Ensemble Hydrometeorological Forecasting in Denmark

teorological extremes such as flood and droughts cause economical and live losses that could be, if not prevented, at least dampened if sufficient time is given to respond to potential threats. This is the ultimate purpose of forecasting which then translates into making reliable predictions. However, this is by no means an easy task. The ever growing and albeit still limited availability of data together with the limiting computational power, in addition to the lack of understanding of some atmospheric/hydrological processes, lead to biased models. Precipitation is often regarded as one of the main sources of uncertainty in hydrological forecasts. This is the reason why substantiated efforts to include information from Numerical Weather Predictors (NWP) or General Circulation Models (GCM) have been made over the last couple of decades. The present thesis expects to advance the field of ensemble hydrometeorological forecasting by evaluating the added value of NWP and GCM ensemble prediction systems (EPS) for hydrological purposes. The use of NWP EPS that differ in both spatial and temporal resolution to feed a hydrological model for discharge forecasts at specific points, revealed two major findings. First, for the forecast-observation data set used in this study, precipitation forecasts with higher spatial resolution have a lower accuracy than that of the coarser spatial resolution, especially at higher values of precipitation. Second, discharge forecasts seem to dampen these differences. One possible explanation to the first point, the difference in quality between the systems, might be the double penalty issue of higher resolution models, one for not predicting rainfall where it rains and an additional penalty for predicting it where it does not rain (displacement error). Finally, the combination of errors in precipitation forecasts, together with the errors in the hydrological model affect the quality of discharge forecasts either by increasing their