Acknowledgements: Laurent Bopp, Karen Kohfeld, Erik Buitenhuis, Olivier Aumont

Climate sensitivity:

what observations tell us about model predictions

Corinne Le QuéréMax-Planck-Institut für Biogeochemie, Jena, Germany

Acknowledgements:

Laurent Bopp, Karen Kohfeld, Erik Buitenhuis, Olivier Aumont

CO

2 sin

k (

PgC

/y)

(J. Orr and OCMIP-2 participants)

today

no biology, no climate change

time

CO

2 sin

k (

PgC

/y)

(J. Orr and OCMIP-2 participants)

Heimann and Maier-Reimer 1996

no biology, no climate change

time

Prentice et al. 2001, based on data from

Manning 2001, Langenfelds et al.,

1999, and Sabine et al., 2002

Le Quéré et al. 2003

Takahashi et al. 2002

Battle et al. 2000

Gruber and Keeling 2001

CO2 export production

100 yr predictions

100,000 yrs variations

interannual variations

outline

oceanic carbon cycle

Silicifiers

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO

3

Si

CaCO3

DMS

PO

4

NH

4

DOM

biological activity

11

45

34

physical transport

11

33

CO2

CO2 + H2O + CO2-3 2HCO-

3

chemical reactions

90

how do marine ecosystems respond to:

• elevated CO2

• warming• nutrient supply• stratification

physical response to elevated CO2

Reduced CO2 solubility

Reduced vertical circulation

(Sarmiento et al., in prep.)

oceanic carbon cycle

Silicifiers

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO

3

Si

CaCO3

DMS

PO

4

NH

4

DOM

biological activity

11

45

34

physical transport

11

33

CO2

CO2 + H2O + CO2-3 2HCO-

3

chemical reactions

90

diatoms

DOM

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO3Si

CaCO3

PO

4

NH4

nutrient-based models

(Najjar et al., 1992; Maier-Reimer 1993)

diatoms

DOM

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO3Si

CaCO3

NPZD

PO4 NH4

(Fasham et al., 1993)

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO3Si

CaCO3

ecosystem models

PO4 NH4

DOM

(Aumont et al. 2003; Moore et al., 2001)

diatoms

(Bopp 2001)

N

S

equator

lati

tud e

• reduction in nutrient supply

• increase of oligotrophic gyres

• longer growing season

Modelled changes in export production at 2xCO2

+30 %-30 %

CO

2 sin

k (

PgC

/y) climate

feedback

(Prentice et al., 2001)

time

CO

2 sin

k (

PgC

/y)

CO2 + climate

(Prentice et al., 2001)

time

CLI MATE RES PONSE O F OCEAN IC UPTAKE

Sarmientoet al. (1998)

Matear andHirst (1999)

J oos et al.(1999)

T ime Span 1990-2065 1850-2100 1765-2100

Warm ing Eff ect -11% -12% -13%

Circ ulatio n Eff ect -22% -10% -3%

Biological Eff ect +24% +8% +6%

TOTA L -9% -14% -10%

(slide from J. Sarmiento)


100 yr predictions

-5 to -15% [warming] 0 to -6% [nutrient supply]- low lat + high lat




100 yr predictions

-5 to -15% [warming] -0 to -6% [nutrient supply]- low lat + high lat



CO2 (ppm)

0°C

-8°C

280 ppm

200 ppm

5.8°C

1.4°C

960 ppm

550 ppm

Temperature (oC)

400,000 years


(data from Petit et al., 1999)

x2 over the ocean

• Circulation Changes (Simulation OPA model, O. Marti)

• Increased Sea -Ice in Winter (Crosta et al. 1998)

• Increased dust deposition on the ocean (Mahowald et al. 1999)

• Cooling of SST (CLIMAP 1981)

Model simulations of the last glacial maximum

(Bopp et al., 2003)

total LGM impact on export production

(Bopp et al., 2003)

• decreased export production (-7 %)• decreased atmospheric CO2 (-30 ppm)

gC/m2/y

total LGM impact on export production

(Bopp et al., 2003)

Nano-phyto Diatoms

diatoms relative abundance

Nano-phyto

Diatomées

Latitude

iron LGM impact on export production

• increased export production (+6 %)• but increase of oligotrophic gyres

• shift from nano-phyto to diatoms

•Opal (SiO2)•Calcium Carbonate (CaCO3)•Organic Carbon•Biomarker (C37 Alkenones)

•10Be•231Pa•Excess Barium

•Authigenic Uranium•Authigenic Cadmium•Benthic Foraminifera Fluxes

Age Models•Radiocarbon dating (AMS)•Oxygen Isotope Stratigraphy•Lithogenic Correlation

Flux measurement•Constant Flux Normalization (230Th)•Mass Accumulation Rates•Sediment Concentration

Evaluation of Paleo-Data

Proxy Agreement•How many?•Percentage agreement

Ranking Criteria:

Ranked Classes:

Paleo-Export Proxies:

Data Confidencehigh

medium

low(Kohfeld et al., in prep.)

LGM-Stage 5ad

LGM-today

“Today”

Stage 5ad-today

Stage 5a-d

LGM

dust

CO2

change in export production

(Kohfeld et al., in prep.)

time

Unpublished map not available

Unpublished map not available

/ OPA-PISCES model (Bopp et al. 2003)

(gC m-2 yr-1)

Data-base (Kohfeld et al., in prep.)

change in export production

Maximum effect with this model

41 ppm

CO2 drawdown with this model 30 ppm

SST + SSS (+ sea ice + circ.) = –15 ppm

Dust increase –15 ppm

(Bopp et al., 2003)

dust

CO2

Watson et al., 200040 ppm

Archer et al. 20008 ppm

Bopp et al. in press15 ppm

ReferenceCO2 reduction due to dust at the LGM

(Watson et al., 2000)

reasonable agreement considering the phasing of dust/CO2 changes

time


100 yr predictions



-8 to -40 ppm [iron]-15 ppm [solub.] -25 to -75 ppm left

~0 [iron + circ]+ mid-low lat [iron]- high lat [circ + bio]


Le Quéré et al., in press

CO

2 var

iab

ilit

y (P

g C

/y)

atmosphere

Mean: 3.2 PgC/y

interannual CO2 variability

time

20 years

(Le Quéré et al., 2003)

CO

2 var

iab

ilit

y (P

g C

/y)

atmosphere

ocean

(Bousquet et al., 2000; data from Feely et al., 1999)

equatorial Pacific

During El Nino events: CO2

• warming• decreased upwelling • decreased export production

CO

2 var

iab

ilit

y (P

g C

/y)

MIT model (McKinley 2002)

Hamburg model (Winguth et al., 1994)

OPA model (Le Quéré et al., 2000)

northern sub-tropics

(Peylin et al., in prep)

CO

2 var

iab

ilit

y (m

ol/m

2 /y) MIT model

OPA model

observations

North Atlantic

(Gruber et al., 2002)

Chla (SeaWiFS)

Standard deviation of interannual signal

SST (Reynolds and Smith 1994)

MLD (indirect estimate using SSH)

SSH (TOPEX/Poseidon)


100 yr predictions






+/- 0.3 ppm +/- 0.3 ppm tropics [circ]

+/- 0.05 ppm mid lat [solub.]+/- 0.05 ppm high lat [circ + bio]

SeaWiFS chla, PP from Behrenfeld and Falkowski (1997), ef-ratio from Laws et al. (2000)

Standard deviation of export production variability 1997-2002 (mol C/m2/yr)1.5

1.0

0.5

0.0

diatoms

DOM

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO3Si

CaCO3

PO

4

NH4

nutrient-based models (HAMOCC3)

(Maier-Reimer 1993)


Standard deviation of export production variability (mol C/m2/yr)1.5

1.0

0.5

0.0

HAMOCC3

diatoms

DOM

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO3Si

CaCO3

NPZD

PO4 NH4

(Aumont et al.,2002 based on Maier-Reimer and Six 1996)



1.0

0.5

0.0

NPZD

HAMOCC3

N2 fixersDMS

producers

CalcifiersNano

phytoplankton

Fe NO3Si

CaCO3

PISCES model based on plankton functional types

PO4 NH4

DOM

diatoms

(Aumont et al., 2003; Bopp et al., 2003)



1.0

0.5

0.0

PISCES

NPZD

HAMOCC3

Dynamic Green Ocean Model

N2 fixersDMS

producers

coccolith.Nano

phytoplankton

Fe NO3Si

CaCO3

PO4 NH4

DOM

diatoms

(Buitenhuis et al., 2003)



1.0

0.5

0.0

DGOM

4

PISCES

NPZD

HAMOCC3

(Le Quéré et al., in prep.)

diatoms

coccolithophorids

nano-phytoplankton

P

Gro

wth

rat

e

(Chavez et al 2003)


100 yr predictions







+/- 0.05 ppm mid lat [solub.]+/- 0.05 ppm high lat [circ + bio]

+/- 1%


100 yr predictions



-8 to -40 ppm -8 to -40 ppm [iron][iron]

-15 ppm -15 ppm [solub.][solub.] -25 to -75 ppm left

~0 ~0 [iron + circ][iron + circ]

+ mid-low lat + mid-low lat [iron][iron]- high lat [circ + bio]


+/- 0.3 ppm +/- 0.3 ppm

+/- 0.3 ppm tropics +/- 0.3 ppm tropics [circ][circ]

+/- 0.05 ppm mid lat +/- 0.05 ppm mid lat [solub.][solub.]+/- 0.05 ppm high lat [circ + bio]

+/- 1%


100 yr predictions



-8 to -40 ppm [iron]-15 ppm [solub.]

-25 to -75 ppm left-25 to -75 ppm left

~0 [iron + circ]+ mid-low lat [iron]

- high lat - high lat [circ + bio][circ + bio]



+/- 0.05 ppm mid lat [solub.]

+/- 0.05 ppm high lat +/- 0.05 ppm high lat [circ + bio][circ + bio]

+/- 1% +/- 1%


100 yr predictions











+/- 1% +/- 1%

plankton functional typesplankton functional types


100 yr predictions











+/- 1% +/- 1%

plankton functional typesplankton functional types

linkages between biogeochemistry and linkages between biogeochemistry and physics (including the coastal ocean)physics (including the coastal ocean)

CO2 (ppm)

0°C

-8°C

280 ppm

200 ppm

5.8°C

1.4°C

960 ppm

550 ppm

Temperature (oC)

400,000 years

CO2 (ppm)

0°C

-8°C

280 ppm

200 ppm

5.8°C

1.4°C

960 ppm

550 ppm

Temperature (oC)

CO2 (ppm)

0°C

-8°C

280 ppm

200 ppm

Temperature (oC)

400,000 years

5.8°C

1.4°C

960 ppm

550 ppm

1850

JGOFS

2100

Vostok

global

Acknowledgements: Laurent Bopp, Karen Kohfeld, Erik Buitenhuis, Olivier Aumont

Documents

Transcript of Acknowledgements: Laurent Bopp, Karen Kohfeld, Erik Buitenhuis, Olivier Aumont