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Modeling nonstationary extreme wave heights in present and future climates of Greek Seas

Water Science and Engineering 2016年第1期9卷 21-32页

作者： Panagiota Galiatsatou Christina Anagnostopoulou Panayotis Prinos Hydraulics Laboratory Division of Hydraulics and Environmental Research Department of Civil Engineering Aristotle University of Thessaloniki Department of Meteorology and Climatology School of Geology Aristotle University of Thessaloniki

In this study the generalized extreme value （GEV） distribution function was used to assess nonstationarity in annual maximum wave heights for selected locations in the Greek Seas, both in the present and future climates. The available significant wave height data were divided into groups corresponding to the present period （1951-2000）, a first future period （2001-2050）, and a second future period （2051-2100）. For each time period, the parameters of the GEV distribution were specified as functions of time-varying covariates and estimated using the conditional density network （CDN）. For each location and selected time period, a total number of 29 linear and nonlinear models were fitted to the wave data, for a given combination of covariates. The covariates used in the GEV-CDN models consisted of wind fields resulting from the Regional Climate Model version 3 （RegCM3） developed by the International Center for Theoretical Physics （ICTP） with a spatial resolution of 10 km ×10 km, after being processed using principal component analysis （PCA）. The results obtained from the best fitted models in the present and future periods for each location were compared, revealing different patterns of relationships between wind components and extreme wave height quantiles in different parts of the Greek Seas and different periods. The analysis demonstrates an increase of extreme wave heights in the first future period as compared with the present period, causing a significant threat to Greek coastal areas in the North Aegean Sea and the Ionian Sea.

关键词： wave extremes Climate change Nonstationarity GEV-CDN Principal component analysis

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