Intermittency in Estuarine Turbulence: A Framework toward Limiting Bias in Microstructure Measurements

Author:

Huguenard Kimberly1,Bears Kris1,Lieberthal Brandon2

Affiliation:

1. Department of Civil and Environmental Engineering, University of Maine, Orono, Maine

2. School of Biology and Ecology, University of Maine, Orono, Maine

Abstract

AbstractIntermittent turbulence behavior has a number of implications for field sampling, namely, that if undersampled, it can result in over- or underestimates of turbulent kinetic energy (TKE) dissipation rates. Sampling thresholds and common distributions have previously been defined for oceanic environments, but estuaries remain relatively underrepresented. Utilizing vertical microstructure profilers is a robust way to directly measure TKE dissipation rates; however, microstructure sensors are delicate and conducting a limited number of profiles in a burst is desirable. In this work, a statistical framework is used to characterize intermittency in a partially mixed estuary. In particular, a multiple comparison test is proposed to evaluate the number of profiles required to sufficiently represent TKE dissipation averages. The technique is tested on a microstructure dataset from the Damariscotta River in Maine, which covers seasonal and fortnightly time scales. The Damariscotta River features a variety of bathymetric and channel complexities, which provide the opportunity to examine intermittency as it relates to different processes. Small-scale intermittency is prominent during stratified conditions in shallow locations as well as near channel-shoal morphology, channel bends, and constrictions.

Funder

National Science Foundation

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

Reference33 articles.

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2. The nature of turbulent motion at large wave-numbers;Batchelor;Proc. Roy. Soc. London,1949

3. Bears, K. , 2018: The dynamics of mixing and subtidal flow in a Maine estuary. M.S. thesis, Dept. of Civil Engineering, University of Maine, 74 pp., https://digitalcommons.library.umaine.edu/etd/2877/.

4. Observational and numerical modeling methods for quantifying coastal ocean turbulence and mixing;Burchard;Prog. Oceanogr.,2008

5. Chandler, E. A. , 2016: Sediment accumulations patterns in the Damariscotta River estuary. M.S. thesis, Dept. of Earth Sciences, University of Maine, 93 pp., https://digitalcommons.library.umaine.edu/etd/2470/.

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