can we infer climate-carbon cycle feedback from past records?
DESCRIPTION
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. - PowerPoint PPT PresentationTRANSCRIPT
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P. Friedlingstein and IC PrenticeParis/Bristol/Exeter/Sidney
+ inputs from V. Masson-Delmotte
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The magnitude of the problem
Brussels, May. 27th 2009
Uncertainty due to the carbon cycle uncertainty
2.6 – 4.1 °C2.4 – 5.6 °C
830 ppm
730 – 1000 ppm
Higher [CO2], larger climate change
IPCC, 2007
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Climate-Carbon Cycle FeedbackCO2 = EMI - Fao - Fab (1) T = CO2 + Tind (2)with: Fao = ao CO2 +ao T (3) Fab = ab CO2 +ab T (4)
(3) and (4) in (1), then (1) in (2) gives:
T = 1/(1-g) Tunc
with:g = (ao + ab )/(1+ ao + ab)
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Climate-Carbon Cycle FeedbackT = 1/(1-g) Tunc = f Tunc
g = (ao + ab )/(1+ ao + ab)
g is the gain of the climate-carbon cycle feedback
f = 1/(1-g) f is the feedback factor
and is the carbon cycle sensitivity to climate (C/T)
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Climate-Carbon Cycle Feedback
Carbon cycle sensitivity
to climate
gClimate carbon cycle
gain
0.04 – 0.30
30 – 200 GtC/K
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What are the available observations ?
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Glacial interglacial CO2 – Temperature
€
g =ΔT
ΔCO2
×ΔCO2
ΔT
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Climate sensitivity is estimated here from 2xCO2 GCMs estimates,in the absence of physical feedbacks (black body response only).
Two caveats
Glacial interglacial CO2 – Temperature
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1. Physical feedbacks
€
g =ΔT
ΔCO2
×ΔCO2
ΔT
€
g = α ×γ
1+ β
Torn and Harte, 2006
Friedlingstein et al., 2006
is the climate sensitivity, accounting for all physical feedbacks
€
TTH 06 =ΔF
λ BB
λ BB = 3.8Wm−2K −1
ΔTF 06 =ΔF
λ i∑λ i∑ =1.3 ± 0.3Wm−2K −1
gG-IG= 0.04*3.8/1.3= 0.12
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Using the Full EPICA record
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Glacial interglacial CO2 – Temperature
€
CO2
ΔT= 7.8633 ppm/K and taking from AR4 gG-IG= 0.08
€
T
ΔCO2
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2. Does this help for future projections?
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Last Millennium and LIA
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Last Millennium and LIA
dCO2/dT= 50.6 ppm/K dCO2/dT= 39.9 ppm/K
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Last Millennium and LIA
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Last Millennium and LIA
dCO2/dT= 7.7 [ 1.7 – 21.4] ppm/K
Confusion in terminology …
dCO2/dT is neither g no …
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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)
€
gLIA = 7.7 ×3[2 to 4.5]
286= 0.08 [0.05 to 0.12]
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€
T
biosphere
Ocean
€
CO2 = γΔT − βΔCO2
i.e.
€
CO2
ΔT=
γ
1+ β
€
Cout = γΔT
€
CO2
time
€
Cin = βΔC
Last Millennium and LIAOr one could derive
But one needs to know on millenium time scales …
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Interannual variability of CO2G
t. C
per
yea
rS
OI
1955 1960 1965 1970 1975 19851980 1990 1995 2000
8
6
4
2
30
0
-30
CO2 Annual Growth Rate
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Interannual variability of CO2
dCO2/dT= 2.9 ppm/K
= -90 GtC/K gG-IG= 0.03
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Summary
gain Carbon sensitivity to climate (GtC/K)
G-IG 0.08 ≈ -110*
LIA 0.08 ≈ -110*
IAV 0.03** -90
C4MIP models average
0.15 -109
*assuming ≈ 5.5, i.e. AF≈ 0.15**assuming equilibrium response
Palaeo and historical CO2 variability could help to constraintClimate carbon cycle feedbackEstimate of seems to be more robust than g across timescales
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SummaryPalaeo and historical CO2 variability might help
to constrain Climate carbon cycle feedbackHowever, large uncertainties on data and on
use of dataEstimate of 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 thanplay with past data to infer future response
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