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Climate sensitivity: what observations tell us about model predictions Corinne Le Quéré Max-Planck-Institut für Biogeochemie, Jena, Germany Acknowledgements:

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Presentation on theme: "Climate sensitivity: what observations tell us about model predictions Corinne Le Quéré Max-Planck-Institut für Biogeochemie, Jena, Germany Acknowledgements:"— Presentation transcript:

1 Climate sensitivity: what observations tell us about model predictions Corinne Le Quéré Max-Planck-Institut für Biogeochemie, Jena, Germany Acknowledgements: Laurent Bopp, Karen Kohfeld, Erik Buitenhuis, Olivier Aumont

2 CO 2 sink (PgC/y) (J. Orr and OCMIP-2 participants) today no biology, no climate change time

3 CO 2 sink (PgC/y) (J. Orr and OCMIP-2 participants) Heimann and Maier- Reimer 1996 no biology, no climate change time Prentice et al. 2001, based on data from Manning 2001, Langenfelds et al., 1999, and Sabine et al., 2002 Le Quéré et al. 2003 Takahashi et al. 2002 Battle et al. 2000 Gruber and Keeling 2001

4 CO 2 export production 100 yr predictions 100,000 yrs variations interannual variations outline

5 oceanic carbon cycle Silicifi ers N 2 fixers DMS producer s Calcifiers Nano phytoplankt on Fe NO 3 SiSi CaCO 3 DM S PO4PO4 NH 4 DOM biological activity 11 45 34 physical transport 11 33 CO 2 CO 2 + H 2 O + CO 2- 3 2HCO - 3 chemical reactions 90

6 how do marine ecosystems respond to: elevated CO 2 warming nutrient supply stratification

7 physical response to elevated CO 2 Reduced CO 2 solubility Reduced vertical circulation (Sarmiento et al., in prep.)

8 oceanic carbon cycle Silicifi ers N 2 fixers DMS producer s Calcifiers Nano phytoplankt on Fe NO 3 SiSi CaCO 3 DM S PO4PO4 NH 4 DOM biological activity 11 45 34 physical transport 11 33 CO 2 CO 2 + H 2 O + CO 2- 3 2HCO - 3 chemical reactions 90

9 diatoms DOM N 2 fixers DMS producers Calcifiers Nano phytoplankton Fe NO 3 SiSi CaCO 3 PO 4 NH 4 nutrient-based models (Najjar et al., 1992; Maier-Reimer 1993)

10 diatoms DOM N 2 fixers DMS producers Calcifiers Nano phytoplankton Fe NO 3 Si CaCO 3 NPZD PO 4 NH 4 (Fasham et al., 1993)

11 N 2 fixers DMS producers Calcifiers Nano phytoplankton Fe NO 3 Si CaCO 3 ecosystem models PO 4 NH 4 DOM (Aumont et al. 2003; Moore et al., 2001) diatoms

12 (Bopp 2001) N S equator latitude reduction in nutrient supply increase of oligotrophic gyres longer growing season Modelled changes in export production at 2xCO 2 +30 % -30 %

13 CO 2 sink (PgC/y) climate feedback (Prentice et al., 2001) time

14 CO 2 sink (PgC/y) CO 2 + climate (Prentice et al., 2001) time

15 (slide from J. Sarmiento)

16 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations interannual variations

17 CO 2 export production 100 yr predictions -5 to -15% [warming]-0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations interannual variations

18 CO 2 (ppm) 0°C -8°C 280 ppm 200 ppm 5.8°C 1.4°C 960 ppm 550 ppm Temperature ( o C) 400,000 years 100,000 yrs variations (data from Petit et al., 1999)

19  x2 over the ocean Circulation Changes (Simulation OPA model, O. Marti) Increased Sea -Ice in Winter (Crosta et al. 1998) Increased dust deposition on the ocean (Mahowald et al. 1999) Cooling of SST (CLIMAP 1981) Model simulations of the last glacial maximum (Bopp et al., 2003)

20 total LGM impact on export production (Bopp et al., 2003) decreased export production (-7 %) decreased atmospheric CO 2 (-30 ppm) gC/m2/y

21 total LGM impact on export production (Bopp et al., 2003) Diatoms Nano-phyto  Diatoms diatoms relative abundance Nano-phyto Diatomées Latitude iron LGM impact on export production increased export production (+6 %) but increase of oligotrophic gyres shift from nano-phyto to diatoms

22 Opal (SiO 2 ) Calcium Carbonate (CaCO 3 ) Organic Carbon Biomarker (C37 Alkenones) 10 Be 231 Pa Excess Barium Authigenic Uranium Authigenic Cadmium Benthic Foraminifera Fluxes Age Models Radiocarbon dating (AMS) Oxygen Isotope Stratigraphy Lithogenic Correlation Flux measurement Constant Flux Normalization ( 230 Th) Mass Accumulation Rates Sediment Concentration Evaluation of Paleo-Data Proxy Agreement How many? Percentage agreement Ranking Criteria: Ranked Classes: Paleo-Export Proxies: Data Confidence high medium low (Kohfeld et al., in prep.)

23 LGM-Stage 5ad LGM-today “Today ” Stage 5ad-today Stage 5a-d LGM dust CO 2 change in export production (Kohfeld et al., in prep.) time Unpublished map not available Unpublished map not available

24 / OPA-PISCES model (Bopp et al. 2003) (gC m -2 yr -1 ) Data-base (Kohfeld et al., in prep.) change in export production

25 / OPA-PISCES model (Bopp et al. 2003) (gC m -2 yr -1 ) Data-base (Kohfeld et al., in prep.) change in export production

26 Maximum effect with this model 41 ppm CO 2 drawdown with this model 30 ppm SST + SSS (+ sea ice + circ.) = –15 ppm Dust increase –15 ppm (Bopp et al., 2003)

27 dust CO 2 Watson et al., 200040 ppm Archer et al. 20008 ppm Bopp et al. in press15 ppm ReferenceCO 2 reduction due to dust at the LGM (Watson et al., 2000) reasonable agreement considering the phasing of dust/CO 2 changes time

28 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations

29 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations

30 Le Quéré et al., in press CO 2 variability (Pg C/y) atmosphere Mean: 3.2 PgC/y interannual CO 2 variability time 20 years

31 (Le Quéré et al., 2003) CO 2 variability (Pg C/y) atmosphere ocean

32 (Bousquet et al., 2000; data from Feely et al., 1999) equatorial Pacific During El Nino events:CO 2 warming decreased upwelling decreased export production CO 2 variability (Pg C/y) MIT model ( McKinley 2002) Hamburg model (Winguth et al., 1994) OPA model (Le Quéré et al., 2000)

33 northern sub-tropics (Peylin et al., in prep) CO 2 variability (mol/m 2 /y) MIT model OPA model observations

34 North Atlantic (Gruber et al., 2002)

35 Chla (SeaWiFS) Standard deviation of interannual signal SST (Reynolds and Smith 1994) MLD (indirect estimate using SSH) SSH (TOPEX/Poseidon)

36 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio]

37 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio]

38 SeaWiFS chla, PP from Behrenfeld and Falkowski (1997), ef-ratio from Laws et al. (2000) Standard deviation of export production variability 1997-2002 (mol C/m 2 /yr) 1.5 1.0 0.5 0.0

39 diatoms DOM N 2 fixers DMS producers Calcifiers Nano phytoplankton Fe NO 3 SiSi CaCO 3 PO 4 NH 4 nutrient-based models (HAMOCC3) (Maier-Reimer 1993)

40 SeaWiFS chla, PP from Behrenfeld and Falkowski (1997), ef-ratio from Laws et al. (2000) Standard deviation of export production variability (mol C/m 2 /yr) 1.5 1.0 0.5 0.0 HAMOCC3

41 diatoms DOM N 2 fixers DMS producers Calcifiers Nano phytoplankton Fe NO 3 Si CaCO 3 NPZD PO 4 NH 4 (Aumont et al.,2002 based on Maier-Reimer and Six 1996)

42 SeaWiFS chla, PP from Behrenfeld and Falkowski (1997), ef-ratio from Laws et al. (2000) Standard deviation of export production variability (mol C/m 2 /yr) 1.5 1.0 0.5 0.0 NPZD HAMOCC3

43 N 2 fixers DMS producers Calcifiers Nano phytoplankton Fe NO 3 Si CaCO 3 PISCES model based on plankton functional types PO 4 NH 4 DOM diatoms (Aumont et al., 2003; Bopp et al., 2003)

44 SeaWiFS chla, PP from Behrenfeld and Falkowski (1997), ef-ratio from Laws et al. (2000) Standard deviation of export production variability (mol C/m 2 /yr) 1.5 1.0 0.5 0.0 PISCES NPZD HAMOCC3

45 Dynamic Green Ocean Model N 2 fixers DMS producers coccolith. Nano phytoplankton Fe NO 3 Si CaCO 3 PO 4 NH 4 DOM diatoms (Buitenhuis et al., 2003)

46 SeaWiFS chla, PP from Behrenfeld and Falkowski (1997), ef-ratio from Laws et al. (2000) Standard deviation of export production variability (mol C/m 2 /yr) 1.5 1.0 0.5 0.0 DGOM 4 PISCES NPZD HAMOCC3 (Le Quéré et al., in prep.)

47 diatoms coccolithophorids nano- phytoplankton P Growth rate

48 (Chavez et al 2003)

49 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio] +/- 1%

50 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio] +/- 1%

51 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio] +/- 1%

52 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio] +/- 1%

53 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio] +/- 1% plankton functional types

54 CO 2 export production 100 yr predictions -5 to -15% [warming]0 to -6% [nutrient supply] - low lat + high lat 100,000 yrs variations -8 to -40 ppm [iron] -15 ppm [solub.] -25 to -75 ppm left ~0 [iron + circ] + mid-low lat [iron] - high lat [circ + bio] interannual variations +/- 0.3 ppm +/- 0.3 ppm tropics [circ] +/- 0.05 ppm mid lat [solub.] +/- 0.05 ppm high lat [circ + bio] +/- 1% plankton functional types linkages between biogeochemistry and physics (including the coastal ocean)

55 CO 2 (ppm) 0°C -8°C 280 ppm 200 ppm 5.8°C 1.4°C 960 ppm 550 ppm Temperature ( o C) 400,000 years CO 2 (ppm) 0°C -8°C 280 ppm 200 ppm 5.8°C 1.4°C 960 ppm 550 ppm Temperature ( o C) CO 2 (ppm) 0°C -8°C 280 ppm 200 ppm Temperature ( o C) 400,000 years 5.8°C 1.4°C 960 ppm 550 ppm 1850 JGOFS 2100 Vostok global

56

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