1. ACCENT Experiment 2 25 different models perform same experiments
15 Europe:
4 UK (STOCHEM x2, UM_CAM, TOMCAT)
3 Germany (MATCH-MPIC x2, MOZECH)
2 France (LMDzINCA x2)
2 Italy (TM5, ULAQ)
1 Switzerland (GEOS-CHEM)
1 Norway (UIO_CTM2)
1 Netherlands (TM4)
1 Belgium (IASB)
7 US:
GMI (x3), NCAR (MOZART4), GFDL (MOZART2), LLNL, GISS
3 Japan:
JAMSTEC – CHASER (x2), FRSGC/UCI
Large ensemble reduces uncertainties, and allows them to be quantified

2. ACCENT Expt 2
Consider 2030 – ‘the next generation’ – of direct interest for policymakers
3 Emissions scenarios
‘Likely’: IIASA CLE (‘Current Legislation’)
‘Low’: IIASA MFR (‘Maximum technically Feasible Reductions’)
‘High’: IPCC SRES A2
Also assess climate feedbacks
expected surface warming of ~0.7K by 2030
Target IPCC-AR4

3. People & Organisation Co-ordination; N+S-deposition, Tropospheric O3
F. Dentener, D. Stevenson
Surface O3 - impacts on health/vegetation; web-site
K. Ellingsen
NO2 columns – comparison of models and satellite data
T. van Noije, H. Eskes
Emissions
M. Amann, J. Cofala, L. Bouwman, B. Eickhout
Data handling and storage (SRB; ~1 TB of model output)
J. Sundet
Other modellers and contributors:
C.S. Atherton, N. Bell, D.J. Bergmann, I. Bey, T. Butler, W.J. Collins, R.G. Derwent, R.M. Doherty, J. Drevet, A. Fiore, M. Gauss, D. Hauglustaine, L. Horowitz, I. Isaksen, M. Krol, J.-F. Lamarque, M. Lawrence, V. Montanaro, J.-F. Müller, G. Pitari, M.J. Prather, J. Pyle, S. Rast, J. Rodriguez, M. Sanderson, N. Savage, M. Schultz, D. Shindell, S. Strahan, K. Sudo, S. Szopa, O. Wild, G. Zeng
Climate change/deposition CO

4. IPCC-AR4-ACCENT ‘High’ Ship Emission Scenario
Scenario S4: IPCC A2, but with ship emissions of the year 2000
Scenario S4s: "Worst" case ship emission scenario in conjunction with S4.
Simulation
ID emissions
Meteo S1
IIASA-CLE-2000
2000
S1c
1990s/2000s S2
IIASA-CLE-2030
S2c S3
IIASA-MRF-2030 S4
SRES-A2-2030, but with ship emissions of the year 2000
S4s
SRES-A2-2030; Traffic A2s
Ship emissions increase with a flat increase of 2.2 % /year compared to the year 2000
S5c
2020s/2030s

5. SO2 High ship emissions: A2s "2030"
NOx High ship emissions: A2s "2030"
SO2 emissions: A2 "2000"
NOx emissions: A2 "2000"

6. IPCC-AR4-ACCENT ‘High’ Ship Emission Scenario
Characteristics:
2000
A2(2030)
A2s(new)
A2s-A2
SO2 in Tg(SO2)/yr
11.23
31.7
38.84
7.14
NOx in Tg(NO2)/yr
52.74
107.4
116.8
9.4
The idea of comparing A2 to A2s:
What is the influence of ship emissions on tropospheric chemistry in 2030 if they were unabated?
Does an ensemble of models give approximately the same answer regarding the influence of ship emissions?
Status: Data analysis recently started
Thanks to everybody who sent data so far (FRSGC_UCI, LMDz/INCA, MATCH-MPIC, TM4)
We invite all other model groups to join in the inter-comparison
If you are interested, please contact and

7. Year 2000 Anthropogenic NOx Emissions
Plot: Martin Schultz, MPI
EDGAR database: Jos Olivier et al., RIVM

8. Year 2000 tropospheric NO2 columns
Model (ensemble mean)
Observed (GOME) (mean of 3 methods)
(10:30am local sampling in both cases)
Courtesy Twan van Noije, Henke Eskes – figure from Dentener et al, submitted

9. Modelled column NO2 vs GOME retrievals over Europe
Courtesy Twan van Noije

10. NOy wet deposition zoom over Europe
Courtesy Frank Dentener

11. Global NOx emission scenarios
SRES A2
CLE
MFR
Figure 1. Projected development of IIASA anthropogenic NOx emissions by SRES world region (Tg NO2 yr-1).

12. Regional NOx emissions
Ships/aircraft:
unregulated;
may become
larger than any
regional source
by 2030
2030 CLE
2030 MFR
1990
2000
USA:
~flat
Europe:
falling
Asia:
rising
Figure 4. Regional emissions separated for sources categories in 1990, 2000, 2030-CLE and 2030-MFR for NOx [Tg NO2 yr-1]

13. Emission Changes 2030 CLE - 2000 Plots: Martin Schultz, MPI
IIASA RAINS model: Markus Amann et al.

14. Year 2000 Annual Zonal Mean Ozone (24 models)

15. Year 2000
Ensemble mean of 25 models
Annual Zonal Mean
Annual Tropospheric Column

16. Year 2000 Annual Mean O3 Absolute % Ensemble mean of 25 models
Standard Deviation of 25 models %
Standard Deviation of 25 models
Ensemble mean of 25 models
Year 2000 Annual Mean O3

17. Comparison of ensemble mean model with O3 sonde measurements
UT 250 hPa
Model ±1SD
Observed ±1SD
J F M A M J J A S O N D MT
500
hPa LT
750
hPa
90-30°S
30°S-Eq
30°N-Eq
90-30°N

18. 2030 CLE - 2000 2030 MRF - 2000 2030 A2 - 2000 +5 ppbv +10 ppbv

19. Tropospheric O3 scales ~linearly with NOx emissions

20. Radiative forcing implications
Forcings (mW m-2) for the 3 scenarios:
-23%
+37%
CO2
CH4 O3

21. 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

22. Budgets of methane and tropospheric ozone

23. 19 Models reported O3 budgets

25. More complicated - other factors
Highest H2O
+High Lightning NOx (8 TgN/yr)
O3 chemical loss / Tg-O3 yr-1
Higher H2O
Higher LNOx ?
More complicated - other factors
Lower H2O
Lower LNOx ?
CH4 lifetime / years

26. Tropospheric water vapour in 6 GCMs
Differences of
± 10% in tropics
Tropospheric H2O column / g(H2O) m-2
90S Eq N

27. AOT40, May-June-July, mean model, ppb*hours
Courtesy Kjerstin Ellingsen

28. Change in AOT40 (CLE)

29. Change in AOT40 (MFR)

30. Change in AOT40 (A2)

31. Conclusions Logistics: Science:
Large group participation – partly due to IPCC-AR4
Lot of work involved – relies on funding ‘goodwill’
Need well defined experiments and diagnostics
Central database and strict data format
Assume mistakes will be made in first attempts
Enforce deadlines if possible
Science:
Multi-model ensemble allows uncertainties to be assessed
Sample large model parameter space
Get hints about the controls on internal model processes
Future work:
Water vapour, convection, lightning NOx, isoprene schemes
STE, biomass burning
Global HOx/NOx/NOy budgets, as well as O3 and CH4