Location robust estimation of predictive Weibull parameters in short-term wind speed forecasting

From turbine control systems at wind farms to extreme weather early-warning systems, short-term probabilistic wind speed forecasts are seeing widespread use in industrial applications. Successful modern forecast methods, often Weibull-based, have been shown to be extremely sensitive to even minor changes in location. We contend that this lack of robustness stems not from model selection, but rather the parameter estimation methods used, and propose a new proper scoring rule to be dynamically minimized. Tested on a weather array spanning the islands of Japan, we verify both superior short-term forecasting performance and model fit of the proposed method over all standard references, and empirically confirm the desired location robustness.