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Atmospheric rivers (ARs) are mechanisms of strong moisture transport capable of bringing heavy precipitation to the West Coast of North America, which drives water resources and can lead to large-scale flooding. Understanding links between climate variability and landfalling ARs is critical for improving forecasts on timescales needed for water resource management. We examined 69years of landfalling ARs along western North America using reanalysis and a long-term AR catalog to identify circulation drivers of AR landfalls. This analysis reveals that AR activity along the West Coast is largely associated with a handful of influential modes of atmospheric variability. Interaction between these modes creates favorable or unfavorable atmospheric states for landfalling ARs at different locations, effectively steering moisture plumes up and down the coast from Mexico to British Columbia. Seasonal persistence of certain modes helps explain interannual variability of landfalling ARs, including recent California drought years and the wet winter of 2016/2017.

Plain Language Summary Understanding links between large-scale climate variability and landfalling ARs is important for improving subseasonal-to-seasonal (S2S) predictability of water resources in the western United States. We have analyzed a seven-decade-long catalog of ARs impacting western North America to quantify synoptic influence on AR activity. Our results identify dominant circulation patterns associated with landfalling ARs and show how seasonal variation in the prevalence of certain circulation features modulates the frequency of AR landfalls at different latitudes in a given year. AR variability played an important role in the recent California drought as well as the wet winter of 2016/2017, and we show how this variability was associated with the relative frequency of favorable versus unfavorable atmospheric states. Our findings also reveal that the bulk of AR landfalls along the West Coast is associated with only a handful of influential circulation features, which has implications for S2S predictability.