1. WP 4: Climate Change and Ocean Acidification 2nd Annual Meeting Paris, 14-16 May 2012 MACROES

2. WP4: Climate Change and Ocean Acidification WP4 main objectives: --- Use the MACROES modelling framework to study the effects of anthropogenic emissions (greenhouse gases, aerosols) through climate change and ocean acidification on the marine ecosystems (incl. fish ressources) --- A particular emphasis will be given to the identification and characterization of the feedbacks between the different (natural) systems considered here (climate, biogeochemical cycles, marine ecosystems) WP4 structure: --- 4.1 Impact of CC and OA on marine ecosystems: end-to-end --- 4.2 Retroactions in the coupled system - Top-down control from higher to lower trophic levels - Biophysical coupling through heat trapping and bio-induced turbulence --- 4.3 Impact of CC and OA on marine ecosystems: biodiversity

3. WP4: Climate Change and Ocean Acidification Les « drivers » : productivité marine, acidification, dé-oxygénation Les premières simulations avec IPSL-CM / PISCES-APECOSM A venir cette année…

4. Climate Change impact on surface chlorophyll 250 450 650 850 6.0 3.0 0.0 RCP8.5 RCP6.0 RCP4.5 RCP2.6 Historical T (°C) Chl de surface (mgChl/m3) 0.15 0.17 0.19 Premiers Résultats avec CM5 CO 2, T et chlorophylle de surface

5. Biogeochemical Drivers Changes in Net Primary Productivity driven by climate change

6. Biogeochemical Drivers Changes in Net Primary Productivity driven by climate change Net Primary Productivity as simulated by 8 CMIP5 models IPSL-CM5A-LRIPSL-CM5A-MRMIROC-ESM-CHEM MIROC-ESMHadGEM2-ESHadGEM2-CC MPI-ESM CanESM2 IPSL-CM5 IPSL-CM5 Biogéochimie Marine : Séférian et al. in press Comparaison des modèles IPCC – CMIP5 / Productivité marine :Kidston et al. in prep

7. IPSL-CM5A-LR IPSL-CM5A-MR MPIM-ESM MIROC-ESM MIROC-ESM-CHEM CanESM2 HadGEM2-ES HadGEM2-CC Biogeochemical Drivers Changes in Net Primary Productivity driven by climate change A global decrease of NPP by -5 to -18% in 2100 Relative Change in NPP from 2005 to 2100 (RCP85 scenario)

8. Biogeochemical Drivers Changes in Net Primary Productivity driven by climate change Relative Change in NPP from 2005 to 2100 (RCP85 scenario, model-mean, %) Hatched regions: when >75% of the models agree on the sign of change Large regional contrasts: -50% in N. Atl, -20% in the tropics, increase in the SO

9. Biogeochemical Drivers Changes in pH / Ocean Acidification

10. Biogeochemical Drivers Changes in pH / Ocean Acidification RCP4.5 RCP8.5 Orr et al. in prep IPSL-CM5A-LR, IPSL-CM5A-MR, HadGEM2-ES, HadGEM2-CC, MPIM-ESM, MIROC-ESM, MIROC-ESM-CHEM, CanESM Consistent decrease in pH from several CMIP5 models RCP45: -0.3 RCP85: from -0.4 to -0.8 in 2300 !

11. Biogeochemical Drivers Changes in pH / Ocean Acidification RCP4.5 RCP8.5 Aragonite / Calcite undersaturation reached at the surface in polar oceans Implications on calcification / trophic food webs? [CO 3 2- ]

12. Biogeochemical Drivers Changes in pH / Ocean Acidification RCP4.5 RCP8.5 Increase in C/N ratios of organic matter (Riebesell et al. 2008) Implications on food quality ? (Tagliabue et al. 2011)

13. Biogeochemical Drivers Changes in Oxygen / Desoxygenation

14. Biogeochemical Drivers Changes in Oxygen / Desoxygenation Stramma et al. 2008 Observed increase of hypoxic waters in the Eq. Pacific

15. O2 ( mol/L) Changes in [O 2 ] (micromol/L) (5-model mean, SRES-A2) : 0 m Biogeochemical Drivers Changes in Oxygen / Desoxygenation Large decrease of O 2 in surface waters: solubility-driven Hatched regions: when >75% of the models agree on the sign of change (IPSL-CM4, UVIC, CSM1.4, CCSM3, BCM-C)

16. O2 ( mol/L) Changes in [O 2 ] (micromol/L) (5-model mean, SRES-A2) : 200 m Biogeochemical Drivers Changes in Oxygen / Desoxygenation Consistent at mid/high lat but models do not agree in the tropics ! Hatched regions: when >75% of the models agree on the sign of change

17. Towards coupled climate & end-to-end ecosystem modelling Towards Online Coupling: PISCES-APECOSM

18. Towards coupled climate & end-to-end ecosystem modelling PISCES-APECOSM :: Preliminary RCP85 results (see talk by S. Dueri for more details) Nanophytoplankton relative changeDiatoms relative change Microzooplankton relative changeMesozooplankton relative change 15% drop of total biomass in 2100 compared to preindustrial values Large disparity among plankton functional types: Phyto : -8%, Diatoms : -16%, Microzoo : -20%, Mesozoo : -20%. Latitude Time (1850 to 2100) LOWER TROPHIC

19. Towards coupled climate & end-to-end ecosystem modelling PISCES-APECOSM :: Preliminary RCP85 results Latitude Time (1850 to 2100) Total biomass relative changeEpipelagic biomass relative change Migratory biomass relative changeMesopelagic relative change 23% drop of total biomass in 2100 compared to preindustrial values Large disparity among communities: Epipelagic : -22%, Migratory : -8%, Mesopelagic : -30% UPPER TROPHIC

20. Etapes / Stratégie pour le WP4 End-to-End Etape 1 M12 : Simulations offline sur 1860-2100 (RCP8.5) IPSL-CM ( PISCES APECOSM ) M18 : Analyse de limpact du CC (et OA) sur les écosystèmes Etape 2 M24: Mise en place de PISCES-APECOSM dans IPSL-CM (biomixing) M24 : Importance du top-down control dans un contexte de CC IPSL-CM ( PISCES APECOSM ) Etape 3 M42: Simulations offline sur 2000-2100 (biodiversité) IPSL-CM PISCES-APECOSM-DEB/Biodiv (?) M48: Analyse de ces simulations En cours

21. Climatic scenarios: Climatic scenarios: Governance scenarios: IPSL model 3.Fishing scenarios ? E2E model 2. Retroactions 1.Sensitivity (acidification ?) Towards coupled climate & end-to-end ecosystem modelling

22. Some issues: spatial resolution, internal variability, model spread Model Spread? : use of CMIP5 models ? Spatial resolution? : towards higher resolution (global) / regional configurations ? Internal variability? Climate simulations: difficult to use for the next decade or so (2010-2030) as internal variability tends to dominate on these time-scales ?

23. Some issues: spatial resolution, internal variability, model spread Model Spread? Spatial resolution? Internal variability? 10 members Ensemble mean Decadaly-smoothed control run 50 ans Séférian et al. in prep -Some decadal predictions with climate models in IPCC-AR5 (over 2000-2030, with initialization procedure) -Do models have some previsibility skills for marine productivity evolution? PP in North Atlantic simulated by IPSL-PISCES