Received: 28 Nov 2016 – Accepted for review: 23 Feb 2017 – Discussion started: 27 Feb 2017
Abstract. To resist marine submersion, coastal protection must be designed by taking into account the most accurate estimate of the return levels of extreme events, such as storm surges. However, because of the paucity of data, local statistical analyses often lead to poor frequency estimations. Regional Frequency Analysis (RFA) reduces the uncertainties associated with these estimations, by extending the dataset from local (only available data at the target site) to regional (data at all the neighboring sites including the target site) and by assuming, at the scale of a region, a similar extremal behavior. RFA, based on the index flood method, assumes that, in a homogeneous region, observations at sites, normalized by a local index, follow the same probability distribution. In this work, the spatial extremogram approach is used to form a physically homogeneous region centered on the target site. The approach is applied on a database of extreme skew storm surges and used to carry out a RFA.
This preprint has been withdrawn.
How to cite. Andreewsky, M., Griolet, S., Hamdi, Y., Bernardara, P., and Frau, R.: Homogenous regions based on extremogram for regional frequency analysis of extreme skew storm surges, Nat. Hazards Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/nhess-2016-378, 2017.
The aim of our study is to achieve extreme statistics on skew storm surges and to reduce uncertainties that are found in a local analysis by using a regional frequency analysis, for which, an important step, is to form a physically homogeneous region. Our method, which allows one to shape those physical homogeneous regions, is based on the use of the spatial extremogram, a correlation between extremes from two sites, and the regions found are consistent geographically and without border effect.
The aim of our study is to achieve extreme statistics on skew storm surges and to reduce...