A Digression on the Analysis of Historical Series of Daily Data for the Characterization of Precipitation Dynamics

Abstract

Precipitation, together with temperature, is the most important variable in defining the climate of a region. Then, the right understanding of rainfall variability, which occurs over a wide range of temporal scales, has relevance for a large variety of problems linked to meteorology and climate, both in theoretical and practical frameworks. The double aspect, continuous and point process, of rainfall sequences manifests itself depending on the scale of aggregation of the rainfall events and on the intensity thresholds associated to storminess risk. This requires the use of different characteristic variables, different reference models as well as different analysis techniques for obtaining a comprehensive characterization of the observational time series and assessing risk. This Chapter provides a quick overview of the many aspects of the reconstruction of the time scale properties based on the investigation of historical data. Storminess observed for several decades at two Italian sites (Genoa and Palermo), which exhibit different climatic features, were analysed both with tools typical of point processes and more standard analysis techniques to provide a coherent picture of the basic properties of rainfalls that can be extracted from daily data about weather, seasonal, and climatic scales. Both analogous and complementary cycles appear when we approach the problem from the two different perspectives separately; additional behaviours are detected when we integrate them. This comprehensive picture of historical data represents the background for understanding precipitation regimes and identifying possible climatic changes or human pressure effects that could increase storminess risk.