Surface Ocean pCO2 and Air-Sea CO2-exchange in Coupled Models

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Surface Ocean pCO2 and Air-Sea CO2-exchange in
Coupled Models
Birgit Schneider1, Laurent Bopp1, Patricia
Cadule1, Thomas Frölicher2, Marion Gehlen1,
Fortunat Joos2, Corinne Le Quéré3 and Joachim
Segschneider4 1Laboratoire des Sciences du
Climat et de LEnvironnement (LSCE),
Gif-sur- Yvette, France 2 Division of Climate-
and Environmental Physics, University of Bern,
Bern, Switzerland 3 University of East Anglia,
Norwich, UK 4 Max-Planck-Institut für
Meteorologie, Hamburg, Germany birgit.schneider
_at_lsce.ipsl.fr
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Outline

• 1. How good are the models in simulating
  surface ocean pCO2 and Air-Sea CO2-exchange?
• -gt climatological fields compared to the new
  Takahashi 2007 data base and OCMIP-2 model
  output
• -gt interannual variability compared to
  observations and output from a forced model
• -gt temporal trends compared to observations
• How good are the models reproducing temporal
  variability of marine biological
  production? -gt interannual variability
  compared to observation-based estimates
  derived from satellite data

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Models and Experiments
IPSL MPIM NCAR ocean
model OPA 8 MPIOM NCAR-CSM1.4 hor.
resolution ORCA 2 x 2x cos lat 1.5 x
1.5 3.6 x 0.8-1.8 vert. resolution 31
levels 40 levels 25 levels mar.
biogeochem. PISCES HAMOCC5.1 OCMIP-2 mod.
All models have been treated according to the
C4MIP protocol. (Friedlingstein et al.,
2006) Period investigated 1985-2005
historical
A2
4
!!!
The models were forced by CO2-emissions
only!) Consequently, they produce their own
patterns of climate variability and can not be
compared to observations on a year by year
basis. Model evaluation needs to be done
statistically and by comparison with
climatological distributions. )NCAR also
includes forcing by other GHGs, solar activity
and volcanic emissions.
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Modeled and Observed ?pCO2
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Spatial and Temporal Correlations of ?pCO2
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Sea-Air CO2-flux Equatorial Pacific(165W-90W,
5N-10S)
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Climate Impact on Marine Biological Production
La Nina
SI stratification index ?200 ?surf (kg m-3)
R20.73
R20.85
El Nino
SEAWIFS-data from Behrenfeld et al., Nature, 2006
R20.02
R20.05
R20.70
R20.67
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Climate Impact on Marine Biological Production
La Nina
R20.73
R20.85
R20.04
R20.03
slope-876
slope-151
El Nino
R20.70
R20.67
R20.02
R20.05
slope-787
slope-246
NCAR
SI stratification index ?200 ?surf (kg
m-3)
Schneider et al., Biogeosciences Discuss., 2007
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Temporal Trends 1985-2005
Anomalies of Surface Ocean pCO2 Increase
(Ocean-Atmosphere), ppm
pCO2 increase (ppm/per year)
ATM OCEIPSL 1.49 1.26MPIM 1.69 1.60NCAR 1.88 1
.73
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Conclusions

• All models compare considerably better to the
  new pCO2 climatology (Takahashi et al., 2007)
  than to the one before.
• The seasonal cycle of surface ocean pCO2 is well
  represented by two out of three coupled models
  yielding a better match with observations than
  annual mean fields. For all OCMIP-2 models it is
  the opposite.
• Coupled model have difficulties in capturing the
  amplitude and/or frequency of the interannual
  variability of Air-Sea CO2-exchange.
• In contrast to observations models show a
  slightly lower surface ocean pCO2 increase than
  the atmosphere, suggesting a still increasing
  oceanic sink for anthropogenic CO2. (-gt ozone
  effect?)
• For a realistic representation of the
  interannual variability of marine productivity
  next to ocean circulation the iron cycle and
  nutrient co- limitations are of major importance.

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Anthropogenic Air-Sea CO2-fluxes
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Regional Sea-Air CO2-fluxes
gt 44 S
44 S - 18 S
18 S - 18 N
18 N - 49 N
gt 49 N
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SST - CO2flux relationships
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SST - CO2flux relationships (anomalies)
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El Nino Variability
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Background

• Can we reduce the uncertainty in estimating the
  oceanic sink for anthropogenic CO2?
• Is there a significant contribution of marine
  biological productivity to the air-sea
  CO2-exchange?