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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2019-320
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-320
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 09 Oct 2019

Submitted as: research article | 09 Oct 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Extreme waves analysis based on atmospheric patterns classification: an application along the Italian coast

Francesco De Leo1, Sebastián Solari2, and Giovanni Besio1 Francesco De Leo et al.
  • 1Dept. of Civil, Chemical and Environmental Engineering – University of Genoa, Genoa, 16145, Italy
  • 2Instituto de Mecánica de los Fluidos e Ingenieria Ambiental – Universidad de la República, Montevideo, 11300, Uruguay

Abstract. The identification of homogeneous populations of data prior to perform Extreme Value Analysis (EVA) is advisable in all fields of sciences. When performing EVA on sea storms, it is also recommended to have an insight on the atmospheric processes behind the occurrence of the extremes, as this might facilitate the interpretation and ultimately use of the results. In this work, a bottom-up approach for the identification and classification of the atmospheric processes producing extreme wave conditions is revisited, and applied to several locations among the Italian buoy network. A methodology is given for classifying samples of significant wave height peaks in homogeneous subsets, and for the computation of the overall extreme values distribution starting from the distributions fitted to each single subset. From the obtained results, it is concluded that the proposed methodology is capable of identifying clearly differentiated subsets driven by homogeneous atmospheric processes, and it allows to estimate high return-period quantiles consistent with those resulting from the usual EVA. Two well-known cyclonic systems are identified as most likely responsible of the extreme conditions detected in the investigated locations. These systems are analysed in the context of the Mediterranean sea atmospheric climatology, and compared with those figured out by previous researches developed in similar frameworks.

Francesco De Leo et al.
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