access:	https://doaj.org/article/9371ccbeddb041df99a10dbf8bb6a2d9
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spelling	oai:doaj.org-article:9371ccbeddb041df99a10dbf8bb6a2d92021-12-02T12:33:36ZEstimating the population mean for a vertical profile of energy dissipation rate10.1038/s41598-020-77414-22045-2322https://doaj.org/article/9371ccbeddb041df99a10dbf8bb6a2d92020-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-77414-2https://doaj.org/toc/2045-2322Abstract Energy dissipation rates are an important characteristic of turbulence; however, their magnitude in observational profiles can be incorrectly determined owing to their irregular appearance during vertical evolution. By analysing the data obtained from oceanic turbulence measurements, we demonstrate that the vertical sequences of energy dissipation rates exhibit a scaling property. Utilising this property, we propose a method to estimate the population mean for a profile. For scaling in the observed profiles, we demonstrate that our data exhibit a statistical property consistent with that exhibited by the universal multifractal model. Meanwhile, the population mean and its uncertainty can be estimated by inverting the probability distribution obtained by Monte Carlo simulations of a cascade model; to this end, observational constraints from several moments are imposed over each vertical sequence. This approach enables us to determine, to some extent, whether a profile shows an occasionally large mean or whether the population mean itself is large. Thus, it will contribute to the refinement of the regional estimation of the ocean energy budget, where only a small amount of turbulence observation data is available.Nozomi SugiuraShinya KouketsuShuhei MasudaSatoshi OsafuneIchiro YasudaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nozomi Sugiura Shinya Kouketsu Shuhei Masuda Satoshi Osafune Ichiro Yasuda Estimating the population mean for a vertical profile of energy dissipation rate
description	Abstract Energy dissipation rates are an important characteristic of turbulence; however, their magnitude in observational profiles can be incorrectly determined owing to their irregular appearance during vertical evolution. By analysing the data obtained from oceanic turbulence measurements, we demonstrate that the vertical sequences of energy dissipation rates exhibit a scaling property. Utilising this property, we propose a method to estimate the population mean for a profile. For scaling in the observed profiles, we demonstrate that our data exhibit a statistical property consistent with that exhibited by the universal multifractal model. Meanwhile, the population mean and its uncertainty can be estimated by inverting the probability distribution obtained by Monte Carlo simulations of a cascade model; to this end, observational constraints from several moments are imposed over each vertical sequence. This approach enables us to determine, to some extent, whether a profile shows an occasionally large mean or whether the population mean itself is large. Thus, it will contribute to the refinement of the regional estimation of the ocean energy budget, where only a small amount of turbulence observation data is available.
format	article
author	Nozomi Sugiura Shinya Kouketsu Shuhei Masuda Satoshi Osafune Ichiro Yasuda
author_facet	Nozomi Sugiura Shinya Kouketsu Shuhei Masuda Satoshi Osafune Ichiro Yasuda
author_sort	Nozomi Sugiura
title	Estimating the population mean for a vertical profile of energy dissipation rate
title_short	Estimating the population mean for a vertical profile of energy dissipation rate
title_full	Estimating the population mean for a vertical profile of energy dissipation rate
title_fullStr	Estimating the population mean for a vertical profile of energy dissipation rate
title_full_unstemmed	Estimating the population mean for a vertical profile of energy dissipation rate
title_sort	estimating the population mean for a vertical profile of energy dissipation rate
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/9371ccbeddb041df99a10dbf8bb6a2d9
work_keys_str_mv	AT nozomisugiura estimatingthepopulationmeanforaverticalprofileofenergydissipationrate AT shinyakouketsu estimatingthepopulationmeanforaverticalprofileofenergydissipationrate AT shuheimasuda estimatingthepopulationmeanforaverticalprofileofenergydissipationrate AT satoshiosafune estimatingthepopulationmeanforaverticalprofileofenergydissipationrate AT ichiroyasuda estimatingthepopulationmeanforaverticalprofileofenergydissipationrate
_version_	1718393872764108800

Estimating the population mean for a vertical profile of energy dissipation rate

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