The Economic Value Of Ensemble-Based Weather Forecasts

Abstract

The potential economic benefit associated with the use of an ensemble of forecasts versus anequivalent or higher-resolution control forecast is discussed. Neither forecast systems are post-processed,except a simple calibration that is applied to make them reliable. A simple decision-making model is used where all potential users of weather forecasts are characterized by the ratio between the cost of their action to preventweather-related damages, and the loss that they incur in case they do not protect their operations. It isshown that the ensemble forecast system can be used by a much wider range of users. Furthermore,for many, and for beyond 4-day lead time for all users, the ensemble provides greater potential economicbenefit than a control forecast, even if the latter is run at higher horizontal resolution. It is argued that theadded benefits derive from 1) the fact that the ensemble provides a more detailed forecast probabilitydistribution, allowing the users to tailor their weather forecast-related actions to their particular cost-loss situation, and 2) the ensemble's ability to differentiate between highand low-predictability cases. While single forecasts can statistically be supplemented by more detailed probability distributions, it is not clear whether with more sophisticated postprocessing they can identify more and less predictable forecast cases as successfully asensembles do.