Hydrological post-processing using quantile regression algorithms constitutes a prime means of estimating the uncertainty hydrological predictions. Nonetheless, conventional large-sample theory for does not apply sufficiently far in tails probability distribution dependent variable. To overcome this limitation that could be crucial when interest lies on flood events, through extremal is introdu...

accurate quantitative precipitation forecasts (qpfs) have been always a demanding and challenging job in numerical weather prediction (nwp). the outputs of ensemble prediction systems (epss) in the form of probability forecasts provide a valuable tool for probabilistic quantitative precipitation forecasts (pqpfs). in this research, different configurations of wrf and mm5 meso-scale models form ...