Tsallis q-Statistics Fingerprints in Precipitation Data across Sicily

Area of Science:

• Environmental Science
• Hydrology
• Statistical Physics

Background:

• Precipitation patterns are crucial for regional hydrology, agriculture, and climate change assessment.
• Sicily's diverse geography makes it an ideal location for precipitation analysis.
• Understanding rainfall dynamics is key to managing water resources and predicting climate impacts.

Purpose of the Study:

• To analyze sub-hourly precipitation data from Sicily spanning two decades (2002-2023).
• To investigate rainfall event characteristics like duration, depth, and inter-event time.
• To apply advanced statistical physics methods, specifically Tsallis q-statistics, to precipitation data.

Main Methods:

• Utilized sub-hourly precipitation data from the Sicilian Agrometeorological Informative System (SIAS).
• Employed Tsallis q-statistics to analyze rainfall event variables and their temporal changes.
• Fitted simple returns of variables with q-Gaussian distributions to identify statistical properties.

Main Results:

• Identified scale-invariant properties in precipitation events.
• Detected evidence of long-range interactions and memory effects in rainfall data.
• Observed significant temporal changes in precipitation variables over two decades.

Conclusions:

• Precipitation in Sicily exhibits characteristics of complex environmental systems.
• Tsallis q-statistics effectively reveals underlying statistical properties of rainfall.
• The findings contribute to a deeper understanding of Mediterranean precipitation dynamics and climate variability.