• Login
    View Item 
    •   DSpace Home
    • AMS
    • Journal of the Atmospheric Sciences
    • View Item
    •   DSpace Home
    • AMS
    • Journal of the Atmospheric Sciences
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    The Impact of Land Surface Properties on Haboobs and Dust Lofting

    Thumbnail
    View/Open
    JAS-D-22-0001.1.pdf (3.529Mb)
    Date
    2022
    Author
    Jennie Bukowski
    Susan C. van den Heever
    Metadata
    Show full item record
    Abstract
    Haboobs are dust storms formed by strong surface winds in convective storm outflow boundaries, or cold pools, which can loft large quantities of mineral dust as they propagate. Both cold pools and the dust they loft are impacted by land surface properties resulting in complex surface interactions on haboobs. As a result of these additional complexities brought about by surface interactions, it is unclear which surface parameters and physical processes are important for predicting haboob intensity and dust concentrations. Here we applied the Morris one-at-a-time (MOAT) global sensitivity statistical method to an ensemble of 120 idealized simulations of daytime and nighttime haboobs to investigate the land surface properties that affect both dust mobilization and cold pool dynamics. MOAT identifies and ranks the importance of different input factors, which for the prediction of haboob strength and dust concentrations are 1) initial cold pool temperature, 2) surface type (vegetation), 3) soil type (clay content), and 4) soil moisture. The underlying physical mechanisms driving these feedbacks were then analyzed using a traditional one-at-a-time factor analysis. Time of day is significant for determining boundary layer height and dissipation via surface fluxes, leading to shallower, more intense cold pools/haboobs at night. Most of the land parameters modify the cold pool through impacts on surface fluxes, while surface type is dominated by roughness length effects. By ranking the importance of these surface factors, we have identified which variables are most sensitive and must be constrained via observations and data assimilation in numerical dust prediction models.
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4290028
    Collections
    • Journal of the Atmospheric Sciences

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV