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    Evaluation of a Physics-Based Tropical Cyclone Rainfall Model for Risk Assessment

    Source: Journal of Hydrometeorology:;2020:;volume( 21 ):;issue: 009::page 2197
    Author:
    Xi, Dazhi;Lin, Ning;Smith, James
    DOI: 10.1175/JHM-D-20-0035.1
    Publisher: American Meteorological Society
    Abstract: Heavy rainfall generated by landfalling tropical cyclones (TCs) can cause extreme flooding. A physics-based TC rainfall model (TCRM) has been developed and coupled with a TC climatology model to study TC rainfall climatology. In this study, we evaluate TCRM with rainfall observations made by satellite (of North Atlantic TCs from 1999 to 2018) and radar (of 36 U.S. landfalling TCs); we also examine the influence on the rainfall estimation of the key input to TCRM—the wind profile. We found that TCRM can simulate relatively well the rainfall from TCs that have a coherent and compact structure and limited interaction with other meteorological systems. The model can simulate the total rainfall from TCs well, although it often overestimates rainfall in the inner core of TCs, slightly underestimates rainfall in the outer regions, and renders a less asymmetric rainfall structure than the observations. It can capture rainfall distribution in coastal areas relatively well but may underestimate rainfall maximums in mountainous regions and has less capability to accurately simulate TC rainfall in higher latitudes. Also, it can capture the interannual variability of TC rainfall and averaged features of the time series of TC rainfall but cannot accurately reproduce the probability distribution of short-term (1 h) rainfall. Among the tested theoretical wind profile inputs to TCRM, a complete wind profile that accurately describes the wind structure in both the inner ascending and outer descending regions of the storm is found to perform the best in accurately generating various rainfall metrics.
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      Evaluation of a Physics-Based Tropical Cyclone Rainfall Model for Risk Assessment

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4264405
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    contributor authorXi, Dazhi;Lin, Ning;Smith, James
    date accessioned2022-01-30T18:02:54Z
    date available2022-01-30T18:02:54Z
    date copyright9/14/2020 12:00:00 AM
    date issued2020
    identifier issn1525-755X
    identifier otherjhmd200035.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4264405
    description abstractHeavy rainfall generated by landfalling tropical cyclones (TCs) can cause extreme flooding. A physics-based TC rainfall model (TCRM) has been developed and coupled with a TC climatology model to study TC rainfall climatology. In this study, we evaluate TCRM with rainfall observations made by satellite (of North Atlantic TCs from 1999 to 2018) and radar (of 36 U.S. landfalling TCs); we also examine the influence on the rainfall estimation of the key input to TCRM—the wind profile. We found that TCRM can simulate relatively well the rainfall from TCs that have a coherent and compact structure and limited interaction with other meteorological systems. The model can simulate the total rainfall from TCs well, although it often overestimates rainfall in the inner core of TCs, slightly underestimates rainfall in the outer regions, and renders a less asymmetric rainfall structure than the observations. It can capture rainfall distribution in coastal areas relatively well but may underestimate rainfall maximums in mountainous regions and has less capability to accurately simulate TC rainfall in higher latitudes. Also, it can capture the interannual variability of TC rainfall and averaged features of the time series of TC rainfall but cannot accurately reproduce the probability distribution of short-term (1 h) rainfall. Among the tested theoretical wind profile inputs to TCRM, a complete wind profile that accurately describes the wind structure in both the inner ascending and outer descending regions of the storm is found to perform the best in accurately generating various rainfall metrics.
    publisherAmerican Meteorological Society
    titleEvaluation of a Physics-Based Tropical Cyclone Rainfall Model for Risk Assessment
    typeJournal Paper
    journal volume21
    journal issue9
    journal titleJournal of Hydrometeorology
    identifier doi10.1175/JHM-D-20-0035.1
    journal fristpage2197
    journal lastpage2218
    treeJournal of Hydrometeorology:;2020:;volume( 21 ):;issue: 009
    contenttypeFulltext
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