Intercomparison of mesoscale meteorological models for precipitation forecasting - Université Toulouse III - Paul Sabatier - Toulouse INP Accéder directement au contenu
Article Dans Une Revue Hydrology and Earth System Sciences Discussions Année : 2003

Intercomparison of mesoscale meteorological models for precipitation forecasting

Résumé

In the framework of the RAPHAEL EU project, a series of past heavy precipitation events has been simulated with different meteorological models. Rainfall hindcasts and forecasts have been produced by four models in use at various meteorological services or research centres of Italy, Canada, France and Switzerland. The paper is focused on the comparison of the computed precipitation fields with the available surface observations. The comparison is carried out for three meteorological situations which lead to severe flashflood over the Toce-Ticino catchment in Italy (6599 km2) or the Ammer catchment (709 km2) in Germany. The results show that all four models reproduced the occurrence of these heavy precipitation events. The accuracy of the computed precipitation appears to be more case-dependent than model-dependent. The sensitivity of the computed rainfall to the boundary conditions (hindcast v. forecast) was found to be rather weak, indicating that a flood forecasting system based upon a numerical meteo-hydrological simulation could be feasible in an operational context.

Keywords: meteorological models, precipitation forecast

Fichier principal
Vignette du fichier
hess-7-799-2003.pdf (825.87 Ko) Télécharger le fichier
Origine : Accord explicite pour ce dépôt
Loading...

Dates et versions

hal-00330864 , version 1 (18-06-2008)

Identifiants

  • HAL Id : hal-00330864 , version 1

Citer

E. Richard, S. Cosma, R. Benoit, P. Binder, A. Buzzi, et al.. Intercomparison of mesoscale meteorological models for precipitation forecasting. Hydrology and Earth System Sciences Discussions, 2003, 7 (6), pp.799-811. ⟨hal-00330864⟩
151 Consultations
97 Téléchargements

Partager

Gmail Facebook X LinkedIn More