Environmental Atmospheric Turbulence at Florence Airport

TL;DR

This study analyzes wind turbulence at Florence Airport using long-term measurements, revealing non-Gaussian statistics and applying superstatistics to model wind velocity fluctuations accurately.

Contribution

It applies superstatistics and Gamma distribution fitting to wind turbulence data, providing a novel approach to characterize atmospheric turbulence.

Findings

Wind velocity fluctuations exhibit non-Gaussian fat tails.

Gamma distribution effectively models the fluctuations.

Superstatistics with Tsallis q-exponential fits the data well.

Abstract

We present an analysis of a time series of a wind strength measurements recorded at Florence airport in the period October 2002 - March 2003. The data were taken simultaneously by two runway head anemometers, located at a distance of 900 m, at a frequency of 3.3 10-3 Hz. The data show strong correlations over long time spans over a few tens of hours. We performed an analysis of wind velocity as it is usually done for turbulence laboratory experiments. Wind velocity returns and wind velocity differences were considered. The pdfs of these quantities exhibit strong non-Gaussian fat tails. The distribution of the standand deviations of the fluctuations can be successfully reproduced by a Gamma distribution, while the Log-normal one fails completely. Following Beck and Cohen superstatistics approach, we extract the Tsallis entropic index q from this Gamma distribution. The corresponding q-exponential curves reproduce with a very good accuracy the pdfs of returns and velocity differences.