Recently Stanford and Ziemke developed a model for predicting total column ozone (Omega) from lower stratospheric temperatures and a pre-calculated look-up table based on several years of satellite ozone observations. The present paper extends that work by examining correlations between Omega and a number of other dynamical variables. Omega prediction models based on multiple dynamical variables are not found to reduce prediction errors over the single-variable model. This is attributed to observational and computational noise. Further results from the temperature-dependent Omega prediction model reveal that it captures medium scale Omega features well in summer midlatitudes of both hemispheres and that, depending on the accuracy of predicted temperatures from operational forecasts, Omega predictions may be made a number of days in advance. Because solar ultraviolet reaching the earth's surface is exponentially dependent on Omega, these results may be useful for UV predictions a number of days in advance in the biologically important summer seasons.