Comprehensive validation of 68 wind speed models highlights the benefits of ensemble approaches

Many different wind speed models support assessing the wind climate. Depending on their development, spatiotemporal resolution, and intended use, typical wind speed model types are wind atlases, reanalysis products, regional climate, and global climate models. They realistically represent different properties of the wind climate. For the first time, 68 wind speed models of different types are assessed for their predictive power for (1) mean wind speed, (2) wind speed distribution, and (3) temporal variability. In addition, eight ensembles of individual models from each model type are created and validated. The hypothesis is tested that ensembles of wind speed models generally improve model accuracy. For the validation, 148 wind speed time series with a data availability of at least ten years in 1979 to 2014 were used. The measurement sites were separated into flat and open, and mountainous locations. The results reveal the improved model performance of ensembles compared to individual models. Only wind atlases are capable of estimating wind speed properties at mountainous locations. Their median coefficient of determination related to mean wind speed at mountainous sites is 0.81 but less than 0.15 for any other model type. One important conclusion is that individual models may not be appropriate for wind resource assessment without prior validation. Furthermore, ensembles are recommended to improve predictive power for any wind climate properties. The results indicate how well the different model types can reproduce the analyzed wind speed characteristics.

Automated summary

Assessing the wind climate involves various wind speed models, including wind atlases, reanalysis products, regional climate, and global climate models. This study evaluated 68 wind speed models of different types for their predictive power on mean wind speed, wind speed distribution, and temporal variability. Ensembles of models were found to improve model accuracy compared to individual models, with wind atlases showing the best performance at mountainous locations. It is concluded that individual models should be validated before use, and ensembles are recommended for better predictive power.