Abstract
Abstract. In this paper we present a multivariate regional test we developed for the detection of trends in extreme rainfall, which takes into account the spatial dependence between rainfall measurements with copula functions. The test is based on four steps. It was applied to a set of 92 series of Annual Daily Maxima (ADM) rainfall in the French Mediterranean area, sampled during the 1949–2004 observation period. The results show a low significant trend, concerning mainly the mountains area in the west part of the French Mediterranean region. The position's parameters of the ADM rainfall probability distribution functions present a low but significant increasing trend of about 5% to 10%, the same increase as that observed in ADM rainfall quantiles in the last 56 years. Further work is needed to understand if this significative trend is related to the global climate change or to the natural variability of Mediterranean climate.
Highlights
The effect of human activity on climate and global warming is accepted by the whole scientific community (IPCC, 2007)
As global warming started at the beginning of the 20th century, another approach is to analyse long series of observations to check if some changes in the observed extreme rainfall time series were already apparent This note presents a method for trend detection adapted to extreme events and an application to daily extreme precipitation in the Mediterranean area
We present a tool for the detection of trends in extreme value time series that take the spatial consistency into account
Summary
The effect of human activity on climate and global warming is accepted by the whole scientific community (IPCC, 2007). In the context of global warming, a major question concerns its consequences for extreme events. One way to answer this question is to analyse different scenarios of extreme events produced by climate models. Such scenarios depend on the model and the spatiotemporal scales
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