Skip to main content
    • Aa
    • Aa
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 47
  • Cited by
    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Huang, G. Simoëns, S. Vinkovic, I. Le Ribault, C. Dupont, S. and Bergametti, G. 2016. Law-of-the-wall in a boundary-layer over regularly distributed roughness elements. Journal of Turbulence, Vol. 17, Issue. 5, p. 518.

    Liu, Yongqiang Mamtimin, Ali Huo, Wen Yang, Xinghua Liu, Xinchun Yang, Fan and He, Qing 2016. Nondimensional Wind and Temperature Profiles in the Atmospheric Surface Layer over the Hinterland of the Taklimakan Desert in China. Advances in Meteorology, Vol. 2016, p. 1.

    Tampieri, Francesco Viola, Angelo Pietro Mazzola, Mauro and Pelliccioni, Armando 2016. On turbulence characteristics at Ny-Ålesund–Svalbard. Rendiconti Lincei,

    Fortuniak, Krzysztof and Pawlak, Włodzimierz 2015. Selected Spectral Characteristics of Turbulence over an Urbanized Area in the Centre of Łódź, Poland. Boundary-Layer Meteorology, Vol. 154, Issue. 1, p. 137.

    Grachev, Andrey A. Andreas, Edgar L Fairall, Christopher W. Guest, Peter S. and Persson, P. Ola G. 2015. Similarity theory based on the Dougherty-Ozmidov length scale. Quarterly Journal of the Royal Meteorological Society, Vol. 141, Issue. 690, p. 1845.

    Pelliccioni, Armando Monti, Paolo and Leuzzi, Giovanni 2015. An alternative wind profile formulation for urban areas in neutral conditions. Environmental Fluid Mechanics, Vol. 15, Issue. 1, p. 135.

    Rahman, M.M. Taghinia, J. Islam, A.K.M. Sadrul Lampinen, M.J. and Siikonen, T. 2015. Modified Norris–Reynolds One–Equation Model. Procedia Engineering, Vol. 105, p. 276.

    Klewicki, J. Philip, J. Marusic, I. Chauhan, K. and Morrill-Winter, C. 2014. Self-similarity in the inertial region of wall turbulence. Physical Review E, Vol. 90, Issue. 6,

    Alfredsson, P.H. Imayama, S. Lingwood, R.J. Örlü, R. and Segalini, A. 2013. Turbulent boundary layers over flat plates and rotating disks—The legacy of von Kármán: A Stockholm perspective. European Journal of Mechanics - B/Fluids, Vol. 40, p. 17.

    Grachev, Andrey A. Andreas, Edgar L Fairall, Christopher W. Guest, Peter S. and Persson, P. Ola G. 2013. The Critical Richardson Number and Limits of Applicability of Local Similarity Theory in the Stable Boundary Layer. Boundary-Layer Meteorology, Vol. 147, Issue. 1, p. 51.

    Kanda, Manabu Inagaki, Atsushi Miyamoto, Takashi Gryschka, Micha and Raasch, Siegfried 2013. A New Aerodynamic Parametrization for Real Urban Surfaces. Boundary-Layer Meteorology, Vol. 148, Issue. 2, p. 357.

    Kramm, Gerhard Amaya, Dillon J. Foken, Thomas and Mölders, Nicole 2013. Hans A. Panofsky’s Integral Similarity Function—At Fifty. Atmospheric and Climate Sciences, Vol. 03, Issue. 04, p. 581.

    Segalini, Antonio Örlü, Ramis and Alfredsson, P. Henrik 2013. Uncertainty analysis of the von Kármán constant. Experiments in Fluids, Vol. 54, Issue. 2,

    Tyagi, Bhishma and Satyanarayana, A. N. V. 2013. Assessment of turbulent kinetic energy budget and boundary layer characteristics during pre-monsoon thunderstorm season over Ranchi. Asia-Pacific Journal of Atmospheric Sciences, Vol. 49, Issue. 5, p. 587.

    Wang, Linlin Gao, Zhiqiu Pan, Zaitao Guo, Xiaofeng and Bou-Zeid, Elie 2013. Evaluation of Turbulent Surface Flux Parameterizations over Tall Grass in a Beijing Suburb. Journal of Hydrometeorology, Vol. 14, Issue. 5, p. 1620.

    2013. Air Dispersion Modeling.

    Andreas, Edgar L 2012. Two Experiments on Using a Scintillometer to Infer the Surface Fluxes of Momentum and Sensible Heat. Journal of Applied Meteorology and Climatology, Vol. 51, Issue. 9, p. 1685.

    Claus, Jean Krogstad, P.-Å. and Castro, Ian P. 2012. Some Measurements of Surface Drag in Urban-Type Boundary Layers at Various Wind Angles. Boundary-Layer Meteorology, Vol. 145, Issue. 3, p. 407.

    Grachev, Andrey A. Andreas, Edgar L. Fairall, Christopher W. Guest, Peter S. and Persson, P. Ola G. 2012. Outlier Problem in Evaluating Similarity Functions in the Stable Atmospheric Boundary Layer. Boundary-Layer Meteorology, Vol. 144, Issue. 2, p. 137.

    Andreas, Edgar L. 2011. The Fallacy of Drifting Snow. Boundary-Layer Meteorology, Vol. 141, Issue. 3, p. 333.

  • Journal of Fluid Mechanics, Volume 559
  • July 2006, pp. 117-149

Evaluations of the von Kármán constant in the atmospheric surface layer

  • DOI:
  • Published online: 19 July 2006

The von Kármán constant $k$ relates the flow speed profile in a wall-bounded shear flow to the stress at the surface. Recent laboratory studies in aerodynamically smooth flow report $k$ values that cluster around 0.42–0.43 and around 0.37–0.39. Recent data from the atmospheric boundary layer, where the flow is usually aerodynamically rough, are similarly ambiguous: $k$ is often reported to be significantly smaller than the canonical value 0.40, and two recent data sets suggest that $k$ decreases with increasing roughness Reynolds number $Re_{\ast}$. To this discussion, we bring two large atmospheric data sets that suggest $k$ is constant, 0.387$\,{\pm}\,$0.003, for $2\, {\le}\,\hbox{\it Re}_\ast \,{\le} \,100$.

The data come from our yearlong deployment on Arctic sea ice during SHEBA, the experiment to study the Surface Heat Budget of the Arctic Ocean, and from over 800 h of observations over Antarctic sea ice on Ice Station Weddell (ISW). These were superb sites for atmospheric boundary-layer research; they were horizontally homogeneous, uncomplicated by topography, and unobstructed and uniform for hundreds of kilometres in all directions.

During SHEBA, we instrumented a 20 m tower at five levels between 2 and 18 m with identical sonic anemometer/thermometers and, with these, measured hourly averaged values of the wind speed $U(z)$ and the stress $\tau (z)$ at each tower level $z$. On ISW, we measured the wind-speed profile with propeller anemometers at four heights between 0.5 and 4 m and measured $\tau $ with a sonic anemometer/thermometer at one height. On invoking strict quality controls, we gleaned 453 hourly $U(z)$ profiles from the SHEBA set and 100 from the ISW set. All of these profiles reflect near-neutral stratification, and each exhibits a logarithmic layer that extends over all sampling heights. By combining these profiles and our measurements of $\tau $, we made 553 independent determinations of $k$. This is, thus, the largest, most comprehensive atmospheric data set ever used to evaluate the von Kármán constant.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Journal of Fluid Mechanics
  • ISSN: 0022-1120
  • EISSN: 1469-7645
  • URL: /core/journals/journal-of-fluid-mechanics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *