Event-based analysis of extreme precipitation trends in Italy using hourly convection-permitting reanalyses

The latest generation of high-resolution and convection-permitting reanalyses, which allows the representation of the atmospheric processes at small spatial scales (<=4 km), are crucial to understand the evolution in time and space of phenomena such as mesoscale systems, convective storms, and orographic precipitation. Given the availability of long (>35 years) and continuum datasets of convection-permitting reanalysis data over Italy, this work aims to use them to investigate the occurrence of extreme events and to quantify their possible intensification over time in this area. Previous studies have compared those convection-permitting reanalyses and validated against observations their precipitation fields from the climatological to the daily scale, demonstrating that they can capture fine-scale precipitation events, though spatial mismatches with observations sometimes occur. When transitioning to sub-daily precipitation fields, new challenges arise: the scarcity and inhomogeneities in observations increase, impacting the quality of the assimilation in the reanalyses; moreover, the representation of the small-scale physical processes increase in complexity, giving even more space to uncertainties in the results. This work tackles these issues by employing an event-based approach when analysing sub-daily precipitations, focusing on the Italian domain, where extreme events cause every year many damages to the population and infrastructures. Using the MERIDA HRES and MOLOCH convection-permitting reanalyses over Italy (1986–2022), precipitation events are identified from hourly fields by applying a 1 mm threshold and a clustering technique. This resulted in a dataset of approximately 250.000 events, each of them characterized by its extent, timing, peak values, average intensity, and shape. The resulting event-based dataset was used to calculate climatological averages and trends over time of these characteristics, both at the annual and seasonal aggregation. Subsequently, from the whole dataset, filtering criteria were applied to subset the most extreme events. Since there is no single criterion to define what constitutes an extreme event, multiple filtering criteria were applied to capture different types of extremes. Preliminary results, based on thresholds using the average of the annual maxima of hourly values, reveal a significant increase in extreme precipitation events in the pre-Alpine region and Western Alps during summer. In autumn, an increasing trend emerges along the southern and insular Italian coastlines. This pattern aligns with regions and seasons where convective phenomena drive intense precipitation at small spatial scales. Further analyses will consider different filtering criteria, to also capture events that are anomalous for a given time of the year and synoptic events that typically occur in winter and spring. The results of this work will not only shed light on the changing sub-hourly precipitation patterns over Italy but also provide guidance to reanalysis users and stakeholders in planning resilient infrastructure to prevent damage from extreme precipitation events.