New Coupled Climate-Carbon Simulations with the IPSL Model

From validation to sensitivity analysis

P. CADULE, L. BOPP, P. FRIEDLINGSTEIN

Seventh International Carbon Dioxide Conference

2

Either weaker sinks or sources according to future projections with identical IPCC CO2 and Climate scenarii

[IPCC TAR, 2001]

Carbon Models Offline Responses

3

Carbon Models Online Responses

Large panel of possible responses due to a wide range of climate and carbon models sensitivities

Atm. [CO2]

[C4MIP- Friedlingstein et al., 2005]

Δ[CO2]max= 224 ppm

Δ[CO2]min = 19 ppm

All models have a positive feedback but …

4

Net total carbon flux Fluxland + Fluxocean

12.2

2 oceanland FluxFluxEMI

dt

COd

Terrestrial biosphereORCHIDEE

(STOMATE activated)

MarineBiochemistry

PISCES

OceanORCA-LIM

OPA 8.2

AtmosphereLMDZ4

EMI = external forcing[Marland et al, 2005

Houghton, 2002]

Ocean flux GtC/mthLand flux GtC/mth

CouplerOASIS 2.4

ClimateAtmospheric[CO2]

CO2 concentration

re-calculated each month

∆t = 1day

Carbon

∆t = physic time step

A New Carbon Climate Coupled Model

5

A New Carbon Climate Coupled Model• LOOP02 : fully coupled, emissions

– Climate aware of CO2 increase

• LOOP03 : decoupled, emissions– Climate agnostic to CO2 increase

fix atmospheric CO2 concentration[CO2] = 286.2 ppm

Climate

Fossil emi.

CO2CO2

Land and Ocean

LOOP03

LOOP02

Geochemical

impact

Climateimpact

Climatefeedback

LOOP01

LOOP03

Highlights CO2 change impact on fluxes

LOOP02

LOOP03

Highlights climate change impact on fluxes

6

[CO2] is re-calculated each month based on :

• fossil fuel and land-use emissions

• net CO2 fluxes computed by ORCHIDEE (land) and PISCES (ocean)

Simulated CO2 Concentration

LOOP2 vs LOOP3Weaker land and oceanic uptakes in coupled run (LOOP2)

positive feedback :8 ppm in 2040

I. Confront results to observationsA. Budgets

B. Seasonal Cycle

C. IAV

D. Long term trends

II. Better understand processes individuallySensitivity experiments (e.g. Ocean Processes)

Outline

8

Carbon Dioxide Concentration

Simulation matches historical data…

Is it enough to be confident in the model projections ?

[CDIAC, 2005]

9

Mean Budget 80's

-4 -3 -2 -1 0 1 2 3 4 5 6

land use

fossil fuel

land sink

ocean sink

GtC/yr

LeQuéré

IPCC

LOOP

Houghton

De Fries

Mean Budget 90's

-4 -3 -2 -1 0 1 2 3 4 5 6 7

land use

fossil fuel

land sink

ocean sink

GtC/yr

LeQuéré

IPCC

LOOP

Houghton

De Fries

Atmospheric carbon variation

Land use fossil fuel land ocean

Global Budgets : 80s and 90s

- 2,8 GtC/yr - 2,6 GtC/yr

- 1.8 GtC/yr - 2,2 GtC/yr

Good agreement between LOOP and IPCC

10

-3 -2,5 -2 -1,5 -1 -0,5 0

GtC/yr

Global

90N-30N

30N-30S

30S-90S

Lat

itu

de

Land Mean1988 - 2003

TRANSCOM

LOOP

-2,5 -2 -1,5 -1 -0,5 0 0,5 1

GtC/yr

Global

90N-30N

30N-30S

30S-90S

Lat

itud

e

Ocean Mean1988 - 2003

Takahashi (+rivers) 1995

Takahashi 1995

TRANSCOM

LOOP

Regional Budgets : 1988-2003

Need to confront modelsresults to inversions data

Over-estimation in thetropical region for thecontinental biosphere

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Regional Breakdown1988 - 2003

-1

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

N. America Eurasia N. Atlantic N. Pacific

GtC

/yr LOOP

TRANSCOM

Takahashi 1995

Regional Breakdown : 1988-2003N. Atl and N. Pacshould be different

[Baker et al., 2005]

22 emission regions and78 CO2 measurements

locations

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Model

Seasonal Cycle at Mauna Loa

A realistic seasonal cycleat a CO2 measurement location

Obs.

13

0 0.5 1 1.5 2 2.5 3 3.5 4

GtC/yr

Global

Lat

itu

de

Land IAV (1988 - 2003)Standard Deviation

TRANSCOM

LOOP

0 0,2 0,4 0,6 0,8 1 1,2

GtC/yr

GlobalL

atit

ud

e

Ocean IAV (1988-2003)Standard Deviation

TRANSCOM

LOOP

Inter-Annual Variability of CO2 Fluxes

Land and ocean inter-annual variability [PgC yr-1]

Over estimation of IAV in LandUnder estimation of IAV in Ocean

[Baker et al., 2005]

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Long Term Trends : The Ocean

106 ± 17 PgC (1800-1994)

LOOP

96.5 PgC (1860-1995)

Atla

ntic

Pac

ific

CO2 Anthropogenic micromol/kg

GLODAP

[GLODAP, Sabine et al., 2004]

I. Confront results to observationsA. Budgets

B. Seasonal Cycle

C. IAV

D. Long term trends

II. Better understand processes individuallySensitivity experiments (e.g. Ocean Processes)

Outline

16

Atm

osp

her

ic p

CO

2 (p

pm

)

Glo

bal

Tem

per

atu

re

(°C

)

Oce

an U

pta

ke

(GtC

/ yr

)

Geochemical EffectGeochemical + Climatic Effects

Offline simulations to determine sensitivity to climate change

Sensitivity Experiments on Ocean Uptake

1 x CO2

4 x CO2

Oceanic sink in coupled run is weaker at 4 x CO2

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Dep

th

Dep

th

Years

Climate Impact on the marine C-Cycle

All effects - 80GtC

Only Impacton the natural C-Cycle-25 GtC

Ocean stratification prevents anth. CO2 penetration.

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Continental biosphere and oceans sinks are influenced by CO2 increase and by climate change.• Obvious need to model Carbon Cycle-

Climate interactions.• Wide range of possible response drives the

need for a better understanding of involved processes.

• Observations and inversions both at global and breakdown region scale constitute the best common reference

• Identify and implement, in the models, human dependent processes (e.g. land-use) that play an important role in the carbon cycle.

Thank You !

With the contribution of Rachid BENSHILA, Patrick BROCKMANN, Philippe BOUSQUET, Arnaud

CAUBEL, Sébastien DENVIL, Jean-Louis DUFRESNE, Laurent FAIRHEAD, Marie-Angèle FILIBERTI, Corinne LEQUERE, Cyril MOULIN,

Philippe PEYLIN, Peter RAYNER

filiberti@ipsl.jussieu.frAtmospheric Tracer transport Engineer

Marie-Angèle FILIBERTI

Laurent.Fairhead@lmd.jussieu.frAtmospheric modelling Engineer

Laurent FAIRHEAD

JeanLouis.Dufresne@lmd.jussieu.frClimate modelling Jean-Louis DUFRESNE

Sebastien.Denvil@ipsl.jussieu.frClimate modelling and global change simulations Engineer

Sébastien DENVIL

Arnaud.Caubel@cea.frSoftware Engineer - coupling aspects

Arnaud CAUBEL

Philippe.Bousquet@cea.fr CO2 transportPhilippe BOUSQUET

Patrick.Brockmann@cea.frVisualisation software Engineer

Patrick BROCKMANN

Rachid.Benshila@lodyc.jussieu.fOcean modelling EngineerRachid BENSHILA

e-mail OccupationNAME

NAME  Occupation e-mail

LAURENT BOPPClimate & Ocean Biogeochemical Cycles Laurent.Bopp@cea.fr

Patricia CADULE

Inter. Between Climate Change & BGC – PhD student Patricia.Cadule@ipsl.jussieu.fr

Pierre FRIEDLINGSTEIN

Climate & Land Carbon Cycle Pierre.Friedlingstein@cea.fr

Peter.Rayner@cea.frCO2 InversionPeter RAYNER

Philippe.Peylin@cea.frCO2 transport and Inversion Philippe PEYLIN

Aumont, O., E. Maier-Reimer, S. Blain, and P. Monfray (2003), An ecosystem model of the global ocean including Fe, Si, P co-limitations, Glob. Biogeochem. Cycles. 17(2), 1060, 10.1029/2001GB00174.Baker D. F.( 2005), submitted to GBCBopp L., (2001), Changements Climatiques et Biogéochimie Marine : Modélisation du dernier Maximum Gliaciaire et de l’Ere IndustrielleBousquet P., Peylin P., Ciais P., Le Quéré C., Friedlingstein P., Tans P.P., (2000). Regional changes in carbon dioxide fluxes of land and oceans since 1980. Science 290, 1342-1345.Cox, P.M., R. A. Betts, C. D. Jones, S. A. Spall, and I. J. Totterdell (2000), Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model, Nature, 408, 184-187.Dufresne, J.-L., P. Friedlingstein, M. Berthelot, L. Bopp, P. Ciais, L. Fairhead, H. LeTreut, and P. Monfray (2002), Effects of climate change due to CO2 increase on land and ocean carbon uptake. Geophys. Res. Lett., 29(10), 10.1029/2001GL013777Friedlingstein P., Dufresne J.L., Cox P.M., Rayner P., (2003) How positive is the feedback batween climate change and the carbon cycle ?. Tellus 55B, 692-700Friedlingstein P., P. Cox, R. Betts, L. Bopp, W. von Bloh, V. Brovkin, S. Doney, M. Eby, I. Fung, B. Govindasamy, J. John, C. Jones, F. Joos, T. Kato, M. Kawamiya, W. Knorr, K. Lindsay, H. D. Matthews, T. Raddatz, P. Rayner, C. Reick, E. Roeckner, K.-G. Scnitzler, R. Schnur, K. Strassmann, A. J. Weaver, C. Yoshikawa, and N. Zeng (2005), Climate –carbon cycle feedback analysis, results from C4MIP model intercomparaison (Submitted to Journal of Climate)Houghton, R.A., and J.L. Hackler (2002), Carbon Flux to the Atmosphere from Land-Use Changes. In Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. Houghton, J.T., Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A. Johnson (2001), Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

References

Krinner G., Nicolas Viovy, N. de Noblet-Ducoudré, J. Ogée, J. Polcher, P. Friedlingstein, P. Ciais, S. Sitch, and I. C. Prentice (2005), A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system, Global Biogeochem. Cycles, 19, GB1015, doi:10.1029/2003/GB002199 LE QUÉRÉ, C., AUMONT, O., BOPP, L., BOUSQUET, P., CIAIS, P., FRANCEY, R., HEIMANN, M., KEELING, C. D., KEELING, R. F., KHESHGI, H., PEYLIN, P., PIPER, S. C., PRENTICE, I. C. & RAYNER, P. J. (2003), Two decades of ocean CO2 sink and variability., Tellus B 55 (2), 649-656.doi: 10.1034/j.1600-0889.2003.00043.xMarland, G., T.A. Boden, and R. J. Andres (2005), Global, Regional, and National CO2 Emissions. In Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.Marti, O., P. Braconnot, J. Bellier, R. Benshila, S. Bony, P. Brockmann, P. Cadule, A. Caubel, S. Denvil, J. L. Dufresne, L. Fairhead, M. A. Filiberti, M.-A. Foujols, T. Fichefet, P. Friedlingstein, H. Goosse, J. Y. Grandpeix, F. Hourdin, G. Krinner, C. Lévy, G. Madec, I. Musat, N. deNoblet, J. Polcher, and C. Talandier (2005), The new IPSL climate system model: IPSL-CM4. Note du Pôle de Modélisation, 26, ISSN 1288-1619.Peylin P., Baker D., Sarmiento G., Ciais P., Bousquet P., (2002), Influence of transport uncertainty on annual mean and seasonal inversions of atmospheric CO2. J. Geophys. Res. 107(D19), 4385, 10.1029/2001JD000857.Sabine Christopher L., Richard A. Feely, Nicolas Gruber, Robert M. Key, Kitack Lee, John L. Bullister, Rik Wanninkhof, C. S. Wong, Douglas W. R. Wallace, Bronte Tilbrook, Frank J. Millero, Tsung-Hung Peng, Alexander Kozyr, Tsueno Ono, and Aida F. Rios (2004) , The Oceanic Sink for Anthropogenic CO2, Science ; 305: 367-371 [DOI: 10.1126/science.1097403]Takahashi, T., Sutherland, S. C., Sweeney, C., Poisson, A., Metzl, N. and co-authors, (2002). Global sea-air CO2 flux based on climatological surface ocean pCO2, and seasonal biological and temperature effects. Deep Sea Res. II 49, 1601-1622Data sets :Historical CO2 concentration : http://www.cnrm.meteo.fr/ensembles/public/data/CO2_fit.txtMODIS : http://cybele.bu.edu/modismisr/products/modis/modislaifpar.htmlSeaWIFS : http://oceancolor.gsfc.nasa.gov/SeaWiFS/

Backup

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• The need for Carbon-Climate Coupling – Modeling the carbon cycle– Coupling it with the climate

• But now essentially– Better understand processes individually– Confront results to observations

Pushing towards convergence of processes and their responses

“ En résumé ”

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LOOP vs C4MIP models

climate sensitivity

ocean sensitivity to [CO2]

land sensitivity to [CO2] land sensitivity to T°

ocean sensitivity to T°

Climate and Carbon Models Sensitivity

[C4MIP- Friedlingstein et al., 2005]

LOOP is inside C4MIP responses range. But is it a sufficient criterion ?

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Climate Change and Carbon Cycle Interactions

Wide range of climate and carbon models sensitivity [C4MIP-Friedlingstein et al., 2005]

climate sensitivity

ocean sensitivity to [CO2]

land sensitivity to [CO2] land sensitivity to T°

ocean sensitivity to T°

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ORCHIDEE

Simulated CO2 Fluxes

PISCES

28

[Krinner, 2005]

TerrestrialBiosphereModel : ORCHIDEE

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[Aumont, 2001; Aumont 2003]

PO43-

Diatoms

MicroZoo

P.O.M

D.O.M

Si

IronNano-phyto

Meso Zoo

NO3-

NH4+

Small Ones Big Ones

Marine biology is highly influenced by the ocean dynamicmotivating the need of both PISCES and OPA

Oceanic Biogeochemical Model PISCES

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Satellite Data Comparison

31

So, what does influence the ocean response to the climate ?

T

C

2100

Sensitivity Analysis

min = - 14 GtC/°C

max = - 60 GtC/°C

Sensitivity of ocean carbon models to climate change

Reduction of carbon quantity entering the ocean shows a large range amongst the models

year