Giaquinto, Domenico (2024) Investigating climate compound events via complex climate networks. [Tesi di dottorato]

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Abstract

The Earth system is a complex ensemble of elements and processes occurring at various spatio-temporal scales. Climate science is indeed one of the most complex field of study: different chemical, biological and physical processes take place among several environmental compartments, each one characterized by their own variables and dynamics. Despite the giant steps made in this field, climate scientists are facing many open questions, which are becoming more and more pressing due to the rising impacts of climate change, such as the multi-scale and chaotic nature of the climate system, tipping elements dynamics and their interactions, the spatio-temporal dynamics and impacts of climate and weather extremes and compound events, the causal relationships between climate processes. In particular, we are facing the simultaneous increase of the frequency and the intensity of weather and climate extremes, which result in major impacts on ecosystems and society. The research presented in this dissertation falls within the field of climate science, utilizing an interdisciplinary approach that bridges the gap between complex systems science and atmospheric physics. This approach employs modern analytical techniques derived from complex networks science and applied to the study of extreme climate events. In particular, we develop a robust methodology to construct climate networks from data, minimizing uncertainties related to link attribution. We apply this methodology to uncover the spatio-temporal structures of hot and dry extremes synchronizations in Europe. Moreover, we identify and describe the causal relationships behind hot and dry compound events and characterize the atmospheric precursors responsible for the occurrence these events. In our first application, we investigate the spatial patterns and features of meteorological droughts in Europe using event synchronization analysis. We establish robust continental networks of meteorological droughts based on the co-occurrence of these events at different locations for the period 1981-2020 and compare the results for different accumulation periods of rainfall. Each continental network is then further examined to unveil regional clusters which are characterized in terms of droughts propagation. For our second application, we extend our methodology to build evolving spatially embedded climate networks of compound hot and dry synchronizations. Focusing on the summer and winter seasons of the period 1941-2020, we highlight hotspot regions in Europe where these spatially compound extremes are increasing and analyse the atmospheric precursors driving these anomalous conditions. This way, we bring out key aspects concerning the underlying spatio-temporal dynamics of concurrent hot and dry events. In the third application, we apply causal discovery to the study of hot and dry extremes in central Europe, by using causal effect networks. We show that hot extreme events in central Europe are driven primarily by anomalous atmospheric patterns and soil water deficiency, while dry extreme events are mainly induced by anomalous atmospheric patterns and soil moisture memory. We describe the historical trends of the found causal links in 1979-2020, and we find that the influence of dry soil on temperature has been amplified by 67% during compound hot and dry extremes, while the impact of atmospheric drivers on soil moisture has intensified by 50% during compound extremes. Climate complex networks help identifying non trivial spatio-temporal patterns of extreme events, getting new insights into the statistical relationships of the analysed phenomena. To the best of our knowledge, so far few works have addressed compound events by using climate networks and causal effect networks. The aim of our research is to fill this gap, improving our understanding of hot and dry extremes in Europe, revealing their synchronization, propagation mechanisms and causal structure.

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