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On Measuring Quality of a Probabilistic Commodity Forecast for a System That Incorporates Seasonal Climate Forecasts by A. B. Potgieter; Y. L. Everingham; G. L. Hammer is a Environmental Science article available to read on EtoBox.

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## Abstract Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision‐making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution.

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Author

A. B. Potgieter; Y. L. Everingham; G. L. Hammer

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0899-8418)

Published

2003

Language

EN

Field

Environmental Science (Physical Sciences)