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    The Uncertainty in the Prediction of Flash Floods in the Northern Mediterranean Environment 

    Source: Journal of Hydrometeorology:;2002:;Volume( 003 ):;issue: 006:;page 714
    Author(s): Ferraris, Luca; Rudari, Roberto; Siccardi, Franco
    Publisher: American Meteorological Society
    Abstract: Development of an operational flood forecasting system and assessment of forecast uncertainty are the principal topics of this paper. Flood forecasting procedures are developed for a Mediterranean environment. A procedure ...
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    An Algorithm for Real-Time Rainfall Rate Estimation by Using Polarimetric Radar: RIME 

    Source: Journal of Hydrometeorology:;2009:;Volume( 010 ):;issue: 001:;page 227
    Author(s): Silvestro, Francesco; Rebora, Nicola; Ferraris, Luca
    Publisher: American Meteorological Society
    Abstract: Polarimetric radars provide measurements that describe the shape and dimensions of hydrometeors and are unaffected by calibration, attenuation, and the presence of ice. These measurements can potentially lead to a more ...
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    Quantitative Flood Forecasting on Small- and Medium-Sized Basins: A Probabilistic Approach for Operational Purposes 

    Source: Journal of Hydrometeorology:;2011:;Volume( 012 ):;issue: 006:;page 1432
    Author(s): Silvestro, Francesco; Rebora, Nicola; Ferraris, Luca
    Publisher: American Meteorological Society
    Abstract: he forecast of rainfall-driven floods is one of the main themes of analysis in hydrometeorology and a critical issue for civil protection systems. This work describes a complete hydrometeorological forecast system for ...
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    RainFARM: Rainfall Downscaling by a Filtered Autoregressive Model 

    Source: Journal of Hydrometeorology:;2006:;Volume( 007 ):;issue: 004:;page 724
    Author(s): Rebora, Nicola; Ferraris, Luca; von Hardenberg, Jost; Provenzale, Antonello
    Publisher: American Meteorological Society
    Abstract: A method is introduced for stochastic rainfall downscaling that can be easily applied to the precipitation forecasts provided by meteorological models. Our approach, called the Rainfall Filtered Autoregressive Model ...
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    Precipitation Nowcasting by a Spectral-Based Nonlinear Stochastic Model 

    Source: Journal of Hydrometeorology:;2009:;Volume( 010 ):;issue: 005:;page 1285
    Author(s): Metta, Sabino; von Hardenberg, Jost; Ferraris, Luca; Rebora, Nicola; Provenzale, Antonello
    Publisher: American Meteorological Society
    Abstract: A novel rainfall nowcasting method based on the combination of an empirical nonlinear transformation of measured precipitation fields and the stochastic evolution in spectral space of the transformed fields is introduced. ...
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    Verification of Quantitative Precipitation Forecasts via Stochastic Downscaling 

    Source: Journal of Hydrometeorology:;2008:;Volume( 009 ):;issue: 005:;page 1084
    Author(s): Brussolo, Elisa; von Hardenberg, Jost; Ferraris, Luca; Rebora, Nicola; Provenzale, Antonello
    Publisher: American Meteorological Society
    Abstract: The use of dense networks of rain gauges to verify the skill of quantitative numerical precipitation forecasts requires bridging the scale gap between the finite resolution of the forecast fields and the point measurements ...
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    DRIHM(2US): an e-Science environment for hydro-meteorological research on high impact weather events 

    Source: Bulletin of the American Meteorological Society:;2017:;volume( 098 ):;issue: 010:;page 2149
    Author(s): Parodi, Antonio; Kranzlmueller, Dieter; Clematis, Andrea; Danovaro, Emanuele; Galizia, Antonella; Garrote, Luis; Llasat, Maria Carmen; Caumont, Olivier; Richard, Evelyne; Harpham, Quillon; Siccardi, Franco; Ferraris, Luca; Rebora, Nicola; Delogu, Fabio; Fiori, Elisabetta; Molini, Luca; Foufoula-Georgiou, Efi; D’Agostino, Daniele
    Publisher: American Meteorological Society
    Abstract: IHM, or the Distributed Research Infrastructure for Hydro-Meteorology, together with its US facing companion project, DRIHM2US, both funded by the European Union, have developed a prototype research infrastructure for ...
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