Assessing Entropy-based Bayesian Model Averaging Method for Probabilistic Precipitation Forecasting

Abstract Bayesian Model Averaging (BMA) is a popular ensemble-based post-processing approach where the weighted average of the individual members is used to generate predictive forecasts. As the BMA formulation is based on the law of total probability, possessing the ensemble of forecasts with mutually exclusive and collectively exhaustive properties is one of the main BMA inherent assumptions. Trying to meet these …