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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 Carbon Models Offline Responses [IPCC TAR, 2001] Either weaker sinks or sources according to future projections with identical IPCC CO2 and Climate scenarii 3 Carbon Models Online Responses Atm. [CO2] All models have a positive feedback but … Δ[CO2]max= 224 ppm Δ[CO2]min = 19 ppm [C4MIP- Friedlingstein et al., 2005] Large panel of possible responses due to a wide range of climate and carbon models sensitivities 4 A New Carbon Climate Coupled Model Atmospheric [CO2] d CO2 EMI Fluxland Fluxocean dt 2.12 CO2 concentration re-calculated each month Climate Atmosphere Coupler LMDZ4 OASIS 2.4 Ocean ORCA-LIM OPA 8.2 ∆t = physic time step Terrestrial biosphere ORCHIDEE (STOMATE activated) ∆t = 1day Marine Biochemistry PISCES Carbon Land flux GtC/mth EMI = external forcing [Marland et al, 2005 Houghton, 2002] Ocean flux GtC/mth Net total carbon flux Fluxland + Fluxocean 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. LOOP02 CO2 LOOP01 LOOP03 LOOP02 LOOP03 LOOP03 Highlights CO2 change impact on fluxes Highlights climate change impact on fluxes Geochemic al impact Land and Ocean Climate impact Climate feedback 6 Simulated CO2 Concentration [CO2] is recalculated each month based on : positive feedback : 8 ppm in 2040 • fossil fuel and land-use emissions • net CO2 fluxes computed by ORCHIDEE (land) and PISCES (ocean) LOOP2 vs LOOP3 Weaker land and oceanic uptakes in coupled run (LOOP2) Outline I. Confront results to observations A. B. C. D. II. Budgets Seasonal Cycle IAV Long term trends Better understand processes individually Sensitivity experiments (e.g. Ocean Processes) 8 Carbon Dioxide Concentration Simulation matches historical data… [CDIAC, 2005] Is it enough to be confident in the model projections ? 9 Global Budgets : 80s and 90s Atmospheric carbon variation fossil fuel Land use land ocean Mean Budget 90's Mean Budget 80's land use land use LeQuéré fossil fuel IPCC LeQuéré fossil fuel IPCC LOOP LOOP land sink - 2,8 GtC/yr ocean sink - 1.8 GtC/yr -4 -3 -2 -1 0 1 GtC/yr 2 3 Houghton De Fries 4 5 6 Houghton land sink - 2,6 GtC/yr ocean sink - 2,2 GtC/yr -4 -3 -2 -1 0 1 2 3 4 De Fries 5 GtC/yr Good agreement between LOOP and IPCC 6 7 10 Regional Budgets : 1988-2003 Ocean Mean 1988 - 2003 Need to confront models results to inversions data Latitude Global Land Mean 1988 - 2003 90N-30N Takahashi (+rivers) 1995 Takahashi 1995 30N-30S TRANSCOM LOOP 30S-90S -2,5 Global -2 -1,5 -1 -0,5 0 0,5 1 Latitude GtC/yr 90N-30N TRANSCOM 30N-30S LOOP 30S-90S -3 -2,5 -2 -1,5 GtC/yr -1 -0,5 0 Over-estimation in the tropical region for the continental biosphere 11 Regional Breakdown : 1988-2003 N. Atl and N. Pac should be different Regional Breakdown 1988 - 2003 N. America 0 -0.1 Eurasia N. Atlantic N. Pacific 22 emission regions and 78 CO2 measurements [Baker etlocations al., 2005] -0.2 GtC/yr -0.3 -0.4 LOOP -0.5 TRANSCOM -0.6 Takahashi 1995 -0.7 -0.8 -0.9 -1 12 Seasonal Cycle at Mauna Loa A realistic seasonal cycle at a CO2 measurement location Obs. Model 13 Inter-Annual Variability of CO2 Fluxes [Baker et al., 2005] Over estimation of IAV in Land Under estimation of IAV in Ocean Ocean IAV (1988-2003) Standard Deviation TRANSCOM Global LOOP 0 0.5 1 1.5 2 2.5 3 3.5 4 Latitude Latitude Land IAV (1988 - 2003) Standard Deviation TRANSCOM LOOP Global 0 0,2 0,4 GtC/yr 0,6 GtC/yr Land and ocean inter-annual variability [PgC yr-1] 0,8 1 1,2 14 Long Term Trends : The Ocean LOOP GLODAP 96.5 PgC (1860-1995) 106 ± 17 PgC (1800-1994) CO2 Anthropogenic micromol/kg [GLODAP, Sabine et al., 2004] Outline I. Confront results to observations A. B. C. D. II. Budgets Seasonal Cycle IAV Long term trends Better understand processes individually Sensitivity experiments (e.g. Ocean Processes) 16 Offline simulations to determine sensitivity to climate change Atmospheric pCO2 (ppm) Sensitivity Experiments on Ocean Uptake 1 x CO2 4 x CO2 Ocean Uptake (GtC / yr) Global Temperature (°C) Oceanic sink in coupled run is weaker at 4 x CO2 Geochemical + Climatic Effects Geochemical Effect 17 Depth Ocean stratification prevents anth. CO2 penetration. Depth Climate Impact on the marine C-Cycle Only Impact on the natural C-Cycle -25 GtC All effects - 80GtC Years 18 Continental biosphere and oceans sinks are influenced by CO2 increase and by climate change. • Obvious need to model Carbon CycleClimate 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 NAME Occupation e-mail LAURENT BOPP Climate & Ocean Biogeochemical Cycles [email protected] Patricia CADULE Inter. Between Climate Change & BGC – PhD student [email protected] Pierre FRIEDLINGSTEIN Climate & Land Carbon Cycle [email protected] NAME Occupation e-mail Rachid BENSHILA Ocean modelling Engineer [email protected] Patrick BROCKMANN Visualisation software Engineer [email protected] Philippe BOUSQUET CO2 transport [email protected] Arnaud CAUBEL Software Engineer - coupling aspects [email protected] Sébastien DENVIL Climate modelling and global change simulations Engineer [email protected] Jean-Louis DUFRESNE Climate modelling [email protected] Laurent FAIRHEAD Atmospheric modelling Engineer [email protected] Marie-Angèle FILIBERTI Atmospheric Tracer transport Engineer [email protected] Philippe PEYLIN CO2 transport and Inversion [email protected] Peter RAYNER CO2 Inversion [email protected] References 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 GBC Bopp L., (2001), Changements Climatiques et Biogéochimie Marine : Modélisation du dernier Maximum Gliaciaire et de l’Ere Industrielle Bousquet 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), 10.1029/2001GL013777 Friedlingstein 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. 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.16000889.2003.00043.x Marland, 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, 1601-1622 Data sets : Historical CO2 concentration : http://www.cnrm.meteo.fr/ensembles/public/data/CO2_fit.txt MODIS : http://cybele.bu.edu/modismisr/products/modis/modislaifpar.html SeaWIFS : http://oceancolor.gsfc.nasa.gov/SeaWiFS/ Backup 24 “ En résumé ” • 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 25 Climate and Carbon Models Sensitivity LOOP vs C4MIP models ocean sensitivity to [CO2] ocean sensitivity to T° land sensitivity to [CO2] land sensitivity to T° climate sensitivity LOOP is inside C4MIP responses range. But is it a sufficient criterion ? [C4MIP- Friedlingstein et al., 2005] 26 Climate Change and Carbon Cycle Interactions ocean sensitivity to [CO2] ocean sensitivity to T° land sensitivity to [CO2] land sensitivity to T° climate sensitivity Wide range of climate and carbon models [C4MIP-Friedlingstein et al., 2005] sensitivity 27 Simulated CO2 Fluxes ORCHIDEE PISCES 28 Terrestrial Biosphere Model : ORCHIDEE [Krinner, 2005] 29 Oceanic Biogeochemical Model PISCES NH4+ NO3- PO43- Diatoms Si Nano-phyto Iron MicroZoo D.O.M Meso Zoo P.O.M Small Ones Big Ones Marine biology is highly influenced by the ocean dynamic motivating the need of both PISCES and OPA [Aumont, 2001; Aumont 2003] 30 Satellite Data Comparison 31 Sensitivity Analysis Sensitivity of ocean carbon models to climate change 2100 min = - 14 GtC/°C max = - 60 GtC/°C C T Reduction of carbon quantity entering the ocean shows a large range amongst the models year So, what does influence the ocean response to the climate ?