Programme OS3f Regional and nationwide
scenarios 2 abstract 122
Regional tests for trend detection in maximum pluviometric series in the
French Mediterranean region.
Author(s): Nicolas Pujol(1), Luc Neppel(1), Robert Sabatier(2)
NICOLAS PUJOL (1), LUC NEPPEL (1), ROBERT
SABATIER(2)
(1) Hydrosciences, Maison des Sciences de l’Eau, cc 57
Université Montpellier 2 – Place
Eugène Bataillon
34095 Montpellier cedex 5, France
e-mail : pujol@msem.univ-montp2.fr ; Tel :
04.67.14.39.6
Keyword(s): climatic change, Mann
-Kendall’s test, Generalized Extreme Value distribution, maximum likelihood method, regional test for trend
detection
Article:
Poster:
Session: OS3f Regional and nationwide
scenarios 2
Abstract Introduction
During the last years, French Mediterranean regions have been affected by
extremely violent precipitations, in particular the ones of November 1999, located in Aude, of September 2002 in
Gard. With the current prospect of a climatic change, these recurrent inundations are regularly ascribed to an
evolution of the rainy regime. In this paper, we are going to focus on extreme precipitations of the Mediterranean
region.
Objective
Our purpose is to test the stationary hypothesis of extreme daily precipitations in the
Mediterranean region. However, a local approach of trend detection is limited. In fact, if 5 non stationary posts
among 100 are detected by a local test, with a 5% risk, what can be concluded? Are they due to chance or to true
changes? To cope with this problem, we propose to estimate the regional significance of locally noticed change, and
then, to check if they are indicative of a real climatic change or not.
Methods
The Mann-Kendall non
parametric test (denoted by MK) is locally used for each post, and a regional statistics is built. Furthermore, maxima
are generally distributed as a Generalized Extreme Value distribution. The maximum likelihood method (denoted by
ML) is built on this hypothesis. A regional interpretation of this test is also built. Both MK and ML regional statistics
are built by bootstrap. This re-sampling method allows to respect the initial cross-correlation in the
data.
Results
It is interesting to notice that, whereas they are no common points, the MK and ML tests
provide very similar results, locally as well as regionally. Moreover, we have seen how liberal the regional MK and
ML tests become when special correlation is ignored. In Languedoc Roussillon, we mainly observe, in March, a
regionally significant fall of the maxima and the sums. Simultaneously, a regionally significant increase of the maxima
and the sums has been observed in April. Moreover, we have observed, in the same way as previously, a regionally
significant fall of the number of days exceeding the threshold 20mm in March, and a significant increase in April.
Besides, we have applied this test to the data constituted of the two monthly sums of March and April: no trend has
been identified. Consequently, we can think that the most severe rainfall events in March have shifted today in April.
This gives substance to the idea of a seasonal gap in Languedoc Roussillon. Finally, a regional increasing trend of
annual maxima has also been detected in Cevennes.
Conclusion
Firstly, the implementation of these
regional statistical procedures requires a climatic zoning of the studied domain, homogeneous with regard to the
variables of interest. Secondly, it is necessary to properly consider the effects of cross-correlation in the data when
building a regional test. Finally, the causes of the detected unstationarities should be analysed: are there any changes
in meteorological factors like the surface pressure fields or the NOAA index that might explain the changes in rainfall
regime? Investigations of this question could be a future development of this first work.