# Fisher-Shannon complexity analysis of high-frequency urban wind speed time series

## TL;DR

This study applies Fisher-Shannon analysis to high-frequency urban wind speed data at various heights, revealing height-dependent complexity and correlations with temperature variability, enhancing understanding of urban wind dynamics.

## Contribution

It introduces the use of Fisher-Shannon complexity analysis to examine how urban wind speed variability changes with height and its relation to ambient temperature.

## Key findings

- Fisher-Shannon complexity decreases with height.
- Complexity correlates with temperature variance, especially near ground.
- Wind variability is influenced by ambient temperature near the surface.

## Abstract

1Hz wind time series recorded at different levels (from 1.5 to 25.5 meters) in an urban area are investigated by using the Fisher-Shannon (FS) analysis. FS analysis is a well known method to get insight of the complex behavior of nonlinear systems, by quantifying the order/disorder properties of time series. Our findings reveal that the FS complexity, defined as the product between the Fisher Information Measure and the Shannon entropy power, decreases with the height of the anemometer from the ground, suggesting a height-dependent variability in the order/disorder features of the high frequency wind speed measured in urban layouts. Furthermore, the correlation between the FS complexity of wind speed and the daily variance of the ambient temperature shows similar decrease with the height of the wind sensor. Such correlation is larger for the lower anemometers, indicating that ambient temperature is an important forcing of the wind speed variability in the vicinity of the ground.