Articles | Volume 14, issue 3
https://doi.org/10.5194/npg-14-193-2007
https://doi.org/10.5194/npg-14-193-2007
22 May 2007
22 May 2007

Meteorological uncertainty and rainfall downscaling

J. von Hardenberg, L. Ferraris, N. Rebora, and A. Provenzale

Abstract. We explore the sources of forecast uncertainty in a mixed dynamical-stochastic ensemble prediction chain for small-scale precipitation, suitable for hydrological applications. To this end, we apply the stochastic downscaling method RainFARM to each member of ensemble limited-area forecasts provided by the COSMO-LEPS system. Aim of the work is to quantitatively compare the relative weights of the meteorological uncertainty associated with large-scale synoptic conditions (represented by the ensemble of dynamical forecasts) and of the uncertainty due to small-scale processes (represented by the set of fields generated by stochastic downscaling). We show that, in current operational configurations, small- and large-scale uncertainties have roughly the same weight. These results can be used to pinpoint the specific components of the prediction chain where a better estimate of forecast uncertainty is needed.