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Ensemble technique application to an XBeach-based coastal Early Warning System for the Northwest Adriatic Sea (Emilia-Romagna region, Italy).
- Source :
-
Coastal Engineering . Apr2022, Vol. 173, pN.PAG-N.PAG. 1p. - Publication Year :
- 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. • A (semi-)probabilistic XBeach-based EWS is tested with multi-model ensemble outputs. • XBeach calibration is fundamental to avoid modeled erosion overestimation. • A GLUE-like calibration procedure yields an optimized parameter set. • The new EWS approach provides additional information to the forecaster/decision maker. [ABSTRACT FROM AUTHOR]
- Subjects :
- *FORECASTING
*WARNINGS
*FUTUROLOGISTS
Subjects
Details
- Language :
- English
- ISSN :
- 03783839
- Volume :
- 173
- Database :
- Academic Search Index
- Journal :
- Coastal Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 155556672
- Full Text :
- https://doi.org/10.1016/j.coastaleng.2022.104081