Monofractal nature of air temperature signals reveals their climate variability

TL;DR

This study demonstrates that European surface air temperature signals are monofractal and that their H"older exponents are linked to climate variability, offering richer insights than previous correlation-based methods.

Contribution

It introduces a wavelet-based approach to connect monofractal properties of temperature signals with climate variability, surpassing previous correlation methods.

Findings

Temperature signals are monofractal across European stations.

H"older exponents correlate with climate variability.

Previous methods did not establish this link.

Abstract

We use the discrete "wavelet transform microscope" to show that the surface air temperature signals of weather stations selected in Europe are monofractal. This study reveals that the information obtained in this way are richer than previous works studying long range correlations in meteorological stations. The approach presented here allows to bind the H\"older exponents with the climate variability. We also establish that such a link does not exist with methods previously carried out.