A Surface-Layer Study of the Transport and Dissipation of Turbulent Kinetic Energy and the Variances of Temperature, Humidity and CO\(_2\)
We discuss scalar similarities and dissimilarities based on analysis of the dissipation terms in the variance budget equations, considering the turbulent kinetic energy and the variances of temperature, specific humidity and specific CO\(_2\) content. For this purpose, 124 high-frequency sampled segments are selected from the Boundary Layer Late Afternoon and Sunset Turbulence experiment. The consequences of dissipation similarity in the variance transport are also discussed and quantified. The results show that, for the convective atmospheric surface layer, the non-dimensional dissipation terms can be expressed in the framework of Monin–Obukhov similarity theory and are independent of whether the variable is temperature or moisture. The scalar similarity in the dissipation term implies that the characteristic scales of the atmospheric surface layer can be estimated from the respective rate of variance dissipation, the characteristic scale of temperature, and the dissipation rate of temperature variance.
KeywordsAtmospheric surface layer Scalar similarity Turbulent dissipation Turbulent transport Variance budget equation
The authors thank the technicians at IAG-USP and at GFI-UiB and several colleagues for assistance, and particularly for the valuable comments and support of Luciano P. Pezzi, Leonardo Domingues, Pamela Dominutti, Line Baserud and Valerie Kumer. The helpful comments of two anonymous reviewers are greatly appreciated. This work was conducted through a scholarship by the International Cooperation Program CAPES/COFECUB at the University of Bergen, financed by CAPES Brazilian Federal Agency for Support and Evaluation of Graduate Education within the Ministry of Education of Brazil. The BLLAST field experiment was made possible thanks to the contribution of several institutions and funding sources: INSU-CNRS (Institut National des Sciences de l’Univers, Centre national de la Recherche Scientifique, LEFE-IDAO program), Météo-France, Observatoire Midi-Pyrénées (University of Toulouse), EUFAR (EUropean Facility for Airborne Research) and COST ES0802 (European Cooperation in Science and Technology). The field experiment would not have occurred without the contribution of all participating European and American research groups, which all have contributed significantly. The BLLAST field experiment was hosted by the instrumented site of Centre de Recherches Atmospheriques, Lannemezan, France (Observatoire Midi-Pyrénées, Laboratoire d’Aérologie). The BLLAST data are managed by SEDOO, from the Observatoire Midi-Pyrénées. The participation of the Meteorology Group of the Geophysical Institute, University of Bergen was facilitated by contributions of the Geophysical Institute and the Faculty of Mathematics and Natural Sciences under the “smådriftsmidler” scheme, a travel stipend by the Meltzer Foundation in Bergen, and the Short Term Scientific Mission (STSM) scheme within the COST Action ES0802 “Unmanned Aerial Vehicles in Atmospheric Research”.
- Bloomfield P (2000) Fourier analysis of time series, 2nd edn. Wiley, Raleigh, 254 ppGoogle Scholar
- Dupuis H, Taylor PK, Weill A, Katsaros K (1997) Inertial dissipation method applied to derive turbulent fluxes over the ocean during the Surface of the Ocean, Fluxes and Interactions with the Atmosphere/Atlantic Stratocumulus Transition Experiment (SOFIA/ASTEX) and Structure des Echanges Mer-Atmosphere. J Geophys Res 102(C9):21115CrossRefGoogle Scholar
- Fairall CW, Larsen SE (1986) Inertial-dissipation methods and turbulent fluxes at the air-ocean interface. Boundary-Layer Meteorol 34(3):287–301. doi:10.1007/BF00122383
- Hartogensis OK, Bruin HARD (2005) Monin–Obukhov similarity functions of the structure parameter of temperature and turbulent kinetic energy dissipation rate in the stable boundary layer. Boundary-Layer Meteorol 116(2):253–276. doi:10.1007/s10546-004-2817-1
- Kolmogorov AN (1941) Dissipation of energy in locally isotropic turbulence. Dokl Akad Nauk SSSR 32(1):16–18Google Scholar
- Lee X, Finnigan J, Paw UKT (2005) Coordinate systems and flux bias error. Springer, Dordrecht, pp 33–66Google Scholar
- Lothon M, Lohou F, Pino D, Couvreux F, Pardyjak ER, Reuder J, de Vilà-Guerau Arellano J, Durand P, Hartogensis O, Legain D, Augustin P, Gioli B, Faloona I, Yagüe C, Alexander DC, Angevine WM, Bargain E, Barrié J, Bazile E, Bezombes Y, Blay-Carreras E, van de Boer A, Boichard JL, Bourdon A, Butet A, Campistron B, de Coster O, Cuxart J, Dabas A, Darbieu C, Deboudt K, Delbarre H, Derrien S, Flament P, Fourmentin M, Garai A, Gibert F, Graf A, Groebner J, Guichard F, Jimenez Cortes Ma, Jonassen M, van den Kroonenberg A, Lenschow DH, Magliulo V, Martin S, Martinez D, Mastrorillo L, Moene aF, Molinos F, Moulin E, Pietersen HP, Piguet B, Pique E, Román-Cascón C, Rufin-Soler C, Saïd F, Sastre-Marugán M, Seity Y, Steeneveld GJ, Toscano P, Traullé O, Tzanos D, Wacker S, Wildmann N, Zaldei A (2014) The BLLAST field experiment: boundary-layer late afternoon and sunset turbulence. Atmos Chem Phys 14(7):10,789–10,852CrossRefGoogle Scholar
- Stull RB (1988) An introduction to boundary layer meteorology. Springer, Dordrecht, 666 ppGoogle Scholar