Global Modelling of UTLS Ozone

1. Global Modelling of UTLS Ozone David Stevenson + many others dstevens@staffmail.ed.ac.uk www.geos.ed.ac.uk/homes/dstevens Institute of Atmospheric and Environmental Science The University of Edinburgh Royal Met. Soc. 18th October 2006, London Zoo

2. Very few observations of long-term trends in tropospheric ozone…

3. Surface ozone at Arosa, Switzerland Staehelin et al., 2001

4. Largeinterannualvariability Even shorter time period of observationsfrom the free atmosphere… NH mid-lats, mid-troposphere Regionallydifferent trends;regionallydifferent AQmeasures Logan et al., 1999; O3 sonde data

5. Models of tropospheric ozone • Limited observational evidence suggests that O3T has increased substantially since pre-industrial times • No ice-core record of O3 (too reactive) • Recent (last 30 years) trends show regional differences and are obscured by large interannual variations • We are dependent on models to produce a global picture of O3T change (past and future) • Best we can do is produce models that closely match the limited set of observations of O3 and its precursors, and hope they can reliably simulate the past/future • But it is difficult to know the true ‘ozone sensitivity’ – i.e. O3/emissions or O3/climate • However, we can assess the consistency (or otherwise) between models – i.e. intercomparisons

6. Zonal mean O3 change Trop. O3 radiative forcing 1860-1990 O3 (Stevenson et al., 1998) Tropospheric O3 radiative forcing • Simulate pre-industrial and present-day O3T,use the change to calculate a radiative forcing • A large part of this is due to changes in UT O3 15-40°N: Cold, high tropopause, hot surface, clear skies

7. Warming from increasesin GHGs +3 W m-2 About ¼ of CO2 forcing

8. A commonly held view? • “Nobody believes a modelling paper except the author; everybody believes an observational paper – except the author” • One solution…

9. ACCENT model intercomparison for IPCC-AR4 • 26 different models perform same experiments • 16 Europe: • 4 UK (Edinburgh, Cambridge x2, Met. Office) • 4 Germany (Hamburg x2, Mainz x2) • 2 France (Paris x2) • 2 Italy (Ispra, L’Aquila) • 1 Switzerland (Lausanne) • 1 Norway (Oslo) • 1 Netherlands (KNMI) • 1 Belgium (Brussels) • 7 US • 3 Japan • Large ensemble reduces uncertainties, and allows them to be quantified

10. Intercomparison simulations • Year 2000 – using EDGAR3.2 emissions • Fix biomass burning & natural emissions • 3 Emissions scenarios for 2030 • ‘Likely’: IIASA CLE (‘Current Legislation’) • ‘High’: IPCC SRES A2 • ‘Low’: IIASA MFR (‘Maximum technically Feasible Reductions’) • Also assess climate feedbacks • expected surface warming of ~0.7K by 2030

11. Comparison of ensemble mean model with O3 sonde measurements Individualmodels in grey UT250 hPa Model ±1SD Observed ±1SD J F M A M J J A S O N D MT 500 hPa LT 750 hPa 30°S-Eq 30°N-Eq 90-30°N 90-30°S

13. GOME NO2 Tropospheric Column 2000 Mean of 3 retrieval methods Std. Dev. of 3 retrieval methods Mean of 17 models Std. Dev. of 17 models E. Asian NOx emissions too low; Biomass burning emissions too high

15. Models’ CO underestimates observations in Northern Hemisphere- Asian CO emissions too low

16. Where is modelled O3T most uncertain? Zonal mean year 2000 O3T

17. Year 2000 Ensemble meanof 26 models AnnualZonalMean Annual TroposphericColumn

18. Year 2000 Inter-model standard deviation (%) AnnualZonalMean Annual TroposphericColumn Models show large variationsin the crucial tropical UT region

19. Change in tropospheric O32000-2030 under 3 scenarios Annual Zonal Mean ΔO3 / ppbv Annual Tropo-spheric Column ΔO3 / DU ‘Optimistic’ IIASA MFR SRES B2 economy + Maximum Feasible Reductions ‘Likely’ IIASA CLE SRES B2 economy + Current AQ Legislation ‘Pessimistic’ IPCC SRES A2High economic growth +Little AQ legislation

20. Main candidates for inter-model differences in tropical UT O3 • Convection • Vertical mixing of both O3 and its precursors • Lightning NOx production • In-cloud chemistry, washout • Distribution of water vapour • Different treatments of emissions • Injection height of biomass burning • Biogenic VOCs and degradation chemistry • Lightning NOx (magnitude/profile) • Stratosphere-troposphere exchange • All of above also sensitive to climate change…

21. Convection increases ozone everywhere MATCH-MPIC (Lawrence et al., 2003) Effect of switching on convection in 2 models Convection increases ozone in tropical MT Decreases elsewhere STOCHEM-HadAM3 (Doherty et al., 2005) We don’t know what convectiondoes to UT O3 !

22. Convective mass fluxes differ markedly STOCHEM-HadAM3; Too strong/high? Or are differencesin the chemical schemes the causeof the differences? ERA-40The truth? MATCH-MPIC Too weak/low?

23. Positive stratosphericinflux feedback Negative watervapour feedback Impact of Climate Change on Ozone by 2030(ensemble of 10 models) Mean + 1SD Mean - 1SD Mean Positive and negative feedbacks – no clear consensus

24. Climate impact of aircraft NOx emissions Short-term warming from ozone Plus minor ozone long-term cooling Long-term cooling from methane ΔNOx NB negative scale expanded ΔO3 NB negative scale expanded ΔOH ΔCH4 Decay with e-folding timescale of 11.1 years UT crucial for correct quantification of aircraft NOx impacts…

25. Summary • Models are essential to simulate past/future ozone (lack of observations) • Comparison of models and observations suggest similar levels of uncertainty in both • Uncertainties in modelled O3 are large in the UT – translates directly into climate forcing • Convection is poorly understood and a major source of uncertainty – not even clear if convection increases or decreases UT O3 • Likely effects of climate change (water vapour increases, STE changes) on O3 even less well constrained • Conclusion: plenty to do… dstevens@staffmail.ed.ac.uk www.geos.ed.ac.uk/homes/dstevens