Many tools exist for predicting ozone concentrations.
Forecasters combine the results of these tools to create a consensus forecast, which tends to be more accurate than the results from a single tool since one tool s strengths balance another s limitations. Although not very useful as a predictive tool alone, forecasters use this information to guide and bound their forecasts. Using a table like the one shown here, a forecaster can determine that the occurrence of several days of ozone concentrations above 0.15 ppm in the Sacramento region in June is highly unlikely. This technique is based on the fact that specific values of certain meteorological and air quality variables are associated with high ozone concentrations. For example, high ozone concentrations are often correlated with hot temperatures and, thus, forecasted hot temperatures indicate a potential for high ozone concentrations.