TIGGE: Preliminary results on comparing and combining ensembles

TIGGE, the THORPEX Interactive Grand Global Ensemble, is a World Weather Research Programme project to accelerate the improvements in the accuracy of 1-day to 2-week high-impact weather forecasts. This report discusses some preliminary results from predictability Studies based on the ensemble data exchanged within TIGGE, and available at the TIGGE archive centres. In the first part of this work. the key characteristics of the eight ensemble systems available in the TIGGE database at the time of writing (December 2007) are compared, and the strengths and weaknesses of each system are highlighted. Then, issues related to the generation of multi-model/multi-analysis ensemble products are discussed. and some preliminary results on the potential value of combining different ensembles to generate medium-range products with a grand multi-model/multi-analysis global ensemble are presented. One of the key results documented in this work is the large difference between the performance of the single ensembles: for Z500 over the Northern Hemisphere. in the medium-range (say around forecast day 5), the difference between the worst and the best control or ensemble-mean forecasts is about 2 days of predictability, while the difference between the worst and the best probabilistic predictions can be larger, about 3 days of predictability. Another key result has been the quantification of the difference between the skill of the best ensemble system and a combined ensemble generated considering LIP to four different ensemble systems. Results have indicated that the difference is very small in areas where the European Centre (EC) ensemble system has a well tuned ensemble spread. equivalent to less than 6 hours of predictability in the medium range, while it is larger and more detectable in areas where the EC system has a too low ensemble spread (e.g. in the Tropics). Copyright (C) 2008 Royal Meteorological Society