Abstract

Abstract. We test the current generation of global chemistry–climate models in their ability to simulate observed, present-day surface ozone. Models are evaluated against hourly surface ozone from 4217 stations in North America and Europe that are averaged over 1° × 1° grid cells, allowing commensurate model–measurement comparison. Models are generally biased high during all hours of the day and in all regions. Most models simulate the shape of regional summertime diurnal and annual cycles well, correctly matching the timing of hourly (~ 15:00 local time (LT)) and monthly (mid-June) peak surface ozone abundance. The amplitude of these cycles is less successfully matched. The observed summertime diurnal range (~ 25 ppb) is underestimated in all regions by about 7 ppb, and the observed seasonal range (~ 21 ppb) is underestimated by about 5 ppb except in the most polluted regions, where it is overestimated by about 5 ppb. The models generally match the pattern of the observed summertime ozone enhancement, but they overestimate its magnitude in most regions. Most models capture the observed distribution of extreme episode sizes, correctly showing that about 80 % of individual extreme events occur in large-scale, multi-day episodes of more than 100 grid cells. The models also match the observed linear relationship between episode size and a measure of episode intensity, which shows increases in ozone abundance by up to 6 ppb for larger-sized episodes. We conclude that the skill of the models evaluated here provides confidence in their projections of future surface ozone.

Highlights

  • We test simulated present-day surface ozone in global chemistry–climate models on temporal scales from diurnal to multi-year variability and on statistics from median geographic patterns to the timing and size of extreme air quality episodes

  • Chemistry-climate models provide a valuable means for projecting future air quality in a changing climate (Kirtman et al, 2013), but recent assessments have lacked commensurate observational comparisons to establish their credibility in reproducing current cycles of surface ozone over polluted regions (Young et al, 2013)

  • In this paper we present the first such model– measurement comparisons, addressing (4) by applying the methodologies from S2014 to the current generation of chemistry–climate models (CCMs) in an effort to quantify their ability to simulate the decadal statistics of the air quality extremes (AQX) episodes

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Summary

Introduction

We test simulated present-day surface ozone in global chemistry–climate models on temporal scales from diurnal to multi-year variability and on statistics from median geographic patterns to the timing and size of extreme air quality episodes. Chemistry-climate models provide a valuable means for projecting future air quality in a changing climate (Kirtman et al, 2013), but recent assessments have lacked commensurate observational comparisons to establish their credibility in reproducing current cycles of surface ozone over polluted regions (Young et al, 2013). There are new, phenologically based land-surface models for interactions between atmospheric chemistry and the biosphere (Büeker et al, 2012) that have yet to be fully implemented in global models In any case, both recent and future land-use change is expected to impact surface O3 abundances (Ganzeveld et al, 2010).

Observations of surface O3
Air quality extremes
Diurnal cycles
Annual cycle
AQX events
Mapping O3 percentiles and enhancements
AQX episode size
Non-stationarity and possible trends
Severity of pollution in largest episodes
Conclusions and discussion
What are the best air quality diagnostics for model development?
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