Observations of an extreme atmospheric river storm with a diverse sensor network

Benjamin J. Hatchett; Q. Cao; Phillip B. Dawson; C. J. Ellis; C. W. Hecht; B. Kawzenuk; J. T. Lancaster; T. C. Osborne; A. M. Wilson; M. L. Anderson; M. D. Dettinger; J. F. Kalansky; M. L. Kaplan; D. P. Lettenmaier; N. S. Oakley; R. M. Ralph; D. W. Reynolds; A. B. White; M. Sierks; E. Sumargo

doi:10.1029/2020EA001129

Observations of an extreme atmospheric river storm with a diverse sensor network

Earth and Space Science

By: Benjamin J. Hatchett, Q. Cao, Phillip B. Dawson, C. J. Ellis, C. W. Hecht, B. Kawzenuk, J. T. Lancaster, T. C. Osborne, A. M. Wilson, M. L. Anderson, M. D. Dettinger, J. F. Kalansky, M. L. Kaplan, D. P. Lettenmaier, N. S. Oakley, R. M. Ralph, D. W. Reynolds, A. B. White, M. Sierks, and E. Sumargo

https://doi.org/10.1029/2020EA001129

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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.

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Additional publication details
Publication type	Article
Publication Subtype	Journal Article
Title	Observations of an extreme atmospheric river storm with a diverse sensor network
Series title	Earth and Space Science
DOI	10.1029/2020EA001129
Volume	7
Issue	8
Year Published	2020
Language	English
Publisher	American Geophysical Union
Contributing office(s)	Volcano Science Center
Description	e2020EA001129, 21 p.
Country	United States
State	California
Google Analytic Metrics	Metrics page