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| Titel |
Modelling of monsoon rainfall for a mesoscale catchment in North-West India I: assessment of objective circulation patterns |
| VerfasserIn |
E. Zehe, A. K. Singh, A. Bárdossy |
| 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 ; 10, no. 6 ; Nr. 10, no. 6 (2006-10-30), S.797-806 |
| Datensatznummer |
250008283
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| Publikation (Nr.) |
 copernicus.org/hess-10-797-2006.pdf |
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| Zusammenfassung |
| Within the present study we shed light on the question whether objective
circulation patterns (CP) classified from either the 500 HPa or the 700 HPa
level may serve as predictors to explain the spatio-temporal variability of
monsoon rainfall in the Anas catchment in North West India. To this end we
employ a fuzzy ruled based classification approach in combination with a
novel objective function as originally proposed by (Stehlik and BᲤossy,
2002). After the optimisation we compare the obtained circulation
classification schemes for the two pressure levels with respect to their
conditional rainfall probabilities and amounts. The classification scheme for
the 500 HPa level turns out to be much more suitable to separate dry from wet
meteorological conditions during the monsoon season. As is shown during a
bootstrap test, the CP conditional rainfall probabilities for the wet and the
dry CPs for both pressure levels are highly significant at levels ranging
from 95 to 99%. Furthermore, the monthly CP frequencies of the wettest CPs
show a significant positive correlation with the variation of the total
number of rainy days at the monthly scale. Consistently, the monthly
frequencies of the dry CPs exhibit a negative correlation with the number of
rainy days at the monthly scale. The present results give clear evidence that
the circulation patterns from the 500 HPa level are suitable predictors for
explaining spatio- temporal Monsoon variability. A companion paper shows that
the CP time series obtained within this study are suitable input into a
stochastical rainfall model. |
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