Atmospheric rivers (ARs) are long, narrow filamentary structures that involve intensive water vapor transport in the lower troposphere and are essential to the global hydrological cycle. They are often associated with extreme winter storms and heavy precipitation along the western coasts of mid-latitude continents and have the ability to produce major flooding events and/or relieve droughts. Understanding how ARs may vary from subseasonal-to-interannual time scale and change in a warmer climate is critical to advancing understanding and prediction of regional precipitation. 

Quantifying uncertainty in AR science, which may originate from detection methodology, reanalysis products, initial condition, and model error or spread, plays a crucial role in assessing confidence in process-level and impact-orientated AR analysis and predictions. Communicating risk and uncertainty to stakeholders from AR impacts is also necessary for adaptation and establishing resilience to high impact AR events that can result in flooding, landslides, and melting of sea ice, snow, and glaciers..  Continuing this session from past years, and in the context of these AR-related challenges, this session will focus on AR science, impacts, and uncertainty quantification across a range of scientific foci and time scales. We encourage submissions from topics such as AR development, driving mechanisms, dynamical and thermodynamical responses, case studies including but not limited to the 2022-2023 wet season on the United States west coast as well as climate change, linkage with multi-scale climate variability and S2S predictability, compound events, and impacts on different components of the Earth system. Uncertainty quantification is encouraged as a part of each topic.

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