On the Impact of Short-Range Meteorological Forecasts for Ensemble Streamflow Predictions

Guillaume Thirel,Eric Martin,Fabienne Rousset-Regimbeau,Florence Habets

doi:10.1175/2008jhm959.1

Abstract

Abstract Ensemble streamflow prediction systems are emerging in the international scientific community in order to better assess hydrologic threats. Two ensemble streamflow prediction systems (ESPSs) were set up at Météo-France using ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System for the first one, and from the Prévision d’Ensemble Action de Recherche Petite Echelle Grande Echelle (PEARP) ensemble prediction system of Météo-France for the second. This paper presents the evaluation of their capacities to better anticipate severe hydrological events and more generally to estimate the quality of both ESPSs on their globality. The two ensemble predictions were used as input for the same hydrometeorological model. The skills of both ensemble streamflow prediction systems were evaluated over all of France for the precipitation input and streamflow prediction during a 569-day period and for a 2-day short-range scale. The ensemble streamflow prediction system based on the PEARP data was the best for floods and small basins, and the ensemble streamflow prediction system based on the ECMWF data seemed the best adapted for low flows and large basins.

Highlights

The use of ensemble techniques for numerical weather prediction is well developed
The aim of the present study is to evaluate the skill of the ensemble streamflow prediction systems (ESPSs) based on the PEARP input and to compare it to the results already obtained with the European Centre for Medium-Range Weather Forecasts (ECMWF) EnsemblePrediction System (EPS) as input by using a large set of statistical scores and verifications
Despite a lack of spread, the validation showed that the PEARP has a good skill for short-range prediction of severe events when compared to the ECMWF EPS (Nicolau 2002)

Summary

Introduction

The use of ensemble techniques for numerical weather prediction is well developed. Several studies have shown promise for using meteorological ensemble prediction to produce probabilistic streamflow forecasts. In France, Rousset-Regimbeau et al (2007; following Habets et al 2004) used the ECMWF EPS to build an ensemble streamflow prediction system (ESPS) based on the three models Système d’analyse. Fournissant des renseignements atmospheriques à la neige (SAFRAN), the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface model, and the distributed hydrological model Modélisation Couplée (MODCOU) This suite of models is known as the SAFRAN–ISBA–MODCOU model (SIM) (Habets et al 2008). Several EPSs dedicated to shortterm forecasts have been constructed, such as the Prevision d’Ensemble Action de Recherche Petite Echelle Grande Echelle (PEARP) system (Nicolau 2002) This system was originally dedicated to predicting high impact storms in France. The probabilistic scores on the streamflows over all of France are presented, with a focus on the Seine River at Paris and the Ardèche River (a small basin in the south of France that is subject to extreme precipitation events)

Description of the SAFRAN–ISBA–MODCOU hydrometeorological model

Characteristics of the test

Findings

Conclusions