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Can we infer climate-carbon cycle feedback from past records?

Can we infer climate-carbon cycle feedback from past records?. P. Friedlingstein and IC Prentice Paris/Bristol/Exeter/Sidney + inputs from V. Masson-Delmotte. The magnitude of the problem. 830 ppm. Uncertainty due to the carbon cycle uncertainty. 730 – 1000 ppm.

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Can we infer climate-carbon cycle feedback from past records?

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  1. Can we infer climate-carbon cycle feedback from past records? P. Friedlingstein and IC Prentice Paris/Bristol/Exeter/Sidney + inputs from V. Masson-Delmotte

  2. The magnitude of the problem 830 ppm • Uncertainty due to the carbon cycle uncertainty 730 –1000 ppm • Higher [CO2], larger climate change 2.6 – 4.1 °C 2.4 – 5.6 °C IPCC, 2007

  3. Climate-Carbon Cycle Feedback CO2 = EMI -  Fao -  Fab (1) T = CO2 + DTind (2) with:  Fao = baoCO2 +gaoT (3)  Fab = babCO2 +gabT (4) (3) and (4) in (1), then (1) in (2) gives: T = 1/(1-g) Tunc with: g =  (gao + gab )/(1+ bao + bab)

  4. Climate-Carbon Cycle Feedback T = 1/(1-g) Tunc = f Tunc g =  (gao + gab )/(1+ bao + bab) g is the gain of the climate-carbon cycle feedback f = 1/(1-g) f is the feedback factor and g is the carbon cycle sensitivity to climate (DC/DT)

  5. Climate-Carbon Cycle Feedback g Carbon cycle sensitivity to climate 30 – 200 GtC/K g Climate carbon cycle gain 0.04 – 0.30

  6. What are the available observations ?

  7. Glacial interglacial CO2 – Temperature

  8. Glacial interglacial CO2 – Temperature Climate sensitivity is estimated here from 2xCO2 GCMs estimates, in the absence of physical feedbacks (black body response only). Two caveats

  9. 1. Physical feedbacks Torn and Harte, 2006 Friedlingstein et al., 2006 • is the climate sensitivity, accounting for all physical feedbacks gG-IG= 0.04*3.8/1.3 = 0.12

  10. Using the Full EPICA record

  11. Glacial interglacial CO2 – Temperature 7.8633 ppm/K and taking from AR4 gG-IG= 0.08

  12. 2. Does this help for future projections?

  13. Last Millennium and LIA

  14. Last Millennium and LIA dCO2/dT= 39.9 ppm/K dCO2/dT= 50.6 ppm/K

  15. Last Millennium and LIA

  16. Last Millennium and LIA dCO2/dT= 7.7 [ 1.7 – 21.4] ppm/K Confusion in terminology … dCO2/dT is neither g no g …

  17. Last Millennium and LIA dCO2/dT= 7.7 [ 1.7 – 21.4] ppm/K One could derive the gain g: (again, taking dT/dCO2 from 2xCO2 sensitivity)

  18. Last Millennium and LIA Or one could derive g i.e. time biosphere Ocean But one needs to know b on millenium time scales …

  19. Gt. C per year SOI 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 Interannual variability of CO2 CO2Annual Growth Rate 8 6 4 2 30 0 -30

  20. Interannual variability of CO2 dCO2/dT= 2.9 ppm/K g = -90 GtC/K gG-IG= 0.03

  21. Summary *assuming b ≈ 5.5, i.e. AF≈ 0.15 **assuming equilibrium response Palaeo and historical CO2 variability could help to constraint Climate carbon cycle feedback Estimate of g seems to be more robust than g across timescales

  22. Summary • Palaeo and historical CO2 variability might help to constrain Climate carbon cycle feedback • However, large uncertainties on data and on use of data • Estimate of g seems to be more robust than g across timescales. Is this accidental ? • Do we get the “right” number for the right reason (right process) ? • Best way is certainly not what I just presented... We should simulate the past rather than play with past data to infer future response

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