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    Characteristics and causes of extreme snowmelt over the conterminous United States

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    [15200477 - Bulletin of the ...
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    Author
    Welty, J.
    Zeng, X.
    Affiliation
    Department of Hydrology and Atmospheric Sciences, The University of Arizona
    Department of Hydrology and Atmospheric Sciences, The University of Arizona
    Issue Date
    2021
    Keywords
    Extreme events
    Flood events
    Precipitation
    Snow
    Snowmelt/icemelt
    Temperature
    
    Metadata
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    Publisher
    American Meteorological Society
    Citation
    Welty, J., & Zeng, X. (2021). Characteristics and causes of extreme snowmelt over the conterminous United States. Bulletin of the American Meteorological Society, 102(8), E1526–E1542.
    Journal
    Bulletin of the American Meteorological Society
    Rights
    Copyright © 2021 American Meteorological Society.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Snowmelt is an essential process for the health and sustenance of numerous communities and ecosystems across the globe, though it also presents potential hazards when ablation processes are exceedingly rapid. Using 4-km daily snow water equivalent, temperature, and precipitation data for three decades (1988-2017), here we provide a broad characterization of extreme snowmelt episodes over the conterminous United States in terms of magnitude, timing, and coincident synoptic weather patterns. Larger-magnitude extreme snowmelt events usually coincide with minimal precipitation and elevated temperatures. However, certain regions, particularly mountainous regions and the northeastern United States, exhibit greater likelihood of extreme snowmelt events during pronounced rain-on-snow events. During snowmelt extremes, snowmelt rate often exceeds precipitation in many regions. Meteorological patterns and associated water vapor transport most directly connected to extreme events over different regions are classified via a machine-learning technique. Over the 30-yr study period, there is a weakly increasing trend in the frequency of extremes, though this does not necessarily signify an increase in snowmelt magnitudes. © 2021 American Meteorological Society.
    Note
    6 month embargo; published online: 17 August 2021
    ISSN
    0003-0007
    DOI
    10.1175/BAMS-D-20-0182.1
    Version
    Final published version
    ae974a485f413a2113503eed53cd6c53
    10.1175/BAMS-D-20-0182.1
    Scopus Count
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    UA Faculty Publications

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