INTER-COMPARISON AND VALIDATION OF GLOBAL AND REGIONAL REANALYSES PRODUCTS FOR THE STUDY OF EXTREME WEATHER EVENTS OVER ITALY

The increasingly severe impacts of extreme weather events, driven by climate change, are pushing an urgent need for reliable tools to understand, monitor, and predict the evolution of atmospheric phenomena. Meteorological reanalyses, blending observations with dynamical models, respond to this need by providing gridded datasets that reconstruct past atmospheric conditions at high temporal resolution, typically hourly, over several decades. These products are essential for planning mitigation strategies against climate change and extreme events in key sectors such as renewable energy development, electric system resilience, water resource management, urban planning, and many others. However, given the wide range of reanalysis datasets developed for Italy in recent years, inter-comparison and validation against observations are crucial to support their informed use and to maximize their potential applications, both in scientific and applied research. During the first part of my PhD, I focused on the validation and the intercomparison of reanalyses 2-meter air temperature (t2m), with particular attention to daily mean values. An accurate representation of t2m is essential, as it is a variable directly relevant to evaluating the effects of warming weather conditions. Moreover, t2m is a fundamental driver of atmospheric dynamics, with a significant influence on other variables. I inter-compared and validated against observations multiple reanalyses available over Italy during the 1991–2020 period, evaluating performances of both climatological averages and daily anomalies (Paper I). In particular, I developed a new validation method which accounts for the biases arising from different representations of orography between reanalysis and observations. In this way, dynamical ability of reanalyses is evaluated separately from their static orographic description. My research subsequently concentrated on the assessment of total precipitation (tp) variable, which presents significant challenges in a correct model representation because of its intermittent nature and high spatial variability. I assessed the ability of reanalyses to reproduce precipitation at different spatial and temporal scales, and I validated them against both station-based and gridded observational datasets (Paper II). A multi-scale approach, ranging from climatological to daily values, was adopted, including the use of wavelet analysis to investigate the role of the finer spatial scales and the potential of convection-permitting reanalyses in describing convective precipitation. In parallel, I contributed to a study on long-term precipitation trends derived from global reanalyses over Italy and the Alpine region (Paper III). In this work, I assessed the temporal stability of reanalyses against homogenized observations. The results of these studies were disseminated across multiple scientific communities, with a major interest among reanalysis developers and users. I therefore actively contributed to the evaluation of new reanalysis products, both collaborating with research institutions already involved in this PhD project (MERIDA HRES, Paper IV) and with external partners (MORE, Paper VI, under review), specifically supporting the validation and intercomparison sections of their publications. In addition, I extended the outreach of my PhD studies to a broader audience through the publication of a science communication article in the Rivista di Meteorologia Aeronautica. Since this contribute was originally in Italian language, an English version is provided in this thesis (Paper V). The final phase of my PhD focused on precipitation extremes over Italy. Building on the awareness of reanalysis strengths and limitations acquired in the previous studies, I develop a method to identify precipitation events from hourly reanalysis fields. Finer temporal scales posed additional methodological and interpretative challenges. Understanding such extremes is particularly important given their significant socio-economic impacts, especially in the context of risk management and climate change adaptation strategies. The study revealed increases in the occurrence of hourly extreme precipitation events during the summer and autumn seasons in some Italian regions. The results are currently under review (Paper VII).