Abstract
The numerical 6-hourly output from the six-layer NMC PE model is used to predict the average daytime cloudiness in the spring for Boston. The variables chosen as predictors are the PE model predictions of the mean surface to 500-mb relative humidity, the 700-mb vertical velocity, and the relative humidity trend through a 12-hr period. The cloud forecasts are obtained using a regression equation. The results demonstrate forecasting skill, in contrast to persistence, which is shown to be a poor predictor.
