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    Impact of Rainfall Assimilation on High-Resolution Hydrometeorological Forecasts over Liguria, Italy

    Source: Journal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 010::page 2659
    Author:
    Davolio, Silvio;Silvestro, Francesco;Gastaldo, Thomas
    DOI: 10.1175/JHM-D-17-0073.1
    Publisher: American Meteorological Society
    Abstract: AbstractThe autumn of 2014 was characterized by a number of severe weather episodes over Liguria (northern Italy) associated with floods and remarkable damage. This period is selected as a test bed to evaluate the performance of a rainfall assimilation scheme based on the nudging of humidity profiles and applied to a convection-permitting meteorological model at high resolution. The impact of the scheme is assessed in terms of quantitative precipitation forecast (QPF) applying an object-oriented verification methodology that evaluates the structure, amplitude, and location (SAL) of the precipitation field, but also in terms of hydrological discharge prediction. To attain this aim, the meteorological model is coupled with the operational hydrological forecasting chain of the Ligurian Hydrometeorological Functional Centre, and the whole system is implemented taking operational requirements into account. The impact of rainfall data assimilation is large during the assimilation period and still relevant in the following 3 h of the free forecasts, but hardly lasts more than 6 h. However, this can improve the hydrological predictions. Moreover, the impact of the assimilation is dependent on the environment characteristics, being more effective when nonequilibrium convection dominates, and thus an accurate prediction of the local triggering for the development of the precipitation system is required.
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      Impact of Rainfall Assimilation on High-Resolution Hydrometeorological Forecasts over Liguria, Italy

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    contributor authorDavolio, Silvio;Silvestro, Francesco;Gastaldo, Thomas
    date accessioned2018-01-03T11:02:06Z
    date available2018-01-03T11:02:06Z
    date copyright8/22/2017 12:00:00 AM
    date issued2017
    identifier otherjhm-d-17-0073.1.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4246349
    description abstractAbstractThe autumn of 2014 was characterized by a number of severe weather episodes over Liguria (northern Italy) associated with floods and remarkable damage. This period is selected as a test bed to evaluate the performance of a rainfall assimilation scheme based on the nudging of humidity profiles and applied to a convection-permitting meteorological model at high resolution. The impact of the scheme is assessed in terms of quantitative precipitation forecast (QPF) applying an object-oriented verification methodology that evaluates the structure, amplitude, and location (SAL) of the precipitation field, but also in terms of hydrological discharge prediction. To attain this aim, the meteorological model is coupled with the operational hydrological forecasting chain of the Ligurian Hydrometeorological Functional Centre, and the whole system is implemented taking operational requirements into account. The impact of rainfall data assimilation is large during the assimilation period and still relevant in the following 3 h of the free forecasts, but hardly lasts more than 6 h. However, this can improve the hydrological predictions. Moreover, the impact of the assimilation is dependent on the environment characteristics, being more effective when nonequilibrium convection dominates, and thus an accurate prediction of the local triggering for the development of the precipitation system is required.
    publisherAmerican Meteorological Society
    titleImpact of Rainfall Assimilation on High-Resolution Hydrometeorological Forecasts over Liguria, Italy
    typeJournal Paper
    journal volume18
    journal issue10
    journal titleJournal of Hydrometeorology
    identifier doi10.1175/JHM-D-17-0073.1
    journal fristpage2659
    journal lastpage2680
    treeJournal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 010
    contenttypeFulltext
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