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Comparison of Different Techniques to Calculate Properties of Atmospheric Turbulence from Low-Resolution Data

1
Institute of Geophysics, Faculty of Physics, University of Warsaw, Pasteura 5, 02-093 Warsaw, Poland
2
African Institute for Mathematical Sciences, Summerhill Estates, East Legon Hills, Santoe, GA184, Accra, Ghana
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(2), 199; https://doi.org/10.3390/atmos11020199
Received: 14 January 2020 / Revised: 31 January 2020 / Accepted: 7 February 2020 / Published: 13 February 2020
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
In this work we study different techniques to estimate basic properties of turbulence, that is its characteristic velocity and length scale from low-resolution data. The methods are based on statistics of the signals like the velocity spectra, second-order structure function, number of signal’s zero-crossings and the variance of velocity derivative. First, in depth analysis of estimates from artificial velocity time series is performed. Errors due to finite averaging window, finite cut-off frequencies and different fitting ranges are discussed. Next, real atmospheric measurement data are studied. It is demonstrated that differences between results of the methods can indicate deviations from the Kolmogorov’s theory or the presence of external intermittency, that is the existence of alternating laminar/turbulent flow patches.
Keywords: turbulence; clouds; intermittency; turbulence kinetic energy; turbulence kinetic energy dissipation rate turbulence; clouds; intermittency; turbulence kinetic energy; turbulence kinetic energy dissipation rate
MDPI and ACS Style

Wacławczyk, M.; Gozingan, A.S.; Nzotungishaka, J.; Mohammadi, M.; Malinowski, S.P. Comparison of Different Techniques to Calculate Properties of Atmospheric Turbulence from Low-Resolution Data. Atmosphere 2020, 11, 199.

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