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    Spatio-Temporal Modeling of Rain Rates

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    110.pdf (1.385Mb)
    Permanent Link
    http://hdl.handle.net/11603/1022
    Collections
    • UMBC Graduate School
    • UMBC Mathematics and Statistics Department
    • UMBC Student Collection
    • UMBC Theses and Dissertations
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    Author/Creator
    Unknown author
    Date
    2007-11-26
    Type of Work
    application/pdf
    Text
    dissertations
    Department
    Mathematics and Statistics
    Program
    Statistics
    Rights
    This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu.
    Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan through a local library, pending author/copyright holder's permission.
    Subjects
    Infinitely divisible distributions
    Multiscaling
    Spatio-temporal homogeneity
    Whittle Likelihood
    Contiguity
    Periodogram
    Statistics (0463)
    Mathematics (0405)
    Physics, Atmospheric Science (0608)
    Abstract
    Modeling episodes of heavy rain is an important component of hydrological studies. Based on the analysis of ship-borne radar data over the tropical ocean, we propose a new class of probability densities that capture the frequency of heavy rain occurrences. This density is constructed by inverting the characteristic function constructed from the moments computed at both integral and fractional orders, for all spatial scales. We demonstrate an improvement over the conventional log-normal distribution at explaining the behavior of intense rain events, and successfully explain the multiscaling characteristics of the rain field. An important assumption in the analysis of space-time characteristics of rain fields is isotropy and homogeneity. We test the equality of spectral densities at multiple locations in a non-parametric setting using the data periodograms. The efficacy of our methodology is demonstrated through simulation, and the theoretical properties of the proposed test statistic are examined. We establish the fact that the test asymptotically maintains the desired level of significance and is consistent at any alternative, and apply our methodology to real life rain rate data set taken from a network of rain gauges in Melbourne, South Florida. This research was supported by a NASA grant under the Precipitations Measurement Missions (PMM) program.


    Albin O. Kuhn Library & Gallery
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    www.umbc.edu/scholarworks

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    Albin O. Kuhn Library & Gallery
    University of Maryland, Baltimore County
    1000 Hilltop Circle
    Baltimore, MD 21250
    www.umbc.edu/scholarworks

    Contact information:
    Email: scholarworks-group@umbc.edu
    Phone: 410-455-3021


    If you wish to submit a copyright complaint or withdrawal request, please email mdsoar-help@umd.edu.