A comprehensive statistical analysis for residuals of wind speed and direction from numerical weather prediction for wind energy

Wind data are vital for the research in renewable energy research. Their quality from numerical weather prediction significantly influences wind models. This paper utilizes a comprehensive statistical analysis analyzing predictive errors, named residuals of speed and direction modeled by The analysis, taken an Arctic site as example, effectively integrates inference, probabilistic modeling, hypothesis tests. It is proven that still contain important meteorological information. introduced may be used to replenish explore complex intrinsic properties models contributions modeling.