How to Choose Credible Ensemble Members of Temperature and Precipitation Long-Range Forecasts for Summer in Central Europe?

Long-range forecasts provide information about expected future atmospheric and oceanic conditions averaged over periods of one to three months and are attractive for many sectors.

Dynamical forecasting employs full, three-dimensional models of the climate to explicitly simulate possible changes in the atmosphere and ocean over the next few months based on current conditions.  Ensembles of simulations of possible weather scenarios are run and provide probabilities of how likely it is that a season will be wetter, drier, warmer, or colder compared to the average for that period of the year.  Is it possible to choose the most credible (or at least more credible) members of ensembles?

This study considers four seasonal forecasting systems available in the Copernicus Climate Change Service (C3S) archive which provide near-surface air temperature and precipitation data at 1°by 1°spatial resolution: European Centre for Medium-range Weather Forecast System SEAS5 (ECMWF), Météo – France System 8 (MF), Deutscher Wetterdienst GCFS 2.1 (DWD) and Centro Euro-Mediterraneo sui Cambiamenti Climatici SPSv3.5 (CMCC). We focus on summer forecasts (the starting date is May 1st) in the period 1993–2016 (the longest period of hindcasts common to all systems) and the domain of the Czech Republic in Central Europe (latitude 47-52°N, longitude 11-20°E). E-OBS daily gridded observational datasets for precipitation and temperature at 0.25°spatial resolution are used as a reference.

Each model has several tens ensemble members of the long-range forecast. Based on correlations between modeled and observed air temperature a precipitation patterns in the first days, we try to find the most credible (or at least more credible) ensemble members for the domain of the Czech Republic for further processing.