Abstract
Weather forecasts are often accurate but never exact. Forecasting must be treated in part therefore as a random process with errors distributed according to some probability distribution. It is important for us to quantify these error distributions not only as a guide to users of the forecasts but also as a measure of progress in the development of improved forecasting methods. A general theory of observation and prediction error was first formulated by Gauss (1809) for orbit calculations in celestial mechanics and has since been applied in many fields of science and technology.
On leave from the National Center for Atmospheric Research which is sponsored by the National Science Foundation.
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© 1984 Springer-Verlag, Berlin Heidelberg
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Leith, C.E. (1984). Statistical Methods for the Verification of Long and Short Range Forecasts. In: Burridge, D.M., Källén, E. (eds) Problems and Prospects in Long and Medium Range Weather Forecasting. Topics in Atmospheric and Oceanographic Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82132-5_7
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DOI: https://doi.org/10.1007/978-3-642-82132-5_7
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