Abstract

Extreme precipitation has increased in frequency and intensity across the Conterminous U.S. (CONUS). This trend is expected to continue under future climate change. The cause is a combination of thermodynamic (i.e., warmer temperatures increase the atmospheric moisture content) and dynamic change... Show moreExtreme precipitation has increased in frequency and intensity across the Conterminous U.S. (CONUS). This trend is expected to continue under future climate change. The cause is a combination of thermodynamic (i.e., warmer temperatures increase the atmospheric moisture content) and dynamic changes (e.g., shifts in cyclone frequency and tracks). It is well-established that thermodynamic changes will intensify extreme precipitation events, but the impacts of dynamic changes are more uncertain. Extreme events are, per definition, rare and occur in unusual weather situations that are distinctly different from regular day-to-day weather. We take advantage of this and identify extreme precipitation-producing weather patterns (XWTs) for all major watersheds across the CONUS by using a novel algorithm. We show that a set of one to four XWTs per watershed are causing extreme precipitation accumulations. These XWTs can be detected based on their synoptic-scale fingerprint and are associated with West Coast atmospheric rivers, troughing in the desert Southwest, cutoff lows and troughs in the central and northwestern plains, and tropical cyclones along the Gulf and Atlantic coast. The algorithm is flexible enough to provide reliable results for city to major watershed-scales and can detect extremes that are unprecedented in the training record. Importantly, this approach allows us to assess long-term trends in extreme precipitation dynamics and reveal that XWT frequencies increased significantly in most U.S. watersheds during the 20th century indicating that changes in the atmospheric dynamics played an important role in historic extreme precipitation increases. Show less