8A.3 Diagnosing Rainfall Variability Within A Series of Atmospheric Rivers over Northern California in February 2017

Tuesday, 30 January 2024: 5:00 PM
318/319 (The Baltimore Convention Center)
Parker Malek, Portland State University, Portland, OR; and P. C. Loikith

Heavy precipitation drives a range of hydrometeorological hazards including flooding and flash flooding, mass wasting events, and rapid snow melt. High intensity, short duration events embedded within larger storms carry the additional threat of exacerbating these kinds of impacts by further destabilizing already saturated soils and swollen waterways. Such shorter duration, higher intensity events embedded within longer duration storms are relatively common during the cool months along the west coast of the United States and are usually associated with landfalling atmospheric rivers. While the rainfall from an atmospheric river is typically associated with the synoptic scale, smaller mesoscale features such as narrow cold frontal rainbands and local orographic forcing are known to drive higher intensity, shorter duration rainfall events within the broader storm system. While these features are generally recognized, the underlying meteorological forcing driving the variability of rainfall intensity within the broader precipitation event has not been thoroughly investigated over the region. Toward improving our understanding of the range of mechanisms that drive within-storm precipitation variability, especially those which lead to high-intensity precipitation, this study investigates several notable atmospheric river events that impacted three watersheds in California. We focus on understanding the drivers behind precipitation variability observed within the longer-duration atmospheric river event using a combination of rain gauge, satellite-based, and reanalysis data. Within event precipitation variability is found to be driven by a number of factors including local and synoptic-scale forcing. Results provide a foundation for a more systematic identification of the key factors driving within-storm precipitation variability with implications for improved hydrometeorological forecasting.
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