10B.4 Timescales in the nocturnal, wintertime boundary layer over heterogeneous surface

Wednesday, 11 June 2014: 11:15 AM
John Charles Suite (Queens Hotel)
Karmen Babić, University of Zagreb, Zagreb, Croatia; and Ž. Večenaj and Z. Bencetić Klaić

In this work we investigate physically relevant timescales associated with the nocturnal, wintertime boundary layer. Cold nights with weak winds favor development of very stable boundary layer (SBL), in which a disconnection between the surface and the upper portion of the boundary layer can occur. Besides, temporal variability of turbulence in the very SBL is characterized by nonstationarity and intermittency, which both can affect computed turbulence fluxes at scales larger than the turbulence scale. Moreover, turbulence fluxes within the SBL are small and can easily be affected by the sub- and mesoscale fluxes. In such case, it is hard to distinguish the turbulence from nonturbulent motions in Fourier spectra and cospectra. To decompose instantaneous signal into mean and turbulent parts, we apply four different methods. Two of them are based on Fourier spectral analysis and two on wavelet analysis. Analyses are performed on high frequency wind and temperature datasets collected at 7 different levels within a ground-based 62 m deep layer. The measurement tower is located in the heterogeneous surroundings, which can significantly influence the turbulence characteristics of the SBL. Depending on the wind direction, measured data can capture rural, suburban or urban signatures. The mesoscale spectral energy gap in the SBL is often not found since there is no clear separation between the scales. In such case, the timescales are calculated based on the location of the maximum in the ogive of the sensible heat flux cospectra or, based on the location of a zero crossing in the multiresolution decomposition of the sensible heat flux. In addition, a wavelet analysis is applied to time series in order to yield the information about the temporal locations of different features characterized by different frequencies. All of this gives us some insights into the timescales (i.e., different physical processes) that influence turbulence characteristics associated with different land-use setups and for a range of stability conditions (from weak to strong stability) at our measurement site.
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