资源环境科技发展态势分析平台

Atmospheric rivers (ARs) are responsible for a majority of extreme precipitation and flood events along the U.S. West Coast. To better understand the present-day characteristics of AR-related precipitation extremes, a selection of nine most intense historical AR events during 1980-2017 is simulated using a dynamical downscaling modeling framework based on the Weather Research and Forecasting Model. We find that the chosen framework and Weather Research and Forecasting Model configuration reproduces both large-scale atmospheric features-including parent synoptic-scale cyclones-as well as the filamentary corridors of integrated vapor transport associated with the ARs themselves. The accuracy of simulated extreme precipitation maxima, relative to in situ and interpolated gridded observations, improves notably with increasing model resolution, with improvements as large as 40-60% for fine scale (3 km) relative to coarse-scale (27 km) simulations. A separate set of simulations using smoothed topography suggests that much of these gains stem from the improved representation of complex terrain. Additionally, using the 12 December 1995 storm in Northern California as an example, we demonstrate that only the highest-resolution simulations resolve important fine-scale features-such as localized orographically forced vertical motion and powerful near hurricane-force boundary layer winds. Given the demonstrated ability of a targeted dynamical downscaling framework to capture both local extreme precipitation and key fine-scale characteristics of the most intense ARs in the historical record, we argue that such a configuration may be highly conducive to understanding AR-related extremes and associated changes in a warming climate.