| Summary: | In recent decades, the Arctic has experienced remarkable changes, including enhanced poleward heat and moisture transport. Atmospheric rivers (ARs), defined as long and narrow corridors with high moisture content, are renowned for their significant moisture transport, with implications on temperature and precipitation. Along with the faster warming, precipitation phase (snow vs. rain) plays a major role in the Arctic, as rainfall contributes to sea-ice decline, thereby triggering the ice-albedo feedback. Since previous studies indicate increasing moisture transport towards the Polar Regions, it is crucial to understand the changes in ARs reaching the Arctic in present and future climates and their impacts in a warmer climate. This thesis started by adapting an algorithm used for AR identification, applied to specific case studies. Building on this knowledge, the study was extended to cover the last 43 years, including further improvement of the algorithm, evaluation of the data used, assessment of changes in the AR characteristics, and the analysis of their impacts, with a specific emphasis on precipitation, its phase, and temperature. The final step involved studying ARs in a future climate under various scenarios. After evaluating the available models, the algorithm was applied, followed by the study of AR changes and their impacts in a future climate. This thesis relied on observational and reanalysis datasets, and model simulations. The detailed analysis of the case studies focused on the synoptic-scale evolution, thermodynamic, and precipitation properties during three intense AR events reaching Svalbard in May-June 2017 during the ACLOUD/PASCAL campaign. The results underscore the importance of using data with adequate temporal and spatial resolution and the relevance of employing different AR detection algorithms. After, this study was extended from 1980 to 2022 and the results show a poleward shift of AR frequency and their intensification in the North Atlantic pathway. ARs are responsible for over 20% ...
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