Logo: to the web site of Uppsala University

Atmospheric Rivers (ARs) are narrow, transient corridors of intense water vapour transport that play a central role in the global hydrological cycle. In the North Atlantic, ARs are frequently associated with extratropical cyclones and both are recognised as key drivers of extreme weather and climate-related hazards, such as heavy precipitation, strong winds, and flooding. This thesis presents a comprehensive investigation of the physical processes underlying the development of ARs and their predictability, with a particular focus on their role in shaping extreme weather under both current and future climate conditions.

To advance the physical understanding of ARs, a novel water vapour budget framework is introduced to trace moisture sources throughout the lifecycle of an AR associated with Storm Dennis. The results reveal a dynamic interplay between tropical moisture inflow and oceanic evaporation, both of which modulate the intensity of the AR, the associated cyclone, and precipitation at different stages of the event. Further analysis reveals that oceanic variability in the Gulf Stream region, associated with mesoscale eddies, surface fluxes, and ocean heat transport, has a significant influence on AR activity during winter and spring, resulting in a latitudinal shift in AR occurrence downstream.

The thesis also examines the role of ARs in driving high-impact weather events. Compound AR and explosive extratropical cyclone occurrences are shown to be common in the present climate and are projected to intensify under future warming scenarios, particularly under the highest emission scenario. These events pose increasing risks for Western Europe, with future ARs potentially exhibiting exceptional integrated vapour transport.

Finally, forecasting capabilities for ARs on meteorological timescales are evaluated by comparing emerging data-driven models with traditional physics-based weather prediction models. While data-driven approaches show promise in forecasting standard AR metrics, they struggle to capture extreme integrated vapour transport values or forecast ARs under geometrically restrictive detection methods, highlighting the need for targeted frameworks when assessing model skill for ARs.

Together, these findings underscore the importance of moisture sources, ocean-atmosphere interactions, and compound extremes in shaping AR behaviour, and provide actionable insights for improving forecasting and climate resilience in a warming world.