Kai Sattler

Development of a European flood forecasting system

Abstract Recent advances in meteorological forecast skill now enable significantly improved estimates of precipitation quantity, timing and spatial distribution to be made up to 10 days ahead for model scales of 40 km in forecast mode. Here we outline a prototype methodology to downscale these precipitation estimates using regional Numerical Weather Prediction models to spatial scales appropriate to hydrological forecasting and then use these to drive high‐resolution scale (1 or 5 km grid scale) water balance and rainfall‐runoff models. The aim is to develop a European Flood Forecasting System (EFFS) and determine what flood forecast skill can be achieved for given basins, meteorological events and prediction products. The output from the system is a probabilistic assessment of n‐day ahead discharge exceedence risk (where n < 10) for the whole of Europe at 5 km resolution which may then be updated as the forecast lead time reduces. At each stage the discharge estimates can be used to drive detailed (25–100 m resolution) hydraulic models to estimate the flood inundation which may potentially occur. Initial results are presented from a prototype version of the system used to perform a hindcast of the January 1995 flooding events in NW‐Europe (Rhine, Meuse).

From wind ensembles to probabilistic information about future wind power production -- results from an actual application

Meteorological ensemble forecasts aim at quantifying the uncertainty of the future development of the weather by supplying several possible scenarios of this development. Here we address the use of such scenarios in probabilistic forecasting of wind power production. Specifically, for each forecast horizon we aim at supplying quantiles of the wind power production conditional on the information available at the time at which the forecast is generated. This involves: (i) transformation of meteorological ensemble forecasts into wind power ensemble forecasts and (ii) calculation of quantiles based on the wind power ensemble forecasts. Given measurements of power production, representing a region or a single wind farm, we have developed methods applicable for these two steps. While (ii) should in principle be a simple task we found that the probabilistic information contained in the wind power ensembles from (i) cannot be used directly and therefore both (i) and (ii) requires statistical modelling. Based on these findings an demo-application, supplying quantile forecasts for operational horizons of up to approximately 6 days, was developed for two utilities participating in a common project. The application use ECMWF-ensembles. One setup corresponds to an offshore wind farm (Nysted, Denmark) and one corresponds to regional forecasting (Western Denmark). In the paper we analyze the results obtained from 8 months of actual operation of this system. It is concluded that the demo-application produce reliable forecasts. The average difference between the 75% and 25% quantile forecasts exceeds 50% of the installed capacity for horizons longer than approximately 4 days for the wind farm setup. For the regional forecasts the corresponding horizon is not reached within 7 days, which is the maximum horizon available. The ability of the demo-application to differentiate between situations with low and high uncertainty is analysed. Also, the relation between the forecasted uncertainty and the actual skill of a point forecast is analysed. A satisfactory agreement is observed