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ORIGINAL RESEARCH article

Front. Phys.
Sec. Interdisciplinary Physics
Volume 13 - 2025 | doi: 10.3389/fphy.2025.1536084

Multiscale Granger Dependencies in the Precipitation Network of Sicily Island

Provisionally accepted
Andrea Rapisarda Andrea Rapisarda 1*Vera Pecorino Vera Pecorino 1Alessandro Pluchino Alessandro Pluchino 1Kateřina Hlaváčková-Schindler Kateřina Hlaváčková-Schindler 2
  • 1 University of Catania, Catania, Italy
  • 2 University of Vienna, Vienna, Vienna, Austria

The final, formatted version of the article will be published soon.

    Sicily island has displayed unusual rainfall behavior and unexpected extreme precipitation events during the last decades. In this paper, we investigate the Granger causal (GC) dependencies in the precipitation measurement sites network of Sicily island at different timescales (every 10 minutes, 1 hour, 6 hours, 12 hours and 24 hours). We study, across seasons and years, different parameters characterizing the GC dependencies: nodes total in/out degree, nodes total in/out strength, network total number of links, number of eastward/westward links, strength of eastward/westward links and link's maximum strength. Then, we investigate the GC-statistics intensities, focusing on the temporal evolution of maximum values over multiple timescales. Our study of precipitation patterns in Sicily indicates that, since 2013, the southern regions near Mount Etna (Catania, Siracusa, Ragusa) have exerted increased influence, while western areas (Trapani, Palermo, Agrigento) have been the most affected. Granger causality networks reveal scale-invariant dependencies, with stronger and sparser connections as timescales that extend beyond 6 hours with a notable westward flow of predictive information. These patterns, consistent across seasons, suggest localized perturbation fronts, with stronger links indicating more significant influence on predictions westward. This study highlights shifts in Sicily's water cycle, calling for adaptive management strategies in light of increasing frequency of extreme events.

    Keywords: Precipitation data, Granger causality, networks, Multiscale time series, Climate Change

    Received: 28 Nov 2024; Accepted: 03 Jan 2025.

    Copyright: © 2025 Rapisarda, Pecorino, Pluchino and Hlaváčková-Schindler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Andrea Rapisarda, University of Catania, Catania, Italy

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.