Brandt, Peter

Dengler, Marcus

Fischer, Tim

OceanRep

T. Fischer, M. Dengler, P. BrandtDissipation rate prediction  from predictor-reducedfine-scale parameterizationsBMBF-Verbundvorhaben SOPRANRD 1   Ocean Circulation and Climate DynamicsDüsternbrooker Weg 20D-24105 Kielcontact: tfischer@geomar.de      www.geomar.deHenyey-Polzin-Gregg (HPG) finescale parameterization to estimate dissipation rateObservations reveal predictor dependence in HPG.That means, HPG should not be used if Eshear or Estrain is missing.Instead, particular predictor-reduced parameterizations have to be found.References                                                                    Gargett, A.E., Hendricks, P.J., Sanford, T.B., Osborn, T.R., and Williams, A.J. (1981): A composite spectrum of vertical shear in the                                                                     upper ocean, J. Phys. Oceanogr., 11, 1258-1271   -----     Henyey, F. S., Wright, J., and Flatté, S. M. (1986): Energy and action ow through the internal wave eld: an eikonal approach,  J. Geophys. Res., 91, C7, 8487-8495  -----   Polzin, K.L., Toole, J.M., and Schmitt, R.W. (1995): Finescale param-eterizations of turbulent dissipation, J. Phys. Oceanogr., 25, 306-328  -----   Gregg, M. C., Sanford, T. B., and Winkel, D. P. (2003): Reduced mixing from the breakingof internal waves in equatorial waters, Nature, 422, 513-515   ------    Fischer, T., Banyte, D., Brandt, P., Dengler, M., Krahmann, G., Tanhua, T., and Visbeck, M. (2013):Diapycnal oxygen supply to the tropical North Atlantic oxygen minimum zone, Biogeosciences, 10, 5079-5093Acknowledgements                                                                                                                        This study was supported by the German Federal Ministry of Education and Research through                                                                                                                        the joint project SOPRAN  (Surface Processes in the Anthropocene) under grant no. SOPRAN IIFKZ 03F0611A  and SOPRAN III  FKZ 03F0662A.  Large parts of data acquisition proted from participation in 3 cruises to the Tropical Atlantic that were partof the German Science Foundation‘s Sonderforschungsbereich 754   -   „Climate Biogeochemistry Interactions in the Tropical Ocean“.   We  acknowledge the support of the European Commission  (FP7  -  EuroSITES grant agreement No. 202955).  Dr. G. Krahmann‘s valuable operating of the ADCP on cruise Meteor 83/1, the assistance of numerous grad students in taking microstructure proles, and the friendly support of all crew members are highly appreciated. Observations in the eastern tropical At-lantic (150 to 500m) of Eshear from vmADCP, N2 and Estrain from CTD, dissi-pation rate from microstructure probe ...Issue:  In field work, often one of the key variables Eshear or Estrain is missing.            That means, no simultaneous knowledge of predictor F(Rω).... enhanced with according observati-onal data from Polzin et al. 1995 from HighResolutionProler (on the latter data HPG exponent tting is founded).Observational data show dependence of HPG predictors  Eshear and F(Rω).Measure spectral level of nescale vertical shearP1:   A particular parameterization without Estrain - and how it compares to HPGUsed predictors and ansatz for P195%-condence ellipse for the tted exponentsP1 and HPG are consistent despite dierent exponentsThis evokes some questions:- Why are P1 and HPG consistent despite different exponents? Predictor dependencies.- How certain are then the HPG exponents? The HPG data allow quite a range of equally well fits.- Could strain rate from CTD enhance P1 or allow a particular strain parameterization? We find Estrain too noisy for this.Consequences for the practical usage of HPG (seemingly paradox, but a consequence of predictor dependence):- Substitution of F(Rω) by an accurate average value causes bias and spurious patterns.- Instead calculating a simultaneous F(Rω) using a noisy Estrain (but complete predictor set) avoids this bias.Conclusions:  - For incomplete predictor sets (the typical case) particular predictor-reduced  parameterizations (PPP) are needed.- P1 is a  PPP without strain, consistent with HPG, particularly fit for ship cruises.100 1011Eshearε param / εmeasuredFWNGFieberling Guyot    (Polzin et al. 1995)Warm Core Eddy   (Polzin et al. 1995)NATRE Region       (Polzin et al. 1995)Guinea Dome Region (GDR, this study)If using HPG with incomplete obser-vational data (e.g. substituting F(Rω) by an estimated constant), systematic deviations in predicted epsilon arise.Eshear520.20.5Composite shear spectrum of internal waves (IW) and turbulence (Gargett et al. 1981)Idealized IW shear spectrum at dierent IW energy levelsIn nescale range accessible to instru-mentation, use white part of spectrum to evaluate shear spec-tral level in relation to Garrett-Munk 1976 IW model:HPG in terms of shear spectral level, strain spectral level, stratication, and latitudeafter Henyey et al. 1986, Polzin et al. 1995, Gregg et al. 2003log10 Ψ1log 10 Ψ2exponent of  Ψ1exponent of  Ψ20.50.51.52.521.510 0 1Polzin et al. 1995data from the deep ocean at very low N2, which were not part of the para-meter tting.P1HPGP1:HPG:dissipation rate of turbulent kinetic energyCoriolis parameterbuoyancy frequencyshear power spectral density (PSD)strain rate PSDPSD in relation to GM76 PSDshear-to-strain ratioFischer et al.       2013

Dissipation rate prediction from predictor-reduced fine-scale parameterizations

Abstract

Similar works

Full text

Available Versions

OceanRep