Are Multiseasonal Forecasts of Atmospheric Rivers Possible?
Kai‐Chih Tseng, Nathaniel C. Johnson, Sarah Kapnick, Thomas L. Delworth, Feiyu Lu, William Cooke, Andrew T. Wittenberg, Anthony Rosati, Liping Zhang, Colleen McHugh, Xiaosong Yang, Matthew Harrison, Fanrong Zeng, Gan Zhang, Hiroyuki Murakami, Mitchell Bushuk, Liwei Jia
Abstract
Abstract Atmospheric rivers (ARs) exert significant socioeconomic impacts in western North America, where 30 of the annual precipitation is determined by ARs that occur in less than 15 of wintertime. ARs are thus beneficial to water supply but can produce extreme precipitation hazards when making landfall. While most prevailing research has focused on the subseasonal ( 5 weeks) prediction of ARs, only limited efforts have been made for AR forecasts on multiseasonal timescales ( 3 months) that are crucial for water resource management and disaster preparedness. Through the analysis of reanalysis data and retrospective predictions from a new seasonal‐to‐decadal forecast system, this research shows the existing potential of multiseasonal AR frequency forecasts with predictive skills 9 months in advance. Additional analysis explores the dominant predictability sources and challenges for multiseasonal AR prediction.