THE ECONOMIC VALUE OF ENSEMBLE-BASED WEATHER FORECASTS

THE ECONOMIC VALUE OF ENSEMBLE-BASED WEATHER FORECASTS The potential economic benefit associated with the use of an ensemble of forecasts versus an equivalent or higher-resolution control forecast is discussed. Neither forecast systems are postprocessed, 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 prevent weather-related damages, and the loss that they incur in case they do not protect their operations. It is shown 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 economic benefit than a control forecast, even if the latter is run at higher horizontal resolution. It is argued that the added benefits derive from 1) the fact that the ensemble provides a more detailed forecast probability distribution, allowing the users to tailor their weather forecastrelated actions to their particular costloss situation, and 2) the ensemble's ability to differentiate between high-and 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 as ensembles do. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

THE ECONOMIC VALUE OF ENSEMBLE-BASED WEATHER FORECASTS

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/1520-0477(2002)083<0073:TEVOEB>2.3.CO;2
Publisher site
See Article on Publisher Site

Abstract

The potential economic benefit associated with the use of an ensemble of forecasts versus an equivalent or higher-resolution control forecast is discussed. Neither forecast systems are postprocessed, 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 prevent weather-related damages, and the loss that they incur in case they do not protect their operations. It is shown 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 economic benefit than a control forecast, even if the latter is run at higher horizontal resolution. It is argued that the added benefits derive from 1) the fact that the ensemble provides a more detailed forecast probability distribution, allowing the users to tailor their weather forecastrelated actions to their particular costloss situation, and 2) the ensemble's ability to differentiate between high-and 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 as ensembles do.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Jan 2, 2002

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