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Titel |
Meteorological uncertainty and rainfall downscaling |
VerfasserIn |
J. Hardenberg, L. Ferraris, N. Rebora, A. Provenzale |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1023-5809
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Digitales Dokument |
URL |
Erschienen |
In: Nonlinear Processes in Geophysics ; 14, no. 3 ; Nr. 14, no. 3 (2007-05-22), S.193-199 |
Datensatznummer |
250012193
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Publikation (Nr.) |
copernicus.org/npg-14-193-2007.pdf |
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Zusammenfassung |
We explore the sources of forecast uncertainty in
a mixed dynamical-stochastic ensemble
prediction chain for small-scale precipitation, suitable for hydrological applications.
To this end, we apply the stochastic downscaling method RainFARM to
each member of ensemble limited-area
forecasts provided by the COSMO-LEPS system.
Aim of the work is to quantitatively compare
the relative weights of the meteorological uncertainty associated with
large-scale synoptic conditions (represented by the ensemble of dynamical
forecasts) and of the uncertainty due to small-scale processes
(represented by the set of fields
generated by stochastic downscaling). We show that, in current operational
configurations, small- and large-scale uncertainties have roughly the same
weight. These results can be used to pinpoint the specific components of the
prediction chain where a better estimate of forecast uncertainty is needed. |
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