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Multi-model ensemble simulations of present-day and nearfuture tropospheric ozone D.S. Stevenson1, F.J. Dentener2, M.G. Schultz3, K. Ellingsen4, T.P.C. van Noije5, O. Wild6, G. Zeng7, M. Amann8, C.S. Atherton9, N. Bell10, D.J. Bergmann9, I. Bey11, T. Butler12, J. Cofala8, W.J. Collins13, R.G. Derwent14, R.M. Doherty1, J. Drevet11, H.J. Eskes5, A.M. Fiore15, M. Gauss4, D.A. Hauglustaine16, L.W. Horowitz15, I.S.A. Isaksen4, M.C. Krol2, J.-F. Lamarque17, M.G. Lawrence12, V. Montanaro18, J.-F. Müller19, G. Pitari18, M.J. Prather20, J.A. Pyle7, S. Rast3, J.M. Rodriguez21, M.G. Sanderson13, N.H. Savage7, D.T. Shindell10, S.E. Strahan21, K. Sudo6, and S. Szopa16 1. University of Edinburgh, School of GeoSciences, Edinburgh, United Kingdom. 2. Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy. 3. Max Planck Institute for Meteorology, Hamburg, Germany. 4. University of Oslo, Department of Geosciences, Oslo, Norway. 5. Royal Netherlands Meteorological Institute (KNMI), Atmospheric Composition Research, De Bilt, the Netherlands. 6. Frontier Research Center for Global Change, JAMSTEC, Yokohama, Japan. 7. University of Cambridge, Centre of Atmospheric Science, United Kingdom. 8. IIASA, International Institute for Applied Systems Analysis, Laxenburg, Austria. 9. Lawrence Livermore National Laboratory, Atmos. Science Div., Livermore, USA. 10. NASA-Goddard Institute for Space Studies, New York, USA. 11. Ecole Polytechnique Fédéral de Lausanne (EPFL), Switzerland. 12. Max Planck Institute for Chemistry, Mainz, Germany. 13. Met Office, Exeter, United Kingdom. 14. rdscientific, Newbury, UK. 15. NOAA GFDL, Princeton, NJ, USA. 16. Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France. 17. National Center of Atmospheric Research, Atmospheric Chemistry Division, Boulder, CO, USA. 18. Università L'Aquila, Dipartimento di Fisica, L'Aquila, Italy. 19. Belgian Institute for Space Aeronomy, Brussels, Belgium. 20. Department of Earth System Science, University of California, Irvine, USA 21. Goddard Earth Science & Technology Center (GEST), Maryland, Washington, DC, USA. Background • ‘OxComp’ model intercomparison for IPCC TAR sampled models in ~1999 • OxComp focussed on SRES A2 in 2100. • Models and emissions have developed in the last 5 years – time for an update • New scenarios from IIASA include AQ legislation measures (not in SRES) • SRES didn’t include ships – new datasets • SRES biomass burning(?) – new satellite data Scope of IPCC-AR4 • Chapter 2: Changes in atmospheric constituents and in radiative forcing • Chapter 7: Couplings between changes in the climate system and biogeochemistry – Includes a section on Air Quality • Design intercomparison to be of direct use to IPCC-AR4 ACCENT IA3 / IPCC-AR4 modeling activities on climate / air pollution impact Experiment 1: Delta O3 and radiative forcing 1850-2000-2100 Experiment 2: Air quality – climate interactions 2000-2030 Institute / model CTM CCM trop.chem strat.chem Europe: Univ. L’Aquila, Italy ULAQ Univ. Oslo, Norway UIO_CTM2 X X X X X X CNRS/CEA, France LMDzINCA X X DLR, Germany DLR_E39C X X X (X) X (X) X X UK MetOffice, UK STOCHEM_HadGEM1 Univ. Cambridge, UK UM_CAM Univ. Edinburgh, UK STOCHEM_HadAM3 X X USA: NCAR, USA NCAR_MACCM X X X X (X) X (X) Japan: JAMSTEC, Japan FRSGC_UCI JAMSTEC, Japan CHASER X X Gauss et al., ACPD, 2005 Radiative forcing due to changes in ozone since preindustrial times -- A model study within ACCENT -M. Gauss1, G. Myhre1, I. S. A. Isaksen1, W. J. Collins2, F. J. Dentener3, K. Ellingsen1, L. K. Gohar4, V. Grewe5, D. A. Hauglustaine6, D. Iachetti7, J.-F. Lamarque8, E. Mancini7, L. J. Mickley9, G. Pitari7, M. J. Prather10, J. A. Pyle11, M. G. Sanderson2, K. P. Shine4, D. S. Stevenson12, K. Sudo13, S. Szopa6, O. Wild13, G. Zeng11 [1] Department of Geosciences, University of Oslo, Oslo, Norway [8] Atmospheric Chemistry Division, NCAR, Boulder, CO, USA [2] UK Met Office, Climate Research Division, Berks, United Kingdom [9] Division of Engineering and Appl. Sci., Harvard Univ., Cambridge, MA, USA [3] Joint Research Centre, Climate Change Unit, Ispra, Italy [10] Earth System Science Department, University of California at Irvine, USA [4] Department of Meteorology, University of Reading, Reading, United Kingdom [11] Cambridge University, Chemistry Department, Cambridge, United Kingdom [5] Institut für Physik der Atmosphäre, DLR, Oberpfaffenhoffen, Germany [12] Institute for Meteorology, University of Edinburgh, Edinburgh, United Kingdom [6] Laboratoire des Sciences du Climat et de L’Environnement, Gif-sur-Yvette, France [13] Frontier Research System for Global Change, Yokohama, Japan [7] Dipartimento di Fisica, Università de L’Aquila, Coppito, L’Aquila, Italy Annually averaged zonal-mean ozone change (%) between 1850 and 2000 (emission change only!) Climate-chemistry interactions • Increased humidity – ozone loss ozone (mostly tropical LT) • Slow-down of gas phase ozone loss – ozone loss ozone (middle stratosphere) • Increased PSC formation – ozone loss ozone (high latitude LS) • Increased Stratosphere-Troposphere Exchange / Lightning-NOx – ozone (UT) • Increase in tropopause height / convection / BD circulation – ozone (tropical LS) Annual-mean ozone change (%) 1850 – 2000 (climate change only!) Ozone column change Blue bars: chemical effect Red bars: climate effect Tropospheric change Stratospheric change tropospheric change -0.3 +1.3 Annual-mean radiative forcing (Wm-2) 1850 – 2000 (emission change only) Chemical change Chemical + Climate Change RF due to ozone change between 1850 and 2000 [Wm-2] Conclusions • Increase in tropospheric ozone column, reduction in stratospheric ozone column since pre-industrial times … trop+strat combined: reduction in total ozone • RF due to tropospheric ozone change: +0.29 Wm-2 … +0.53 Wm-2 (CCMs, chemical change only) RF due to stratospheric ozone change: –0.10 Wm-2 … +0.08 Wm-2 (CCMs, chemical change only) … trop+strat combined: positive RF • Climate change: leads to an increase in total ozone since pre-industrial times in both the troposphere and the stratosphere. RFtrop gets larger, RFstrat smaller. ACCENT IA3 / IPCC-AR4 modeling activities on climate / air pollution impact Experiment 1: Delta O3 and radiative forcing 1850-2000-2100 Experiment 2: Air quality – climate interactions 2000-2030 ACCENT intercomparison (Expt. 2) • Focus on 2030 – of direct interest to policymakers • Go beyond radiative forcing: also consider ozone AQ, Nand S-deposition, and the use of satellite data to evaluate models • Present-day base case for evaluation: Future changes – S1: 2000 in composition • Consider three 2030 emissions scenarios: related to – S2: 2030 IIASA CLE (‘likely’) emissions – S3: 2030 IIASA MFR (‘optimistic’) 1 year runs Future changes – S4: 2030 SRES A2 (‘pessimistic’) in composition • Also consider the effect of climate change: related to – S5: 2030 CLE + imposed 2030 climate climate change 5-10 year runs Global NOx emission scenarios 200.0 SRES A2 160.0 120.0 CLE 80.0 40.0 MFR 0.0 1990 2000 2000 Europe Asia + Oceania Africa + Middle East SRES A2 - World Total 2010 2020 2030 2030 North America Latin America Maximum Feasible Reduction (MFR) SRES B2 - World Total Figure 1. Projected development of IIASA anthropogenic NOx emissions by SRES world region (Tg NO2 yr-1). Other emissions categories • EDGAR3.2 ship emissions, and assumed 1.5%/yr growth in all scenarios • Biomass burning emissions from van der Werf et al. (2003) – assumed these remained fixed to 2030 in all scenarios • Aircraft emissions from IPCC(1999) • Modellers used their own natural emissions • Specified fixed global CH4 for each case (from earlier transient runs) Requested model diagnostics • Monthly mean, full 3-D – – – – – O3, NO, NO2, CO, OH, … O3 budget terms CH4 + OH NOy, NHx and SOx deposition fluxes T, Q, etc. for climate change runs • Daily NO2 column (GOME comparison) • Hourly surface O3 (for AQ analysis) • NETCDF files submitted to central database 26 Participating Models • • • • • • • • • • • • • CHASER_CTM CHASER_GCM FRSGC/UCI GEOS-CHEM GISS GMI/CCM3 GMI/DAO GMI/GISS IASB LLNL-IMPACT LMDz/INCA-CTM LMDz/INCA-GCM MATCH-MPIC/ECMWF • • • • • • • • • • • • • MATCH-MPIC/NCEP MOZ2-GFDL MOZART4 MOZECH MOZECH2 p-TOMCAT STOCHEM-HadAM3 STOCHEM-HadGEM TM4 TM5 UIO_CTM2 ULAQ UM_CAM CTMs driven by analyses CTMs coupled to GCMs CTMs driven by GCM output NO3 wet deposition N. America Mean model, all stations All models, regional analysis Dentener et al., in preparation NO2 column comparison of GOME with model output [van Noije et al., in prep.] Global spatial correlation KNMI-BIRA Harvard Bremen CHASER 0.85 0.73 0.88 CTM2 0.81 0.66 0.86 FRSGC 0.84 0.71 0.87 GEOS-CHEM 0.84 0.74 0.84 GMI-CCM 0.81 0.75 0.81 GMI-DAO 0.82 0.75 0.81 GMI-GISS 0.81 0.73 0.81 IMAGES 0.79 0.70 0.82 IMPACT 0.79 0.68 0.80 LMDz-INCA 0.85 0.75 0.88 MOZ2G 0.85 0.72 0.88 NCAR year 2 0.79 0.69 0.83 NCAR year 3 0.79 0.69 0.83 p-TOMCAT 0.82 0.73 0.90 TM4 0.88 0.76 0.88 TM5 0.88 0.75 0.88 ULAQ 0.67 0.61 0.75 NO2 column over van Noije et al., in prep. Analysis of O3 results • Masked at tropopause using O3=150 ppbv • Interpolated to common vertical and horizontal grid • Ensemble mean model and standard deviations calculated • Compared to sonde measurements • Other ongoing validation work: NO2 columns, surface O3, CO, deposition fluxes • Global tropospheric O3 and CH4 budgets, radiative forcings Year 2000 O3 Year 2000 Annual Zonal Mean Ozone (24 models) Year 2000 Ensemble mean of 25 models Annual Zonal Mean Annual Tropospheric Column Sonde data from Logan (1999) + SHADOZ data from Thompson et al (2003) Model ± 1SD UT: 250 hPa Sonde ± 1SD JFMAMJJASOND MT: 500 hPa LT: 750 hPa 90-30S 30S-EQ EQ-30N 30-90N Ensemble mean model closely resembles ozone-sonde measurements Year 2000 Inter-model standard deviation (%) Annual Zonal Mean Annual Tropospheric Column O3 in 2030, radiative forcing & influence of climate change Multi-model ensemble mean change in tropospheric O3 2000-2030 under 3 scenarios Annual Zonal Mean ΔO3 / ppbv Annual Tropospheric Column ΔO3 / DU ‘Likely’ ‘Optimistic’ ‘Pessimistic’ IIASA CLE SRES B2 economy + Current AQ Legislation IIASA MFR SRES B2 economy + Maximum Feasible Reductions IPCC SRES A2 High economic growth + Little AQ legislation Radiative forcing implications Forcings (mW m-2) 2000-2030 for the 3 scenarios: -23% +37% CLE MRF A2 CO2 795 795 1035 CH4 116 0 141 O3 63 -43 155 1500 mW / m2 1000 CO2 500 0 -500 CH4 O3 Impact of Climate Change on Ozone by 2030 (ensemble of 9 models) Positive stratospheric influx feedback Negative water vapour feedback Mean - 1SD Mean Mean + 1SD Positive and negative feedbacks – no clear consensus Global budgets of O3 and CH4 O3 lifetime / days Global O3 budget terms Higher burden goes with longer lifetime Results for a single model, several scenarios Colours signify different models MFR A2 As emissions rise, burden increases, lifetime falls O3 burden / Tg(O3) Ensemble mean model (offset) Climate change shortens lifetime but burden can rise/fall O3 chemical loss / Tg(O3)/yr O3 budget and CH4 lifetime Colours signify different models Climate change reduces CH4 Ensemble mean model (offset) Results for a single model, several scenarios IPCC TAR 8.4 years Models with longer CH4 have lower the interO3 destruction rates: EmissionsWhat have causes 1D) + H O → 2OH O( 2 minor influence model differences? on CH4Water vapour? Lightning NOx? Photolysis schemes? CH4 lifetime / years Conclusions • Ensemble mean model O3 closely resembles observations • Inter-model standard deviations highlight where models differ the most • Quantitative assessment of 2030 scenarios provide clear options for policymakers (radiative forcing and AQ) • Influence of climate change uncertain • Global budgets reveal interesting and fundamental model differences • Analysis is ongoing – please come to meeting on Thursday night for more information. • [email protected] Related Posters • • • • • • • D155a Szopa et al. G186a Dentener et al. G190b Rast et al. G193 Gauss et al. G204 Van Dingenen et al. G205 Ellingsen et al. G210 Sudo & Akimoto