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| Titel |
The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps |
| VerfasserIn |
K. Liechti, L. Panziera, U. Germann, M. Zappa |
| 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 ; 17, no. 10 ; Nr. 17, no. 10 (2013-10-10), S.3853-3869 |
| Datensatznummer |
250085950
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| Publikation (Nr.) |
 copernicus.org/hess-17-3853-2013.pdf |
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| Zusammenfassung |
This study explores the limits of radar-based forecasting for hydrological
runoff prediction. Two novel radar-based ensemble forecasting chains for
flash-flood early warning are investigated in three catchments in the
southern Swiss Alps and set in relation to deterministic discharge forecasts
for the same catchments. The first radar-based ensemble forecasting chain is
driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an
analogue-based heuristic nowcasting system to predict orographic rainfall for
the following eight hours. The second ensemble forecasting system evaluated
is REAL-C2, where the numerical weather prediction COSMO-2 is initialised
with 25 different initial conditions derived from a four-day nowcast with the
radar ensemble REAL. Additionally, three deterministic forecasting chains
were analysed. The performance of these five flash-flood forecasting systems
was analysed for 1389 h between June 2007 and December 2010 for which NORA
forecasts were issued, due to the presence of orographic forcing.
A clear preference was found for the ensemble approach. Discharge forecasts
perform better when forced by NORA and REAL-C2 rather then by deterministic
weather radar data. Moreover, it was observed that using an ensemble of
initial conditions at the forecast initialisation, as in REAL-C2,
significantly improved the forecast skill. These forecasts also perform
better then forecasts forced by ensemble rainfall forecasts (NORA)
initialised form a single initial condition of the hydrological model. Thus
the best results were obtained with the REAL-C2 forecasting chain. However,
for regions where REAL cannot be produced, NORA might be an option for
forecasting events triggered by orographic precipitation. |
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