A robust error-based rain estimation method for polarimetric radar. Part II

case study

Acacia S. Pepler, Peter T. May

    Research output: Contribution to journalArticle

    7 Citations (Scopus)


    Rainfall estimation using polarimetric radar involves the combination of a number of estimators with differing error characteristics to optimize rainfall estimates at all rain rates. In Part I of this paper, a new technique for such combinations was proposed that weights algorithms by the inverse of their theoretical errors. In this paper, the derived algorithms are validated using the "CP2" polarimetric radar in Queensland, Australia, and a collocated rain gauge network for two heavy-rain events during November 2008 and a larger statistical analysis that is based on data from between 2007 and 2009. Use of a weighted combination of polarimetric algorithms offers some improvement over composite methods that are based on decision-tree logic, particularly at moderate to high rain rates and during severe-thunderstorm events.
    Original languageEnglish
    Pages (from-to)1702-1713
    Number of pages12
    JournalJournal of Applied Meteorology and Climatology
    Issue number9
    Publication statusPublished - 2012


    • Algorithms
    • Radars/Radar observations

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