Observations of an Extreme Atmospheric River Storm With a Diverse Sensor Network. Issue 8 (4th August 2020)

• Record Type: Journal Article
• Authors: Hatchett, B. J.; Cao, Q.; Dawson, P. B.; Ellis, C. J.; Hecht, C. W.; Kawzenuk, B.; Lancaster, J. T.; Osborne, T. C.; Wilson, A. M.; Anderson, M. L.; Dettinger, M. D.; Kalansky, J. F.; Kaplan, M. L.; Lettenmaier, D. P.; Oakley, N. S.; Ralph, F. M.; Reynolds, D. W.; White, A. B.; Sierks, M.; Sumargo, E.
• Is Part Of: Earth and space science. Volume 7:Issue 8(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-04
• Subjects: observations -- extreme events -- hydrometeorology -- atmospheric river -- winter -- California; Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2020EA001129
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract: Observational networks enhance real‐time situational awareness for emergency and water resource management during extreme weather events. We present examples of how a diverse, multitiered observational network in California provided insights into hydrometeorological processes and impacts during a 3‐day atmospheric river storm centered on 14 February 2019. This network, which has been developed over the past two decades, aims to improve understanding and mitigation of effects from extreme storms influencing water resources and natural hazards. We combine atmospheric reanalysis output and additional observations to show how the network allows: (1) the validation of record cool season precipitable water observations over southern California; (2) the identification of phenomena that produce natural hazards and present difficulties for short‐term weather forecast models, such as extreme precipitation amounts and snow level variability; (3) the use of soil moisture data to improve hydrologic model forecast skill in northern California's Russian River basin; and (4) the combination of meteorological data with seismic observations to identify when a large avalanche occurred on Mount Shasta. This case study highlights the value of investments in diverse observational assets and the importance of continued support and synthesis of these networks to characterize climatological context and advance understanding of processes modulating extreme weather. Key Points: A multitiered observational network in California is evaluated during an extreme atmospheric river storm spanning 13–15 February 2019 The network validates record precipitable water and detects mesoscale atmospheric processes driving flood, snowfall, and mass wasting events Diverse, high frequency observational networks are valuable investments to aid water resource management and natural hazard mitigation