• Login
    View Item 
    •   Home
    • UA Faculty Research
    • UA Faculty Publications
    • View Item
    •   Home
    • UA Faculty Research
    • UA Faculty Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UA Campus RepositoryCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournal

    My Account

    LoginRegister

    About

    AboutUA Faculty PublicationsUA DissertationsUA Master's ThesesUA Honors ThesesUA PressUA YearbooksUA CatalogsUA Libraries

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Can Convection‐Permitting Modeling Provide Decent Precipitation for Offline High‐Resolution Snowpack Simulations Over Mountains?

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    He_et_al-2019-Journal_of_Geoph ...
    Size:
    16.75Mb
    Format:
    PDF
    Description:
    Final Published Version
    Download
    Author
    He, Cenlin
    Chen, Fei
    Barlage, Michael
    Liu, Changhai
    Newman, Andrew
    Tang, Wenfu
    Ikeda, Kyoko
    Rasmussen, Roy
    Affiliation
    Univ Arizona, Dept Hydrol & Atmospher Sci
    Issue Date
    2019-11-22
    
    Metadata
    Show full item record
    Publisher
    AMER GEOPHYSICAL UNION
    Citation
    He, C., Chen, F., Barlage, M., Liu, C., Newman, A., Tang, W., et al. (2019). Can convection‐permitting modeling provide decent precipitation for off line high‐resolution snowpack simulations over mountains?. Journal of Geophysical Research: Atmospheres, 124, 12,631–12,654. https://doi.org/10.1029/2019JD030823
    Journal
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
    Rights
    Copyright © 2019. American Geophysical Union.All Rights Reserved.
    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
    Accurate precipitation estimates are critical to simulating seasonal snowpack evolution. We conduct and evaluate high-resolution (4-km) snowpack simulations over the western United States (WUS) mountains in Water Year 2013 using the Noah with multi-parameterization (Noah-MP) land surface model driven by precipitation forcing from convection-permitting (4-km) Weather Research and Forecasting (WRF) modeling and four widely used high-resolution datasets that are derived from statistical interpolation based on in situ measurements. Substantial differences in the precipitation amount among these five datasets, particularly over the western and northern portions of WUS mountains, significantly affect simulated snow water equivalent (SWE) and snow depth (SD) but have relatively limited effects on snow cover fraction (SCF) and surface albedo. WRF generally captures observed precipitation patterns and results in an overall best-performed SWE and SD in the western and northern portions of WUS mountains, where the statistically interpolated datasets lead to underpredicted precipitation, SWE, and SD. Over the interior WUS mountains, all the datasets consistently underestimate precipitation, causing significant negative biases in SWE and SD, among which the results driven by the WRF precipitation show an average performance. Further analysis reveals systematic positive biases in SCF and surface albedo across the WUS mountains, with similar bias patterns and magnitudes for simulations driven by different precipitation datasets, suggesting an urgent need to improve the Noah-MP snowpack physics. This study highlights that convection-permitting modeling with proper configurations can have added values in providing decent precipitation for high-resolution snowpack simulations over the WUS mountains in a typical ENSO-neutral year, particularly over observation-scarce regions.
    Note
    6 month embargo; published online: 22 November 2019
    ISSN
    2169-897X
    DOI
    10.1029/2019jd030823
    Version
    Final published version
    ae974a485f413a2113503eed53cd6c53
    10.1029/2019jd030823
    Scopus Count
    Collections
    UA Faculty Publications

    entitlement

     
    The University of Arizona Libraries | 1510 E. University Blvd. | Tucson, AZ 85721-0055
    Tel 520-621-6442 | repository@u.library.arizona.edu
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.