Will Tropical Forests Dieback
Under Climate Change?
Clues from Year-to-Year Variations
in Atmospheric Carbon Dioxide
Peter Cox
Co-chair of IGBP-AIMES
University of Exeter
Ben Booth, Pierre Friedlingstein, Chris Jones,
Chris Huntingford, David Pearson
Climate-Carbon Cycle
Feedbacks
The Carbon Cycle and Climate Change
Currently only about half of human emissions of CO2
remain in the atmosphere - the ocean and land
ecosystems appear to be absorbing the remainder.
Atmospheric Increase
= 3.2 +/- 0.1 GtC/yr
(50%)
Emissions (fossil fuel, cement) = 6.4 +/- 0.4 GtC/yr (100%)
Ocean-atmosphere flux
= -1.7 +/- 0.5 GtC/yr
(27%)
Land-atmosphere flux
= -1.4 +/- 0.7 GtC/yr
(22%)
Estimated Global Carbon Balance for 1990s (IPCC TAR)
The Carbon Cycle and Climate Change
Currently only about half of human emissions of CO2
remain in the atmosphere - the ocean and land
ecosystems appear to be absorbing the remainder.
Atmosphere-land and atmosphere-ocean fluxes of
CO2 are sensitive to climate.
Interannual Variability in CO2 Growth-rate
CO2 Partitioning (PgC y-1)
Evolution of the fraction of total emissions that remain in the atmosphere
10
Total
CO2 emissions
8
6
4
Atmosphere
2
1960
1970
1980
1990
Time (y)
Updated from Le Quéré et al. 2009, Nature Geoscience; Data: NOAA 2010, CDIAC 2010
2000
2010
Estimated Land and Ocean CO2 Sinks
2
5 models
Land sink
(PgCy-1)
0
-2
-4
-6
1960
1970
1980
1990
2000
2010
1960
1970
1980
1990
2000
2010
0
4 models
Ocean sink
(PgCy-1)
2
-2
-4
-6
Time (y)
Updated from Le Quéré et al. 2009, Nature Geoscience
The Carbon Cycle and Climate Change
Currently only about half of human emissions of CO2
remain in the atmosphere - the ocean and land
ecosystems appear to be absorbing the remainder.
Atmosphere-land and atmosphere-ocean fluxes of
CO2 are sensitive to climate.
How important might climate-carbon cycle feedbacks
be for future climate change?
Standard Climate Change Predictions
Online
CLIMATE
Offline
Greenhouse
Effect
CO2
CO2 Uptake by Ocean /
CO2 buffering effect
CO2 Uptake by Land /
CO2-fertilization of plant
growth
OCEAN
LAND
Fossil Fuel +
Net Land-use
CO2 Emissions
Climate Change Predictions
including Carbon Cycle Feedbacks
Online
CLIMATE
Climate Change effects on
Solubility of CO2
Vertical Mixing
Circulation
Greenhouse
Effect
CO2
OCEAN
Offline
Climate Change effects on
plant productivity, soil
respiration
LAND
Fossil Fuel +
Net Land-use
CO2 Emissions
Hadley Centre climate-carbon GCM simulation showed climate
change suppressing land carbon uptake…..
Global Climate-Land Carbon Cycle Feedbacks
Anthropogenic
Emissions
Climate Sensitivity
+
CO2
CO2
Fertilisation
+
_
Temp
+
-
NPP
+
Climate
Sensitivity of Soil
respiration to Temp
+
Decomp
Land
Modelled GCM feedbacks are competition between CO2-fertilisation of growth
(negative feedback), and accelerated decomposition in warmer climate (positive
feedback).
Key unknowns: Climate sensitivity to CO2
Soil respiration sensitivity to temperature.
CO2-fertilisation of growth
A Key Uncertainty :
Response of Amazonian Forest to
Climate Change
1850
2000
2100
How can we constrain this uncertainty ?
Tipping Points
(Lenton et al., 2008)
Map of potential policy-relevant tipping elements in the climate system, updated from ref. 5
and overlain on global population density
Lenton T. M. et.al. PNAS 2008
Coupled Climate Carbon Cycle Intercomparison
Project (C4MIP)
10 Coupled Climate-Carbon models were used to
simulate 21st century climate and CO2 under similar
scenarios.
Models agreed that effects of climate change on the
carbon cycle will lead to more CO2 in the atmosphere
(positive climate-carbon cycle feedback).
But magnitude of this effect, and primary cause,
varied between models
Predictions of extra CO2 due to climate effects on
the carbon cycle.....
Friedlingstein et al., 2006
....magnitude of positive feedback highly uncertain........
Uncertainty in Future Land
Carbon Storage in Tropics (30oN-30oS)
C4MIP Models (Friedlingstein et al., 2006)
Models without
climate affects on Carbon Cycle
∆CL = β. ∆CO
∆
2
Models with
climate affects on Carbon Cycle
∆CL = β. ∆CO
∆
∆ L
2 + γ. ∆T
GtC/K
(a) Climate Impact on Tropical Land Carbon,
-140
-120
-100
-80
-60
-40
-20
0
γLT
Observational
Constraints
..on Amazon Forest Dieback...
Rationale
The growth-rate of atmospheric CO2 varies
significantly from year-to-year.
Interannual Variability in CO2 Growth-rate
CO2 Partitioning (PgC y-1)
Evolution of the fraction of total emissions that remain in the atmosphere
10
Total
CO2 emissions
8
6
4
Atmosphere
2
1960
1970
1980
1990
Time (y)
Updated from Le Quéré et al. 2009, Nature Geoscience; Data: NOAA 2010, CDIAC 2010
2000
2010
Rationale
The growth-rate of atmospheric CO2 varies
significantly from year-to-year.
These variations are driven by climate variability
especially ENSO.
Influence of ENSO on CO2 Variability
Annual changes in
atmospheric CO2 are
dominated by ENSO
– after removing
anthropogenic rise
– rise during El Nino
– fall during La Nina
∆CO2 - black, Nino3 - red
Rationale
The growth-rate of atmospheric CO2 varies
significantly from year-to-year.
These variations are driven by climate variability
especially ENSO.
Can we use the interannual variability in the CO2
growth-rate as a constraint on the sensitivity of
tropical land carbon to climate change ?
Turning Noise into Signal:
Using Temporal Variability as a
Constraint on Feedbacks
..using model spread
to our advantage…
An Example from Climate Science
IPCC 2007
Forest Dieback and IAV in CO2
The sensitivity of tropical land carbon to climate change is
one of the main reasons for the spread in climate-carbon
cycle feedback across the C4MIP ensemble.
GtC/K
(a) Climate Impact on Tropical Land Carbon,
-140
-120
-100
-80
-60
-40
-20
0
γLT
Try to Decompose the
Land Carbon Sink into (MPI Model)
CO2
T
Degenerate unless interannual
variability is included !
Best linear fit to detrended T
Relationship between
Interannual Variability in
Tropical Land Carbon Sink
and Temperature (1960-2010)
(MPI Model)
Forest Dieback and IAV in CO2
The sensitivity of tropical land carbon to climate change is
one of the main reasons for the spread in climate-carbon
cycle feedback across the C4MIP ensemble.
The tropical “GAMMA” across the C4MIP GCMs is linearlyrelated to the sensitivity of the CO2 growth-rate to
interannual variability in tropical temperatures.
GtC/K
(a) Climate Impact on Tropical Land Carbon,
-140
-120
-100
-80
-60
-40
-20
0
12
GtC/yr/K
10
8
6
4
2
0
γLT
(b) Sensitivity of CO2 Growth-Rate to Tropical Temperature
Constraints from Observed
Interannual Variability
Global CO2 Growth-rate
Mean Temperature 30oN-30oS
Constraints from Observed
Interannual Variability
Forest Dieback and IAV in CO2
The sensitivity of tropical land carbon to climate change is
one of the main reasons for the spread in climate-carbon
cycle feedback across the C4MIP ensemble.
The tropical “GAMMA” across the C4MIP GCMs is linearlyrelated to the sensitivity of the CO2 growth-rate to
interannual variability in tropical temperatures.
The CO2 record (RCP = ML+SP?) suggests a real-world
sensitivity of the CO2 growth-rate to tropical temperature of
dCO2/dt = 4.01+/-0.76 GtC/yr/K
Observational
Constraint
Forest Dieback and IAV in CO2
The sensitivity of tropical land carbon to climate change is
one of the main reasons for the spread in climate-carbon
cycle feedback across the C4MIP ensemble.
The tropical “GAMMA” across the C4MIP GCMs is linearlyrelated to the sensitivity of the CO2 growth-rate to
interannual variability in tropical temperatures.
The CO2 record (RCP = ML+SP?) suggests a real-world
sensitivity of the CO2 growth-rate to tropical temperature of
dCO2/dt = 4.01+/-0.76 GtC/yr/K
Using the relationship across the C4MIP GCMs implies a
relatively weak sensitivity of tropical land carbon to climate
change.
Tropical Forest dieback much less of a worry now.....
Conclusions
The sensitivity of tropical land carbon to climate change (i.e.
Amazon forest dieback) is one of the main reasons for the
huge spread in climate-carbon cycle feedback amongst
models.
Models suggest a linear relationship between tropical carbon
loss and interannual variability (IAV) in atmospheric CO2,
and this may be used to constrain the risk of tropical forest
dieback using the observed IAV in CO2.
Are there similar “emergent constraints” on other aspects of
climate-carbon feedbacks?