Assessing trends in extreme precipitation events intensity and magnitude using non‐stationary peaks‐over‐threshold analysis: a case study in northeast Spain from 1930 to 2006

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Abstract

Abstract Most applications of the extreme value (EV) theory have assumed stationarity, i.e. the statistical properties of the process do not change over time. However, there is evidence suggesting that the occurrence of extreme events is not stationary but changes naturally, as it has been found for many other climate variables. Of paramount importance for hazard analysis is whether the observed precipitation time series exhibit long‐term trends or cycles; such information is also relevant in climate change studies. In this study, the theory of non‐stationary extreme value (NSEV) analysis was applied to data series of daily precipitation using the peaks‐over‐threshold (POT) approach. A Poisson/generalized Pareto (P/GP) model, in which the model parameters were allowed to vary linearly with time, was fitted to the resulting series of precipitation event's intensity and magnitude. A log‐likelihood ratio test was applied to determine the existence of trends in the model parameters. The method was applied to a case study in northeast Spain, comprising a set of 64 daily rainfall series from 1930 to 2006. Statistical significance was achieved in less than 5% of the stations using a linear non‐stationary model at the annual scale, indicating that there is no evidence of a generalized trend in extreme precipitation in the study area. At the seasonal scale, however, a significant number of stations along the Mediterranean (Catalonia region) showed a significant decrease of extreme rainfall intensity in winter, while experiencing an increase in spring. Copyright © 2010 Royal Meteorological Society

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