Comparison of a 51-Member Low-Resolution (TL399L62) Ensemble with a 6-Member High-Resolution (TL799L91) Lagged-Forecast Ensemble

Abstract

Abstract The 51-member TL399L62 ECMWF ensemble prediction system (EPS51) is compared with a lagged ensemble system based on the six most recent ECMWF TL799L91 forecasts (LAG6). The EPS51 and LAG6 systems are compared to two 6-member ensembles with a “weighted” ensemble-mean: EPS6wEM and LAG6wEM. EPS6wEM includes six members of EPS51 and has the ensemble mean constructed giving optimal weights to its members, while LAG6wEM includes the LAG6 six members and has the ensemble mean constructed giving optimal weights to its members. In these weighted ensembles, the optimal weights are based on 50-day forecast error statistics of each individual member (in EPS51 and LAG6 the ensemble mean is constructed giving the same weight to each individual member). The EPS51, LAG6, EPS6wEM, and LAG6wEM ensembles are compared for a 7-month period (from 1 April to 30 October 2006—213 cases) and for two of the most severe storms that hit the Scandinavian countries since 1969. The study shows that EPS51 has the best-tuned ensemble spread, and provides the best probabilistic forecasts, with differences in predictability between EPS51 and LAG6 or LAG6wEM probabilistic forecasts of geopotential height anomalies of up to 24 h. In terms of ensemble mean, EPS51 gives the best forecast from forecast day 4, but before forecast day 4 LAG6wEM provides a slightly better forecast, with differences in predictability smaller than 2 h up to forecast day 6, and of about 6 h afterward. The comparison also shows that a larger ensemble size is more important in the medium range rather than in the short range. Overall, these results indicate that if the aim of ensemble prediction is to generate not only a single (most likely) scenario but also a probabilistic forecast, than EPS51 has a higher skill than the lagged ensemble system based on LAG6 or LAG6wEM.