资源环境科技发展态势分析平台

Understanding the role of climate variability in modulating the behavior of land-falling atmospheric rivers (ARs) is important for seasonal and subseasonal predictability for water resource management and flood control. We examine daily activity of ARs targeting the Northern California coast over six decades using observations of synoptic-scale circulation, high-resolution precipitation, and a long-term AR detection catalog to quantify distinct types of land-falling ARs categorized by their circulation features. We demonstrate how dramatically different atmospheric states evolve into landfalling ARs along distinct pathways that are modulated by interannual (El Nino/Southern Oscillation (ENSO)and the Pacific Decadal Oscillation) and subseasonal (Arctic Oscillation, Pacific North American Pattern, Western Pacific Oscillation, and the Eastern Pacific Oscillation) modes of large-scale climate variability. Different configurations of climate variability modes are shown to favor ARs having different characteristics in terms of synoptic evolution, integrated vapor transport and landfall orientation resulting in different patterns of precipitation over the landscape. In particular, our results show that while ENSO plays an important role in modulating the synoptic evolution of ARs and their orientation at landfall, subseasonal regional climate modes, which also influence landfall orientation as well as the position of the storm track, appear to be more influential than ENSO in modulating precipitation variability in California. This could have implications for seasonal to subseasonal (S2S) forecasting. Finally, we examine AR activity over the most recent and highly anomalous winter 2016-2017 and show how the unprecedented wet conditions in Northern California were at least partly due to the persistence of ARs characterized by a southward storm track and southerly orientation, which represent the type of ARs associated with heavy rainfall in California, and which are associated with the negative phase of subseasonal regional teleconnection patterns.