Editorial Type:
Article
Article Type:
Research Article

Observed Impacts of Duration and Seasonality of Atmospheric-River Landfalls on Soil Moisture and Runoff in Coastal Northern California

F. M. Ralph Physical Sciences Division, NOAA/ESRL, Boulder, Colorado

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T. Coleman Physical Sciences Division, NOAA/ESRL, and CIRES, Boulder, Colorado

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P. J. Neiman Physical Sciences Division, NOAA/ESRL, Boulder, Colorado

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R. J. Zamora Physical Sciences Division, NOAA/ESRL, Boulder, Colorado

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M. D. Dettinger Scripps Institution of Oceanography, University of California, San Diego, and U.S. Geological Survey, La Jolla, California

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Print Publication:
01 Apr 2013
Collections:
State of the Science of Precipitation Research
DOI:
https://doi.org/10.1175/JHM-D-12-076.1
Page(s):
443–459
Restricted access

Abstract

This study is motivated by diverse needs for better forecasts of extreme precipitation and floods. It is enabled by unique hourly observations collected over six years near California’s Russian River and by recent advances in the science of atmospheric rivers (ARs). This study fills key gaps limiting the prediction of ARs and, especially, their impacts by quantifying the duration of AR conditions and the role of duration in modulating hydrometeorological impacts. Precursor soil moisture conditions and their relationship to streamflow are also shown. On the basis of 91 well-observed events during 2004–10, the study shows that the passage of ARs over a coastal site lasted 20 h on average and that 12% of the AR events exceeded 30 h. Differences in storm-total water vapor transport directed up the mountain slope contribute 74% of the variance in storm-total rainfall across the events and 61% of the variance in storm-total runoff volume. ARs with double the composite mean duration produced nearly 6 times greater peak streamflow and more than 7 times the storm-total runoff volume. When precursor soil moisture was less than 20%, even heavy rainfall did not lead to significant streamflow. Predicting which AR events are likely to produce extreme impacts on precipitation and runoff requires accurate prediction of AR duration at landfall and observations of precursor soil moisture conditions.

Corresponding author address: Dr. F. Martin Ralph, Physical Sciences Division, NOAA/ESRL, 325 Broadway, Boulder, CO 80305. E-mail: marty.ralph@noaa.gov

This article is included in the State of the Science of Precipitation special collection.

Abstract

This study is motivated by diverse needs for better forecasts of extreme precipitation and floods. It is enabled by unique hourly observations collected over six years near California’s Russian River and by recent advances in the science of atmospheric rivers (ARs). This study fills key gaps limiting the prediction of ARs and, especially, their impacts by quantifying the duration of AR conditions and the role of duration in modulating hydrometeorological impacts. Precursor soil moisture conditions and their relationship to streamflow are also shown. On the basis of 91 well-observed events during 2004–10, the study shows that the passage of ARs over a coastal site lasted 20 h on average and that 12% of the AR events exceeded 30 h. Differences in storm-total water vapor transport directed up the mountain slope contribute 74% of the variance in storm-total rainfall across the events and 61% of the variance in storm-total runoff volume. ARs with double the composite mean duration produced nearly 6 times greater peak streamflow and more than 7 times the storm-total runoff volume. When precursor soil moisture was less than 20%, even heavy rainfall did not lead to significant streamflow. Predicting which AR events are likely to produce extreme impacts on precipitation and runoff requires accurate prediction of AR duration at landfall and observations of precursor soil moisture conditions.

Corresponding author address: Dr. F. Martin Ralph, Physical Sciences Division, NOAA/ESRL, 325 Broadway, Boulder, CO 80305. E-mail: marty.ralph@noaa.gov

This article is included in the State of the Science of Precipitation special collection.

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