This work presents the performance analysis of a multi-model ensemble of wave climate projections in the Mediterranean Sea against hindcast data. The wave projections were developed with the numerical model Wavewatch III forced by surface wind fields of 17 EURO-CORDEX GCM-RCMs providing time series of the main wave parameters on a 3-h and 10-km resolution. The performance of the wave GCM-RCM simulations during the baseline period (1979–2005) was assessed by means of the deterministic metrics RMSE and Bias. Different bias correction methodologies were analyzed by means of the application of the widespread Empirical Quantile Mapping method considering different time periods of significant wave height in order to analyze the ability of the bias-correcting methods to capture the different wave climate temporal scales ranging from storm events, monthly, seasonal and interannual variability. The results show that the use of the EQM method for the full-time series without taking into account other timescales, can lead to increased biases in some regions and seasons and that the use of time-dependent bias-correction techniques leads to an improved accurate characterization of biases considering the interannual temporal variability of significant wave height. More specifically the use of the EQM method for monthly data provides a good performance in capturing the correlation and interannual temporal variability of wave climate.

Various methods are available for assessing uncertainties in climate impact studies. Among such methods, model weighting by expert elicitation is a practical way to provide a weighted ensemble of models for specific real-world impacts. The aim is to decrease the influence of improbable models in the results and easing the decision-making process. In this study both climate and hydrological models are analysed, and the result of a research experiment is presented using model weighting with the participation of six climate model experts and six hydrological model experts. For the experiment, seven climate models are a priori selected from a larger EURO-CORDEX (Coordinated Regional Downscaling Experiment – European Domain) ensemble of climate models, and three different hydrological models are chosen for each of the three European river basins. The model weighting is based on qualitative evaluation by the experts for each of the selected models based on a training material that describes the overall model structure and literature about climate models and the performance of hydrological models for the present period. The expert elicitation process follows a three-stage approach, with two individual rounds of elicitation of probabilities and a final group consensus, where the experts are separated into two different community groups: a climate and a hydrological modeller group. The dialogue reveals that under the conditions of the study, most climate modellers prefer the equal weighting of ensemble members, whereas hydrological-impact modellers in general are more open for assigning weights to different models in a multi-model ensemble, based on model performance and model structure. Climate experts are more open to exclude models, if obviously flawed, than to put weights on selected models in a relatively small ensemble. The study shows that expert elicitation can be an efficient way to assign weights to different hydrological models and thereby reduce the uncertainty in climate impact. However, for the climate model ensemble, comprising seven models, the elicitation in the format of this study could only re-establish a uniform weight between climate models.