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| Titel |
Introducing a rainfall compound distribution model based on weather patterns sub-sampling |
| VerfasserIn |
F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, P. Bernardara |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 14, no. 6 ; Nr. 14, no. 6 (2010-06-16), S.951-964 |
| Datensatznummer |
250012335
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| Publikation (Nr.) |
 copernicus.org/hess-14-951-2010.pdf |
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| Zusammenfassung |
This paper presents a probabilistic model for daily rainfall, using
sub-sampling based on meteorological circulation. We classified eight typical
but contrasted synoptic situations (weather patterns) for France and
surrounding areas, using a "bottom-up" approach, i.e. from the shape of the
rain field to the synoptic situations described by geopotential fields. These
weather patterns (WP) provide a discriminating variable that is consistent
with French climatology, and allows seasonal rainfall records to be split
into more homogeneous sub-samples, in term of meteorological genesis.
First results show how the combination of seasonal and WP sub-sampling
strongly influences the identification of the asymptotic behaviour of
rainfall probabilistic models. Furthermore, with this level of
stratification, an asymptotic exponential behaviour of each sub-sample
appears as a reasonable hypothesis. This first part is illustrated with two
daily rainfall records from SE of France.
The distribution of the multi-exponential weather patterns
(MEWP) is then defined as the composition, for a given season, of all WP
sub-sample marginal distributions, weighted by the relative frequency of
occurrence of each WP. This model is finally compared to Exponential and
Generalized Pareto distributions, showing good features in terms of
robustness and accuracy. These final statistical results are computed from a
wide dataset of 478 rainfall chronicles spread on the southern half of
France. All these data cover the 1953–2005 period. |
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