A study to determine the relative skill of four model output statistics prediction methods using simulated data fields.
Fatjo, Steve J.
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This report describes the testing of four Model Output Statistics prediction methods on simulated data fields for the purpose of determining their relative skills in forecasting a generic weather parameter (predictand) . Of the four methods, three use Bayes Law of Inverse Probability to discriminate, while the other method uses conditional probability. The simulated data sets, models and observers necessary to accomplish this goal are created according to a uniquely developed simulation design. The results indicate that there is a definite difference in the ability of one of the four methods, namely the method using conditional probability, to forecast the weather parameter. Through the use of the Analysis of Variance (ANOVA) technique, this difference is found to be significant with respect to chance.
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