1. Core Theme 5 – WP 17 Overview on Future Scenarios - Update on WP17 work (5 european modelling groups : IPSL, MPIM, Bern, Bergen, Hadley) - Strong link with Euroceans (FP6-NoE) (WP3.3 Lead : Fortunat Joos) - Ocean part of C4MIP (Coupled Carbon Cycle - Climate Model Intercomparison Project : an IGBP/AIMES project, Lead : Pierre Friedlingstein) Laurent Bopp, IPSL/LSCE, Gif, France On behalf of the WP17 members

2. R esults from C4MIP (Friedlingstein et al. 2006) W17 CARBON –CLIMATE COUPLING - 11 Climate-Carbon Coupled Models (7 GCMs + 4 EMICs) - Same emissions scenario from 1860 to 2100 - 2 simulations each : Uncoupled + Coupled

3. R esults from C4MIP W17 CARBON –CLIMATE COUPLING Feedback Analysis : g = –  (  L +  O ) / (1 +  L +  O )  Climate sensitivity to CO2  Ocean and Land carbon sensitivity to atmospheric CO2  Ocean and Land carbon sensitivity to climate  ocean  ocean

4. Part I. More constrains on the   term [ Uptake / Atm. pCO2 ] Use of anthropogenic DIC estimates Use of other tracers (CFC…) Mechanisms that explain the models divergence Part II. More constrains on the   term [ Uptake / Climate change ] Mechanisms that explain the models divergence Sensivity experiments to explore the mechanisms Constrains from observations

5. Part I. More constrains on the   term [ Uptake / Atm. pCO2 ] Use of anthropogenic DIC estimates Use of other tracers (CFC…) Mechanisms that explain the models divergence IPSL- CM2C IPSL-CM4MPIM UNIBE/NCAR HADLEY FRCGC  o (PgC/ppm)1.61.1 0.90.8 1.2

6. Sabine et al. 2004 Anthropogenic DIC Waugh et al. 2006

7. Anthropogenic DIC : Regional Scale IPSLGLODAP (Sabine et al. 2004) Atlantic Pacific 96.5 GtC 106 +/- 17 GtC 119 +/- 17 GtC (Cadule et al.)

8. Matsumoto et al. 2004, Orr et al. 2003 CFC : Learn from OCMIP Use other tracers observations to get higher constrain on modelled carbon uptake

9. CFC11 in the IPSL coupled model Run offline with the same circulation fields than the coupled run Modelled CFC11 inventories from 1960 to 1998

10. CFC11 in the IPSL coupled model CFC11 inventories (pmol/m2) IPSL Model GLODAP Run offline with the same circulation fields than the coupled run

11. Ocean Cant uptake ↔ Volume of light water Mechanisms that explain the models divergence

12. Ocean Cant uptake (beta factor) ↔ Volume of light water

13. From Climatology of Mixed Layer Depth :  o = 0.93-0.95 (Boyer de Montegut et al. 2004) Mechanisms that explain the models divergence

14. Part II. More constrains on the   term [ Uptake / Climate change ] Mechanisms that explain the models divergence Sensivity experiments to explore the mechanisms Constrains from observations ? IPSL- CM2C IPSL-CM4MPIM UNIBE/NCAR HADLEY FRCGC  o (PgC / °C)-30-16-22-17-24 -46

15. Mechanisms : -Increasing Sea Surface Temperature decreases CO2 solubility - Decreased Mixing prevents the penetration of C ant. - Decrease in Biological Production reduces the amount of carbon transported to depth. ….. Mechanisms that explain the models divergence  SST (°C)  MXL (m)  THC (Sv)  O.M export (PgC/y)

16. No clear global relationship : Need to break down the responses at regional levels.

17. 3 simulations with the same Coupled GCM (1 Control and 2 scenarios) THC (Sv) CTL GW1 GW2 CTL : Control – No Climate Change GW1 : 1xCO2 > 4xCO2 – No additional ice melting in the North GW2 : 1xCO2 > 4xCO2 – Additional ice melting in the North Swingedouw et al. subm. Sensitivity experiment : Role of THC

18. 3 simulations with the same Coupled GCM (1 Control and 2 scenarios) THC (Sv) CTL GW1 GW2 Cumulative Carbon Uptake (GtC) THC-related SST and SSS effects counter-balance the dynamical effect CTL > GW1 = GW2 Swingedouw et al. subm. Sensitivity experiment : Role of THC

19. Constrains from observations on gamma ? - Interannual / decadal variability of Carbon Fluxes / DIC inventories : (difficult because model / real years do not match) : difficult because of the additional C_ant signal - Interannual / decadal variability of oceanic O2 - Interannual / decadal variability of atmospheric APO signal. … relation bewteen  and the modelled O2 outgassing ? … observed trends in APO ? Matear et al. 2000 (1995-1968)

21. Motivation :Climate Impact on Carbon Fluxes How can we test the models ?  Using Oceanic Carbon measurements : difficult because climate effect only a second order impact. First order is the anthopogenic signal  Using Oceanic Oxygen measurements : impacted by same processes that Carbon : Dyn., Bio., Thermo. … but no atmospheric signal in the ocean / no chemistry the O2 oceanic data-base is expanding : several publications have reported changes in O2 concentrations over the last decades and for different basins North Pacific : Emerson, Ono, Wanatabe, Kim South Pacific : Shaffer South Indian : Bindoff and McDougall North Atlantic : Garcia Southern Ocean : Matear …….

22. Modelling Results Models compare reasonably well with observed changes Matear et al. 2000 (1995-1968) Plattner et al. 2002 (90s – 70s) North Pacific

23. Modelling Results Models compare reasonably well with observed changes Deutsch et al. 2005 90s-80s North Pacific

25. N ew input from CARBOOCEAN D17.2 CARBON –CLIMATE COUPLING. 5 new coupled climate-carbon coupled GCMs. some groups have already completed their runs Atmospheric CO2 Difference (ppm) IPSL : +32 ppm MPI : + 83 ppm

26. N ew input from CARBOOCEAN : Oceanic Focus D17.2 CARBON –CLIMATE COUPLING  ocean  ocean MPI IPSL - Comparison to observations when possible ? - Comparison of models to determine major mechanisms

27. Oceanic Focus  ocean  ocean - Comparison of models to determine major mechanisms of climate impact - Comparison to observations (validation, benchmarking, …)