Ensemble prediction with OpenIFS

Probabilistic forecasts provide information on how predictions of the atmospheric evolution may differ from the best guess solution provided by a deterministic forecast. Ensemble prediction systems generate this information through assessing uncertainties in both the model initial state and the model itself. In order to open up ensemble prediction research for a wider research community, we have recreated all 50+1 operational ECMWF ensemble initial states for OpenIFS. The data set covers one year (December 2016 to November 2017) twice a day. A range of model resolutions are provided to cover different research needs (TL159, TL399 and TL639). The probabilistic skill of OpenIFS ensembles using these initial states is showcased. A case study of typhoon Damrey, which severely affected Vietnam in 2017, will also be presented.