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

Abstract

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 (<i>Tmax</i>) and maximum daily 8-hour average (MDA8) ozone in May-September over 2003-2012 using a Point Process (PP) model. At ~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-<i>Tmax</i> relationships, and so we refit the ozone-<i>Tmax</i> slope using logistic regression and a Generalized Pareto Distribution model. We then apply the resulting hybrid-EVT model to projections of <i>Tmax</i> from an ensemble of downscaled climate models. Assuming constant anthropogenic emissions at the present level, we find an average increase of 2.3 days a^-1 in ozone episodes (> 75 ppbv) across the United States by the 2050s, with a change of +3-9 days a^-1 at many sites.