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Chevalier, Clément
Résultat de la recherche
Efficient batch-sequential Bayesian optimization with moments of truncated Gaussian vectors
2019, Marmin, Sébastien, Chevalier, Clément, Ginsbourger, David
Adaptive design of experiments for conservative estimation of excursion sets
2019, Azzimonti, Dario, Ginsbourger, David, Chevalier, Clément, Bect, Julien, Richet, Yann
Quantifying uncertainties on excursion sets under a Gaussian random field prior
2016-8-2, Azzimonti, Dario, Bect, Julien, Chevalier, Clément, Ginsbourger, David
Differentiating the multipoint Expected Improvement for optimal batch design
2016, Chevalier, Clément
Modeling non-stationary extreme dependence with stationary max-stable processes and multidimensional scaling
2019, Chevalier, Clément, Martius, Olivia, Ginsbourger, David
Nested Kriging predictions for datasets with a large number of observations
2018-7, Rullière, Didier, Durrande, Nicolas, Bachoc, François, Chevalier, Clément
A global quantification of compound precipitation and wind extremes
2016-7-9, Martius, Olivia, Pfahl, Stephan, Chevalier, Clément
Properties and comparison of some Kriging sub-model aggregation methods
2019, Bachoc, François, Durrande, Nicolas, Rullière, Didier, Chevalier, Clément
Design of computer experiments using competing distances between set-value inputs
2016-11-1, Ginsbourger, David, Baccou, Jean, Chevalier, Clément, Perales, Frédéric
Clustering of Regional-scale Extreme Precipitation Events in Southern Switzerland
2016-1-7, Barton, Yannick, Giannakaki, Paraskevi, von Waldow, Harald, Chevalier, Clément, Pfahl, Stephan, Martius, Olivia
Temporal clustering of extreme precipitation events on sub-seasonal time-scales is of crucial importance for the formation of large-scale flood events. Here, the temporal clustering of regional-scale extreme precipitation events in southern Switzerland is studied. These precipitation events are relevant for the flooding of lakes in southern Switzerland and northern Italy. This research determines whether temporal clustering is present and then identifies the dynamics that are responsible for the clustering. An observation-based gridded precipitation data set of Swiss daily rainfall sums and ECMWF reanalysis data sets are used. We use a modified version of Ripley’s K-function, which determines the average number of extreme events in a time period, to characterize temporal clustering on sub-seasonal time-scales and to determine the statistical significance of the clustering. Significant clustering of regional-scale precipitation extremes is found on sub-seasonal time-scales during the fall season. Four high-impact clustering episodes are then selected and the dynamics responsible for the clustering are examined. During the four clustering episodes, all heavy precipitation events were associated with an upper-level breaking Rossby wave over Western Europe and in most cases strong diabatic processes upstream over the Atlantic played a role in the amplification of these breaking waves. Atmospheric blocking downstream over Eastern Europe supported this wave breaking during two of the clustering episodes. During one of the clustering periods, several extratropical transitions of tropical cyclones in the Atlantic contributed to the formation of high-amplitude ridges over the Atlantic basin and downstream wave breaking. During another event, blocking over Alaska assisted the phase locking of the Rossby waves downstream over the Atlantic.