The COST-731 action is focused on uncertainty propagation in hydrometeorological forecasting chains. Goals and activities of the action Working Group 2 are presented. Five foci for discussion and research have been identified: (1) understand uncertainties, (2) exploring, designing and comparing methodologies for the use of uncertainty in hydrological models, (3) providing feedback on sensitivity to data and forecast providers, (4) transferring methodologies among the different communities involved and (5) setting up test-beds and perform proof-of-concepts. Current examples of different perspectives on uncertainty propagation are presented.
Using a 20-yr ECMWF ensemble reforecast dataset of total precipitation and a 20-yr dataset of a dense precipitation observation network in the Netherlands, a comparison is made between the raw ensemble output, Bayesian model averaging (BMA), and extended logistic regression (LR). A previous study indicated that BMA and conventional LR are successful in calibrating multimodel ensemble forecasts of precipitation for a single forecast projection. However, a more elaborate comparison between these methods has not yet been made. This study compares the raw ensemble output, BMA, and extended LR for single-model ensemble reforecasts of precipitation; namely, from the ECMWF ensemble prediction system (EPS). The raw EPS output turns out to be generally well calibrated up to 6 forecast days, if compared to the area-mean 24-h precipitation sum. Surprisingly, BMA is less skillful than the raw EPS output from forecast day 3 onward. This is due to the bias correction in BMA, which applies model output statistics to individual ensemble members. As a result, the spread of the bias-corrected ensemble members is decreased, especially for the longer forecast projections. Here, an additive bias correction is applied instead and the equation for the probability of precipitation in BMA is also changed. These modifications to BMA are referred to as ''modified BMA'' and lead to a significant improvement in the skill of BMA for the longer projections. If the area-maximum 24-h precipitation sum is used as a predictand, both modified BMA and extended LR improve the raw EPS output significantly for the first 5 forecast days. However, the difference in skill between modified BMA and extended LR does not seem to be statistically significant. Yet, extended LR might be preferred, because incorporating predictors that are different from the predictand is straightforward, in contrast to BMA.
Cooperation in Science and Technology (COST) funding allows European scientists to establish international links, communicate their work to colleagues, and promote international research cooperation. COST731 was established to study the propagation of uncertainty from hydrometeorological observations through meteorological and hydrological models to the final flood forecast. Our focus is on how information about uncertainty is presented to the end user and how it is used. COST731 has assembled a number of demonstrations/case studies that illustrate a variety of practical approaches and these are presented here. While there is yet no consensus on how such information is presented, many end users do find it useful.
The development and verification of a new model output statistics (MOS) system is described; this system is intended to help forecasters decide whether a weather alarm for severe thunderstorms, based on high total lightning intensity, should be issued in the Netherlands. The system consists of logistic regression equations for both the probability of thunderstorms and the conditional probability of severe thunderstorms in the warm half-year (from mid-April to mid-October). These equations have been derived for 12 regions of about 90 km ϫ 80 km each and for projections out to 12 h in advance (with 6-h periods). As a source for the predictands, reprocessed total lightning data from the Surveillance et d'Alerte Foudre par Interférométrie Radioélectrique (SAFIR) network have been used. The potential predictor dataset not only consisted of the combined postprocessed output from two numerical weather prediction (NWP) models, as in previous work by the first three authors, but it also contained an ensemble of advected radar and lightning data for the 0-6-h projections. The NWP model output dataset contained 17 traditional thunderstorm indices, computed from a reforecasting experiment with the High-Resolution Limited-Area Model (HIRLAM) and postprocessed output from the European Centre for Medium-Range Weather Forecasts (ECMWF) model. Brier skill scores and attributes diagrams show that the skill of the MOS thunderstorm forecast system is good and that the severe thunderstorm forecast system generally is also skillful, compared to the 2000-04 climatology, and therefore, the preoperational system was made operational at the Royal Netherlands Meteorological Institute (KNMI) in 2008.
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