1 / 32

2020 vision: Modelling the near future tropospheric composition

2020 vision: Modelling the near future tropospheric composition. David Stevenson Institute of Atmospheric and Environmental Science School of GeoSciences The University of Edinburgh Thanks to: Ruth Doherty (Univ. Edinburgh) Dick Derwent (rdscientific)

jamese
Download Presentation

2020 vision: Modelling the near future tropospheric composition

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 2020 vision:Modelling the near future tropospheric composition David Stevenson Institute of Atmospheric and Environmental ScienceSchool of GeoSciencesThe University of Edinburgh Thanks to: Ruth Doherty (Univ. Edinburgh) Dick Derwent (rdscientific) Mike Sanderson, Colin Johnson, Bill Collins (Met Office) Frank Dentener (JRC Ispra), Markus Amann (IIASA)

  2. Talk Structure • Chemistry-climate model: STOCHEM-UM • Several transient runs: 1990 → 2030 • the 1990s • how modellers use observations • comparisons with ozone-sonde data • the 2020s • what is needed to predict the future? • a believable model (hence the first bit) • a computationally efficient model • future emissions • climate change • other things? • What are the results telling us?

  3. STOCHEM • Global Lagrangian 3-D chemistry-climate model • Meteorology: HadAM3 + prescribed SSTs • GCM grid: 3.75° x 2.5° x 19 levels • CTM: 50,000 air parcels, 1 hour timestep • CTM output: 5° x 5° x 9 levels • Detailed tropospheric chemistry • CH4-CO-NOx-hydrocarbons • detailed oxidant photochemistry • Interactive lightning NOx, C5H8 from veg. • ~1 year/day on 36 processors (Cray T3E)

  4. Model experiments • Several transient runs: 1990 → 2030 • Driving meteorology • Fixed SSTs (mean of 1978-1996) • SSTs from a climate change scenario (is92a) • shows ~1K surface warming 1990s-2020s • Shorter run with observed SSTs 1990-2002 • New IIASA* global emissions scenarios: • Business as usual (BAU) • Maximum reductions feasible (MRF) • Stratospheric O3 is a fixed climatology • Vegetation (land-use) also a fixed climatology *IIASA: International Institute for Applied Systems Analysis (Austria)

  5. IIASA Emissions scenarios Global totals – there are significant regional variations Courtesy of Markus Amann (IIASA) & Frank Dentener (JRC)

  6. Compare with 1990s obs Model experiments BAU, observed SSTs 1990-2002 BAU, fixed SSTs 1990-2030 MRF, fixed SSTs 1990-2030 BAU, is92a SSTs 1990-2030 2030 1990

  7. Chemical tropopause (O3=150 ppbv) Hohenpeissenberg Ozone-sonde model vs observations (monthly data for the 1990s) Ozone-sonde data from Logan et al. (1999 - JGR)

  8. Chemical tropopause (O3=150 ppbv) Hohenpeissenberg Ozone-sonde model vs observations (monthly data for the 1990s) Ozone-sonde data from Logan et al. (1999 - JGR)

  9. Chemical tropopause (O3=150 ppbv) Hohenpeissenberg Ozone-sonde model vs observations (monthly data for the 1990s) Model> obs Model< obs Ozone-sonde data from Logan et al. (1999 - JGR)

  10. Chemical tropopause (O3=150 ppbv) ±1 std dev in obs Hohenpeissenberg Ozone-sonde model vs observations (monthly data for the 1990s) Ozone-sonde data from Logan et al. (1999 - JGR)

  11. Chemical tropopause (O3=150 ppbv) ±1 std dev in obs ±1 std dev in model Hohenpeissenberg Ozone-sonde model vs observations (monthly data for the 1990s) Ozone-sonde data from Logan et al. (1999 - JGR)

  12. Chemical tropopause (O3=150 ppbv) Hohenpeissenberg Ozone-sonde model vs observations (monthly data for the 1990s) Model overestimatesby >1 std dev Model underestimatesby >1 std dev Ozone-sonde data from Logan et al. (1999 - JGR)

  13. Chemical tropopause (O3=150 ppbv) Hohenpeissenberg Ozone-sonde model vs observations (monthly data for the 1990s) Model overestimatesby >1 std dev Identify where andwhen the model iswrong Model underestimatesby >1 std dev Ozone-sonde data from Logan et al. (1999 - JGR)

  14. Model O3 too low in lower tropospherefor all seasons except spring Ny Alesund (79N, 12E), Spitzbergen Ozone-sonde data from Logan et al. (1999 - JGR)

  15. Model O3 too low in boundary layerin summer - autumn Resolute (75N, 95W), Canada Ozone-sonde data from Logan et al. (1999 - JGR)

  16. Surface O3 generally too high Mid-troposphere in summer too low Sapporo (43N, 141E), Japan Ozone-sonde data from Logan et al. (1999 - JGR)

  17. Mid- & upper-troposphericO3 too low in summer Wallops Island (38N, 76W), Eastern USA Ozone-sonde data from Logan et al. (1999 - JGR)

  18. Major O3 underestimate intropical mid-troposphere –too much destruction?or not enough sources? OK at surface, but… Ascension (8S, 14W), Mid-Atlantic Ozone-sonde data from Thompson et al. (2003 - JGR)

  19. The model has some skill at simulating tropospheric ozone, but is far from perfect. • Careful comparisons with other gases (NOx, NOy, etc.) also needed, but there is much less data. • For climate-chemistry model validation, lengthy climatologies, including vertical profiles are most useful. • If you want modellers to uses the data, provide it in easy-to-use formats (we’re lazy!) • MOZAIC (operational aircraft data) and satellite data are examples of the sort of datasets needed. • If you trust the model, it may be useful for future predictions…

  20. Compare with 1990s obs Compare changes betweenthe 1990s and 2020s Model experiments BAU, observed SSTs 1990-2002 BAU, fixed SSTs 1990-2030 MRF, fixed SSTs 1990-2030 BAU, is92a SSTs 1990-2030 2030 1990

  21. 1990s Decadal mean values

  22. BAU 2020s

  23. +2 to 4 ppbv over N. Atlantic/Pacific >+10 ppbvIndia A large fraction is due to ship NOx Change in surface O3, BAU 2020s-1990s BAU

  24. MRF 2020s

  25. Up to -10 ppbvover continents Change in surface O3, MRF 2020s-1990s MRF BAU

  26. BAU+climate change 2020s

  27. Look at the difference between these two to see influence of climate change Change in surface O3, BAUcc 2020s-1990s MRF BAU BAU+cc

  28. ΔO3 from climate change Warmertemperatures & higher humidities increase O3 destruction over the oceans But also a role from increases in isoprene emissions from vegetation?

  29. Zonal mean O3 & ΔO3 (2020s-1990s) BAU ΔO3 1990s MRF ΔO3 BAUcc ΔO3

  30. Zonal mean OH & ΔOH(2020s-1990s) BAU ΔOH 1990s MRF ΔOH BAUcc ΔOH

  31. CH4, CH4 & OH trajectories 1990-2030 Current CH4 trend looks like MRF – coincidence? All scenarios show increasing OH

  32. Conclusions • Model development and validation is ongoing, & is guided by observations • Anthropogenic emissions will be the main determinant of future tropospheric O3 • Ship NOx looks important • Climate change will introduce feedbacks that modify air quality • We can estimate the radiative forcing implications of air quality control measures • NB: Many processes still missing

More Related