ACCENT Experiment 2

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 NS-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

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 IIASA-CLE-2000 1990s/2000s
S2 IIASA-CLE-2030 2000
S2c IIASA-CLE-2030 1990s/2000s
S3 IIASA-MRF-2030 2000
S4 SRES-A2-2030, but with ship emissions of the year 2000 2000
S4s SRES-A2-2030 Traffic A2s Ship emissions increase with a flat increase of 2.2 /year compared to the year 2000 2000
S5c IIASA-CLE-2030 2020s/2030s
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SO2 High ship emissions A2s "2030"
NOx High ship emissions A2s "2030"
SO2 emissions A2 "2000"
NOx emissions A2 "2000"
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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
  Veronika.Eyring_at_dlr.de and Axel.Lauer_at_dlr.de

7
Year 2000 Anthropogenic NOx Emissions
EDGAR database Jos Olivier et al., RIVM
Plot Martin Schultz, MPI
8
Year 2000 tropospheric NO2 columns
Model(ensemble mean)
Observed (GOME)(mean of 3 methods)
(1030am 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
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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).
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Regional NOx emissions
Ships/aircraft unregulated may become larger
than any regional source by 2030
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
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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)
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Year 2000 Ensemble meanof 25 models AnnualZonal
Mean Annual TroposphericColumn
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Standard Deviationof 25 models
Absolute Standard Deviationof 25 models
Ensemble meanof 25 models
Year 2000 Annual Mean O3
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Year 2000 Inter-model standard deviation
() AnnualZonalMean Annual
TroposphericColumn
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Comparison of ensemble mean model with O3 sonde
measurements
UT250 hPa
Model 1SD
Observed 1SD
J F M A M J J A S O N D
MT 500 hPa
LT 750 hPa
30S-Eq
30N-Eq
90-30N
90-30S
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2030 MRF - 2000
2030 A2 - 2000
2030 CLE - 2000
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Tropospheric O3 scales linearly with NOx
emissions
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Radiative forcing implications
Forcings (mW m-2) 2000-2030 for the 3 scenarios
37
-23
CO2
CH4
O3
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Impact of Climate Change on Ozone by
2030(ensemble of 9 models)
Mean
Mean - 1SD
Mean 1SD
Positive and negative feedbacks no clear
consensus
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Budgets ofmethaneandtropospheric ozone
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19 Models reported O3 budgets
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(No Transcript)
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Highest H2O High Lightning NOx (8 TgN/yr)
O3 chemical loss / Tg-O3 yr-1
More complicated- other factors
CH4 lifetime / years
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Tropospheric water vapour in 6 GCMs
Differences of 10 in tropics
Tropospheric H2O column / g(H2O) m-2
90S Eq
90N
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AOT40, May-June-July, mean model, ppbhours
Courtesy Kjerstin Ellingsen
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Change in AOT40 (CLE)
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Change in AOT40 (MFR)
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Change in AOT40 (A2)
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Conclusions

• Logistics
• 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