the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Observations of the multi-year variability of mixing in shelf seas
Abstract. We present 5-year long continuous mixing observations from four mooring locations, spanning 10° degrees of latitude, on the continental shelf of North-Western Australia. The sites are subject to a diverse range of atmospheric and oceanic forcing and each has distinct local bathymetry. We estimated the diapycnal diffusivity and vertical turbulent heat flux at all sites and throughout the water column using a fine-scale mixing length model. There were four dominant peaks in the power spectrum: annual, spring-neap, diurnal, and semi-diurnal. We examined the variability in the mixing at all sites in terms of the seasonal stratification, depth, and tidal range and phase. The highest annual variability occurred at the highest latitude sites which had the greatest seasonal variation in stratification. The mixing also varied with the strength of the dominant tidal constituents (both baroclinic and barotropic). Heat flux was a more useful measure of mixing than diffusivity due to the strong seasonal variations in density stratification on the shelf. Finally, we provide guidance on the determination of the appropriate sampling period to adequately describe the mixing, and discuss the effects of short sampling periods on the ability to describe the long-term mixing.
Competing interests: Matt Rayson is on the editorial board for Ocean Science
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RC1: 'Comment on egusphere-2026-2498', Anonymous Referee #1, 29 May 2026
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2498/egusphere-2026-2498-RC1-supplement.pdfReplyCitation: https://doi.org/
10.5194/egusphere-2026-2498-RC1 -
RC2: 'Comment on egusphere-2026-2498', Anonymous Referee #2, 10 Jun 2026
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This paper uses an extensive dataset of relatively high frequency temperature and velocity measurements obtained from moorings at various locations on the Australian North West Shelf to estimate mixing variability on time scales from hours to years. Various key frequencies associated with particular oscillatory processes are highlighted and detailed statistics regarding the dependence of mixing on each process are presented. There is also some discussion on the sensitivity of calculated 'bulk' values to various choices of time-window averaging. An important theme throughout is that the results vary regionally. Overall, I found the results to be interesting and thought-provoking, and the data and its processing was impressive. A couple of thoughts, questions and reasonably minor critiques are given below.
1. Introduction: I don't fully understand question 2. The answer to the question as stated seems obviously 'yes', because these quantities measure different things and so will of course be quantitatively different. I would say only one of them is really interpretable as a mixing rate: the turbulent heat flux, being loosely proportional to (part of, considering also salinity) the turbulent buoyancy flux i.e. the rate of change of potential energy per unit mass. But that does not mean that diapycnal diffusivity is not useful. If the question is 'which one is more useful?' (as suggested in the abstract) then the authors must define precisely what is meant by 'useful' in this context.
2. Figure 2: Should the legend say fs >0.05Hz here rather than 0.5Hz for the blue line? Out of interest, what was the maximum thermistor frequency used? Were the computations of K_rho all made using signals with the same maximum frequency?
3. Some discussion on the limitations of the finescale method used, especially for turbulent fluctuation measurements that are close to (or possibly outside of?) the low limit of the expected turbulent frequency band, would be appreciated. I was under the impression that your previous 2024 paper had shown that using a 0.05Hz tended to underestimate the total temperature variance. Reference to the spectral method of Becherer & Moum (An Efficient Scheme for Onboard Reduction of Moored xpod Data, 2017 in JTech - see in particular their Fig. 10) might be appropriate and useful for justifying the choice of minimum required frequency.
4. Figure 7: Axis labels would be helpful. It would be very interesting to see the cumulative integral of the spectral density over frequency space. This would show you the relative contribution of each frequency to the total J_Q. It could be interesting to see if the results are comparable with the conclusions of section 3.5, which suggest (using a different approach) that 7 days is a reasonably safe averaging window.
5. Figure 8: Is there a need to repeat Figure 3 on the left here? I like the summer and winter color-coding, but those could be included in Fig. 3.
6. Section 3.5. I found the discussion in this section a little bit confusing. Are the medians of the time-windowed averages meaningful? I would have perhaps thought that, in general, the key thing is the average error you would make from the 'true' mean if you only took a limited number (1 as the most extreme example) of short time windows as a function of window length. In which case it would be helpful to plot this more continuously as a function of window length, rather than the distributions you have shown. Does the error decrease at a constant rate with window length, or does it start to plateau somewhere? This was not clear from using only 3 different windows. As noted above, there are close links to the suggestion in comment 4.
7. Line 345: 'As the vertical heat flux was less sensitive to the changes in background stratification, it is more useful for characterizing variation in the diapycnal mixing in shelf seas with their greatly varying seasonal stratification.' As above, 'useful' should probably be defined or discussed here.
8. Discussion: The conclusion that the best compromise for the choice of time window for evaluating mixing statistics depends on the site in question is very interesting. Do you have any thoughts on what would be required to estimate this time window without high frequency long-term measurements of mixing (e.g. for those designing new field experiments wanting to know how long to sample for)?
Citation: https://doi.org/10.5194/egusphere-2026-2498-RC2
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