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To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model.

This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. The model combines the self-organizing map (SOM), which is a clustering technique, with a stepwise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The recent change in the Environmental Protection Agency’s surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S.