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| Titel |
The use of meteorological analogues to account for LAM QPF uncertainty |
| VerfasserIn |
T. Diomede, F. Nerozzi, T. Paccagnella, E. Todini |
| 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 ; 12, no. 1 ; Nr. 12, no. 1 (2008-01-31), S.141-157 |
| Datensatznummer |
250010465
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| Publikation (Nr.) |
 copernicus.org/hess-12-141-2008.pdf |
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| Zusammenfassung |
| Flood predictions based on quantitative precipitation forecasts (QPFs)
provided by deterministic models do not account for the uncertainty in the
outcomes. A probabilistic approach to QPF, one which accounts for the
variability of phenomena and the uncertainty associated with a hydrological
forecast, seems to be indispensable to obtain different future flow
scenarios for improved flood management. A new approach based on a search
for analogues, that is past situations similar to the current one under
investigation in terms of different meteorological fields over Western
Europe and East Atlantic, has been developed to determine an ensemble of
hourly quantitative precipitation forecasts for the Reno river basin, a
medium-sized catchment in northern Italy. A statistical analysis, performed
over a hydro-meteorological archive of ECMWF analyses at 12:00 UTC relative
to the autumn seasons ranging from 1990 to 2000 and the corresponding
precipitation measurements recorded by the raingauges spread over the
catchment of interest, has underlined that the combination of geopotential
at 500 hPa and vertical velocity at 700 hPa provides a better estimation of
precipitation. The analogue-based ensemble prediction has to be considered
not alternative but complementary to the deterministic QPF provided by a
numerical model, even when employed jointly to improve real-time flood
forecasting. In the present study, the analogue-based QPFs and the
precipitation forecast provided by the Limited Area Model LAMBO have been
used as different input to the distributed rainfall-runoff model TOPKAPI,
thus generating, respectively, an ensemble of discharge forecasts, which
provides a confidence interval for the predicted streamflow, and a
deterministic discharge forecast taken as an error-affected "measurement"
of the future flow, which does not convey any quantification of the forecast
uncertainty. To make more informative the hydrological prediction, the
ensemble spread could be regarded as a measure of the uncertainty of the
deterministic forecast. |
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