Impact of increasing heat waves on US ozone episodes in the 2050s: Results from a multimodel analysis using extreme value theory

We develop a statistical model using extreme value theory to estimate the 2000-2050 changes in ozone episodes across the United States. We model the relationships between daily maximum temperature (T-max) and maximum daily 8 h average (MDA8) ozone in May-September over 2003-2012 using a Point Process (PP) model. At similar to 20% of the sites, a marked decrease in the ozone-temperature slope occurs at high temperatures, defined as ozone suppression. The PP model sometimes fails to capture ozone-T-max relationships, so we refit the ozone-T-max slope using logistic regression and a generalized Pareto distribution model. We then apply the resulting hybrid-extreme value theory model to projections of T-max from an ensemble of downscaled climate models. Assuming constant anthropogenic emissions at the present level, we find an average increase of 2.3 d a(-1) in ozone episodes (> 75 ppbv) across the United States by the 2050s, with a change of +3-9d a(-1) at many sites.