Abstract
Non-stationarity is a common feature in geophysical flows, though it still remains an open question on how the non-stationarity of flow affects its statistical structure. Using the telegraph approximation (TA) method, we quantified how non-stationarity in the measured atmospheric turbulent vertical velocity time series affects its clustering properties—one of the two main components of intermittency in turbulence. We compare different TA results between stationary and non-stationary atmospheric turbulent vertical velocity records, and find that the non-stationary data possess different cluster and intermittency exponents from stationary data. The inter-pulse period of the non-stationary records takes a near power-law distribution while the inter-pulse period of the stationary records exhibits a stretched exponential distribution. These results suggest that non-stationarity of the underlying processes can affect the statistical structure of turbulence, especially the clustering properties.
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