Probabilistic forecasting of temperature: comments on the Bayesian Model Averaging approach

Abstract

A specific implementation of Bayesian model averaging has recently been suggested as a method for the calibration of ensemble temperature forecasts. We point out the similarities between this new approach and an earlier method known as kernel regression. We also argue that the Bayesian model averaging method (as applied) has a number of flaws that would result in forecasts with suboptimally calibrated mean and uncertainty.