During the last three decades, ensemble modelling has switched the focus from deterministic to probabilistic outcomes after its successful application in meteorological forecasting. This work involves the application of Ensemble Prediction System (EPS)-based results as forcing for a coastal EWS employing the morphodynamic model XBeach in a so-called (semi-)probabilistic way. First, calibration following the GLUE approach is performed for a profile in Cesenatico (Emilia-Romagna coast, Italy), while the (semi-)probabilistic system is implemented subsequently for two nearby locations. Ensemble mean and standard deviation from the Transnational Multi-Model Ensemble (TMES) forecasting system are combined in varied ways and used to force XBeach. A testing period of two months is analyzed (March and April 2020) together with the already operational deterministic implementation with one specific day of high sea conditions being used to assess the performance of the system. The deterministic results present higher outcome variability compared to the usage of the TMES mean and mean plus/minus one standard deviation (SD). Adding two SDs to the TMES mean results in higher variability than the deterministic approach. The (semi-)probabilistic system shows high potential as it provides more information on possible outcomes. However, its implementation has to be carefully designed as the application of the TMES mean plus SDs might result in false threshold exceedance and unproportionate responses.

Biolchi, L.G., Unguendoli, S., Bressan, L., Giambastiani, B.M.S., Valentini, A. (2022). Ensemble technique application to an XBeach-based coastal Early Warning System for the Northwest Adriatic Sea (Emilia-Romagna region, Italy). COASTAL ENGINEERING, 173, 1-19 [10.1016/j.coastaleng.2022.104081].

Ensemble technique application to an XBeach-based coastal Early Warning System for the Northwest Adriatic Sea (Emilia-Romagna region, Italy)

Giambastiani B. M. S.
Penultimo
;
2022

Abstract

During the last three decades, ensemble modelling has switched the focus from deterministic to probabilistic outcomes after its successful application in meteorological forecasting. This work involves the application of Ensemble Prediction System (EPS)-based results as forcing for a coastal EWS employing the morphodynamic model XBeach in a so-called (semi-)probabilistic way. First, calibration following the GLUE approach is performed for a profile in Cesenatico (Emilia-Romagna coast, Italy), while the (semi-)probabilistic system is implemented subsequently for two nearby locations. Ensemble mean and standard deviation from the Transnational Multi-Model Ensemble (TMES) forecasting system are combined in varied ways and used to force XBeach. A testing period of two months is analyzed (March and April 2020) together with the already operational deterministic implementation with one specific day of high sea conditions being used to assess the performance of the system. The deterministic results present higher outcome variability compared to the usage of the TMES mean and mean plus/minus one standard deviation (SD). Adding two SDs to the TMES mean results in higher variability than the deterministic approach. The (semi-)probabilistic system shows high potential as it provides more information on possible outcomes. However, its implementation has to be carefully designed as the application of the TMES mean plus SDs might result in false threshold exceedance and unproportionate responses.
2022
Biolchi, L.G., Unguendoli, S., Bressan, L., Giambastiani, B.M.S., Valentini, A. (2022). Ensemble technique application to an XBeach-based coastal Early Warning System for the Northwest Adriatic Sea (Emilia-Romagna region, Italy). COASTAL ENGINEERING, 173, 1-19 [10.1016/j.coastaleng.2022.104081].
Biolchi, L. G.; Unguendoli, S.; Bressan, L.; Giambastiani, B. M. S.; Valentini, A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/859978
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