Accent experiment 2
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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:

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ACCENT Experiment 2

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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


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


Climate change/deposition

CO

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


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.


SO2 High ship emissions: A2s "2030"

NOx High ship emissions: A2s "2030"

SO2 emissions: A2 "2000"

NOx emissions: A2 "2000"


IPCC-AR4-ACCENT ‘High’ Ship Emission Scenario

Characteristics:

  • 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@dlr.de and Axel.Lauer@dlr.de


Year 2000 Anthropogenic NOx Emissions

EDGAR database: Jos Olivier et al., RIVM

Plot: Martin Schultz, MPI


Year 2000 tropospheric NO2 columns

Observed (GOME)(mean of 3 methods)

Model(ensemble mean)

(10:30am local sampling in both cases)

Courtesy Twan van Noije, Henke Eskes – figure from Dentener et al, submitted


Modelled column NO2 vs GOME retrievals over Europe

Courtesy Twan van Noije


NOy wet deposition zoom over Europe

Courtesy Frank Dentener


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).


1990

2000

2030 CLE

2030 MFR

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]


Emission Changes 2030 CLE - 2000

Plots: Martin Schultz, MPI

IIASA RAINS model: Markus Amann et al.


Year 2000 Annual Zonal Mean Ozone (24 models)


Year 2000

Ensemble meanof 25 models

AnnualZonalMean

Annual TroposphericColumn


%

Standard Deviationof 25 models

Absolute

Standard Deviationof 25 models

Ensemble meanof 25 models

Year 2000 Annual Mean O3


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

30°S-Eq

30°N-Eq

90-30°N

90-30°S


+10 ppbv

+5 ppbv

-5 ppbv

2030 A2 - 2000

2030 MRF - 2000

2030 CLE - 2000


Tropospheric O3 scales ~linearly with NOx emissions


Radiative forcing implications

Forcings (mW m-2) 2000-2030 for the 3 scenarios:

+37%

-23%

CO2

CH4

O3


Positive stratosphericinflux feedback

Negative watervapour feedback

Impact of Climate Change on Ozone by 2030(ensemble of 9 models)

Mean + 1SD

Mean - 1SD

Mean

Positive and negative feedbacks – no clear consensus


Budgets ofmethaneandtropospheric ozone


19 Models reported O3 budgets


Higher H2O

Higher LNOx ?

Lower H2O

Lower LNOx ?

Highest H2O

+High Lightning NOx (8 TgN/yr)

O3 chemical loss / Tg-O3 yr-1

More complicated- other factors

CH4 lifetime / years


Tropospheric water vapour in 6 GCMs

Differences of

± 10% in tropics

Tropospheric H2O column / g(H2O) m-2

90S Eq 90N


AOT40, May-June-July, mean model, ppb*hours

3000 ppb.h !!!

Courtesy Kjerstin Ellingsen


Change in AOT40 (CLE)


Change in AOT40 (MFR)


Change in AOT40 (A2)


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


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