A fog forecasting method in a deeply embanked valley.

This paper presents a statistical model used to forecast fog in the Meuse Valley in Belgium. The method is a bootstrap discriminant analysis using eight predictors: river surface temperature, air pressure, air temperature at two elevations, wind speed and relative humidity at the same two locations. These data are measured from November 1989 to April 1990. Tests are done to determine the number of resampling needed for this data set and the optimum projection delay for prediction from the meteorological data. The best results are obtained for the prediction at 0700h UT using meteorological data at 0400 h UT.