Statistical processing of forecasts for hydrological ensemble prediction: a comparative study of different bias correction strategies
Article, Unknown, Other literature type
Zalachori , I.
Ramos , M.H.
Garçon , R.
Mathevet , T.
Gailhard , J.
- Publisher: HAL CCSD
[ SDE ] Environmental Sciences | FLOW FORECASTING | PREVISION HYDROLOGIQUE | BIAS CORRECTION | ENSEMBLE PREDICTION | HYDROLOGICAL FORECAST | STATISTICAL MODEL | MODELE STATISTIQUE | PREVISION METEOROLOGIQUE | WEATHER FORECASTING | PREVISION DE DEBIT | STREAMFLOW FORECAST
arxiv: Physics::Geophysics | Physics::Atmospheric and Oceanic Physics
The aim of this paper is to investigate the use of statistical correction
techniques in hydrological ensemble prediction. Ensemble weather forecasts
(precipitation and temperature) are used as forcing variables to a
hydrologic forecasting model for the production of ensemble streamflow
forecasts. The impact of different bias correction strategies on the quality
of the forecasts is examined. The performance of the system is evaluated
when statistical processing is applied: to precipitation and temperature
forecasts only (<i>pre-processing</i> from the hydrological model point of view), to flow
forecasts (<i>post-processing</i>) and to both. The pre-processing technique combines
precipitation ensemble predictions with an analog forecasting approach,
while the post-processing is based on past errors of the hydrological model
when simulating streamflows. Forecasts from 11 catchments in France are
evaluated. Results illustrate the importance of taking into account
hydrological uncertainties to improve the quality of operational streamflow