Transcript New Coupled Climate-Carbon Simulations with the IPSL Model

New Coupled Climate-Carbon
Simulations with the IPSL Model
From validation to sensitivity analysis
P. CADULE, L. BOPP, P. FRIEDLINGSTEIN
Seventh International Carbon Dioxide Conference
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Carbon Models Offline Responses
[IPCC TAR, 2001]
Either weaker sinks or sources according to
future projections with identical IPCC CO2
and Climate scenarii
3
Carbon Models Online Responses
Atm. [CO2]
All models have a
positive feedback but …
Δ[CO2]max= 224 ppm
Δ[CO2]min = 19 ppm
[C4MIP- Friedlingstein et al., 2005]
Large panel of possible responses due to a
wide range of climate and carbon models
sensitivities
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A New Carbon Climate Coupled Model
Atmospheric
[CO2]
d CO2  EMI  Fluxland  Fluxocean 

dt
2.12
CO2 concentration
re-calculated each month
Climate
Atmosphere Coupler
LMDZ4
OASIS 2.4
Ocean
ORCA-LIM
OPA 8.2
∆t = physic time step
Terrestrial biosphere
ORCHIDEE
(STOMATE activated)
∆t = 1day
Marine
Biochemistry
PISCES
Carbon
Land flux GtC/mth
EMI = external forcing
[Marland et al, 2005
Houghton, 2002]
Ocean flux GtC/mth
Net total carbon flux
Fluxland + Fluxocean
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A New Carbon Climate Coupled Model
•
LOOP02 : fully coupled, emissions
– Climate aware of CO2 increase
•
LOOP03 : decoupled, emissions
– Climate agnostic to CO2 increase
fix atmospheric CO2 concentration
[CO2] = 286.2 ppm
Climate
Fossil emi.
LOOP02
CO2
LOOP01
LOOP03
LOOP02
LOOP03
LOOP03
Highlights CO2
change impact
on fluxes
Highlights
climate change
impact on fluxes
Geochemic
al
impact
Land and Ocean
Climate
impact
Climate
feedback
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Simulated CO2 Concentration
[CO2] is recalculated
each month
based on :
positive feedback :
8 ppm in 2040
• fossil fuel and
land-use
emissions
• net CO2 fluxes
computed by
ORCHIDEE
(land) and
PISCES
(ocean)
LOOP2 vs LOOP3
Weaker land and oceanic uptakes in coupled run (LOOP2)
Outline
I.
Confront results to observations
A.
B.
C.
D.
II.
Budgets
Seasonal Cycle
IAV
Long term trends
Better understand processes individually
Sensitivity experiments (e.g. Ocean Processes)
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Carbon Dioxide Concentration
Simulation
matches
historical
data…
[CDIAC, 2005]
Is it enough to be confident in the model
projections ?
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Global Budgets : 80s and 90s
Atmospheric carbon variation
fossil fuel
Land use
land
ocean
Mean Budget 90's
Mean Budget 80's
land use
land use
LeQuéré
fossil fuel
IPCC
LeQuéré
fossil fuel
IPCC
LOOP
LOOP
land sink
- 2,8 GtC/yr
ocean sink
- 1.8 GtC/yr
-4
-3
-2
-1
0
1
GtC/yr
2
3
Houghton
De Fries
4
5
6
Houghton
land sink
- 2,6 GtC/yr
ocean sink
- 2,2 GtC/yr
-4
-3
-2
-1
0
1
2
3
4
De Fries
5
GtC/yr
Good agreement between LOOP and IPCC
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7
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Regional Budgets : 1988-2003
Ocean Mean
1988 - 2003
Need to confront models
results to inversions data
Latitude
Global
Land Mean
1988 - 2003
90N-30N
Takahashi (+rivers) 1995
Takahashi 1995
30N-30S
TRANSCOM
LOOP
30S-90S
-2,5
Global
-2
-1,5
-1
-0,5
0
0,5
1
Latitude
GtC/yr
90N-30N
TRANSCOM
30N-30S
LOOP
30S-90S
-3
-2,5
-2
-1,5
GtC/yr
-1
-0,5
0
Over-estimation in the
tropical region for the
continental biosphere
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Regional Breakdown : 1988-2003
N. Atl and N. Pac
should be different
Regional Breakdown
1988 - 2003
N. America
0
-0.1
Eurasia
N. Atlantic
N. Pacific
22 emission regions and
78 CO2 measurements
[Baker etlocations
al., 2005]
-0.2
GtC/yr
-0.3
-0.4
LOOP
-0.5
TRANSCOM
-0.6
Takahashi 1995
-0.7
-0.8
-0.9
-1
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Seasonal Cycle at Mauna Loa
A realistic seasonal cycle
at a CO2 measurement location
Obs.
Model
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Inter-Annual Variability of CO2 Fluxes
[Baker et al., 2005]
Over estimation of IAV in Land
Under estimation of IAV in Ocean
Ocean IAV (1988-2003)
Standard Deviation
TRANSCOM
Global
LOOP
0
0.5
1
1.5
2
2.5
3
3.5
4
Latitude
Latitude
Land IAV (1988 - 2003)
Standard Deviation
TRANSCOM
LOOP
Global
0
0,2
0,4
GtC/yr
0,6
GtC/yr
Land and ocean inter-annual variability [PgC yr-1]
0,8
1
1,2
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Long Term Trends : The Ocean
LOOP
GLODAP
96.5 PgC (1860-1995)
106 ± 17 PgC (1800-1994)
CO2 Anthropogenic micromol/kg
[GLODAP, Sabine et al., 2004]
Outline
I.
Confront results to observations
A.
B.
C.
D.
II.
Budgets
Seasonal Cycle
IAV
Long term trends
Better understand processes individually
Sensitivity experiments (e.g. Ocean Processes)
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Offline simulations to
determine sensitivity to
climate change
Atmospheric pCO2
(ppm)
Sensitivity Experiments on Ocean
Uptake
1 x CO2
4 x CO2
Ocean Uptake
(GtC / yr)
Global Temperature
(°C)
Oceanic sink in coupled run is weaker at 4 x CO2
Geochemical + Climatic Effects
Geochemical Effect
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Depth
Ocean stratification prevents
anth. CO2 penetration.
Depth
Climate Impact on the marine C-Cycle
Only Impact
on the
natural
C-Cycle
-25 GtC
All
effects
- 80GtC
Years
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Continental biosphere and oceans sinks are
influenced by CO2 increase and by climate
change.
• Obvious need to model Carbon CycleClimate interactions.
• Wide range of possible response drives the
need for a better understanding of involved
processes.
• Observations and inversions both at global
and breakdown region scale constitute the
best common reference
• Identify and implement, in the models, human
dependent processes (e.g. land-use) that
play an important role in the carbon cycle.
Thank You !
With the contribution of
Rachid BENSHILA, Patrick BROCKMANN, Philippe BOUSQUET, Arnaud
CAUBEL, Sébastien DENVIL, Jean-Louis DUFRESNE, Laurent FAIRHEAD,
Marie-Angèle FILIBERTI, Corinne LEQUERE, Cyril MOULIN, Philippe
PEYLIN, Peter RAYNER
NAME
Occupation
e-mail
LAURENT BOPP
Climate & Ocean
Biogeochemical Cycles
[email protected]
Patricia CADULE
Inter. Between Climate
Change & BGC – PhD
student
[email protected]
Pierre
FRIEDLINGSTEIN
Climate & Land Carbon
Cycle
[email protected]
NAME
Occupation
e-mail
Rachid BENSHILA
Ocean modelling Engineer
[email protected]
Patrick
BROCKMANN
Visualisation software
Engineer
[email protected]
Philippe
BOUSQUET
CO2 transport
[email protected]
Arnaud CAUBEL
Software Engineer - coupling
aspects
[email protected]
Sébastien DENVIL
Climate modelling and global
change simulations Engineer
[email protected]
Jean-Louis
DUFRESNE
Climate modelling
[email protected]
Laurent
FAIRHEAD
Atmospheric modelling
Engineer
[email protected]
Marie-Angèle
FILIBERTI
Atmospheric Tracer transport
Engineer
[email protected]
Philippe PEYLIN
CO2 transport and Inversion
[email protected]
Peter RAYNER
CO2 Inversion
[email protected]
References
Aumont, O., E. Maier-Reimer, S. Blain, and P. Monfray (2003), An ecosystem model of the global ocean
including Fe, Si, P co-limitations, Glob. Biogeochem. Cycles. 17(2), 1060, 10.1029/2001GB00174.
Baker D. F.( 2005), submitted to GBC
Bopp L., (2001), Changements Climatiques et Biogéochimie Marine : Modélisation du dernier Maximum
Gliaciaire et de l’Ere Industrielle
Bousquet P., Peylin P., Ciais P., Le Quéré C., Friedlingstein P., Tans P.P., (2000). Regional changes in
carbon dioxide fluxes of land and oceans since 1980. Science 290, 1342-1345.
Cox, P.M., R. A. Betts, C. D. Jones, S. A. Spall, and I. J. Totterdell (2000), Acceleration of global warming
due to carbon-cycle feedbacks in a coupled climate model, Nature, 408, 184-187.
Dufresne, J.-L., P. Friedlingstein, M. Berthelot, L. Bopp, P. Ciais, L. Fairhead, H. LeTreut, and P.
Monfray (2002), Effects of climate change due to CO2 increase on land and ocean carbon uptake.
Geophys. Res. Lett., 29(10), 10.1029/2001GL013777
Friedlingstein P., Dufresne J.L., Cox P.M., Rayner P., (2003) How positive is the feedback batween
climate change and the carbon cycle ?. Tellus 55B, 692-700Friedlingstein P., P. Cox, R. Betts, L. Bopp, W.
von Bloh, V. Brovkin, S. Doney, M. Eby, I. Fung, B. Govindasamy, J. John, C. Jones, F. Joos, T. Kato,
M. Kawamiya, W. Knorr, K. Lindsay, H. D. Matthews, T. Raddatz, P. Rayner, C. Reick, E. Roeckner, K.G. Scnitzler, R. Schnur, K. Strassmann, A. J. Weaver, C. Yoshikawa, and N. Zeng (2005), Climate –
carbon cycle feedback analysis, results from C4MIP model intercomparaison (Submitted to Journal of
Climate)
Houghton, R.A., and J.L. Hackler (2002), Carbon Flux to the Atmosphere from Land-Use Changes. In
Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge
National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.
Houghton, J.T., Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A.
Johnson (2001), Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third
Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA.
Krinner G., Nicolas Viovy, N. de Noblet-Ducoudré, J. Ogée, J. Polcher, P. Friedlingstein, P. Ciais, S.
Sitch, and I. C. Prentice (2005), A dynamic global vegetation model for studies of the coupled
atmosphere-biosphere system, Global Biogeochem. Cycles, 19, GB1015, doi:10.1029/2003/GB002199
LE QUÉRÉ, C., AUMONT, O., BOPP, L., BOUSQUET, P., CIAIS, P., FRANCEY, R., HEIMANN, M.,
KEELING, C. D., KEELING, R. F., KHESHGI, H., PEYLIN, P., PIPER, S. C., PRENTICE, I. C. & RAYNER,
P. J. (2003), Two decades of ocean CO2 sink and variability., Tellus B 55 (2), 649-656.doi: 10.1034/j.16000889.2003.00043.x
Marland, G., T.A. Boden, and R. J. Andres (2005), Global, Regional, and National CO2 Emissions. In
Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak
Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.
Marti, O., P. Braconnot, J. Bellier, R. Benshila, S. Bony, P. Brockmann, P. Cadule, A. Caubel, S.
Denvil, J. L. Dufresne, L. Fairhead, M. A. Filiberti, M.-A. Foujols, T. Fichefet, P. Friedlingstein, H.
Goosse, J. Y. Grandpeix, F. Hourdin, G. Krinner, C. Lévy, G. Madec, I. Musat, N. deNoblet, J. Polcher,
and C. Talandier (2005), The new IPSL climate system model: IPSL-CM4. Note du Pôle de Modélisation,
26, ISSN 1288-1619.
Peylin P., Baker D., Sarmiento G., Ciais P., Bousquet P., (2002), Influence of transport uncertainty on
annual mean and seasonal inversions of atmospheric CO2. J. Geophys. Res. 107(D19), 4385,
10.1029/2001JD000857.
Sabine Christopher L., Richard A. Feely, Nicolas Gruber, Robert M. Key, Kitack Lee, John L.
Bullister, Rik Wanninkhof, C. S. Wong, Douglas W. R. Wallace, Bronte Tilbrook, Frank J. Millero,
Tsung-Hung Peng, Alexander Kozyr, Tsueno Ono, and Aida F. Rios (2004) , The Oceanic Sink for
Anthropogenic CO2, Science ; 305: 367-371 [DOI: 10.1126/science.1097403]
Takahashi, T., Sutherland, S. C., Sweeney, C., Poisson, A., Metzl, N. and co-authors, (2002). Global
sea-air CO2 flux based on climatological surface ocean pCO2, and seasonal biological and temperature
effects. Deep Sea Res. II 49, 1601-1622
Data sets :
Historical CO2 concentration : http://www.cnrm.meteo.fr/ensembles/public/data/CO2_fit.txt
MODIS : http://cybele.bu.edu/modismisr/products/modis/modislaifpar.html
SeaWIFS : http://oceancolor.gsfc.nasa.gov/SeaWiFS/
Backup
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“ En résumé ”
• The need for Carbon-Climate Coupling
– Modeling the carbon cycle
– Coupling it with the climate
• But now essentially
– Better understand processes individually
– Confront results to observations
Pushing towards convergence of
processes and their responses
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Climate and Carbon Models Sensitivity
LOOP vs
C4MIP models
ocean sensitivity to [CO2]
ocean sensitivity to T°
land sensitivity to [CO2]
land sensitivity to T°
climate sensitivity
LOOP is inside C4MIP
responses range. But is
it a sufficient criterion ?
[C4MIP- Friedlingstein et al., 2005]
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Climate Change and Carbon Cycle
Interactions
ocean sensitivity to [CO2]
ocean sensitivity to T°
land sensitivity to [CO2]
land sensitivity to T°
climate sensitivity
Wide range of climate and carbon models
[C4MIP-Friedlingstein et al., 2005]
sensitivity
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Simulated CO2 Fluxes
ORCHIDEE
PISCES
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Terrestrial
Biosphere
Model : ORCHIDEE
[Krinner, 2005]
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Oceanic Biogeochemical Model
PISCES
NH4+
NO3-
PO43-
Diatoms
Si
Nano-phyto
Iron
MicroZoo
D.O.M
Meso Zoo
P.O.M
Small Ones
Big Ones
Marine biology is highly influenced by the ocean dynamic
motivating the need of both PISCES and OPA
[Aumont, 2001; Aumont 2003]
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Satellite Data Comparison
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Sensitivity Analysis
Sensitivity of ocean carbon models to climate change
 2100

min
= - 14 GtC/°C

max
= - 60 GtC/°C
C

T
Reduction of
carbon quantity
entering the
ocean shows a
large range
amongst the
models
year
So, what does influence the ocean response to the climate ?