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Biomixing in Monterey Bay: Aggregations, Turbulence, and Biomixing Background

Explore the dynamic interplay of aggregations, turbulence, and net dissipation in Monterey Bay. Discuss the impacts of biomixing on global primary production and the behavior of fish schools. Gain insights into the estimation of overturns and mixing efficiency in marine environments.

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Biomixing in Monterey Bay: Aggregations, Turbulence, and Biomixing Background

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  1. Biomixing in Monterey BayMichael Gregg & John Horne • Some Biomixing Background • Aggregations & turbulence • Turbulence particulars • Net dissipation & diffusivity • Discussion Indebted to Jack Miller, Dave Winkel, Steve Bayer, Glenn Carter, Andrew Cookson; Capt Eric Buck and his crew on RV Revelle

  2. Bulk Energetics Estimate ofDiapycnal Diffusivity, Kr, by Biomixing • Estimated that 1% of 62.7 TW global primary production produces mixing • Assuming G = 0.2 (mixing efficiency) • Distributing 1 TW of biomixing below euphotic zone in upper 3 km  Kr = 2 x 10-5 m2/s Dewar (2006)

  3. Fish School • Aggregation – fish concentration • Schools – aggregations with uniform spacing and behavior Strobe photo of anchovy school from free-fall camera (Graves, 1977)

  4. Work by Fish in Schools • Work by single swimmer: e = u D [W] • e = (e / rh) (Nf/ V) {h is efficiency} = (1.3 x 10-5 M1.39 / h) (Nf / V) [W / kg] • Fish density inversely related to body mass, Nf / V = 0.64 M-1.2 • e ≈ 10-5 [W / kg] regardless of mass, i.e., schools of whales and copepods produce the same average dissipation rates

  5. Krill in Saanich Inlet Kunze et al. (2006)

  6. Kunze et al. (2006) Continued • Kr increased from 2 x 10-6 to 4-40 x 10-4 m2/s, using G = 0.2 • Speculated on possible global significance • In response: • Rippeth et al. (2007) failed to find diurnal increase • Visser (2007) argued that organisms cannot produce overturns larger than themselves. Adapting Richardson’s 4/3 law obtained G = (LThorpe/Lozmidov)4/3 where G is the mixing efficiency

  7. AESOP – August 2006 • Surveying mixing in the • bay • Microstructure lines • repeated for 12.5 hours • RV Revelle

  8. Modular Microstructure Profiler (MMP)

  9. Log10(Dissipation Rate)

  10. Sv = 10log10(p2scattered/p2incident) • Sv - Volume • Backscattering • Strength

  11. MMP 15017 ReB = e / nN2

  12. MMP 15018 – After the aggregation

  13. MMP 15041

  14. MMP 15057

  15. MMP 17259

  16. Estimating overturns from Temperature Nearly linear TS Over 30-65 m

  17. Temperature from FP07 Thermistor

  18. Thorpe & Ozmidov Scales in Aggregation • Loz = (e/N2)1/3 • Lth from FP07 • Lth = 0.8 Loz • (Dillon, 1982)

  19. Thorpe & Ozmidov Scales outside Aggregation

  20. Thorpe vsOzmidov Scales

  21. Spectra of Dissipation-scale Shear MMP 15017 MMP 15018

  22. Spectra of Dissipation-scale Velocity MMP 15017 MMP 15018

  23. Dissipation-scale Temperature-Gradient Spectra MMP 15017 MMP 15018

  24. Thermal Diffusivity • Rate of thermal dissipation of temperature variability • Cox number • Thermal diffusivity: KT = C kT

  25. Mixing Efficiency, G • Assuming KT = C kT= Kr = Ge / N2 G = C kTN2 / e • Literature: 0.24 (Oakey, 1982), 0.18 (Gregg et al., 1986), 0.15-0.20 (Moum, 1996) • Osborn (1980) assumed 0.2 • G: 0.20, 0.33, 0.24, 0.0078, 0.0026, 0.0015, 0.0019, 0.20, 0.11, 0.0016, 0.0049, 0.02, 0.0012, 0.0014

  26. Averages for 12.5 hr Group with Most Aggregations

  27. Conclusions • Largest Aggregations: dz = 60 m, dx = 200 m, • e = 10-6 – 10-5 W/kg, 10 to 1000 times bkg • Overturns (Thorpe scale) << Ozmidov scale • Velocity & Shear spectra narrower than universal spectra • Mixing efficiency, G ≈ 1% of typical values • Negligible net effect of mixing in aggregations

  28. Discussion • Small # samples & probably only 1 species • Extended sections with e ≈ 10-5 consistent with Huntley & Zhou (2004) prediction & Kunze et al. (2006) observation of krill • Visser (2007) prediction of low efficiency prescient even if his rationale is less so. G = Lth2/Loz2 (Visser, 2006) may be upper bound as

  29. Cruising Fish Shed Vertical Vortices • Juvenile mullet, 0.12 m long, swimming in a tank • 2-dimensional particle velocimetry • Two vortex rings per tailbeat cycle with a jet between them • Maximum velocity, 91 mm/s in 2nd vortex from tail • Fish density, Nf/V = 100, would give e = 5.6 x 10-5 W / kg Muller et al. (1997), Videler et al. (2002)

  30. Discussion Continued • Small overturning scaleslikely result of turbulent production by nearly vertical tail vortices – 3d motions smaller than vortex dia. • Kunze’s finding may result from krill vertical motions rather than horizontal swimming Fini

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