Detection Uncertainty Matters for Understanding Atmospheric Rivers

Abstract

Atmospheric rivers (ARs) are increasingly recognized globally as an important weather phenomenon associated with extreme precipitation. There is a substantial body of literature indicating that ARs are responsible for a large fraction of wet-season precipitation on western coasts (Rutz et al. 2019) and that they can cause large changes in snowpack (both positive and negative; Guan et al. 2010; Chen et al. 2019). Individual ARs and collections of ARs can bring large amounts of precipitation that drive floods and other storm-related hazards (Ralph et al. 2006, 2019a). ARs are a significant factor for water and associated water systems in the vicinity of western coasts (Gao et al. 2016; Ralph et al. 2019b). It is increasingly evident that they have major impacts on the energy and water budgets of the cryosphere: including mountains (Chen et al. 2019) and high-latitude regions (Gorodetskaya et al. 2014). These research advances hinge on technical advances in tracking ARs in observations, reanalyses, and climate model simulations and on understanding uncertainties associated with different tracking methods. In parallel with the recent increase in research activity around ARs, an increasing number of research groups have developed unique methods for tracking ARs (Shields et al. 2019).