Surface ozone regulation policies rely heavily on air quality models, such as CAMx, as important guiding tools. Comparison with observations is crucial to validating a model’s ability to represent ozone production chemistry. Identifying factors influencing surface ozone formation is complicated because ozone photochemical production rates are non-linearly dependent on concentrations of precursors such as nitrogen oxides (NOx) and volatile organic compounds (VOCs). We compare ozone production regimes (OPRs) identified from satellite observations and model simulations, as defined by the ratio of column formaldehyde to nitrogen dioxide (FNR, HCHO/NO2). We perform CAMx simulations for June-July-August 2016 over the Contiguous United States (CONUS) and compared these outputs against two OMI NO2and HCHO retrievals. Our analysis spans diurnal and altitudinal variations of OPRs, offering important insights for effective policy formulation. At the time of the OMI overpass (~1:30 PM LT), OPR is NOx-limited over most of the CONUS, as determined from OMI column ratios. Analysis of CAMx column ratios shows similar results. In contrast, more regions are VOC-limited when we constrain our ratio to within the Planetary Boundary Layer (PBL). In the morning (~9 AM LT), the CAMx PBL column ratios shift towards VOC-limited regime. We highlight areas of the CONUS for which satellite measurements of FNR may not be an accurate indicator of near-surface OPRs. Air quality regulations based on satellite observations should consider the diurnal variations of surface OPRs and assess how well their ratios represent near-surface OPR. Our results have implications for interpretation of TEMPO data for policy relevant applications.

We use the Empirical Model of Global Climate (EM-GC) to show that human activity has been responsible for ~0.14 °C/decade (range: 0.08 to 0.20) of warming from 1979 to 2010. This EM-GC based quantification of Attributable Anthropogenic Warming Rate (AAWR) is constrained by the observed global mean surface temperature and ocean heat content records; the largest contribution to the uncertainty in our estimate of AAWR is imprecise knowledge of the radiative forcing due to tropospheric aerosols (AER RF). Our value of AAWR is noticeably lower than the mean value from the IPCC 2013 models, 0.22 °C/decade (range: 0.08 to 0.32) with no overlap of interquartile ranges. We also compute probabilistic forecasts of the rise in GMST where again the largest source of uncertainty is AER RF, and cast results in terms of the likelihood of achieving either 1.5 °C or 2.0 °C warmings relative to pre-industrial. We show that the likelihoods of limiting global warming to 2°C are 92%, 50%, and 20% if greenhouse gases follow the RCP 2.6, 4.5, and 6.0 scenarios; the likelihoods of limiting warming to 1.5°C drop to 67%, 10%, and 0.1% for these same three RCPs. Warming forecasts based upon our EM-GC are more optimistic than found by CMIP5 GCMs, following how many GCMs exhibit faster warming than inferred from the recent climate record. Our EM-GC forecasts show that aggressive controls on emissions of both CO2 and CH4 starting this decade are needed to limit global warming to 1.5°C with high probability.