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Persistence is defined as the probability that the local value of afluctuating field remains at a particular state for a certain amount of time,before being switched to another state. The concept of persistence has beenfound to have many diverse practical applications, ranging from non-equilibriumstatistical mechanics to financial dynamics to distribution of time scales inturbulent flows and many more. In this study, we carry out a detailed analysisof the statistical characteristics of the persistence probability densityfunctions (PDFs) of velocity and temperature fluctuations in the surface layerof a convective boundary layer, using a field-experimental dataset. Our resultsdemonstrate that for the time scales smaller than the integral scales, thepersistence PDFs of turbulent velocity and temperature fluctuations display aclear power-law behaviour, associated with self-similar eddy cascadingmechanism. Moreover, we also show that the effects of non-Gaussian temperaturefluctuations act only at those scales which are larger than the integralscales, where the persistence PDFs deviate from the power-law and dropexponentially. Furthermore, the mean time scales of the negative temperaturefluctuation events persisting longer than the integral scales are found to beapproximately equal to twice the integral scale in highly convectiveconditions. However, with stability this mean time scale gradually decreases toalmost being equal to the integral scale in the near neutral conditions.Contrarily, for the long positive temperature fluctuation events, the mean timescales remain roughly equal to the integral scales, irrespective of stability.

Persistence analysis of velocity and temperature fluctuations in convective surface layer turbulence